July 2012

NASA/TM–2012–215872

Optical Sensors for Planetary Radiant Energy (OSPREy):

Calibration and Validation of Current and Next-Generation

NASA Missions

Stanford B. Hooker, Germar Bernhard, John H. Morrow, Charles R. Booth, Thomas Comer, 

Randall N. Lind, and Vi Quang
	







 

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National Aeronautics and 

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

July 2012

NASA/TM–2012–215872

Optical Sensors for Planetary Radiant Energy (OSPREy):

Calibration and Validation of Current and Next-Generation

NASA Missions

Stanford B. Hooker

NASA Goddard Space Flight Center, Greenbelt, Maryland

Germar Bernhard

Biospherical Instruments Inc., San Diego, California

John H. Morrow

Biospherical Instruments Inc., San Diego, California

Charles R. Booth

Biospherical Instruments Inc., San Diego, California

Thomas Comer

Biospherical Instruments Inc., San Diego, California

Randall N. Lind

Biospherical Instruments Inc., San Diego, California

Vi Quang

Biospherical Instruments Inc., San Diego, California
Available from:

NASA Center for AeroSpace Information National Technical Information Service

7115 Standard Drive 5285 Port Royal Road

	




 	






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Space Administration.

Level of Review: This material has been technically reviewed by technical management.
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Table of Contents

Prologue .................................................. ............................................... 1

1. The OSPREy System Concept ..................................................................... 6

1.1 Introduction ....................................................................................... 6

1.2 System Concept .................................................................................. 10

1.3 Sensor Descriptions .............................................................................. 11

1.4 Data Products ......................................... .......................................... 13

1.5 Quality Assurance Plan .......................................................................... 14

2. Application of Microradiometers to EMR and OXR Sensors ........................................ 18

2.1 Introduction ............................................ .......................................... 18

2.2 Microradiometer Modifications .................................................................... 19

2.3 Linearity Tests .................................................................................... 20

2.4 Microradiometer Clusters ......................................................................... 21

3. SWIR Cosine Collector Design and Evaluation .................................................... 23

3.1 Introduction ............................................ .......................................... 23

3.2 Selection of Diffuser Material ...................................................................... 23

3.3 Irradiance Collector Design ........................................................................ 24

3.4 Optimized Cosine Collector ....................................................................... 25

3.5 Final Collector Design Test ....................................................................... 25

3.6 Conclusions ....................................................................................... 26

4. Radiance Field-of-View Specifications ............................................................. 27

4.1 Introduction ............................................ .......................................... 27

4.2 Engineering Considerations ........................................................................ 27

4.3 Results and Discussion ............................................................................ 29

4.4 Fore Optics Design ................................................................................ 30

4.5 Conclusions ....................................................................................... 31

5. Sun Tracker Performance Evaluation .............................................................. 32

5.1 Introduction ............................................ .......................................... 32

5.2 Tracker Requirements ............................................................................. 32

5.3 Tracker Selection .................................................................................. 33

5.4 Test Protocol ..................................................................................... 34

5.5 Results ........................................................................................... 34

5.6 Conclusions ....................................................................................... 36

6. Lamp Library Performance ....................................................................... 38

6.1 Introduction ............................................ .......................................... 38

6.2 Lamp Inventory ......................................... .......................................... 39

6.3 Lamp Operation .................................................................................. 41

6.4 Lamp Transfer Radiometers ....................................................................... 42

6.5 Lamp Transfer Uncertainties ...................................................................... 43

6.6 Lamp Usage Protocol ............................................................................. 45

6.7 Lamp Comparisons ............................................................................... 45

6.8 Usage of OSPREy Lamp Library .................................................................. 49

6.9 Conclusions ....................................................................................... 49

iii
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

7. Spectrograph Testing and Review: An Engineering Analysis of COTS Spectrographs ............... 50

7.1 Introduction ............................................ .......................................... 50

7.2 Test Protocols .................................................................................... 51

7.3 Candidate Instruments ............................................................................ 52

7.4 Results ........................................................................................... 53

7.5 Conclusions ....................................................................................... 60

8. The Integrated OSPREy System .................................................................. 62

8.1 Introduction ............................................ .......................................... 62

8.2 Common Design Features ......................................................................... 64

8.3 Starter System .................................................................................... 68

8.4 Minimum System ................................................................................. 69

8.5 Spectral System ......................................... .......................................... 70

8.6 Operational System ............................................................................... 70

8.7 Maximum System ................................................................................. 71

8.8 Transfer Radiometers ............................................................................. 71

8.9 Radiometer Performance .......................................................................... 72

8.10 Remote Sensing Applications ...................................................................... 77

8.11 Discussion and Conclusions ....................................................................... 79

Acknowledgments ......................................... .......................................... 83

Appendices ............................................... ............................................. 83

Appendix A: Above and In-Water Methods ........................................................ 83

Appendix B: Vicarious Calibration Protocols ...................................................... 86

Appendix C: The BSI Calibration Facility ......................................................... 87

Appendix D: Ancillary Measurements ............................................................. 88

Appendix E: The BioSHADE Accessory ........................................................... 89

Appendix F: Platform Power and Data Telemetry ................................................. 89

Appendix G: Extended Test Deployments ......................................................... 91

Appendix H: Operational Deployment ............................................................. 92

Appendix I: Absolute Calibration ................................................................. 93

Appendix J: Uncertainty Analysis ................................................................. 96

Appendix K: Platform-Perturbation Mapping ...................................................... 97

Appendix L: The SABSOON Towers .............................................................. 98

Appendix M: BSI Quality Assurance Experience ................................................. 100

Frequently Asked Questions (FAQs) ............................................................. 102

Glossary ............................................................................................. 109

Symbols .............................................................................................. 111

References .......................................................................................... 113

iv
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Abstract

A principal objective of the Optical Sensors for Planetary Radiance Energy (OSPREy) activity is to establish an

above-water radiometer system mounted on an offshore-platform as a lower-cost alternative to existing in-water

buoys for the collection of ground-truth observations. The goal is to be able to make high-quality measurements

satisfying the accuracy requirements for the vicarious calibration and algorithm validation of current and nextgeneration ocean color satellites. This means the measurements will have a documented uncertainty satisfying

the established performance metrics for producing climate-quality data records (CDRs). The activity is based

on enhancing commercial-off-the-shelf (COTS) fixed-wavelength and hyperspectral sensors to create thermally

regulated hybridspectral instruments with an improved accuracy and spectral resolution, as well as a dynamic

range extended into shorter and longer wavelengths. Greater spectral diversity in the ultraviolet (UV) will be

exploited to separate the living and nonliving components of marine ecosystems; UV bands will also be used

to flag and improve atmospheric correction algorithms in the presence of absorbing aerosols. The short-wave

infrared (SWIR) is expected to improve atmospheric correction, because the ocean is radiometrically blacker at

these wavelengths. The cost savings are derived not only from using existing technologies as a foundation of the

instrument designs, most notably recently developed microradiometers, but also from the above-water approach

itself. From the oceanographic perspective, above-water radiometry involves the use of offshore platforms,

which have several advantages: a) offshore platforms and towers already exist, b) a tower provides a very stable

platform and deterministic solar geometry, c) biofouling is a significantly lesser problem compared to an in-water

instrument system, d) acquiring high-quality data at longer wavelengths is easier to achieve, and e) the offshore

structure offers a great deal of protection for the instruments. In addition to the relevance to NASA Earth

Science, the OSPREy approach significantly impacts the state of the art of optical calibration technology, which

is in transition. The production of a transfer radiometer and demonstration of its utility should help interrupt the

cycle of escalating costs associated with lamp standards, because it encourages the transition toward detectorbased standards. The world ocean is immense and it is not possible for one agency or one country to produce

global CDRs of a uniform quality without strong partners from other nations. Establishing a high-quality and

cost-effective sampling capability that is readily reproduced—because it can be purchased as a COTS system—is

an important first step towards establishing a global calibration and validation paradigm. This report describes

the overall design of OSPREy; the documented uncertainty will be presented in a subsequent report.

Prologue

NASA has a continuing requirement to collect highquality in situ data for the vicarious calibration of ocean

color satellite sensors and to validate the algorithms for

which the remotely-sensed observations are used as input parameters. Within this context, “high quality” refers

to measurements with a documented uncertainty in keeping with established performance metrics for producing

climate-quality data records (CDRs). The Optical Sensors for Planetary Radiant Energy (OSPREy) activity establishes a lower-cost alternative to existing practices for

such data collection activities while satisfying the necessary accuracy and precision requirements. The lower cost

is achieved by enhancing existing, but recently developed,

state-of-the-art commercial instruments (with a spectral

sampling capability exceeding current and planned satellite requirements), the use of sensors already being used in

the field, reduced maintenance costs from the use of abovewater sensors (which have no significant biofouling), and

deploying the equipment on an offshore structure already

maintained by other institutes and agencies.

The enhancements to existing radiometric technology

permits the measurement of a suite of atmospheric parameters, so for the first time, self-consistent observations—that

is, data from instruments with a common calibration—of

the ocean and atmosphere are possible. The benefits of this

new sampling capability are expected to be better atmospheric correction of ocean color data, an improved ability

to accurately separate the living and nonliving components

of seawater, and improved understanding of the interaction

between the ocean and atmosphere.

The OSPREy activity is designed as an important initial step in the ability of the ocean color community to support a coupled ocean–atmosphere observing system, i.e., a

calibration and validation capability for a combined satellite mission. Such a mission will very likely emphasize

coastal as well as open ocean processes, so a capability for

making high-quality measurements in the near-shore environment is an inevitable requirement. The work presented

here is based on the use of offshore structures as sampling

sites, which means this important work can start now with

enough time for establishing what will be needed to support the next mission. In addition, as long as the location

1
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

of the site is selected carefully to ensure the range in environmental properties are satisfactory for both vicarious

calibration and algorithm validation, the opportunity exists to test whether or not the response of a vicariously

calibrated system is linear across a much wider dynamic

range than has been done before.

In addition to the relevance to NASA Earth Science,

the OSPREy activity will significantly impact the state

of the art of optical calibration technology, which is in

transition. The evolution is occurring, because traditional

calibration sources (e.g., a lamp standard of spectral irradiance) are becoming incrementally expensive at an increasing rate. For example, the National Institute of Standards

and Technology (NIST) increased primary standard lamp

prices from $7,202 in 1997, to $14,945 in 2007, with delivery times as long as eight months. In addition, a reduction

in lamp quality, possibly due to the closing of domestic

manufacturing facilities, have led to substantially shorter

lifetimes for working standards that are derived from the

NIST primary standard lamps.

These direct and indirect escalations in costs impact

calibration facilities, scientific researchers, and NASA programs. In addition, commercial activities are affected, because the cost of calibrating instruments must be passed

on to the customer. As a further complication, increased

costs discourages researchers from recalibrating their instruments on a frequent schedule, which can in turn lead

to spurious scientific results and degraded CDRs. Development of the OSPREy Transfer Radiometer (OXR) and

demonstration of its utility should help interrupt the cycle of escalating costs, because it encourages the transition away from lamp-based standards, which are consumed

with use, to detector-based standards, which are not. Another type of calibration that is not consumed with use

is a solar calibration, but this requires instruments that

function as sun photometers.

The OXR instruments are from a new class of thermally

regulated sensors that are based on combining two different, but complementary, commercial off-the-shelf (COTS)

detection capabilities—fixed-wavelength microradiometers

and a hyperspectral spectrograph—to build a hybridspectral instrument called the Enhanced Performance Instrument Class (EPIC) sensor. Unlike legacy sensors, which

were built primarily for narrowly specified light sources

and sampling targets, EPIC sensors are anticipated to be

used with a tracker and can view a multitude of intended

sources and targets under varying conditions. For brevity

and specificity, an individual radiance (L) and irradiance

(E) instrument from this EPIC Multitarget Radiometer

(EMR) product line is denoted as EML and EME, respectively. This same naming approach is also used for the radiance and irradiance OXR sensors as the OXL and OXE,

respectively.

The use of two different detector technologies coupled

with custom-built primary (housing) and secondary (spectrograph) thermal regulation increases the spectral resolution and decreases the uncertainty of OXR and EMR

measurements. The addition of a nine-position filter wheel

in front of the spectrograph fiber in an EML (radiance)

sensor provides an index (home) position, improved straylight correction (cut-on filter), dark offset measurements

(opaque disk), three-axis polarimetry, solar (bright target)

viewing through the use of two neutral density (ND) filters, and an open position (for relatively dim targets, e.g.,

the Moon, with respect to the Sun). Integration of a video

camera into an EML sensor and mounting the sensor on an

automated tracker creates a sensor that can target the Sun,

sea, sky, and Moon with sufficient accuracy and precision

to function as a sun photometer.

When an EML (radiance) sensor is used with an EME

(irradiance) sensor having a shadowband accessory, the

sensor pair—or dyad—produces a wide diversity of oceanic and atmospheric (or atmospheric and terrestrial) data

products with a common calibration history. The large

number of variables means an OSPREy system can support a commensurately large number of missions. The use

of two dyads provides synchronous and asynchronous sampling scenarios plus intra- and inter-sensor comparisons to

maximize quality assurance (QA) and quality control (QC)

opportunities, while minimizing the likelihood of degrading the CDRs.

Another mechanism for minimizing the likelihood of

degraded CDRs is to implement a completely open data

policy—from the very beginning, at the point of acquisition—whereby researchers can access the data in near-real

time. The philosophy espoused in the OSPREy activity

is to use the increasing availability of online resources to

make the data available on a Web site, so the quality of the

work at every step in the process can be evaluated independently. The access of near-real time data to worldwide

institutes is also an educational-outreach that Government

agencies, such as the National Science Foundation (NSF)

and NASA, have found valuable. The OSPREy activity

is anticipated to have an online data availability, which

should generate similar interest from educational programs

in remote sensing.

The increasing interest of foreign agencies in satellite

remote sensing, and their attempts at emulation (or at

least, appreciation) of NASA calibration and validation

activities, brings increased market opportunities to domestic companies, such as Biospherical Instruments Inc. (BSI)

the manufacturers of OSPREy systems, in exploiting these

markets. Activities like OSPREy contain technologies that

could be exported, and when robust calibration and validation programs are exported, worldwide remote sensing

programs gain a more common calibration base. The world

ocean is immense and it is not possible for one agency or

one country to produce global CDRs of a uniform quality

without strong partners from other nations. Establishing a high-quality, but nonetheless cost-effective sampling

system that is readily reproduced—because it can be purchased commercially—is an important first step in providing solutions for the global calibration and validation

problem set.

2
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

The OSPREy approach delivers data with documented

quality metrics for both the oceanic and atmospheric science communities (with terrestrial applications, as well).

These data form a solid basis for ocean color calibration

and validation activities. Continuous monitoring at high

sampling rates further provides a wealth of information

that can be used to analyze geophysical parameters on

time scales from seconds to years. The level of temporal

coverage combined with the diversity and number of data

products is unprecedented, when compared to existing calibration and validation systems, and will stimulate new research. Where OSPREy deployments overlap with other

research programs, there is an opportunity to foster mutual

synergistic opportunities. For example, the aerosol optical

depth (AOD) measurements from OSPREy can augment

the measurements made by the Aerosol Robotic Network

(AERONET), which has numerous sun photometers deployed worldwide (Holben et al. 1998). In turn, algorithms

developed for AERONET may benefit OSPREy in terms

of standardizing aspects of the data product suite.

The NIST irradiance scales implemented by the Spectral Irradiance and Radiance Responsivity Calibrations using Uniform Sources (SIRCUS), which are intended to be

used for OSPREy calibrations as maintained by OXR instruments and a library of 21 FEL lamps (plus a reflectance

plaque), will be compared to the calibrations from the

NIST Facility for Spectroradiometric Calibrations (FASCAL), as well as solar calibrations, which are used for

the Ultraviolet Spectral Irradiance Monitoring Network

(UVSIMN). The calibrations will be validated against each

other to the benefit of all programs. Because the UVSIMN

scale is also interlinked with other domestic and international UV monitoring networks through the National

Oceanic and Atmospheric Administration (NOAA) Central UV Calibration Facility (CUCF) located in Boulder

(Colorado), the detector-based irradiance scale established

for OSPREy may also be of sufficient benefit to further

those programs.

The connection of OSPREy to other programs is also

linked to the legacy sensors still used in those programs

and extends into the baseline understanding of calibration

uncertainties, particularly in the UV domain. Because the

topics of interest span calibration, data acquisition, data

processing, and quality monitoring, the OSPREy approach

is necessarily complex with many nuances to understand.

To aid the reader, frequently asked questions (FAQs) regarding many aspects of EMR and OXR sensors, as well as

OSPREy systems, are provided as a separate section (see

Table of Contents). A summary of the material presented

in each chapter is given below.

1. The OSPREy System Concept

The primary objective of the OSPREy activity is to

develop and deploy a new class of commercial radiometers to support existing and next-generation NASA ocean

color satellites. An EPIC sensor is a hybridspectral device combining measurements of spectral irradiance and

radiance from recently developed microradiometers with

a commercially available hyperspectral spectrograph plus

a pointing system. Over common parts of the spectrum,

fixed-wavelength microradiometers and the spectrograph

can be continuously intracompared to maintain stability

and accuracy of the system. Radiance sensors have a nineposition filter-wheel assembly in line with the spectrograph

fiber optics to permit hyperspectral polarimetric measurements (three polarized filters), direct-Sun viewing (neutral

density filters), stray-light correction (395 nm cut-on filter), and dark current measurements (opaque disk). Radiance sensors also have an integrated camera for locating

the Sun and Moon (in lieu of a quadrant detector), as well

as verifying the condition of all targets (cloud-free solar

and lunar disks, cloud presence in sky data, and sea surface debris or foam detection). All sensors include thermal

stability control to increase filter and detector stability and

reduce drift. The field sensor suite includes shadowband

accessories to the solar irradiance sensors, which are combined with radiance observations of the Sun, Moon, sea,

and sky across a wide spectral range—the UV, through

the visible (VIS) and into the short-wave infrared (SWIR);

305–1,640 nm is the full spectral range for radiance, as well

as irradiance because of a new cosine collector design. The

diversity of targets and measurement types provides an unprecedented number of near-simultaneous atmospheric and

oceanic data products. This new sampling capability is expected to improve a) the atmospheric correction of ocean

color data; b) the accuracy in satellite data products, particularly in optically complex (coastal) waters; and c) the

understanding of the interaction between the ocean and atmosphere. The combination of wide spectral and dynamic

ranges with accurate pointing are also anticipated to have

application to terrestrial observations.

2. Application of Microradiometers to

EMR and OXR Sensors

Microradiometers are small, fast, reliable, and costeffective radiometers that are composed of a filter, photodetector, wide-range electrometer, analog-to-digital converter (ADC), microprocessor, and digital interface. Microradiometers were originally developed for in-water profiling systems and were adapted to the requirements of

OSPREy applications by increasing their dynamic range

to over 10 orders of magnitude with excellent (better than

1%) linearity over this interval. The devices now support

measurements of both very bright sources like the solar

disk and comparatively very dim sources like the ocean,

calibration targets, and lunar disk. The circuitry was further modified to handle both silicon diodes for UV-VIS

measurements and InGaAs photodetectors for measurements in the SWIR domain. The Multiple Microradiometer System (MMS) architecture allows clusters of up to 19

tightly-packed microradiometers to be networked together

3
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

using an aggregator, such that the multitude of sensors can

be controlled as a solitary device. The aggregator also provides an interface to external devices, such as temperature

controllers and filter-wheel stepping motors used in EMR

instruments. Compared to legacy platforms, the new technology offers lower cost, fully automated manufacturing,

higher reliability, smaller size, and higher detector densities

while maintaining excellent performance characteristics.

3. SWIR Cosine Collector Design and Evaluation

The irradiance collectors used with EMR sensors require small cosine errors and high transmission for wavelengths within 305–1,640 nm (UV–SWIR range). To satisfy this objective, a new irradiance collector was designed

by selecting diffuser materials optimized for this spectral

range and by modifying the shape of the existing irradiance collector originally developed for the UV-VIS range

of legacy sensors. Laboratory tests indicated that a composite diffuser made of one layer of generic polytetrafluoroethylene (PTFE) sheet and one layer of porous PTFE

(pPTFE) material produces the best characteristics. The

tests also confirmed that a small cosine error can only

be achieved with a shaped diffuser (for instance, a diffuser with a trapezoidal cross-section). A numerical model

was developed to optimize the dimensions of the composite diffuser (e.g., height, plus top and bottom diameters

of the diffuser) and its support structure (e.g., diameters and heights of two shadow rings surrounding the diffuser). Based on the results of material testing and modeling, a prototype irradiance collector was manufactured

and tested. For wavelengths in the UV-VIS range, the

cosine error of the new collector is less than ±3% for incident angles up to 75◦ and does not depend on wavelength

and azimuth angle. Cosine errors at SWIR wavelengths

are larger (e.g., −5% at 1,020 nm for an incident angle of

74◦), but are still within acceptable limits for OSPREy

applications.

4. Radiance Field-of-View Specifications

The field of view of EML (radiance) instruments used

for OSPREy applications, specified here in terms of the full

view angle (FVA), must be optimized to accurately measure a variety of different radiometric sources: the direct

solar irradiance when pointing the instrument at the Sun;

the total radiance emanating from the sea surface, the sky

radiance, and the radiance of a calibration plaque. The optimum FVA was determined based on the following considerations: a) the FVA must encompass the entire solar and

lunar disks when performing direct measurements under

all observation conditions; b) compliance with recommendations for sun photometers issued by the World Meteorological Organization (WMO); c) an FVA large enough to

allow accurate measurements of low-intensity sources (e.g.,

calibration plaques, the sea surface, and the lunar disk);

d) an FVA small enough to permit statistical filtering of

surface and capillary wave effects when measuring the sea

surface; and e) a reasonable overall instrument length. The

latter are needed to ensure accurate pointing and control of

the sensor, particularly by the sun tracker; easier handling

during servicing and the types of activities that take place

during those events (e.g., monitoring the stability of the

sensors with a portable source); and minimization of wind

loading. After taking all considerations into account, it

was concluded that an FVA of 2.5◦ combined with a slope

angle of 0.7◦ is the optimal configuration. These geometric

parameters were translated into a fore-optic design consisting of Gershun tubes with an overall length of 182 mm, a

front aperture of 4 mm, and three internal baffles for straylight suppression.

5. Sun Tracker Performance Evaluation

An OSPREy system requires a pointing device or tracker to accurately direct radiance radiometers at relevant targets, including the Sun, Moon, sky, sea surface, calibration

sources, and monitoring devices. Of all applications, the

measurement of the direct Sun requires the highest pointing accuracy. Based on the angular size of the Sun, the

geometry of radiance fore optics, and alignment uncertainties, it was determined that a pointing accuracy to within

0.2◦ is required. The tracker should be small in size with a

low power requirement, and must also be weather and corrosion resistant for use in the marine environment. A market analysis was performed, which resulted in three candidate instruments. Based on specifications provided by

the manufacturers, it was concluded that the PTU-D300

pan-tilt unit from FLIR Motion Control Systems would

be the most suitable tracker for OSPREy applications. A

test unit was procured and installed on the roof platform

at BSI. The pointing accuracy was tested by mounting a

video camera on the device for tracking the Sun. Software

was developed to capture and examine the images of the

video camera. The software was able to find the center

of the Sun in the video images with an accuracy of 0.01◦.

The method is a viable and cost-effective alternative to the

use of quadrant detectors for Sun finding. Image analysis,

later confirmed with a test deployment of an EML (radiance) sensor, showed the PTU-D300 unit can track the

Sun with a sufficient accuracy of to within 0.1◦.

6. Lamp Library Performance

Twenty-one 1,000W tungsten-halogen FEL lamps were

chosen to become part of the OSPREy lamp library. Nine

lamps were calibrated by NIST, while the rest are uncalibrated, but seasoned lamps (by the supplier). These lamps

were operated for periods ranging from 4–35 h to assess

their stability. Changes in brightness were typically in the

range of ±0.02% per hour with a few lamps exhibiting

slightly larger drifts. These lamps should be seasoned for

an additional 8–30 h to improve their stability. The calibration laboratory at BSI was upgraded to operate lamps

4
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

of the OSPREy lamp library at the highest level of accuracy achievable. Upgrades included a new system for

powering the lamps, which allows regulation of the lamp

current to within a precision of 50 μA (or 0.0006% for a target current of 8.2 A). Other facilities required for accurate

lamp transfers were also upgraded to reduce uncertainties

caused by stray light, misalignment, and temperature variations. Three radiometers are available for maintaining optical standards: an OXL instrument calibrated at BSI, an

OXE instrument currently awaiting results of a NIST SIRCUS calibration (and not used for the results presented in

this chapter), and a transfer radiometer based on the BSI

ground-based UV (GUV) class of radiometers that is called

an XGUV. A comprehensive uncertainty analysis showed

the use of moderate-bandwidth radiometers, such as the

XGUV and OXL, are suitable to transfer calibrations of

FEL lamps. Uncertainties related to the relatively large

bandwidth of these instruments are on the order of 0.3%.

All NIST lamps were intercompared and agreed to within

±2%, which is a very good result considering that some

lamps are rather old and were calibrated against different

NIST scales. A protocol on the usage of the lamp library

was developed with the goal of preserving the spectral irradiance scale over a timescale of 15 years or more.

7. Spectrograph Testing and Review

EMR sensors are hybridspectral instruments with 19

fixed wavelength microradiometers plus an integrated spectrograph. Requirements for these devices are challenging,

because they represent two sensing technologies in one

housing, which must both sample a very wide dynamic

range—the very bright Sun and the relatively much darker

ocean. Candidate devices must be sufficiently sensitive to

detect the low signals inherent in OSPREy work in the

red region of the spectrum above seawater, exhibit sufficiently accurate spectral selection, stable dark noise, and

good temperature stability. A review of commercial spectrograph manufacturers identified a large number of instruments, from which 10 spectrographs were obtained and

systematically tested. The latter included two from Hamamatsu, three from Avantes, four from Zeiss/Tec5, and one

from B&W Tek. Testing protocols included the analysis of

the following: a) wavelength range, b) spectral resolution,

c) slit function, d) dynamic range, e) out-of-band rejection,

f) stray light, g) saturation, h) change of dark signal with

integration time and temperature, i) spectral responsivity,

j) noise equivalent irradiance or radiance, and k) linearity.

The test results indicate that an ideal instrument does not

exist, but workable candidates are available. For example,

all instruments suffer from stray light and nonlinearity to

some degree, which limits their usable dynamic range and

measurement accuracy. After considering all tests results

and other factors relevant for operation and system integration, it was determined that the MMS UV-VIS II and

MMS1† spectrographs from Zeiss/Tec5 were the most suitable devices for OSPREy applications.

8. The Integrated OSPREy System

The previous chapters describe the major elements in

the radiometers used in an OSPREy system: a microradiometer cluster with necessary modifications to support

OSPREy design criteria, a spectrograph, optical collectors (both radiance and irradiance), primary (housing) and

secondary (spectrograph) thermal regulation, and accessories like the tracker and shadowband. This chapter describes how these components—plus housing design, primary and secondary temperature control, and other support electronics—are integrated to make the radiometers

used in OSPREy systems. These include radiance and irradiance field sensors, and a similar pair designated as transfer radiometers. The fully integrated system provides an

unprecedented capability in a single housing. The spectrograph provides hyperspectral resolution over a subset

of the complete spectral range, while the microradiometers

provide a larger dynamic range in responsivity, higher sampling speeds, better sensitivity, and sampling across the

entire OSPREy spectral range (290–1,670 nm). The two

sensor technologies supplement each other. For example,

spectrograph data can be used to detect potential degradation of the interference filters used by the microradiometer channels, while the microradiometers help to correct

dark-current drifts and nonlinearity in spectrograph measurements. The capability of radiance sensors is further

enhanced by a nine-position filter wheel and integrated

camera. In the standard configuration, the filter wheel

permits hyperspectral polarimetric measurements, directSun viewing, stray-light correction, dark current measurements, and a home position. The video camera is used

for locating the Sun and verifying the condition of all targets (cloud-free solar and lunar disks, cloud presence in

sky data, and sea surface debris or foam detection). The

components of each radiance and irradiance sensor type

are integrated in a common housing that is environmentally sealed, nitrogen purged, and temperature controlled.

Synchronous and asynchronous sampling modes measure

the sea, Sun, and sky, across a wide spectral range (UV–

SWIR). The OSPREy architecture is modular and scalable, which permits the configuration (sensor inventory)

and complexity (sampling redundancy) to be matched with

science objectives and resource allocations. The modularity allows the observing system to expand or contract as

mission requirements evolve. These measurements support

an unprecedented number of current and next-generation

satellite missions involving both atmospheric and oceanic

data products.

† Note that “MMS” with regards to the MMS UV-VIS II and

MMS1 from Zeiss/Tec5 is defined as the “Monolithic

Miniature-Spectrometer,” and is not to be confused with the

MMS from Biospherical Instruments Inc., which is the Multiple Microradiometer System.

5
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 1

The OSPREy System Concept

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

John H. Morrow

Biospherical Instruments Inc.

San Diego, California

Abstract

The primary objective of the OSPREy activity is to develop and deploy a new class of commercial radiometers

to support existing and next-generation NASA ocean color satellites. An EPIC sensor is a hybridspectral device

combining measurements of spectral irradiance and radiance from recently developed microradiometers with a

commercially available hyperspectral spectrograph plus a pointing system. Over common parts of the spectrum,

fixed-wavelength microradiometers and the spectrograph can be continuously intracompared to maintain stability and accuracy of the system. Radiance sensors have a nine-position filter-wheel assembly in line with the

spectrograph fiber optics to permit hyperspectral polarimetric measurements (three polarized filters), direct-Sun

viewing (neutral density filters), stray-light correction (395 nm cut-on filter), and dark current measurements

(opaque disk). Radiance sensors also have an integrated camera for locating the Sun and Moon (in lieu of a quadrant detector), as well as verifying the condition of all targets (cloud-free solar and lunar disks, cloud presence

in sky data, and sea surface debris or foam detection). All sensors include thermal stability control to increase

filter and detector stability and reduce drift. The field sensor suite includes shadowband accessories to the solar

irradiance sensors, which are combined with radiance observations of the Sun, Moon, sea, and sky across a wide

spectral range—the UV, through the visible (VIS) and into the short-wave infrared (SWIR); 305–1,640 nm is the

full spectral range for radiance, as well as irradiance because of a new cosine collector design. The diversity of

targets and measurement types provides an unprecedented number of near-simultaneous atmospheric and oceanic data products. This new sampling capability is expected to improve a) the atmospheric correction of ocean

color data; b) the accuracy in satellite data products, particularly in optically complex (coastal) waters; and c)

the understanding of the interaction between the ocean and atmosphere. The combination of wide spectral and

dynamic ranges with accurate pointing are also anticipated to have application to terrestrial observations.

1.1 Introduction

Global ocean color satellites provide a revolutionary

capability for understanding Earth. Within a of couple

days, significant portions of natural systems are sampled,

and within only one week, even the vastness of the world

ocean—which covers about two-thirds of Earth’s surface—

is sampled with relatively minor cloud contamination. Although now considered a routine accomplishment, such a

global snapshot of the oceanic ecosystem still cannot be assembled with traditional sampling tools even if all the shipbased measurements throughout history are combined.

The ability to assess the world synoptically makes satellites an appealing tool for studying the oceanic contribution and response to climatic change. This approach requires a longevity and quality of the data in keeping with

the problem set, however, which means decadal and longer

time series are needed. Satellite missions are short in comparison; most have a five-year design lifetime, so sequential, multiple missions are needed. With sufficient mission

overlap and properly characterized sensors, one mission

can be properly intercompared to the next to ensure an

uninterrupted time series of CDRs.

Understanding how climatic change will influence oceanic systems is a major research theme of the NASA Ocean

Biology and Biogeochemistry (OBB) research program†.

† The long-term OBB programmatic objectives and research

requirements are articulated in a comprehensive Advance

Science Plan, On the Shores of a Living Ocean: The Unseen World, and is available from the following Web site:

http://oceancolor.gsfc.nasa.gov/DOCS.

6
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Global monitoring of the oceanic biosphere is accomplished

through the determination of radiometric variables. Specifically, the spectral radiances measured at the top of the

atmosphere, from which (after atmospheric correction),

the spectral radiances emerging from the surface of the

ocean, LW (λ), are derived (λ denotes wavelength). Considerable emphasis is placed on the accurate determination

of these so-called water-leaving radiances, because they are

the primary parameters in the inversion algorithms to derive the CDRs. For the latter, the most common algorithm

is the chlorophyll a (Chl a) concentration (O’Reilly et al.

1998), denoted [Chl a]†.

The development of a decadal time series has been

highlighted in a number of reports (Space Studies Board

2000). Although time series of key biogeochemical parameters date back to the 1978 launch of the Coastal Zone Color

Scanner (CZCS), the CZCS was a proof-of-concept mission

and is unsuitable for initiating a CDR time series. Almost

20 years later, a sequence of sophisticated ocean color missions were launched including the Sea-viewing Wide Fieldof-view Sensor (SeaWiFS) in 1997, followed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on

the Earth Observing System (EOS) Terra and Aqua platforms in 2000 and 2002, respectively (denoted MODIS-T

and MODIS-A, respectively). The development and maintenance of CDRs derived from these and other missions

must incorporate a sophisticated set of requirements before and throughout the lifetime of the satellite. The tasks

involved are usually organized into a single activity called

calibration and validation (Hooker and McClain 2000).

In remote sensing applications, calibration is frequently

defined as the prelaunch characterization followed by the

continuing analysis of the onboard sensor calibrators once

on-orbit operations commence, and validation is usually

thought of as the development of data processing schemes

(e.g., atmospheric correction and derived quantities), plus

the verification of product accuracies using in situ data.

The OSPREy activity is primarily concerned with calibration, although aspects of the envisioned system are applicable to validation activities.

Aside from absolute system response versus radiance

calibration, several characteristics must be quantified for

each instrument channel prior to launch: polarization, temperature, linearity, stray light, electronic crosstalk, bandto-band spatial registration, and response versus scan angle. Uncertainties in these parameterizations are almost

impossible to separate on orbit because their effects are

convolved and many are a function of solar and sensor

viewing geometries. All of these tasks are important, and

in most cases properly planned before launch, but the pressures to launch on time usually result in a compromised

† In fact, radiometric inversions to derive chlorophyll are made

with respect to the total chlorophyll a concentration, which

is denoted [TChl a]; the latter are typically determined using

high performance liquid chromatography (HPLC).

understanding of sensor performance. The severe launch

conditions and the harshness of space can alter the anticipated capabilities of the spaceborne sensor, regardless of

how thoroughly it was characterized before launch. Consequently, a vicarious calibration is performed after a sufficient time permitting the collection of an adequate number

of ground-truth—more properly, sea-truth—observations.

Approximately 30 contemporaneous matchups of clear-sky

in situ measurements and glint-free satellite images are

typically needed to derive a fixed set of calibration gains.

1.1.1 Vicarious Calibration

Regardless of how sea-truth data are acquired, accurate measurements are required. The most recent SeaWiFS validation results show the satellite normalized LW

(412–555 nm) and [Chl a] values are within 5% and 8%

of observed values, respectively, for waters deeper than

1,000 m (Bailey and Werdell 2006). This level of agreement significantly satisfies the performance specification

first established for SeaWiFS (Hooker and Esaias 1993)

and adopted by most missions thereafter.

A likely reason for the success of SeaWiFS is simply

good planning. Early in the mission, the SeaWiFS Ocean

Optics Protocols (hereafter referred to as the Protocols)

were drafted to ensure the potentially large variety of field

measurements were in keeping with the remote sensing accuracy requirements. The Protocols initially adhered to

the Joint Global Ocean Flux Study (JGOFS) sampling

procedures (JGOFS 1991) and defined the standards for

SeaWiFS calibration and validation activities (Mueller and

Austin 1992). Over time, the Protocols were initially revised (Mueller and Austin 1995), and then updated on essentially an annual basis (Mueller 2000, 2002, and 2003).

The methodology for vicarious calibration began with

the Protocols. Some of the procedures are best described

as assertions, i.e., they were not the direct result of a

field or modeling exercise that quantitatively established

why certain practices had to be adopted—they were simply stated. Some assertions were not applied and were

discarded. For example, the original vicarious calibration

concept required radiometric profiles to be collected during a dedicated cruise shortly after launch when routine

satellite operations had commenced (Clark et al. 1997 and

Gordon 1998). The long-term stability of the gains from

the initialization cruise were to be monitored with a radiometric buoy. Initialization cruises were only executed

for SeaWiFS and both MODIS instruments, but the data

were ultimately used for validation purposes—not vicarious calibration—and all three satellites relied on Marine

Optical Buoy (MOBY) data (Clark et al. 1997) to set the

first, and all subsequent, gains.

The evolution of MOBY from a monitoring instrument

into the only source of vicarious calibration data establishes the concept that the entire process can—and probably should—evolve. Recent attempts to continue the

7
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

evolutionary process includes the study by Werdell et al.

(2007) who demonstrated the feasibility of using a Case-1†

model to derive ocean-surface reflectance for determining

the target LW (λ) values for vicarious calibration. More

recently, Bailey et al. (2008) used data from COTS profiling radiometers (Werdell and Bailey 2005) and a buoy

with COTS sensors (Antoine et al. 2008) to show: a) satellite gains from COTS instruments are comparable to those

from MOBY (the uncertainties for both are essentially the

same); b) a simulated COTS version (multispectral 10 nm

bands) of the hyperspectral MOBY data produced gains

very similar to the full resolution data; c) even without addressing a finite near-infrared (NIR) radiance, data from

waters with [Chl a] up to 0.7 mg m−3 can be used, and

if any NIR radiance is appropriately removed, [Chl a] as

high as 1–3 mg m−3 is satisfactory; and d) aerosol type

and concentrations are not as critical as current criteria

suggests. In summary, a number of the key vicarious calibration requirements, specifically those for low chlorophyll

waters, low aerosol atmosphere, and radiometric resolution sufficient to match the spectral response functions for

the satellite instrument to be calibrated, can be relaxed

without seriously compromising the calibration effort.

A large number of sea-truth and satellite data pairs

are needed for statistical confidence in both calibration

and validation activities. For most latitudes, coverage is

every other day and clouds interfere significantly, so a site

with continuous operation is an advantage. To produce

the needed matchups in a reasonable time period, multiple sites are preferred. For nontilting satellites, additional

data is lost from sun glint during a substantial part of the

year. For these missions, sites in both hemispheres are advantageous, which means an easily replicated capability—

both in terms of hardware and cost—is desirable. In addition, if a sensor has an uncharacterized geometric sensitivity (e.g., polarization), the vicarious calibration from

a particular site will be tuned to the restricted range of

geometries encountered at that location; an easily replicated and deployable system will probably be needed to

collect data across the full range of geometries to address

the problem.

1.1.2 Above- and In-Water Sampling

A simple strategy to ensure replicability is to be able

to buy the needed equipment outright from an existing

supplier, which also lowers the cost. The basic requirement of providing accurate LW (λ) values can be satisfied

by making above- or in-water radiometric measurements.

As discussed in more detail in App. A, the average level of

agreement between contemporaneous above- and in-water

† By definition, the optical properties of Case-1 waters are

solely determined by the phytoplankton and its derivative

products (Morel and Prieur 1977), whereas Case-2 optical

properties are also determined by other material, e.g., from

terrestrial or bottom origin.

determinations of LW (λ) is to within a) the uncertainty of

the instrument intercalibrations (2–3%), and b) the intercomparisons derived from simultaneous in-water deployments (also 2–3%).

Returning to the need for a system easily deployed to

multiple sites or new locations, a compact system satisfies this need more readily than a large and cumbersome

system. Above-water systems are inherently the easiest

to deploy, because they are mounted on existing offshore

structures; in-water instruments, in comparison, usually

must provide their own mounting platform, which is usually a very large buoy. In terms of a cost-benefit analysis,

an above-water approach offers several other advantages:

• Deploying the radiometers on an existing offshore

tower already built and maintained by another group

or agency ensures significant cost savings;

• A tower provides a very stable platform and deterministic solar geometry for mounting instruments, so

there are no ill effects from sensor motion, and additional instruments can be readily deployed to ensure

the most comprehensive data set possible;

• Fouling is a minor problem, and if the sensors are

stowed after use, the particle deposition is minimized;

• Acquiring high-quality data in the red, as well as

the near-infrared, parts of the spectrum is easier to

achieve with an above-water system; and

• An offshore structure offers substantial protection for

the instruments against foul weather and maritime

hazards (most buoys have experienced long data gaps

because of storm damage or ship collisions).

The latter is a significant cost advantage. In-water moorings, for example, are usually replaced more than once, if

deployed for any length of time, from ship collisions.

The follow-on requirements for the system introduced

in this section are derived from a) the mission concepts

and research questions already discussed; b) the aforementioned recent results obtained from actual and simulated

COTS instrumentation, as well as the ocean-surface reflectance model (ORM); and c) the need to satisfy existing protocols for vicarious calibration, but reinterpreted in

terms of viable COTS alternatives to the MOBY paradigm

(App. B). Given the trade-offs between all of the different

possible ways of measuring LW (λ), it seems most reasonable to use a method that is the least likely to have any

inherent biases and to check it with as many other methods as possible. If this is the objective, an above-water approach is the least likely to have any biases, because it has

almost no fouling and the derivation of LW (λ) has almost

no subjective parameters. The asserted best approach—an

in-water buoy—is probably the most likely to have biases,

because of fouling and surface effects on the shallow sensors; it is also the most likely to have data losses, because

of bad weather, recreational boaters, and ship collisions.

Quantifying the capability of towers equipped with an

above-water instrument is an important achievement, but

8
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

it is made more convincing if results can be confirmed using a different procedure and with a vicarious calibration

objective. A system for acquiring autonomous above-water

radiance data, based on a commercial sun photometer and

called the SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM), was field commissioned

at a tower (Hooker et al. 2000) and assessed for the validation of satellite products in coastal waters (Zibordi et al.

2002b). A one-year time series was compared with simultaneous in-water measurements for a wide variety of conditions. The average relative percent difference (RPD†)

values between the two LW (λ) determinations were less

than 2% in the 412–555 nm spectral interval (Zibordi et al.

2004b). More importantly, the vicarious calibration gains

for SeaWiFS derived from MOBY and SeaPRISM data

agreed to within 1% in the 412–555 nm domain, and to

within 2% at 670 nm.

1.1.3 Future Challenges

Accurate vicarious calibration is not the only prerequisite in the production of CDRs; accurate atmospheric

correction is equally important, because a) it is convolved

with the vicarious calibration process, and b) the oceanic

signal is an order of magnitude less than the total radiance

observed by the satellite sensor. Two unresolved issues in

the ocean color data processing are the detection and correction of moderate concentrations of absorbing aerosols

and finite NIR reflectance in turbid waters‡. Methods are

being developed to address both, but limitations due to

the sensor designs exist and some methods are simply too

computationally intensive to use in a routine global processing capability. For example, the NIR reflectance issue

may be addressed in MODIS processing by using bands

above 1.2 μm (SeaWiFS has no bands above 865 nm), even

though these bands do not have the desired signal-to-noise

ratios (SNRs) for this application (McClain et al. 2006).

A future challenge will be to maintain the level of success achieved in deep-ocean, so-called Case-1, waters in the

coastal ocean and marginal seas—The Advanced Science

Plan, for example, has many mission themes and research

questions associated with the coastal zone. This emphasis on shallower water means investigating the optically

more complex Case-2 environment and understanding the

influence of dissolved and particulate constituents will be

increasingly important (Hooker et al. 2007).

Bio-optical algorithms (e.g., Chl a) primarily rely on

empirical relationships and have inherent limitations because of absorbing substances that do not covary with

† The RPD is computed as the difference between an observation (xo) and reference (yr) value, normalized by the reference value, and then expressed as a percent: 100(xo−yr)/yr.

‡ In open-ocean waters, the NIR signal is negligible and this

black response was used in the past (e.g., with CZCS) to

produce a simplified atmospheric correction scheme.

the parameter of interest (Siegel et al. 2005). As coastal

research matures, it is anticipated that UV wavelengths

might be exploited to distinguish the absorption signals of

colored dissolved organic matter (CDOM), Chl a, detritus,

and minerals (because of high UV absorbance by CDOM

relative to the other components), yielding new algorithms

for coastal waters. Furthermore, UV bands may promote

the detection of harmful algal blooms, such as red tides,

because they produce UV absorbing compounds known as

mycosporine-like amino acids (Laurion et al. 2003).

The shortest wavelength used by SeaWiFS and both

MODIS instruments, as well as their successor the National

Polar Orbiting Environmental Satellite System (NPOESS)

Visible and Infrared Imaging Radiometer Suite (VIIRS),

is 412 nm. Future missions will need to include additional

measurements down to about 345 nm, to improve the separation of various pigments and the contributions of covarying constituents. In addition, future algorithms will

be based on semi-analytical models and inherent optical

properties (IOPs). Although this evolution might ultimately alter the vicarious calibration approach, the immediate future will require a continuation of relying on direct

measurements of the apparent optical properties (AOPs)

of seawater. A benefit from adding UV bands will be the

possibility of using them to flag and improve atmospheric

correction algorithms in the presence of absorbing aerosols.

Despite their many valuable contributions, legacy ocean

color sensors use a measurement approach developed in the

1970s, while the scientific and analytical capabilities being

applied have evolved substantially. The next generation of

satellites, which does not include VIIRS because its specifications have already been set, will require a technological

maturation in remote sensing.

Two of the most important objectives currently being

planned for future ocean color missions are a) an improved

ability to accurately separate the living and nonliving components of marine ecosystems, and b) a clear understanding of the interaction between the ocean and atmosphere.

The National Academy of Sciences (NAS) Earth Science

Decadal Survey acknowledged the importance of these objectives by proposing the Aerosol-Clouds and Ecosystems

(ACE) mission, which includes the added capability of

also measuring the cloud contribution to atmospheric forcing. Regardless of the final satellite mission configuration,

both of these future objectives are the most challenging in

coastal (heterogeneous) waters where the scales of motion

are necessarily shorter, so an enhanced spatial or temporal

sampling capability is anticipated.

Also important is extending the range and resolution

of the measurement wavelengths, while including a suite

of ground-truth sensors to simultaneously characterize atmospheric aerosols and oceanic optical properties. The culmination of a coupled ocean–atmosphere observational system is expected to allow investigators to correlate changes

in ocean ecosystems with individual components and environmental forcing, and then to integrate that understanding into biogeochemical models.

9
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

EML

EME

Lamp-based Sun-based

SIRCUS

FASCAL

Method 1

Method 2

Method 3

OXE

Fig. 1. The OSPREy system from an instrument and calibration perspective showing (left) two dyads

of sensors (denoted A and B), each containing one irradiance sensor (with shadowband accessory) and one

radiance sensor, and (right) the three calibration methods. The pedestal mounting is for illustrative purposes,

as are the pointing angles and shadowband positions. The shrouds on the radiance sensors are not illustrative;

they minimize unwanted scattering of direct sunlight on the detector during sky measurements.

1.2 System Concept

Based on the increased likelihood of combined oceanic–

atmospheric satellite missions, the established capabilities

of COTS radiometers, and the demonstrated success obtained with above-water radiometry, the primary objective

of an OSPREy system is to satisfy all three of these aspects as design requirements for vicarious calibration and

algorithm validation (Fig. 1). OSPREy system configurations are based on EPIC radiometers, which have a cluster of microradiometers (Morrow et al. 2010a) combined

with a spectrograph to increase spectral resolution, primary and secondary thermal regulation to enhance accuracy, and other unique features (Sect. 1.3).

As noted earlier, legacy sensors were built primarily

for specific light sources and sampling targets, whereas an

OSPREy system has a tracker to allow sampling of a multitude of sources and targets. For brevity and specificity,

an individual radiance (L) and irradiance (E) instrument

from this so-called EPIC Multitarget Radiometer (EMR)

product line is denoted as EML and EME, respectively.

This same naming approach is also used for a radiance

and irradiance sensor within the OSPREy Transfer Radiometer (OXR) instrument class as the OXL and OXE,

respectively.

The system configuration for the development activity

(Fig. 1) has the following design elements and capabilities:

Two duplicate EMR sensor pairs intercompared to

enhance data quality and minimize temporal gaps

(Sect. 1.5.5.2), recalling that intracomparisons are

possible within an instrument with two overlapping

detector systems;

Programming scenarios (Sects. 1.3.2 and 8.6) preventing any loss of data products if one or more radiometers in a set malfunctions (some of the intercomparison capabilities will be lost);

Extensively characterized and intercompared calibration facilities for the radiometric sensors (App. C);

Three EML or EME calibration methods, wherein

two are based on lamps (SIRCUS calibration transfer

to a lamp with an OXE and a FASCAL lamp calibration) and one based on the Sun (Langley method);

Traceability to NIST with the OXR, which is also

based on enhanced COTS instrumentation (Chap. 2),

plus a lamp library (Chap. 6) is used to help maintain

the calibration of OXR instruments;

A set of ancillary sensors for meteorological measurements useful to calibration and validation activities

and for detecting hazardous conditions (App. D);

Biospherical Shadowband Accessory for Diffuse Irradiance (BioSHADE) accessories on the irradiance

sensors support atmospheric measurements (App. E

and Morrow et al. 2010a);

A pointing and tracking unit (Chap. 5) to provide the

needed metrology for sea and sky radiance measurements (App. A), plus Sun and Moon data products;

Monthly calibration monitoring in the field with a

portable light source;

Autonomous operations using hybrid (e.g., solar and

wind) power and COTS data telemetry (App. F); and

Prototype testing at a controlled and easily accessed

site (App. G) and operational deployment on an offshore structure to reduce infrastructure costs and enhance survivability (App. H).

OSPREy systems are complex with many nuances to understand. To aid the reader, an FAQs section is provided.

In addition to developing hardware, an objective of the

OSPREy activity is to develop a well-documented method

for providing high-quality calibration and validation data

10
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Fig. 2. Deployment of the OSPREy system with many of the components required for operations: two

EMR dyads at the top of an offshore tower measuring the atmosphere and the ocean; an ocean color satellite

(SeaWiFS) sampling the on- to off-shore gradient (green to blue) in productivity; the Sun and Moon as

calibration targets for SeaWiFS and OSPREy; a telecommunications satellite for data telemetry from the

platform sensor suite (including meteorological sensors), which are all powered by solar panels and a wind

generator; a shore-based calibration and logistical support facility, including test capabilities at a pier; and

monthly validation (including in-water AOP profiles) and maintenance visits with a small boat.

from remote (offshore) platforms. The important subelements of this development are an extension of the sea-truth

data collection into the SWIR domain to support future

NASA missions; a capability for producing atmospheric,

in addition to oceanic, data products; and the incorporation of a stronger methodology for calibrating radiometers

used in satellite calibration and validation (App. I).

The improved calibration approach helps ensure the

uncertainties in the measurements are properly minimized

(App. J). The adopted technique—the production of a

transfer radiometer—involves a shift in methodologies from

lamp-based to detector-based references used for calibrating field radiometers, which is more aligned with current

practices at NIST. Another aspect of the main objective is

the production of a protocol that can provide the needed

parameters, complete with analysis and quality-controlled

data delivery, at significantly lower costs. A summary depiction of two EMR dyads deployed on a platform is presented in Fig. 2 (recalling that platform-induced perturbations must be avoided, as described in App. K) with

an anticipated third spare set of calibrated sensors available for deployment if needed on the monthly maintenance

visits (not shown). An example of an appropriate site is

presented in App. L.

1.3 Sensor Descriptions

The enhancements to the COTS sensors to produce

EMR sensors involves the following:

1. The newest three-gain-stage microradiometer design

(Chap. 2);

2. Channels in the SWIR domain for applicability to

future missions with a modified cosine collector and

new detector filter combinations;

11
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Fig. 3. An EMR configured for radiance measurements, or EML, shown without a shroud and revealing the 19

microradiometers arranged in a central cluster, which is thermally regulated, with the Gershun-tube assembly

to the left and the aggregator electronics to the right. The spectrograph with thermal regulation connects to

a nine-position, filter-wheel assembly with a fiber-optic cable and has its own Gershun-tube assembly. The

digital camera has an exit aperture on the other side of the filter-wheel assembly. The end cap also contains

the spectrograph support electronics.

3. A new diffuser design for the irradiance sensors permitting a single cosine collector (Chap. 3) to cover

the UV to SWIR spectral domain (290–1,670 nm);

4. Modification of the radiance entrance optics for a

smaller FVA of 2.5◦ (Chap. 4) in compliance with

sun photometry requirements (WMO 2003);

5. A spectrograph with an optical fiber front-end sampling through the entrance optics (Chap. 7);

6. Thermal stability control to increase filter and detector stability and reduce drift;

7. A pressure transducer to monitor the internal pressure of the positively-pressurized, dry-nitrogen atmosphere of radiometer housings;

8. An integrated camera for locating the Sun and Moon

(in lieu of a quadrant detector), as well as verifying

the condition of all targets, i.e., cloud-free solar and

lunar disks, cloud presence in sky data, and sea surface debris or foam detection (although an irradiance

sensor can also detect if clouds are obscuring the solar

and lunar disks†); and

9. A nine-position, filter-wheel assembly positioned in

front of the spectrograph fiber optics to provide hyperspectral polarimetric measurements (three polar-

† The direct irradiance in the long wavelengths changes dramatically when clouds move in front of the Sun or Moon.

By monitoring changes in the 1,640 nm channel when pointing at the Sun or Moon, a quantitative measure for cloud

contamination is obtained.

ized filters), direct-Sun viewing (ND filters), straylight correction (395 nm cut-on filter), and dark current measurements (opaque disk).

All but the last two items are also incorporated into the

functionally similar OXR instruments, which are designed

for application in the calibration laboratory. Aspects of the

very last item are also provided by an anticipated all-sky

camera for OSPREy systems.

An engineering drawing of an EML (radiance) sensor is

presented in Fig. 3. An irradiance sensor has only 18 aggregated microradiometers—as do all OXR units—because

one of the microradiometer positions is replaced with the

fiber optics for the spectrograph. An irradiance sensor

does not have the filter-wheel assembly or the integrated

camera (as well as the Gershun-tube assembly).

1.3.1 Hardware

The addition of the spectrograph permits sampling of

the spectrum in regions not covered by the filtered detector channels, and allows the spectrum of calibration

sources to be scanned for unwanted emission lines. Furthermore, the advantage of the higher resolution of the

spectrograph can be combined with the superiorities of

the fixed wavelength microradiometers—greater dynamic

range, lower stray light, improved SNR, and higher scan

speed—to provide a sensor combination superior to either

of the individual constituents alone.

Future satellite missions are planned that will push the

spectral coverage toward both shorter wavelengths, as well

12
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

as out into the SWIR region. To gain experience with this

expanded spectral requirement, the complete band set for

both types of prototype EMR sensors is as follows: 340,

380, 412, 443, 490, 510, 532, 555, 589, 625, 665, 683, 710,

780, 875, 1,020, 1,245, and 1,640 nm. The EML sensor has

an additional 395 nm channel.

Environmental control is critical for longevity of interference filters, in particular, and electronics, in general.

Because interference filters are composed of complex layers of differing materials, some mismatch in coefficients of

expansion are inevitable; oxygen can also cause degradation through oxidation. For sensors built with MMS technology, the interference filters are manufactured with ion

deposited TiO2, which BSI has found to have superior—

although not perfect—stability. To improve upon this stability, two enhancements are used: a) protecting against

temperature transients by using custom thermal regulation

from additional insulation and a temperature controller;

and b) maintaining an internal atmosphere devoid of oxygen and moisture, which is made possible with hermetic

seals and internal pressure monitoring.

The electronics are installed in a weatherproof enclosure, and selected for low power dissipation to avoid active cooling requirements. OSPREy dyads are controlled

by ruggedized microprocessors selected for low power consumption. The microprocessors are controlled by a master

computer, that coordinates the measurements of all sensors (Sect. 1.3.2), stores the data, and transfers it via the

Internet. If no high-bandwidth Internet connection exists

(e.g., on a remote platform), data can be written to an external hard drive which is swapped during monthly visits.

An OSPREy system is monitored by a security camera

known as an IP camera, because it connects directly to

an Internet connection. The camera is mounted above the

plane of the EMR sensors (several meters away and not

in the direct-Sun path), and is able to zoom in to inspect

both radiance windows and irradiance collectors for signs

of contamination. The camera can generate an event (start

a recording and e-mail a photo) when something moves in

the field of view (FOV). The degree of motion can be set,

and it should be able to respond to bird activity, unauthorized visitors, etc. Prior to site visits or in the event of

system failures, it can aid in diagnosing problems (e.g., a

radiance sensor does not point correctly).

The camera also addresses a coastal sampling problem:

towers and buoys are known by fisherman as fish attraction devices (FADs), because they attract fish. Having the

camera record the ocean viewed by the radiometer can help

explain anomalous measurements. Furthermore, it should

enable engineers back at BSI to aid in site repairs or monitor site visits if local staff are used.

1.3.2 Software

The OSPREy system is designed with a variety of sampling modes optimized for coincident measurements during stable illumination and satellite overpass. Additional

modes are used for producing the greatest number of quality assurance (QA) and quality control (QC) opportunities. For example, intercomparing data from the various radiometers, checking their calibration via the Langley

method, and retrieving secondary data products, such as

AOD. A summary of the modes in each sampling scenario

is provided in Table 1.

Table 1. Examples of when each operational mode

would be executed as a function of the anticipated

sampling scenario.

Scenario 1234

Night (nominal radiance) ×

Satellite overpass (±60 min) ×

Overcast (homogeneous) × ×

Clear-sky (no overpass) ×××

Overcast (night, irradiance) ×

Rain or extreme weather ×

During a satellite overpass, operation would be primarily mode 1, which is the usual mode for LW (λ) measurements. This requires sky, Li(λ), and sea, LT (λ), observations at the appropriate geometry with respect to the

Sun, as well as the correct nadir and zenith metrology

(recalling the previously established platform-perturbation

avoidance criteria). Shadowband observations are used

primarily to acquire the global irradiance, Ed(λ), and the

diffuse irradiance, Ei(λ), from which the ratio of direct-toglobal irradiance can be computed†. The latter is useful in

the derivation of atmospheric data products.

During other clear-sky conditions, modes 2 and 3 would

be run alternatingly. During overcast conditions, specialized versions of mode 2 would be executed, viewing either

the overcast sky or the sea. After an episode in this mode,

operation would continue with mode 1. Mode 4 is primarily associated with scenarios when the sensors would be

stowed, e.g., during severe weather.

During platform visits, additional modes would be activated to facilitate sensor evaluations (e.g., the portable

light source) and calibrations. Additional modes, either to

increase the data products or add additional redundancy,

can be added for special experiments (e.g., characterization

of skylight polarization).

1.4 Data Products

The field radiometers used in an OSPREy system measure quantities that can be directly compared with satellite data, as well as secondary products, which can be used

† The global irradiance is the sum of the direct plus diffuse

irradiance. The direct beam, E(λ), must be multiplied by the

cosine of the solar zenith angle, θs, to obtain the radiation for

a horizontal surface. Omitting the wavelength dependence

for brevity, Ed = E cos(θs) + Ei, and the ratio of direct-toglobal irradiance is E/Ed = (1 − Ei/Ed)/ cos(θs).

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

for atmospheric corrections of satellite retrievals. The full

suite of data products are partitioned according to their

radiometric sources.

1.4.1 Stationary Sensors

The primary data products of the stationary radiometers are downward global, diffuse, and direct (global minus

diffuse) irradiance between 340–1,640 nm. The spectrograph integral to irradiance radiometers measures the solar

spectrum from 305–785 nm with a resolution of 7 nm, and

the spectrograph integral to radiance radiometers measures the solar spectrum from 305–1,100 nm with a resolution of 9 nm. When occluding the Sun, a shadowband

also blocks a portion of the sky. The resulting systematic

uncertainty can be quantified by additional measurements

where the shadowband is positioned at ±10◦ away from

the solar disk. This method is routinely applied for correcting measurements of rotating shadowband radiometers

(Harrison et al. 1994 and Wesely 1982). A new and more

accurate correction method was recently developed (Bernhard et al. 2010), whereby the shadowband is moving at

a constant rate over the cosine collector. This method is

used with all OSPREy shadowband units.

Secondary data products include AOD and cloud optical depth, which are estimated from the difference of global

measurements for overcast and clear skies. The clear-sky

reference can be estimated from long-term measurements

or from radiative transfer (RT) calculations. The latter

method is well established and has been applied to measurements of multifilter radiometers (Dahlback 1996) and

spectroradiometric measurements (Bernhard et al. 2004).

1.4.2 Rotating (Sun-Tracking) Sensors

The primary data products of the radiometers on the

sun trackers are water-leaving radiances, direct-normal Sun

irradiance, and sky radiance for arbitrary zenith and azimuth angles. Secondary data products include the AOD,

aerosol single scattering albedo (SSA), total column, and

precipitable water vapor (PWV). The ratio of direct-toglobal irradiance can be calculated by comparison with

global irradiance measured by the stationary radiometers.

AOD is determined via the Langley technique or by applying the Beer-Lambert law to individual direct-normal

measurements. Both methods are well established (Schmid

and Wehrli 1995, and Schmid et al. 1999).

Aerosol  ̊Angstr ̈om parameters are calculated from AOD

measurements. Aerosol SSA is calculated from sky scans

along the principal plane and almucantar. Inversion algorithms were developed for the AERONET activity (Holben et al. 1998) network and can be adopted for OSPREy

(Dubovik and King 2000). These algorithms also allow for

the calculation of higher-level aerosol data products such as

the aerosol scattering phase function, the aerosol refractive

index (real and imaginary parts), aerosol size distributions,

and the radiative forcing induced by aerosols. Using the

polarization measurement capability of the spectrograph,

the polarization (Stokes vector) of sky and total sea surface

radiance can be determined. Alternatives for calculating

the SSA using look-up tables are being explored.

1.5 Quality Assurance Plan

Providing high-quality data with minimal uncertainties requires a comprehensive QA and QC plan. The OXR

instruments (Chap. 6) are initially characterized by BSI,

calibrated by NIST, and a rigorous uncertainty analysis

is performed (Sect. 1.5.1 and App. J). The calibration is

then transferred at BSI to other EMR instruments, as

well as to a set of lamp standards (Chap. 6) to preserve

the NIST scale of irradiance over the time span of the

project. All field radiometers, plus other major hardware

components, are redundant. The radiometers are automatically intracompared (microradiometers and spectrograph)

and intercompared (one instrument versus another) on a

daily basis to detect performance outside of selected control limits (e.g., elevated dark currents or calibration drifts)

on the day of occurrence (Sect. 1.5.3.). A portable light

source is used to monitor the radiometric calibrations during monthly site visits (Sect. 1.5.4).

In addition, natural targets including the Sun, Moon,

clear sky, and homogeneous clouds are regularly scanned

to verify correct operation across the dynamic range of

the sensors (Sect. 1.5.5). The applicable above-water data

products are also intercompared with in-water AOP products produced during monthly maintenance visits, shortterm intercomparisons with existing field sensors (e.g., a

SeaPRISM unit), as well as radiometers used in other networks for cross-network performance review (Sect. 1.5.5.2).

Software will ultimately be implemented that automatically generates alerts if individual instrument parameters

are outside control limits, or if sensor measurements do not

agree within control limits.

Finally, data will be reviewed by a scientist once per

week, corrected for known systematic uncertainties, compared with results from RT models, and reprocessed if

necessary. Performance metrics will be published in operations reports available on the Internet, and in peerreviewed papers for external review. The QA and QC

plan will be based on experience gained during 20 years

of operating the UVSIMN for the NSF (App. M).

1.5.1 Uncertainty Budget

The uncertainty of irradiance and radiance measurements of OXR and EMR sensors is composed of uncertainties related to the following:

1. Responsivity calibrations of the OXR by the NIST

SIRCUS facility;

2. OXR calibration transfers to EMR sensors (App. I);

3. Changes in responsivity over time;

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

4. Collector contamination (fouling);

5. The non-ideal cosine response of irradiance diffusers;

6. Transferring laboratory calibrations to field measurements (App. I) of Ed(λ), Ei(λ), sky radiance Li(λ),

and the total radiance at the sea surface LT (λ) for a

prescribed viewing angle (usually 40◦ or 45◦);

7. The nonlinearity of radiometer signals; and

8. Photon and electronic noise.

Additional uncertainties arise from the conversion of

LT (λ) and Li(λ) to LW (λ), with the latter defined as the

radiance emerging from the sea at nadir viewing. Uncertainties in this conversion procedure are related to the following:

9. Corrections for natural reflectance sources (e.g., glint

from Sun, sky, and clouds);

10. Corrections for anisotropy of the upwelling radiance

due to different viewing geometries for LT and LW ;

11. Perturbation from the observation platform; and

12. Surface waves plus other environmental effects.

A quantitative summary of the uncertainty contributions by all 12 of these sources is provided in Table 2, and

additional detail concerning the computation of uncertainties is given in App. J. The combined uncertainties range is

estimated to be 1.6–3.1%, with or without the contribution

of environmental factors, which meet the specifications required by the Protocols.

Table 2. Uncertainty budget for the OSPREy measurement parameters and principal radiometric data

product (LW ). All uncertainties refer to a 95% confidence level.

Uncertainty Source Ed Ei Li LT LW

1. SIRCUS calibration 0.2 0.2 0.2 0.2 0.2

2. Calibration transfer† 0.2 0.2 0.2 0.2 0.2

3. Responsivity changes 1.0 1.0 1.0 1.0 1.0

4. Collector contamination 2.0 2.0 1.0 1.0 1.0

5. Non-ideal cosine‡ 1.0 2.0

6. Calibration transfer§ 0.5 0.5 0.5 0.5 0.5

7. Nonlinearity 0.5 0.5 0.5 0.5 0.5

8. Photon and electronic noise¶ 0.1 0.1 0.1 0.1 0.1

9. Surface reflectance 0.7

10. Platform perturbation 0.3

11. Anisotropy correction 0.6

12. Environmental factors 2.5

1–11 Quadrature sum 2.6 3.1 1.6 1.6 1.9

1–12 Quadrature sum 2.6 3.1 1.6 1.6 3.1

† Transfer of the SIRCUS calibration to BSI.

‡ For solar zenith angles less than 70◦; the Ei value is

larger in the SWIR domain where the diffuse irradiance is very small.

§ Transfer of a laboratory calibration to the field.

¶ The Ed and Ei values are larger for the SWIR channels, because the diffuser is thicker.

1.5.2 Absolute Calibrations

Although not completed in time for this publication because of difficulties with personnel, scheduling, and equipment, calibration of the OXE instrument was initiated at

the NIST SIRCUS facility as part of the development activity. The calibration of the OXR and EMR sensors will

be published as a separate report (Bernhard et al. 2012).

A subsequent calibration of the OXL instrument is anticipated. A principal purpose of the OXE unit is to calibrate six 1,000W FEL lamps, which have three functions:

a) preserving the SIRCUS scales of irradiance over time,

b) calibrating other EMR sensors, and c) monitoring and

correcting temporal changes in the calibration of field radiometers.

Using calibration information obtained in the laboratory, conversion factors are calculated to convert the radiometric raw data obtained in situ (typically measured

in volts or digital counts) to spectral irradiance or radiance. The method takes into account the change of the

solar spectrum within the bandpass of the individual instrument channels, as well as the variation of this change

as a function of atmospheric constituents (e.g., ozone and

water vapor), sensor biases such as residual cosine error,

as well as components in the water (e.g., Chl a and CDOM

concentrations).

OXR instruments are used on a recurring basis to monitor the calibration of EMR instruments deployed in the

field, when the latter are returned to BSI for calibration

and maintenance. The absolute calibrations of field radiometers in the field are checked on a monthly basis with

the portable light source, and the portable light source is

checked before and after field use with the OXR sensors.

Daily checks for changes in responsivity are performed by

comparing the various EMR instruments. The number of

comparisons depends on the system configuration. The

simplest is an intracomparison of the spectrograph and

microradiometers, followed by redundant sensor intercomparisons (i.e., two types of instruments that are the same),

and then two types of instruments that are different (i.e.,

radiance and irradiance), but can be used to produce the

same data product. More details on absolute calibrations

and the transfer of lamp calibrations to solar measurements

are provided in App. I.

1.5.3 Hardware Redundancy

Redundancy is a central aspect of the built-in reliability of the OSPREy system being built for the development

activity. In addition to the functional security duplicate

hardware provides (radiometers, shadowbands, and tracking systems), a high level of intercalibration between the

instruments can be supported by replicating the data products with simultaneous individual measurements. The latter is effective in calibration QA, and also in detecting most

kinds of sensor drift, mechanical problems in the tracking

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

mechanisms, and certain types of system wiring and power

problems.

An additional layer of functional redundancy is provided if a third set of fully characterized radiometers is

available for exchange during monthly maintenance and

sampling visits, either in response to unanticipated problems or scheduled replacement (to minimize the chance

of failures). Rotating new sensors into the system allows

a sensor set with a fresh calibration to be automatically

compared with the older sensors. Note, when multiple OSPREy systems are deployed in the future, the third set of

radiometers (and other spare components) can be shared

between installations.

To control cost and complexity, not all components

of an OSPREy system are redundant, because commercially manufactured components such as personal computers, satellite downlink terminals, and power distribution

systems can be designed and tested to ensure a reasonable

degree of robustness. In this case, computers with redundant, high-quality power supplies and a redundant array

of independent drives (RAID) are used. Power generation

redundancy can be designed into the solar and wind components so that a failure in one part of the power system

still permits partial OSPREy system operation at reduced

power levels.

1.5.4 Portable Light Source

For lengthy deployment time periods, a portable light

source is useful for monitoring instrument response in the

field. For OSPREy, the source needs to be usable with

both the radiance and irradiance EMR sensors, over the

full spectral range of interest (UV–SWIR). To facilitate

use on a remote platform, it needs to be fully self-contained

(except power), and able to be modified to match the OSPREy kinematic mounts. In addition to the support electronics (regulated power supply), the portable source needs

monitoring photodetectors to ensure the output is stable

and repeatable.

Several portable sources have been produced, which are

based principally on the SeaWiFS Quality Monitor (SQM),

which was developed with NIST more than a decade ago

(Johnson et al. 1998). Although shown to be capable of

monitoring radiometric performance to within 1% (Hooker

and Aiken 1998), the SQM design was not as portable as

desired for OSPREy systems, and it did not have sufficient

flux in the UV and blue parts of the spectrum for the

wavelength range of interest now.

A likely portable source to be used for the OSPREy activity is the Portable Universal Radiometer Light Source

(PURLS) manufactured by Hydro-Optics, Biology & Instrumentation Laboratories, Inc. (Tucson, Arizona). The

PURLS device uses light-emitting diodes (LEDs) to provide a tunable output with a whiter spectrum than can

be achieved with an incandescent source. It provides sufficient flux across 340–875 nm, but does not support the

UV-B and SWIR wavelength domains in its default configuration.

The PURLS unit also has minimal power consumption (150W for full-spectrum output), rugged and weatherresistant construction, minimal weight (15 kg), small size

(30×30×30 cm3), and easy adaptability to both irradiance

and radiance sensors. It has an “auto-adjust” feature to

improve its long-term stability. Preliminary tests indicate

that the feature can keep the output constant to within

±0.2% over a time period of six months. The device is

currently still under evaluation (results will be published

in a subsequent report).

1.5.5 Product Validation

Validation of the various radiometers and their corresponding data products are conducted during all test

deployments (App. G), where possible, and in particular

during the operational testing phase (App. H); the latter

includes a platform-perturbation mapping of the selected

offshore structure (App. K). The primary sources of validation data are natural targets under a variety of illumination

conditions, to ensure the full dynamic range of the sensors

are validated, plus above- and in-water intercomparisons

with independent observational systems.

1.5.5.1 Natural Targets

The stability of the EMR field instruments is monitored

with the portable source plus regular scanning of natural

targets including the Sun and the Moon, as well as homogeneous skies during twilight, overcast, and cloud-free

conditions. By measuring the direct-Sun irradiance with

the tracker-mounted radiometer and the shadowband radiometer at different air masses, the irradiance at the top

of the atmosphere, E0(λ), is regularly calculated based on

the Langley technique (Schmid and Wehrli 1995). This

method is operationally used by the UV monitoring of the

U.S. Department of Agriculture (USDA) network for tracking calibration changes of rotating shadowband radiometers over time (Slusser et al. 2000, and Bigelow and Slusser

2000), and can identify changes in responsivity of approximately 1% per year.

This same technique is also applied to direct-Moon

measurements for monitoring stability at low light levels.

Measurements at twilight, low Sun, and overcast conditions are used to detect any changes in the linearity of the

radiometers. For example, consecutive measurements with

different gain settings allow the detection of drifts in amplifier offsets and scale factors. By scanning across the solar

disk in small angular increments, the tracking accuracy of

the sun tracker is regularly checked.

1.5.5.2 Validation Intercomparisons

Because EMR radiometers are capable of making a

wide variety of measurements, there are necessarily a diversity of options for validating OSPREy measurements. The

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

following instruments can be used to provide independent

observations of EMR measurements:

• The SUV-100 spectroradiometer, which is a part of

the UVSIMN and installed at the BSI rooftop facility.

The instrument measures Ed(λ) between 280–600 nm

with a 1.0 nm bandwidth (Booth et al. 1994). Data

are corrected for the instrument’s cosine uncertainty

and have a wavelength accuracy to within 0.02 nm

(Bernhard et al. 2004).

• A sun photometer designed to measure solar irradiance and AOD. Possible applicable instruments include the CIMEL CE-318 photometer of the type

used in the AERONET activity and a Middleton Solar SP02 instrument used by the NOAA Earth System Research Laboratory (ESRL).

• The Multi-Filter Rotating Shadowband Radiometer

(MFRSR) for measuring global and diffuse irradiance at seven channels in the visible domain built by

Yankee Environmental Systems (Turners Falls, Massachusetts) to validate the BioSHADE approach.

• An above-water radiometric sampling system such as

an automated SeaPRISM or the Biospherical Surface Optical Reflectance System (BioSORS), which

is manually pointed (Hooker et al. 2010a).

• An in-water system called the Submerged Biospherical Optical Profiling System (SuBOPS), which is

radiometrically identical to BioSORS (Hooker et al.

2010b), or the newer Compact-Optical Profiling System (C-OPS), which is built from microradiometers

(Morrow et al. 2010b). These instruments are floated

away from the deployment platform to avoid perturbations to the light field. The buoyancy can be adjusted using a so-called hydrobaric system for a very

slow descent rate and the vertical orientation can be

trimmed using counterbalances (floats, weights, and

the sensor orientation), which provides excellent vertical resolution (approximately 1 cm or less) and a

capability to collect data in shallow water.

All these instruments exist, but the principal automated

instrument in use to derive LW (λ) using the above-water

LT and Li approach is the eight-channel SeaPRISM unit.

1.5.5.3 Comparative Technology Assessment

Following are the OSPREy technologies that enable it

to have significantly better performance than the technologies presently available for validation:

1. EML microradiometers measure all wavelengths simultaneously more than an order of magnitude faster,

which allows LT filtering for surface wave effects (a

SeaPRISM unit has a data sampling rate that is too

slow for significant filtering).

2. For two radiance sensors in a dyad (Fig. 1), LT and

Li can be measured simultaneously, which reduces

glint correction uncertainties. For one radiance sensor (a SeaPRISM analog), LT and Li are measured

to within 5 s, because of the high angular velocity of

the tracker (50◦ s−1).

3. OSPREy systems permit seamless integration of a

solar reference. By measuring Ed(λ) rather than estimating it from direct-Sun data (as is the case with

SeaPRISM), normalized LW (λ) data products (e.g.,

the remote sensing reflectance, Rrs), have smaller uncertainties.

4. The use of InGaAs detectors for the SWIR domain allows OSPREy channel options to span 340–1,640 nm

(the CE-318 uses a single silicon detector, which is

radiation insensitive beyond 1,100 nm).

5. OSPREy spectrograph measurements offer a more

accurate mechanism to interpolate between the measurements of the filter wavelengths than is possible

with SeaPRISM.

6. OSPREy has three polarizers (0, 45, and 90◦) for sky

and sea Stokes vector determinations (SeaPRISM can

have one polarization wavelength, but that reduces

the wavelengths to six).

The only commercial shadowband unit that is similar to an

OSPREy EME instrument is the aforementioned MFRSR

from Yankee Environmental Systems. The MFRSR is used

in the USDA UV-B Monitoring and Research Program

(Harrison et al. 1994), but OSPREy shadowbands have a

higher sampling rate, larger spectral range, more channels,

and larger dynamic range.

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 2

Application of Microradiometers to EMR and OXR Sensors

Randall N. Lind, Charles R. Booth, Germar Bernhard, and John H. Morrow

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

Microradiometers are small, fast, reliable, and cost-effective radiometers that are composed of a filter, photodetector, wide-range electrometer, analog-to-digital converter (ADC), microprocessor, and digital interface.

Microradiometers were originally developed for in-water profiling systems and were adapted to the requirements

of OSPREy applications by increasing their dynamic range to over 10 orders of magnitude with excellent (better

than 1%) linearity over this interval. The devices now support measurements of both very bright sources like the

solar disk and comparatively very dim sources like the ocean, calibration targets, and lunar disk. The circuitry

was further modified to handle both silicon diodes for UV-VIS measurements and InGaAs photodetectors for

measurements in the SWIR domain. The Multiple Microradiometer System (MMS) architecture allows clusters

of up to 19 tightly-packed microradiometers to be networked together using an aggregator, such that the multitude of sensors can be controlled as a solitary device. The aggregator also provides an interface to external

devices, such as temperature controllers and filter-wheel stepping motors used in EMR instruments. Compared

to legacy platforms, the new technology offers lower cost, fully automated manufacturing, higher reliability,

smaller size, and higher detector densities while maintaining excellent performance characteristics.

2.1 Introduction

The initial plan for the OSPREy development activity was to build the needed radiometers by enhancing the

existing capabilities of the PRR-800 class of instruments

from BSI. Although developed in the late 1990s, the mostly

handmade PRR-800 sensors and associated sampling systems continue to provide outstanding value in terms of

the sampling speed, measurement accuracy, and dynamic

range. While the OSPREy activity was under review, BSI

had just completed development of a new approach to radiometer design—the microradiometer—which was funded

by the NASA Small Business Innovation Research (SBIR)

program.

Priority objectives in the microradiometer development

included lower cost, fully automated manufacturing with

built in QA and QC functions, potentially higher reliability (by reducing the number of handmade components),

smaller size, and higher detector densities (or packing efficiencies). Details concerning the development of the microradiometer (Fig. 4) are documented by Booth et al. (2010),

so only summary information is presented here.

Fig. 4. A side view of a microradiometer (top)

showing the two-sided circuit board design, and a

sleeved unit with fore optics attached (bottom). The

ruler is marked in centimeters.

At the start of the OSPREy activity, microradiometers were being commercially manufactured and had been

successfully integrated into the Compact-Optical Profiling

System (C-OPS), a NASA in-water profiling instrument

(Morrow et al. 2010b). An engineering analysis was performed to determine if the OSPREy activity would be better served using microradiometers, the newest advanced

technology, or to use PRR-800 legacy technology. The

comparison was approached from the perspective of managing risk. The microradiometers were thought to be more

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

0.0

0.8

1.6

2.4

300 500 700 900

Responsivity in Water [10-8]

Wavelength [nm]

PRR

MMS

a 0.03

0.05

0.07

0.09

300 500 700 900

Relative Standard Deviation [%]

Wavelength [nm]

PRR

MMS

b

Fig. 5. A comparison of legacy PRR-800 performance with an MMS cluster: a) in-water radiance responsivity

(in amps per μW cm−2 nm−1 sr−1), and b) the noise levels for radiance calibration.

capable, but riskier to use given how few systems had been

built with them, whereas the PRR-800 sensors had been

used successfully for more than a decade, but were less

flexible to adapt to new requirements (e.g., the smaller size

and packaging configuration of the microradiometer architecture allowed somewhat smaller overall size, and enabled

full integration of spectrograph and filter radiometers, particularly in the irradiance configuration).

The PRR and MMS systems have similar input optics and use similar filters and photodetectors, but substantially different electronics (Booth et al. 2010). The

individual channels of the PRR electronics feature three

electrometer gain stages sharing a single 16 bit ADC multiplexed to all channels. Microradiometers also feature three

electrometer gain stages, but each detector has a dedicated

24 bit ADC, simplifying calibration, and enhancing stability. Although similar in expected performance, comparisons of the legacy PRR and new MMS technologies show

the MMS to have somewhat better responsivity and similar

noise characteristics (Fig. 5).

Between the start of the OSPREy development activity and the conclusion of the engineering analysis involving PRR and MMS capabilities, an increasing number of

C-OPS instruments were sold to scientists. The emerging

success and experience being achieved with C-OPS, and by

extension with microradiometers, added to the list of advantages inherent in using the microradiometer as the basis

of instruments for OSPREy systems. A significant practical advantage of the MMS architecture was it was mostly

machine assembled and tested, so many of the commissioning problems experienced with handmade legacy sensors were not realized with microradiometer instruments.

A simple consequence of the handmade versus machinemade approach is easily seen in Fig. 6, wherein the MMS

sensor (on the right) has no internal cabling. Consequently,

it was decided to move the OSPREy activity ahead using

microradiometers rather than the legacy PRR technology.

Fig. 6. A side-by-side comparison of a legacy PRR

sensor (left) and a new MMS sensor (right).

2.2 Microradiometer Modifications

Several engineering tasks had to be addressed in order to adapt the MMS architecture to the design requirements for EMR and OXR sensors. These tasks included

extending the signal range within the lowest resistor setting (i.e., largest signal) in the gain amplification, adapting

the circuitry to handle SWIR detectors, and adapting the

microradiometer support electronics to support additional

tasks, such as temperature regulation and filter-wheel integration.

19
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Operated over the SWIR and visible regions of the electromagnetic spectrum, EML sensors must be able to measure the sky radiance, the total radiance above the sea

surface, the radiance of a reflectance plaque, as well as the

direct solar and lunar irradiances. These applications require a dynamic range spanning more than nine orders of

magnitude, with good linearity (less than 1% departure)

and no saturation. The original microradiometer as implemented in C-OPS used two automatically selected gain

stages. This limited the upper signal range, which would

saturate if the sensor was pointed directly at the Sun. To

extend the upper signal range, the current-to-voltage conversion front end of the microradiometer was redesigned to

add a third gain stage.

Adding a third gain stage had several advantages: a)

the factor between gains was reduced from 1,000 to 200,

which decreased the stabilization time after a gain change;

b) the voltages at which gains increase were raised by a

factor of 2.5, resulting in a decrease of the medium and

low gain offset uncertainty; and c) the photocurrent signal range was increased to accommodate 40 times higher

saturating signal levels (160 μA). The analog front end of

the three-gain microradiometer was redesigned with different components, but the physical package outline and

connections are identical.

The circuit architecture is very similar in the two- and

three-gain microradiometers. The photodetector is connected to a high-performance operational amplifier. The

amplifier is configured as a current-to-voltage converter,

with the gain set using a resistor and capacitor combination that is selected with an analog switch. The resulting

voltage is digitized by a 24 bit ADC normally running at

125 Hz. The three-gain microradiometer has an ADC resolution of 0.5 μV, and at maximum gain, a current resolution

of less than 1 fA. A microprocessor controls the switch and

ADC, implements autoranging, and calculates a running

average.

By operating at 125 Hz, range changes can usually be

made, and time can be allowed for settling, while maintaining an uninterrupted stream for multiple instruments, at

sampling rates as high as 20 Hz. Before each reading is averaged, it is corrected for offset and gain and expressed as a

floating point number, which is then added to the average.

If a range change occurs during an averaging period, readings can be dropped while still being able to calculate and

report an average, thereby minimizing data gaps at signal

regions where gain changes occur. The firmware contains

modes for automatically determining dark offsets at each

gain, gain ratios when exposed to appropriate light levels,

and configuring various operational modes, e.g., ranging

mode, switch points, and other parameters. It is also possible to program the system for manual gain, different ADC

sample rates ranging from 4–125 Hz, and sample averaging

periods from less than 0.05 s to 60 s.

Both the two- and three-gain versions of the microradiometer contain a temperature sensor, and circuitry to

monitor the supply voltages. When configured for radiance measurement at 490 nm, 1 s averaging, and using entrance optics with 14◦ field of view, a three-gain microradiometer has a detection limit of 0.14 pW cm−2 nm−1 sr−1

and a saturation radiance of 8.5 mW cm−2 nm−1 sr−1, corresponding to a dynamic range of approximately 6 × 1010.

2.3 Linearity Tests

Linearity testing is particularly important with respect

to the EMR and OXR instruments, because they must

operate over an extremely large signal range. As an example, the signal measured by the 340 nm microradiometer

channel when pointing at the direct Sun is approximately

5×106 times greater than the signal measured by the same

channel when pointing at the laboratory source used for

radiance calibrations (a reflectance plaque). At 700 nm,

the signal from the direct Sun is about a factor of 3 × 107

larger than the signal generated by the water-leaving radiance. Microradiometers are typically linear over a range

of larger than 109 as discussed below.

The principal apparatus for testing linearity was the

so-called lineator, which consists of multiple LED light

sources coupled to a fiber optic bundle with a three-infour-out beam combining and splitting mixer. The multiple LED light sources are operated at intensities set by a

16 bit computer-controlled power supply, and each of the

LEDs has a significantly different brightness when operated at the maximum level. One of the output fiber optics

was coupled to a silicon photodiode of the same type used

in microradiometers, and the output of that photodiode

was digitized by a Keithley 6485 Picoammeter.

By controlling each individual LED, the signal level was

varied over a range of approximately three decades. Using one LED, the test currents ranged from 10 pA to 1 μA

(in subsequent testing, the test system was expanded to

characterize 19 microradiometers over photocurrent ranges

of 1 pA to 100 μA). Another source gave a slightly higher

range, between 100 pA and 10 μA and spanned both rangechange points. Linearity testing (Fig. 7) suggests increasing nonlinearity at signal levels greater than 10 μA, which

is the maximum signal level achieved from the lineator.

This level is 16 times smaller than the 160 μA saturation

level of a three-gain microradiometer.

Linearity at higher light levels not supported by the

lineator was tested using an apparatus based on a beam

conjoiner principle (Sanders 1962). Two LEDs operating

in constant current mode (sources A and B) were arranged

on an optical bench such that the two beams would enter a 50% beam splitting cube, with both beams exiting

through the opposite two sides of the cube. In theory, each

exit beam receives 50% of the flux from each LED source.

Shutters were installed so that the LEDs could remain on

constantly during each test sequence in order to maximize

stability. The shutters can independently block the beams

of the two LEDs to measure the dark signal, the signal of

either of the LEDs, or both LEDs.

20
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

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Fig. 7. Lineator test results for the mid-intensity

source. Microradiometer gain change points are

marked with diamonds on the x-axis.

If the device under test is linear, the net signal measured with both LEDs unblocked should be identical to the

arithmetic sum of the net signals of the LEDs measured

separately. By changing the intensity of the two LEDs and

repeating the test, linearity can be tested with this apparatus over a dynamic range of approximately five orders of

magnitude up to the saturation level.

A sample test result for a microradiometer equipped

with a silicon detector is presented in Fig. 8, which indicates that the device is linear to within 1% between 20 nA

and 160 μA (the highest point is on the verge of saturation).

Fig. 8. Beam conjoiner linearity test results at high

flux levels using silicon and InGaAs (SWIR) photodetectors.

Figure 8 also presents a similar result for a microradiometer equipped with an InGaAs detector using LEDs

with a peak wavelength at 1,550 nm. The test indicates

that the system is linear to within 0.5%. By combining

the results of the lineator and the beam conjoiner, linearity could be examined over ranges from 160 μA down to

signals approaching the noise level.

2.4 Microradiometer Clusters

Arrays of microradiometers are operated in conjunction with associated interface circuitry that is collectively

referred to as an aggregator. The aggregator is a pivotal component of the MMS architecture, because in addition to providing the basic networking bus, an aggregator

provides regulated +5 V digital and ±5 V analog supplies

to the microradiometers, conditions the logic level data

streams, and provides the Recommended Standard (RS)

interfaces (RS-232 and RS-485).

An aggregator also provides measurements of sensor attitude (two-axis angular orientation), supply current and

voltage, plus internal housing temperature and pressure.

With respect to data reporting, aggregators coordinate

all microradiometer data frames into a single data stream

for acquisition. The latest model aggregator used with

OXR and EMR instruments is considerably smaller than

the original design (Fig. 9), and significantly smaller than

could have been possible with the PRR-800 components.

Fig. 9. The old aggregator (left) shown next to a

new aggregator assembly (right) oriented to reveal

an unpopulated 19-channel microradiometer backplane (top). From top to bottom, the boards under the backplane are as follows: power supply, microprocessor and communications, temperature and

depth, and connections.

To support the OSPREy radiometric requirements, additional aggregator capabilities were added, including interfaces to external devices. For example, to support the

integration of a spectrograph (Chap. 7), a programmable

21
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

voltage source was added to the aggregator. The source is

used to set the target temperature of a precision temperature controller, which is used for temperature stabilization.

To support the filter wheel that is integrated into radiance

radiometers (Chap. 8), a motor driver and command set

were incorporated into the aggregator. Lastly, the circuit

board assembly that implements the aggregator functions

was redesigned for a smaller form factor and to allow the

spectrograph fiber optics to be integrated into the irradiance collector.

The power supply board creates all of the voltages necessary to run the sensor (+5 VDC digital, +5 VDC analog,

and −5 VDC analog) and includes a pressure transducer

that measures the internal housing pressure (to monitor

the nitrogen backfill). The microprocessor- and communications board is the brain of the sensor and contains the

RS-232 and RS-485 drivers. The temperature and depth

board (so named because of the heritage that the first microradiometer sensors were for in-water sampling) includes

two microradiometer circuits configured to measure high

resolution temperature and depth (for above-water EMR

sensors, the depth channel is converted into a second high

resolution temperature channel). Finally, the connections

board provides connection back to the deck box, as well as

connection of the water temperature and depth transducers.

22
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Chapter 3

SWIR Cosine Collector Design and Evaluation

Germar Bernhard and Randall L. Lind

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

The irradiance collectors used with EMR sensors require small cosine errors and high transmission for wavelengths within 305–1,640 nm (UV–SWIR range). To satisfy this objective, a new irradiance collector was designed

by selecting diffuser materials optimized for this spectral range and by modifying the shape of the existing irradiance collector originally developed for the UV-VIS range of legacy sensors. Laboratory tests indicated that

a composite diffuser made of one layer of generic polytetrafluoroethylene (PTFE) sheet and one layer of porous

PTFE (pPTFE) material produces the best characteristics. The tests also confirmed that a small cosine error

can only be achieved with a shaped diffuser (for instance, a diffuser with a trapezoidal cross-section). A numerical model was developed to optimize the dimensions of the composite diffuser (e.g., height, plus top and

bottom diameters of the diffuser) and its support structure (e.g., diameters and heights of two shadow rings

surrounding the diffuser). Based on the results of material testing and modeling, a prototype irradiance collector

was manufactured and tested. For wavelengths in the UV-VIS range, the cosine error of the new collector is

less than ±3% for incident angles up to 75◦ and does not depend on wavelength and azimuth angle. Cosine

errors at SWIR wavelengths are larger (e.g., −5% at 1,020 nm for an incident angle of 74◦), but are still within

acceptable limits for OSPREy applications.

3.1 Introduction

The EMR sensors used with the OSPREy activity include radiometers for measuring irradiance across the 305–

1,640 nm domain—an unprecedented spectral range for a

legacy sensor using a single optical collector. Ideally, these

instruments should have a cosine response, meaning that

the signal from the radiometer should vary with the cosine

of the angle of incidence (defined as the angle between

the normal vector of the fore optics and the direction of

the light source to be measured). The fore optics of BSI

production irradiance radiometers consist of a thin (e.g.,

0.02 in) PTFE sheet acting as a primary diffuser, which

is supported by a solid piece of quartz glass to maintain

the geometric shape. A second PTFE sheet placed at the

bottom of the quartz glass acts as the secondary diffuser,

ensuring that the emission from the fore optics is independent of the azimuth direction of the source radiation.

Research has shown that PTFE sheet is an ideal material to construct diffusers for measuring solar light over

the UV–VIS range, because of its good scattering properties, low absorption, high inertness, and excellent longterm stability. The scattering properties of PTFE sheet,

however, deteriorate rapidly for wavelengths longer than

600 nm. Thin sheets of PTFE become virtually translucent at SWIR wavelengths and cannot be used as diffusers

beyond 1,000 nm. This chapter documents the research

leading to the development of a unique new diffuser design, optimized for operation over the wavelength range of

305–1,640 nm.

3.2 Selection of Diffuser Material

Early engineering analyses concentrated primarily on

using thicker pieces (e.g., 4 mm or several sheets) of PTFE

material to compensate for the loss in scattering at longer

wavelengths. The resulting design was used successfully

for building a prototype irradiance sensor with two channels at 1.55 μm and 1.65 μm, but the increased thickness

resulted in low transmission at wavelengths below 1.0 μm,

so the design was eventually discarded. A search for a

new diffusing material uncovered a pPTFE sheet that was

available commercially and showed increasing scattering at

23
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Drain

Hole

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Ring

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Fig. 10. A production-line irradiance radiometer, based on design characteristics for a legacy cosine collector,

showing a) a photograph of the diffuser (left), and b) the cosine error for wavelengths between 380–780 nm

(right). Water shedding is accomplished with three drain grooves cut into the inner shadow ring (oriented to

prevent vignetting) and four drain holes in the outer shadow ring (only one is visible). To help discern the

effect of detector positioning outside the visible region of the spectrum, the sensor used for the cosine error

analysis had three 780 nm channels, one in the center of the microradiometer cluster and two at the perimeter,

at opposing sides.

SWIR wavelengths, but that was thin enough to allow sufficient flux at 600 nm for satisfactory performance in the

UV and visible domains. The manufacturer’s data sheet

indicated that this new material should have good scattering properties for wavelengths up to at least 2.5 μm.

Using a directional test bench consisting of a 1,000W

FEL tungsten lamp and a rotary table under computer

control, the response for incidence angles between −90◦

and +90◦ of PTFE and pPTFE samples of various thicknesses were measured over wavelengths from 305–1,550 nm.

This was accomplished by placing the samples in front of

two microradiometers, one equipped with a silicon detector (sensitive from 300–1,100 nm) and the other with an

InGaAs detector (sensitive between 700–1,700 nm). Wavelength selection was accomplished using interference filters at 305, 710, 780, 1,015, 1,300, and 1,550 nm sequentially placed between the material samples and the microradiometers for each directional scan.

One disadvantage of pPTFE is its porous structure,

which makes it unsuitable for outdoor use without protection from dust and the elements. Consequently, a multilayered diffuser consisting of a top layer of PTFE overlying

a layer of pPTFE was developed. The angular response of

the composite diffuser shows that the cosine error is similar to that of a single sheet of generic PTFE material for

wavelengths ranging from 305–780 nm. For wavelengths

from 1,015–1,550 nm, the cosine error of the composite diffuser resembles that of a single piece of pPTFE, at least up

to an incidence angle of 65◦. At larger angles, the cosine

error is somewhat larger.

3.3 Irradiance Collector Design

Among other issues, reflection (Fresnel) losses at the

air–diffuser interface cause the angular response of any diffusing material to depart from the ideal cosine response,

particularly for incidence angles larger than 40◦. A common solution for this problem is to design the collector such

that the effective area, as viewed from the light source,

increases with increasing incidence angle. This can be accomplished by shaping the diffuser in the form of a dome

(Bernhard and Seckmeyer 1997), a cylinder (Harrison et

al. 1994), or a trapezoid (Morrow et al. 1994). A trapezoidal cross-section is used by BSI, because it provides the

optimal shape for underwater collectors that must withstand high pressure while presenting a well-defined reference plane for calibrations. One or more shadow rings surrounding the diffuser are often required to avoid excessive

response at angles larger than approximately 50◦.

A picture of the diffuser end of an irradiance sensor

based on microradiometers is shown in Fig. 10a. The collector features a diffuser with a trapezoidal cross-section,

plus inner and outer shadow rings surrounding the diffuser.

The two rings limit the angular response at very large incidence angles by casting a shadow on the diffuser. Grooves

in the inner rings (slanted to prevent vignetting) and four

holes (not all visible) in the outer ring ensure proper water

drainage. The angular response of this sensor for wavelengths between 380–780 nm is presented in Fig. 10b. Departures from the cosine law depend very little on wavelengths between 300–600 nm. The secondary diffuser made

24
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

of generic PTFE is not suitable for removing the azimuth

asymmetry at wavelengths beyond 600 nm, and the cosine

error of the three 780 nm channels depends on the location

of the detector within the microradiometer cluster.

3.4 Optimized Cosine Collector

Calculations of the effective area of a diffuser as a function of incident angle, coupled with the measured angular

response of a diffusing material, were used to model the

response of a cosine collector design. Model parameters

included the following:

1. Diameter of the diffuser top,

2. Height of the diffuser,

3. Diameter of the diffuser bottom,

4. Diameter of the outer shadow ring,

5. Diameter of the inner shadow ring, and

6. The distance between the inner shadow ring and the

top of the diffuser.

To optimize the collector geometry, the model parameters

were varied until the desired response was achieved.

A comparison of the modeled and measured cosine response of an optimized cosine collector design, compared

to the departures from cosine for a flat plate collector made

from PTFE, is shown in Fig. 11. In this example, increasing the height of the inner shadow ring in the model by

0.45 mm reduced the cosine error associated with the modeled angular response to less than 3.5% for incidence angles

smaller than 85◦. The measured values are very similar

to the modeled, and any remaining deviations can be explained by the uncertainty of the estimate.

-30

-15

0

15

0 30 60 90

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Diffuser

Modeled

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Fig. 11. Modeled and measured cosine error of the

new collector compared with the cosine error from

using a PTFE flat sheet as a collector.

3.5 Final Collector Design Test

A form with the optimized dimensions of an irradiance

collector was machined out of aluminum. The pPTFE

composite diffuser was then fitted into the form to shape

the diffuser into the desired shape of the collector. The

new collector was attached to a sensor composed of 18

microradiometers and equipped with filters for 380, 395,

412, 443, 490, 510, 532, 555, 560, 670 nm (one filter per

wavelength), six filters for 1,020 nm, and two filters for

1,610 nm. Because pPTFE is relatively inflexible, a piece

of the material was fashioned in a star-burst pattern (Fig.

12 top) and pressed into the outer diffuser layer made of

generic PTFE (Fig. 12 bottom). A pPTFE sheet was also

used as a secondary diffuser.

Fig. 12. The pPTFE material insert cut into a

star-burst pattern (top) and viewed through the

back of the quartz glass support (bottom).

Measurements indicated that the angular responses for

the six 1,020 nm channels were virtually identical (i.e., the

differences involved were to within 1% for incidence angles

up to 80◦), thereby confirming the angular response for this

wavelength does not depend on the position of the detector

within the cluster of 18 microradiometers. Measurements

25
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

of the two 1,610 nm channels agreed to within 0.3%. Measurements of the other wavelengths (380–670 nm) did not

show a significant difference as a function of azimuth angle and wavelength (systematic variations were to within

0.5%). These results confirmed that the secondary diffuser

is able to satisfactorily remove dependence of the angular

response on azimuth angle that may have existed in the

light field exiting the primary diffuser.

As shown in Fig. 13, the cosine error for the 490–670 nm

wavelength range is to within 3% for incidence angles up

to 75◦. The maximum cosine error is −10% at 84◦. The

angular response of the channels at 1,020 and 1,610 nm

are generally lower, because of a gradual deterioration of

the scattering properties of the composite diffuser as the

wavelength increases. For the six 1,020 nm channels, the

cosine error is smaller than −5% for incident angles up

to 74◦. The maximum cosine error is −16% at 84◦. For

the two 1,610 nm channels, the cosine error is smaller than

−10% for incident angles up to 70◦, and the cosine error

at 84◦ is −25%.

-30

-15

0

15

0 30 60 90

Cosine Error [%]

Incidence Angle [°]

300–700

1,020

1,610

Fig. 13. The average cosine error of the test radiometer for which measurements at azimuth angles

of 0 and 180◦ were averaged.

A picture of the new cosine collector is presented in Fig.

14 and has the same overall shape as the legacy collector

shown in Fig. 10a. The irradiance sensor shown in Fig.

14 is without any insulation or end cap, i.e., the inner

part of the instrument is shown. The two shiny objects to

the top left and right are the ends of threaded rods that

hold everything together, and normally they are hidden

by the end cap. The inner shadow ring is undercut such

that the drain holes do not cause azimuthal dependence in

the angular response. The ability for water to drain away

from the collector is an important design feature, because

it allows rain to keep the collector clean, that is, rain water

flushes particles off the collector and as long as they can

drain away, they are not redeposited on the collector.

Outer Shadow

Ring Trapezoidal

Diffuser

Undercut Inner

Shadow Ring

Drain

Holes

Fig. 14. A photograph of the new cosine collector highlighting important features of the design,

including perpendicularly placed drain holes in the

outer and inner shadow rings.

3.6 Conclusions

Tests using sheets of PTFE and pPTFE showed that

one layer of generic PTFE sheet and one layer of pPTFE is

an acceptable composite material for constructing an irradiance collector suitable for measurements at wavelengths

spanning 305–1,640 nm. A numerical model was used to

optimize the dimensions of a trapezoidal cross-section irradiance collector (originally designed for measurements

for the UV-VIS) to extend its usable range to SWIR wavelengths. A new collector was machined, fitted with the

composite diffuser, and tested.

The angular response of the new collector does not depend on azimuth angle and wavelength for 350–670 nm.

The cosine error for this wavelength range is to within 3%

for incident angles up to 75◦. Cosine errors at 1,020 and

1,610 nm are larger because of the deterioration of scattering properties of PTFE for SWIR wavelengths. In terms

of the knowledge base presented here, alternative materials

with better scattering properties are not available. Consequently, the new collector represents the best broadband

angular response possible with current diffuser technology.

Additional modeling results indicate that the angular

response at SWIR wavelengths could be improved by modifying the dimensions of the collector design (e.g., by increasing the height of the diffuser), but this modification

would degrade the angular response in the UV-VIS domain. To achieve the best accuracy, OSPREy systems

can be equipped with two irradiance radiometers, one fitted with an irradiance collector optimized for the UV-VIS

range, while the other is equipped with a collector optimized for SWIR wavelengths. Such an optimization might

be particularly useful for systems deployed at high-latitude

locations where the solar elevation is low year-round.

26
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Chapter 4

Radiance Field-of-View Specifications

Germar Bernhard, Randall N. Lind, Charles R. Booth, and John H. Morrow

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

The field of view of EML (radiance) instruments used for OSPREy applications, specified here in terms of the full

view angle (FVA), must be optimized to accurately measure a variety of different radiometric sources: the direct

solar irradiance when pointing the instrument at the Sun; the total radiance emanating from the sea surface,

the sky radiance, and the radiance of a calibration plaque. The optimum FVA was determined based on the

following considerations: a) the FVA must encompass the entire solar and lunar disks when performing direct

measurements under all observation conditions; b) compliance with recommendations for sun photometers issued

by the World Meteorological Organization (WMO); c) an FVA large enough to allow accurate measurements of

low-intensity sources (e.g., calibration plaques, the sea surface, and the lunar disk); d) an FVA small enough

to permit statistical filtering of surface and capillary wave effects when measuring the sea surface; and e) a

reasonable overall instrument length. The latter are needed to ensure accurate pointing and control of the

sensor, particularly by the sun tracker; easier handling during servicing and the types of activities that take

place during those events (e.g., monitoring the stability of the sensors with a portable source); and minimization

of wind loading. After taking all considerations into account, it was concluded that an FVA of 2.5◦ combined

with a slope angle of 0.7◦ is the optimal configuration. These geometric parameters were translated into a

fore-optic design consisting of Gershun tubes with an overall length of 182 mm, a front aperture of 4 mm, and

three internal baffles for stray-light suppression.

4.1 Introduction

EML radiometers must be able to measure sky radiance, the total radiance LT emanating from the sea surface, the radiance of a calibration plaque, and the direct

irradiance from the Sun and Moon. These tasks have different entrance optics requirements for the instrument, and

the resulting design is, inevitably, a compromise. When

measuring the direct solar irradiance, for example, the

FVA of the radiometer should ideally be smaller than 1◦

to minimize circumsolar radiation contributions (i.e., photons scattered in the direction of the radiometer by air

molecules or aerosols). In contrast, the FVA has to be sufficiently large to support accurate measurements at low light

levels, e.g., the UV radiance of the calibration plaque and

LT measurements in the near infrared (NIR). The original

OSPREy objectives established that the fore optics of radiance radiometers should have an FVA between 1.5–2.5◦

(Sect. 1.3). This chapter presents the engineering analysis

behind selecting the optimal FVA within this range.

4.2 Engineering Considerations

There are two preliminary engineering considerations

that help define an optimized value for the FVA: straylight suppression and overall instrument length. Direct

sunlight is several orders of magnitude brighter than sky

radiance, so any contamination from stray light is maximal when sky radiance is measured in close proximity to

the Sun. Consequently, the design of the fore-optics for

the sensor must include baffles to control stray light. A final engineering consideration is that the fore optics should

not be more than 20 cm long to keep the overall length of

the instrument within reasonable limits. These limits are

needed to ensure accurate pointing and control of the sensor, particularly by the sun tracker. Minimization of the

size of the sensor is also important for reducing wind loading and ensuring easier handling during servicing and the

types of activities that take place during those events (e.g.,

monitoring the stability of a radiometer with a portable

source).

27
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

The EMR field instruments are designed to measure

the total radiance above the sea surface, which is a combination of photons that have exited the air–sea interface

from below (the water-leaving radiance, LW ), and photons

reflected by the sea surface (e.g., glint from the sky and

Sun). Waves, white caps, sea spray, and glint may lead to

an inhomogeneous radiance within the FVA of the sensor.

Data points affected by sea glint and other factors can be

filtered out, but only if the FVA is small and the sensor

sampling rate is high (e.g., 6 Hz or more). This suggests

that the chosen FVA should be as small as possible.

As a starting point in the numerical specifications of a

design, EMR sensors should also have an FVA that is comparable to other sun photometers currently in use. Table 3

shows that the FVA values of such instruments are between

1.2–2.5◦.

Table 3. A summary of the FVA of commercial

sun photometers. Both of the PFR and SP02-L

units have a 0.7◦ slope angle.

Manufacturer Model Used By FVA

Cimel

Electronique CE-318 NASA

AERONET 1.2◦

YES† SPUV6/10 2.5◦

PMOD/WRC‡ PFR PMOD/WRC

WMO/GAW 2.5◦

Kipp &

Zonen POM-01 2.0◦

Carter-Scott

Middelton Solar SP02-L NOAA/ESRL

GMD§ 2.5◦

† Yankee Environmental Systems

‡ Physikalisch-Meteorologisches Observatorium Davos

(PMOD), World Radiation Center (WRC)

§ NOAA Earth System Research Laboratory (ESRL),

Global Monitoring Division (GMD)

To establish the FVA required to measure the direct

solar irradiance when pointing the instrument at the Sun,

the first consideration is the angular size of the Sun when

viewed from Earth. Over the course of the year, the angular size of the Sun varies from 0.527–0.545◦. In practice,

the FVA of a sun-viewing radiometer must be considerably larger than these values such that the complete solar disk is viewed by the instrument during all operating

conditions. The latter must include compensation for the

pointing inaccuracies of the sun tracker, the instrument,

and positional uncertainties associated with the physical

mounting of the instrument. For example, the finite stepresolution of the tracker, alignment differences in individual channels of the radiometer, and positional uncertainties

where the instrument is installed (perhaps caused by environmental or platform vibrations), respectively. Based on

these considerations, it was determined that the optimal

sun-viewing FVA should not be smaller than 1.5◦.

EMR field sensors must also be in compliance with the

recommendations and specifications for sun photometers

as issued by cognizant authorities. The WMO Guide to

Meteorological Instruments and Methods of Observations

(WMO 2008), for example, requires that modern pyroheliometers designed for making direct solar shortwave radiation observations should only measure “radiation from the

Sun and a narrow annulus of sky.” The resulting half-angle

(half of the FVA) is “about 2.5◦.” The WMO Global Atmosphere Watch (GAW) aerosol measurement procedures

guidelines and recommendations require that direct-beam

radiometers have a “full opening angle of 2.5◦” (WMO

2008), i.e., an FVA of 2.5◦.

The FVA of an EMR sensor must also be large enough

to allow accurate measurements of all sources considered

by the OSPREy activity, including low-light applications.

The signal of a radiance sensor, from a uniform source

fully filling the field of view, is proportional to the solid

angle Ω associated with the FVA. For small FVA values,

Ω changes quadratically with FVA (Table 4). For example,

changing the FVA from 17◦, a baseline value established

for the Ocean Optics Protocols (Mueller and Austin 1992),

to 2.5◦ (a factor of 0.1471) changes Ω by a factor of 0.0218.

In consequence, a decrease in the FVA greatly reduces the

radiative flux reaching the photodetector, which in turn

affects the detection limit for the instrument.

Table 4. The relationship between FVA and solid

angle.

Full View Half Solid Angle Relative

Angle Angle Ω [sr] Solid Angle†

1.5◦ 0.75◦ 0.000538 0.0078

2.5 1.25 0.001471 0.0218

17.0 8.50 0.069000 1

† Relative to the solid angle for an FVA of 17◦.

The noise equivalent radiance (NER) of an instrument,

NL, is defined as

NL(λ) = σL(λ)

γL(λ) (1)

where σL(λ) is the standard deviation of the dark signal

and γL(λ) is the responsivity. The responsivity of a radiance sensor, from a uniform source fully filling the field

of view, is proportional to Ω, and NER for a hypothetical

system with a smaller FVA can be estimated by scaling

with Ω (the right-most column in Table 4). The increase

in NER with decreasing FVA can partly be compensated

by increasing the integration time of the instrument, but

σL(λ) cannot be reduced by endlessly increasing the averaging time because of many factors, e.g., dark current

drifts (which can be caused by small temperature changes).

For measurements at the 1% accuracy level, radiances of

artificial and natural targets should be at least 2.5 orders

of magnitudes larger than the NER of the instrument, and

this limit establishes the required FVA.

28
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

10-7

10-4

10-1

102

250 500 750 1000 1250 1500 1750 

Spectral Radiance

Wavelength [nm]

a

b c

d

e

g f

h

i

j

k

Fig. 15. Spectral radiances, in units of μW cm−2 nm−1 sr−1, of various sources compared with NER values

for BSI microradiometers. The 11 data sets (a–k) are described in the text (Sect. 4.3).

4.3 Results and Discussion

Figure 15 compares radiances of various sources with

the NER of microradiometers for data sets a–k:

a. The radiance of a Spectralon plaque that is mounted

287.1 cm from a 1,000W FEL standard of spectral

irradiance (the typical BSI configuration).

b. The radiance of the plaque (a), but mounted 107 cm

from the calibration standard (used historically for

calibrating radiometers with large NER).

c. The sky radiance modeled for a zenith angle of 40◦,

offset by 90◦ in azimuth from the solar principal

plane. Radiance was calculated with the radiative

transfer model UVSPEC (Mayer and Kylling 2005),

for a solar zenith angle (θs) of 40◦, cloudless sky,

and aerosol optical depth of 0.5 at 500 nm.

d. The c data, but with no aerosols.

e. The c data, but for θs = 80◦.

f. The simulated radiance ΔL of the sea surface originating from the sky radiance defined by c data and

reflected by the sea surface (assuming a surface reflectivity of ρ = 0.028).

g. Omitting any spectral dependencies for brevity, LW ,

is calculated according to:

LW = 0.54 R(0-) 0.965 Ed(0+) Q−1, (2)

where the 0.54 term is the radiance transmittance

of seawater, LW /Lu(0-), for which Lu(0-) is upwelling radiance; R(0-) is the irradiance reflectance,

Eu(0-)/Ed(0-), where Eu(0-) is the upward irradiance and Ed(0-) is the downward irradiance at

null depth; 0.965 is the irradiance transmittance of

sea water, Ed(0-)/Ed(0+); Ed(0+) is downward irradiance above the water surface (the global solar

irradiance); and Q is the irradiance-to-radiance ratio, Eu(0-)/Lu(0-). Assuming Q = 4, R is set for

a chlorophyll concentration of 0.045 mg m−3 using

data adopted from Morel and Maritorena (2001);

and Ed(0+) is modeled for a θs = 40◦, cloudless sky,

and aerosol optical depth of 0.5 at 500 nm.

h. The NER of a microradiometer with an FVA of 17◦

and a sampling frequency of 5 Hz, as determined

with the a data.

i. The hypothetical NER of the h microradiometer,

but equipped with an FVA of 2.5◦.

j. The hypothetical NER of the h microradiometer,

but equipped with an FVA of 1.5◦.

k. The same as i, but calculated for data averaged over

a period of 60 s.

Figure 15 illustrates that sky radiances (c–e data) can

be expected to be more than three orders of magnitude

larger than NER values (h–k data). At this level of flux,

even an instrument equipped with an FVA of 1.5◦ and

sampling at 5 Hz can accurately measure sky radiance for

solar zenith angles as large as 80◦. In comparison, radiance

emanating from the sea surface resulting from the reflection of sky radiance alone (f data) is about 2.5 orders of

magnitude larger than NER for the fore optics with FVA

equal to 1.5◦. This difference is at the limit of the criterion discussed earlier. Because accurate measurements

of sea surface radiances are of paramount importance for

the OSPREy activity, an FVA larger than 1.5◦ should be

29
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

chosen. Averaging measurements over longer time periods

is not an option because of the rapidly changing light field

(caused by surface waves).

Conservative estimates of water-leaving radiances (g

data) suggest an FVA of 2.5◦ or larger is required for

wavelengths longer than about 550 nm, because the expected NER is less than 2.5 orders of magnitude smaller

than the light field. For wavelengths shorter than 550 nm,

water-leaving radiances are likely more than 2.5 orders of

magnitude larger than the NER.

For an FEL lamp mounted 287.1 cm from a plaque,

the radiance of the plaque is 0.003 μW cm−2 nm−1 sr−1 at

320 nm (h data). This value is only one order of magnitude

larger than the NER of the fore optics with an FVA equal

to 1.5◦. While the difference could be increased by moving

the lamp closer to the plaque or by averaging the radiometer signal, it is thought that choosing a fore optics with

the FVA equal to 2.5◦ is a more conservative approach.

Based on these considerations, it was concluded that

the fore optics of the instrument should have an FVA of

2.5◦. To keep the length of the fore optics at or below

20 cm, a slope angle of 0.75◦ or smaller is required. A

slope angle of 0.7◦ is used, because this angle is also used

by some existing sun photometers (Table 3).

4.4 Fore Optics Design

The geometry and dimensions of the fore optics are

defined by the FVA, the slope angle, and the size of the

active area of the photodiodes used for each channel (Fig.

16). Photodiodes with an active area of 3.5×3.5 mm2 were

selected. To avoid any azimuthal asymmetry, photodetector mounts must have a circular opening with a radius rp

of 1.75 mm. The half-angle is defined as the arctan(ra/dp),

where ra is the radius of the front aperture and dp is the

distance between the front aperture and the photodetector. The slope angle is arctan 

(ra − rp)/dp



. Setting rp

to 1.75 mm, the FVA to 2.5◦, and the slope angle to 0.7◦,

results in ra = 3.98 mm and d = 182.25 mm.

dp

ra

rp

Slope

Angle

Photodetector

FVA

Fig. 16. An illustration of a single Gershun tube

and definition of FVA and slope angle. The center

line of the aperture is shown dashed.

The fore optics of sun photometers are typically Gershun tubes that include two or three internal baffles (e.g.,

Wehrli 1989). The EML instruments also use this design

(Fig. 17). Baffles divide the tube in sections determined by

ray trace paths of direct and scattered light. Considerable

effort has gone into the details specifying baffle placement.

The radius of the baffle apertures is chosen such that the

baffles do not interfere with the FVA defined by ra, rp,

and dp, but at the same time are as small as possible for

efficient stray-light suppression.

Fig. 17. The initial assembly of the first of four

layers of Gershun tubes, made from hollow black

cylinders, which are stacked to control the FVA.

Figure 18 shows a side-view drawing of the 19-channel

Gershun tube and baffle arrangement needed to achieve

the desired narrow FVA. The chamfers (beveled edges)

surrounding the knife edges of the outermost baffle are oriented towards the eternal light field. Chamfers surrounding the knife edges of the interior baffles are oriented towards the detectors. Only three out of 19 possible Gershun

tubes are depicted for clarity.

Fig. 18. A drawing of the four layers of Gershun

tubes, and baffle placement for a 2.5◦ FVA.

30
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

4.5 Conclusions

The optimal FVA for EML instruments was determined

based on the differing measurement requirements associated with the diversity of data products that were first anticipated for radiance measurements. The principal data

products were associated with direct observations of the

Sun and Moon for AOD data products, plus sea and sky

measurements for oceanic data products. It was concluded

that an FVA of 2.5◦ combined with a slope angle of 0.7◦

is the optimal combination. These geometric parameters

were translated into a fore-optic design consisting of Gershun tubes with an overall length of 182 mm, a front aperture radius of 4 mm, and four internal baffles for stray-light

suppression.

The data product suite can be expanded from sky photometry sampling scenarios, but an additional design requirement associated with measuring the sky close to the

Sun is required. At the aperture end of an EML radiometer is an 8 in (20 cm) long by 4 in (10 cm) cylindrical

shroud that serves multiple purposes. The design dimensions and placement of internal baffling help minimize offangle stray light reaching the radiance entrance optics of

the instrument and associated spectrograph and camera

ports. The system also provides protection from swirling

debris that can stick to the optical surfaces and cause scattering artifacts, especially when directed to the stowed position where the entrance port is oriented downward. The

shroud is removable to enable cleaning of the entrance optics of the instrument.

31
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 5

Sun Tracker Performance Evaluation

Germar Bernhard, Charles R. Booth, and Vi Quang

Biospherical Instruments, Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

An OSPREy system requires a pointing device or tracker to accurately direct radiance radiometers at relevant

targets, including the Sun, Moon, sky, sea surface, calibration sources, and monitoring devices. Of all applications, the measurement of the direct Sun requires the highest pointing accuracy. Based on the angular size of

the Sun, the geometry of radiance fore optics, and alignment uncertainties, it was determined that a pointing

accuracy to within 0.2◦ is required. The tracker should be small in size with a low power requirement, and must

also be weather and corrosion resistant for use in the marine environment. A market analysis was performed,

which resulted in three candidate instruments. Based on specifications provided by the manufacturers, it was

concluded that the PTU-D300 pan-tilt unit from FLIR Motion Control Systems would be the most suitable

tracker for OSPREy applications. A test unit was procured and installed on the roof platform at BSI. The

pointing accuracy was tested by mounting a video camera on the device for tracking the Sun. Software was

developed to capture and examine the images of the video camera. The software was able to find the center of

the Sun in the video images with an accuracy of 0.01◦. The method is a viable and cost-effective alternative

to the use of quadrant detectors for Sun finding. Image analysis, later confirmed with a test deployment of an

EML (radiance) sensor, showed the PTU-D300 unit can track the Sun with a sufficient accuracy of to within

0.1◦.

5.1 Introduction

A primary innovation for the OSPREy above-water system is the ability to make atmospheric as well as oceanic

measurements. The former is best exploited if each radiance sensor can also function as a sun photometer, which

means an ability to track and locate the Sun is required.

Although a custom-built device is a solution, in keeping

with other aspects of the OSPREy activity, a commercial

source provides potential cost savings.

The OSPREy system has other metrology requirements

that a tracker must satisfy. The radiometers need to be

potentially pointed at a variety of targets—including the

Moon, sky, ocean, and a monitoring device—and in each

case at a specified angle. The primary measurements, however, are the direct-normal Sun irradiance, sky radiance

for a multitude of zenith and azimuth angles, and the total radiance emanating from the sea, LT , at a prescribed

geometry with respect to the Sun. From these measurements, secondary data products can be derived, including

the AOD, the SSA, the ratio of direct-to-global irradiance,

and the water-leaving radiance, LW .

The material presented here establishes the requirements for a tracker, provides an overview of commercially

available systems, and gives the rationale for selecting the

model PTU-D300 tracker from FLIR Motion Control Systems, Inc.† (Burlingame, California). Test results indicate

that this tracker meets the requirements for the OSPREy

activity. Suggestions for improving the performance of the

tracker are also provided.

5.2 Tracker Requirements

EML radiometers must be able to measure sky radiance, the total radiance emanating from the ocean surface, and direct solar irradiance when pointing the instrument at the Sun. Of all applications, measurements of

the direct Sun require the highest pointing accuracy of

the tracker. For these measurement tasks, the entire Sun

† Formerly called Directed Perception.

32
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

must be within the field of view of the radiometer that is

mounted on the tracker.

Minimum requirements for the pointing accuracy of the

tracker were calculated from the geometric properties of

the radiometer’s fore optics and the angular size of the Sun.

The fore optics of EML sensors have a half angle of 1.25◦

and a slope angle of 0.7◦ (Chap. 4). The latter specification means that a point source, which is infinitely distant

from the radiometer, fills the entire area of the radiometer’s photodetector even if the radiometer is misaligned by

0.7◦. The actual pointing accuracy must be significantly

better, because the Sun is not a point source: it has an angular diameter of 31.6 (0.5266◦) on 4 July (aphelion) and

32.7 (0.545◦) on 3 January (perihelion). This means that

the pointing accuracy must be at least ±0.7◦ − 1

2 0.545◦ or

±0.4275◦.

In practice, the accuracy must be even better still, because of radiometric diffraction effects at the sensor’s front

aperture and possible departures of the field of view from

the (theoretical) design specifications. In addition, the radiometer is made up of separate Gershun tubes for each

channel, and small differences in the pointing direction of

those tubes (e.g., 0.1◦) further restrict the required pointing accuracy of the tracker. Based on these considerations,

it was determined that a pointing accuracy to within 0.2◦

is required. The repeatability of the tracker should be considerably better than this value, e.g., to within 0.05◦.

Radiances of the sky, ocean, and calibration sources

change very little (less than 1%) with small variations (less

than 1◦) of the pointing direction. A tracker that is adequate for measuring the direct Sun is, therefore, also suitable for other OSPREy measurements.

In addition to good pointing accuracy, the OSPREy

requirements for a Sun tracker include the need for surviving long exposure times in the marine environment, low

power consumption, small size (to reduce platform space

requirements and wind loading), and low cost. An analysis of existing tracker manufacturers was performed based

on these considerations, which resulted in three candidate

instruments:

• Model 2AP-GD, Kipp & Zonen, Inc. (Bohemia, New

York);

• Model PTU-D300, FLIR Motion Control Systems,

Inc. (Burlingame, California); and

• Model ASTX-1, Prede Co., Ltd. (Tokyo, Japan).

The latter had the most number of unknown operating

specifications.

5.3 Tracker Selection

The Kipp & Zonen 2AP-GD tracker, commonly used in

European sun photometry applications, is based on a spur

gear primary plus a final double-involute worm gear. The

primary products of FLIR Motion Control Systems use a

worm gear pan-tilt design, and are sold for surveillance, antenna positioning, lidar mounting, and other applications.

The FLIR units are designed to military specifications for

harsh outdoor environments and vehicle-mounted applications, and are equipped with a slip ring and militarystyle hardware. Information concerning number and type

of users for the ASTX-1 tracker from Prede was not available.

A comparison of the three trackers that were considered

for OSPREy systems (Table 5) showed the PTU-D300 from

FLIR would be the most suitable sun tracker for OSPREy

applications†. Its main advantages over the other units are

high rotational velocity (required for quickly changing observing modes), superior specifications for harsh environments (including exposure to sea spray), and lower price.

It is also compact, relatively light, and typically does not

consume as much power. Its resolution is not as good as the

2AP-GD, but is considerably better than the requirements

for sun photometry discussed above. Based on these considerations, a PTU-D300 (Fig. 19) was procured, installed,

and tested.

Table 5. A summary of the three sun tracking

systems considered for OSPREy. A blank entry indicates an unknown specification.

Specification 2AP-GD PTU-D300 ASTX-1

Communications RS-232 RS-232 RS-232

Resolution 0.0025◦ 0.0064◦ 0.0036◦

Pointing

Accuracy < 0.05◦ 0.01◦ 0.01◦

Repeatability < 0.02◦ 0.01◦

Zenith

Range 210◦ 180◦ 90◦

Velocity [◦/s] 1.8 50

Azimuth

Range 540◦ 360◦ 300◦

Torque [N m] 40

Power [W] 50 18.2‡ 10

Payload [kg] 65 31.7 10

Weight [kg] 30 11.8 27

Environment Outdoor IP67§ Outdoor

Operating

Temp. [◦C] −50 to 50¶ −30 to 70

Price $21,640 $11,540

‡ Typical consumption; up to 49.2W peak.

§ Up to 6 mm of ice buildup, sustained exposure to

blowing dust and sand, and sustained operation in

salt-spray environments.

¶ With heater.

† A list of the specifications for the model PTU-D300 pantilt unit from FLIR Motion Control Systems is available at

http://www.dperception.com/pdf/specs-ptu-d300.pdf.

33
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Fig. 19. The PTU-D300 pan-tilt unit from FLIR

Motion Control Systems, which is approximately

7.1×11.6×8.5 in3. The perforated plate extending

to the right away from the control housing is the

payload (radiometer) mounting bracket.

5.4 Test Protocol

The PTU-D300 was mounted on the BSI rooftop platform with sturdy Unistrut framing (Fig. 20a). A video

surveillance camera (Sony model SNC-Z20N) was installed

inside a protective housing and fastened to the tracker’s

mounting bracket (Fig. 20b). The camera has a resolution

of 640 (horizontal) by 480 (vertical) pixels and is equipped

with a telephoto lens (magnification 1–18×).

a b

Fig. 20. The mounting of a PTU-D300 on the BSI

rooftop platform showing a) support provided by

stainless steel Unistrut framing, and b) the Sony

SNC-Z20N video camera mounted on a PTU-D300.

All settings, including exposure time and zoom, are

computer controlled. A neutral density filter was installed

in front of its lens to prevent overexposure. The tracker

was programmed to point the camera at the Sun by implementing the ephemeris algorithm by Wilson (1980). Additional software was developed to capture and analyze the

images of the video camera. This software implements a

Hough Transform (Ballard 1981) for finding the center of

the Sun. The pixel coordinates of the Sun’s center are displayed on the screen (Fig. 21) and also written to a database at a rate of 3 Hz. Data are automatically rejected

from further analysis if the Sun is obscured by clouds.

+

Fig. 21. A screen shot of a program to determine

the center of the Sun. The left panel shows the image of the Sun captured by the video camera and

the center of the Sun as determined by the software

(red cross). The top right panel shows the horizontal pixel position of the Sun’s center as a function

of azimuth angle calculated by the ephemeris algorithm. Morning and afternoon data are displayed

in different colors. The bottom right panel shows

similar results for the Sun’s vertical position. The

radius of the Sun, and tracker zenith and azimuth

offsets are configurable by the user.

5.5 Results

The pixel position of the Sun’s center, as determined

with the software, should ideally be independent of the

solar azimuth angle. The first test results, taken between

13 and 16 March 2009, showed this was not the case. The

horizontal position (xp) of the center pixel varied between

273–361, and the vertical position (yp) of the center pixel

varied from 129–344. The data from the four days almost

entirely overlay one another, however, indicating that the

tracker’s position is very reproducible from day to day.

Because the diameter of the Sun is known (0.5391◦ on

14 March), the positional data can be converted to angular

variation (denoted by the subscript a) via the equations:

xa = 0.5391

xp − 320

122 , (3)

and

ya = 0.5391 yp − 240

122 , (4)

where 320 and 240 are the center pixel in the x and y directions, respectively, and 122 is the pixel diameter of the

Sun for 14 March. Figure 22 shows the result of the conversion. The diurnal variation in the image of the Sun’s

34
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

B

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X

X

XXXX

X

XXXXXX XX XX

XXXX

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XXXX XXXXXXX

X

G G G G G G GGGGG

G

GGGG GGGGG GGGG GG GGGGGGG GG GGGGGGGGGGGGGGG GGGGGGGGGGGGGGGGGGGG GG

-0.6

-0.2

0.2

0.6

90 150 210 270 

Deviation [°]

Azimuth Angle [°]

B x

X Fit

G Residual

a

J

J

JJJJ

J

JJ

JJJJJJJJ

J

JJJJJJ

JJJJ

J

JJJ

J

J

J

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J

JJ

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JJ

JJJJJJJ

JJJJJJ

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JJ JJJJJJJJJJ

J

JJJJJJJJJ

J

JJJJJ

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X

X

XXXXXXXX

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XX

XXX

XXXXXXXXXX

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

X

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

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EE

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E

E

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-0.6

-0.2

0.2

0.6

90 150 210 270 

Deviation [°]

Azimuth Angle [°]

J y

X Fit

E Residual

b

Fig. 22. The angular position of the center of the Sun with the fit to the data and the resulting residuals for

a) the horizontal direction, and b) in the vertical direction.

center is ±0.2◦ in the horizontal and ±0.45◦ in the vertical directions. This variation is likely due to small leveling uncertainties of the instrument. For example, if the

instrument mounting plate was tilted by 0.4◦ towards the

western horizon, the image of the Sun would be low by 0.4◦

in the morning and correspondingly high in the evening.

It can be expected that the image position varies with the

cosine of the azimuth angle φ for other times.

Harmonic functions of the form a + b cos(φ − c) were

fitted to the measured data. These fit functions, as well

as their residuals, are shown in Fig. 22. It is evident that

the functions provide an excellent fit, because the residuals (i.e., ratio of measurement to fit) are typically smaller

than ±0.03◦. Much of the remaining variability is made

up by a small-scale variation on the order of ±0.015◦ with

a periodicity of approximately 10◦ in the azimuth angle.

This variability is likely correlated to a full resolution of

the tracker’s worm drives. Imprecisions in the manufacturing of the worm drives provide the ultimate limitation

in the pointing accuracy.

Closer inspection of Fig. 22b reveals that residuals exceed 0.05◦ for solar azimuth angles smaller than 100◦ or

larger than 260◦. For these azimuth angles, θs > 78◦. At

these large zenith angles, the position of the Sun becomes

dependent on refraction by Earth’s atmosphere, which is

not implemented in the ephemeris program. These departures are, therefore, not related to inaccuracies of the

tracker but rather are related to simplifications in the calculation of the Sun’s position.

As a next step of instrument characterization, the two

fit functions shown in Figs. 22a and 22b were included in

the tracker software, and the tests were repeated. The

results are shown in Fig. 23, and should match with the

residuals shown in Fig. 22. A comparison of Figs. 22 and 23

indicates that implementation of the fit functions resulted

in a significant improvement of the tracker’s accuracy.

GG

GGGG G

GG G G GG G G G GG GGGG G GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG GGGGGGG GGGGGG GGGGGGGGG GGGGGGGG G

GG G GGGGG GGGG G

G GG GGGGGGGGG GG EEEE E E

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EEE EE

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-0.6

-0.2

0.2

0.6

90 150 210 270

Deviation [°]

Azimuth Angle [°]

Fig. 23. The angular position of the center of

the Sun for the horizontal and vertical directions

as measured after the fit functions in Fig. 22 were

implemented in the tracker software.

Both the vertical and horizontal deviations in Fig. 23

closely match the residuals of Fig. 22. For horizontal tracking, maximum deviations are smaller than ±0.1◦; for vertical tracking, maximum deviations are smaller than ±0.06◦,

except at either very small or large azimuth angles where

atmospheric refraction becomes important. These deviations are below the required accuracy of ±0.2◦ specified in

35
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Sect. 5.2. The day-to-day variability, which is indicated by

the vertical spread of the data points in Fig. 23, is about

±0.02, which is also better than the target limit of ±0.05.

All tests discussed above are based on measurements

where the tracker was following the Sun in a continuous

motion from the morning to the evening. The tracker gears

were loaded from one side only and any possible “play” (or

backlash) in the worm drives would not show up in these

tests. To investigate whether backlash of the drives would

appreciably compromise tracker accuracy, a modified test

was performed. The tracker was commanded at the top

of every hour to point to the zenith or various points on

the horizon. Results of this modified test are presented in

Fig. 24, for which the same correction functions determined

from Fig. 22 were implemented.

GG G G GG G G GGGG

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-0.6

-0.2

0.2

0.6

90 150 210 270

Deviation [°]

Azimuth Angle [°]

Fig. 24. The angular position of the center of

the Sun for the horizontal and vertical directions

as measured during the backlash testing.

Figures 23 and 24 are very similar for the horizontal direction (blue), indicating that changing the azimuth before

resuming Sun tracking does not have an appreciable influence on the data. This means that there is no detectable

backlash in the gears for the azimuth position. This is not

the case for the vertical direction. Figure 24 shows discontinuities in the vertical direction at azimuth angles of

182◦, 190◦, 212◦, 231◦, and 245◦ at times when the tracker

was briefly pointing to either the zenith or horizon before

resuming Sun tracking. These discontinuities are about

0.1◦ (i.e., an order of magnitude larger than the specified

accuracy of the system), and are likely related to backlash

of the zenith drive.

The backlash test results were discussed with the manufacturer, who acknowledged that the observed amount

of backlash is beyond the specified limits. The company

suggested that the system be returned for adjustment of

the gears. This advice was followed, and the system was

retested after refurbishment. The angular precision (calculated as the standard deviation of repeat measurements)

of the serviced systems was 0.008◦, both in the zenith and

azimuth directions. This value is close to the theoretical

limit defined by the PTU-D300 pan and tilt resolution of

0.0064◦. Consequently, the refurbished system met the

pointing accuracy specification of 0.01◦ (Table 5).

5.6 Conclusions

Based on a market analysis, it was determined that

the PTU-D300 unit is the most suitable tracker for OSPREy applications. Its specifications meet OSPREy requirements in terms of tracking accuracy, resolution, speed,

range of motion, payload, power consumption, size, and

weather resistance. In addition, its price is substantially

less than that of comparable systems. A PTU-D300 was

subsequently procured, installed on the BSI rooftop facility, and tested by pointing a video camera at the Sun and

analyzing the data recorded.

The tests verified most of the specifications provided

by the manufacturer, however, it was determined that the

zenith drive of the system is affected by a backlash of about

0.1◦. The manufacturer acknowledged this value does not

meet specification and readjusted the drive mechanism.

The angular precision (calculated as the standard deviation of repeat measurements) of the refurbished unit was

0.008◦, both in the zenith and azimuth directions. This

value is close to the theoretical limit defined by the pan

and tilt resolution of 0.0064◦.

Sun trackers for OSPREy require a pointing accuracy

of better than ±0.2◦, and the refurbished system met the

pointing accuracy specification of 0.01◦ (Table 5). Even if

backlash were to reappear after additional months of operation, its effect could be mitigated by adjusting the measurement protocol accordingly. For example, the tracking software could be modified such that a specific angular position is always approached from the same direction.

By mounting the payload slightly off balance, gravity also

helps to load the zenith gear in one direction.

Tests also indicated that the range of motion for the

tracker is ±89.5◦ in the zenith direction and ±175◦ in

the azimuth direction. These values are somewhat smaller

than specified. It is, therefore, not possible to point to the

zenith (directly overhead) and nadir (directly below). Radiometers attached to the tracker could be mounted with

a small offset, however, so that observations of the zenith

sky are possible. The ability to point downward is desirable for “safing” or “stowing” the instrument (e.g., during

inclement weather), and for measuring dark currents during daylight (e.g., when a light-tight enclosure is installed

at the base of the instrument). These measurements could

also be performed at a zenith angle of −89◦, and the ability

to point to the exact nadir is, therefore, not a requirement

for OSPREy.

36
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

There is an azimuth range of about ±5◦, nominally

towards North, that cannot be accessed. This is not a

problem for OSPREy applications because measurements

in this direction are not required. The PTU-D300 provides cable pass-throughs for the payload, which reduces

the risk that cables from a radiometer mounted to the instrument get entangled or damaged, e.g., during periods

of high wind.

The software for finding the center of the Sun is very

reliable and fast. Determinations of the Sun’s center are

reproducible to within ±0.01◦. Using a video camera in

combination with this software is a viable and cost-effective

alternative to quadrant detectors, which are typically used

for Sun trackers, such as the 2AP-GD unit. The trackermounted EML sensors are equipped with a small video

camera, and the integrated approach improves the tracking accuracy from about ±0.05◦ for the test system, to

better than ±0.01◦. The accuracy is only limited by the

step resolution of the tracker, which is 0.0064◦. Active

tracking using a video camera extends the tracker’s range

to θs > 80◦, where refraction by the atmosphere limits

the accuracy of the ephemeris algorithm. Subsequent tests

with an EML radiometer confirmed the suitability of this

tracker for OSPREy systems.

37
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 6

Lamp Library Performance

Germar Bernhard and Charles R. Booth

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

Twenty-one 1,000W tungsten-halogen FEL lamps were chosen to become part of the OSPREy lamp library.

Nine lamps were calibrated by NIST, while the rest are uncalibrated, but seasoned lamps (by the supplier).

These lamps were operated for periods ranging from 4–35 h to assess their stability. Changes in brightness

were typically in the range of ±0.02% per hour with a few lamps exhibiting slightly larger drifts. These lamps

should be seasoned for an additional 8–30 h to improve their stability. The calibration laboratory at BSI was

upgraded to operate lamps of the OSPREy lamp library at the highest level of accuracy achievable. Upgrades

included a new system for powering the lamps, which allows regulation of the lamp current to within a precision

of 50 μA (or 0.0006% for a target current of 8.2 A). Other facilities required for accurate lamp transfers were

also upgraded to reduce uncertainties caused by stray light, misalignment, and temperature variations. Three

radiometers are available for maintaining optical standards: an OXL instrument calibrated at BSI, an OXE

instrument currently awaiting results of a NIST SIRCUS calibration (and not used for the results presented in

this chapter), and a transfer radiometer based on the BSI ground-based UV (GUV) class of radiometers that

is called an XGUV. A comprehensive uncertainty analysis showed the use of moderate-bandwidth radiometers,

such as the XGUV and OXL, are suitable to transfer calibrations of FEL lamps. Uncertainties related to the

relatively large bandwidth of these instruments are on the order of 0.3%. All NIST lamps were intercompared

and agreed to within ±2%, which is a very good result considering that some lamps are rather old and were

calibrated against different NIST scales. A protocol on the usage of the lamp library was developed with the

goal of preserving the spectral irradiance scale over a timescale of 15 years or more.

6.1 Introduction

The radiance and irradiance scales for OSPREy are

linked to the NIST SIRCUS radiometric scale. Two OXR

sensors were planned to be calibrated by SIRCUS, and the

calibrations transferred to OSPREy field instruments. The

OXE sensor was sent to NIST for SIRCUS calibration in

2010 and is awaiting the calibration report. Pending final

results, the OXL unit may also be calibrated at SIRCUS.

Calibration details of the radiometers used in the OSPREy

activity is provided by Bernhard et al. (2012).

While OXR instruments are designed for maximum

short- and long-term stability that is achievable with current technology, small drifts of the instrument’s responsivity over time can be expected, as is the case for any radiometer. To maintain the calibration of OXR radiometers

for long periods of time (e.g., one decade), a cost-effective

approach is to transfer the scale to standards of spectral

irradiance, which are commonly realized by 1,000W tungsten halogen lamps of type FEL.

Lamps, like radiometers, change over time. To avoid

drifts in the spectral radiance and irradiance scales over

time, it is essential to transfer the scale to several lamps,

which are regularly intercompared to ensure consistency

of their calibrations. This suite of lamps is called the OSPREy lamp library.

Ensuring the stability of radiometric scales to within

1% over the long term, either using radiometers or lamps, is

a demanding task. To achieve this goal, lamps must be operated with specialized equipment in a well-characterized

dark room. The laboratory at BSI was, therefore, upgraded with state-of-the-art equipment, including precision power supplies, laser alignment tools, and additional

baffles to reduce stray light as much as possible. The lamp

library currently consists of 21 lamps, some of which were

38
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Table 6. A summary of the OSPREy lamp inventory. The specified number of amps indicates the calibration

current for the lamp. Lamps with a blank calibration scale entry are provided uncalibrated by the supplier

(lower half of table). The date of first use is at BSI and is with respect to establishing the OSPREy lamp

library.

S/N Manufacturer Owner Supplier Amps Scale First Use Tested

F-137 General Electric NASA NBS† 8.0 Unknown Jan. 2010 OXR

F-182 General Electric NASA NIST 7.9 NIST 1990 Jan. 2010 OXR, XGUV

F-473 Osram Sylvania BSI NIST 8.2 NIST 1990 1997 OXR, XGUV

F-474 Osram Sylvania BSI NIST 8.2 NIST 1990 1997 OXR, XGUV

F-527 General Electric NASA NIST 7.9 NIST 1990 Jan. 2010 OXR

F-550 General Electric NASA NIST 8.2 NIST 1990 Jan. 2010 OXR

F-614 Osram Sylvania NASA NIST 8.2 NIST 2000 Jan. 2010 OXR, XGUV

F-615 Osram Sylvania NASA NIST 8.2 NIST 2000 Jan. 2010 OXR, XGUV

F-616 Osram Sylvania NASA NIST 8.2 NIST 2000 Jan. 2010 OXR, XGUV

V-017 Osram Sylvania NASA CUCF‡ 8.2 Apr. 2008 Not Tested

V-018 Osram Sylvania NASA CUCF 8.2 Apr. 2008 OXR

V-019 Osram Sylvania NASA CUCF 8.2 Apr. 2008 OXR

V-020 Osram Sylvania NASA CUCF 8.2 Apr. 2008 XGUV

V-021 Osram Sylvania NASA CUCF 8.2 Apr. 2008 OXR

V-022 Osram Sylvania NASA CUCF 8.2 Apr. 2008 OXR

GS-1019 Osram Sylvania BSI Gamma Scientific 8.0 Aug. 2008 Not Tested

GS-1024 Philips Electronics BSI Gamma Scientific 8.0 May 2008 XGUV

GS-1025 Philips Electronics BSI Gamma Scientific 8.0 May 2008 XGUV

GS-1026 Philips Electronics BSI Gamma Scientific 8.0 May 2008 XGUV

GS-1027 Philips Electronics BSI Gamma Scientific 8.0 May 2008 XGUV

GS-1028 Philips Electronics BSI Gamma Scientific 8.0 May 2008 XGUV

† The National Bureau of Standards (NBS) was the precursor Federal agency to NIST.

‡ The NOAA Central UV Calibration Facility (CUCF) is a joint activity with NIST.

calibrated by NIST FASCAL, which issues calibrated FEL

standard lamps. It is possible, therefore, to compare the

radiometric scales provided by SIRCUS and FASCAL using the lamp library and OXR instruments.

6.2 Lamp Inventory

Twenty-one FEL lamps were chosen to establish the

OSPREy lamp library (Table 6). All lamps are potted

in bi-post bases compatible with the recommended NIST

kinematic lamp socket (Zalewski et al. 1972). Not all lamps

are calibrated by NIST, because it would have been costprohibitive to base the lamp library exclusively on NIST

lamps. Two NIST lamps (F-473 and F-474) have been in

use at BSI since 1997 and their calibration refers to the

NIST FASCAL irradiance scale from 1990 (Walker et al.

1987). Lamps F-182, F-527, and F-550, which belong to

NASA, are also traceable to the NIST 1990 scale.

Standard lamp F-137 was calibrated by NBS in 1982

against DXW standards. The traceability of this lamp is

unknown. Three lamps (F-614, F-615, and F-616) were

acquired from NIST specifically for the OSPREy activity,

and their calibration is traceable to the latest NIST irradiance scale, which was established in 2000 (Yoon et al.

2002). The NIST irradiance scale of 2000 has a smaller uncertainty than the NIST 1990 scale (Table 7) and is about

1.0–1.5% larger in intensity (Yoon et al. 2002).

Table 7. Typical irradiance values (in units of

μW cm−2 nm−1) and uncertainties as a function of

wavelength (λ) for NIST spectral irradiance standards (Yoon et al. 2002). The uncertainties are relative expanded uncertainties (k = 2, where k is the

coverage factor) and are shown for the 1990 and

2000 NIST scales.

λ Typical Uncertainty

[nm] Value 1990 2000

250 0.02 1.8% 1.56%

350 0.85 1.1 1.12

655 17.0 0.7 0.63

900 23.0 1.1 0.47

1,600 12.0 1.4 0.33

2,400 4.00 4.4 0.57

39
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

FEL lamps have a limited calibration lifetime of about

50 h. To preserve the NIST scale over longer periods,

it is necessary to transfer the irradiance scale to other

lamps. Consequently, six lamps were procured from the

NOAA Central Ultraviolet Calibration Facility (CUCF)

and added to the lamp library (GS-017 through GS-022, inclusive). The CUCF† (Boulder, Colorado) is a joint project

between NOAA and NIST whose mission is to provide

highly accurate standards for UV monitoring networks in

the US.

Because the quality of FEL lamps has deteriorated over

the last years, the CUCF has refined methods to pot,

screen, and season 1,000W FEL lamps (Disterhoft 2005).

CUCF procured and tested 50 lamps from Osram Sylvania

and found the batch of lamps was very stable and did not

exhibit emission lines of aluminum, which were observed

in many lamps tested during the last years (pers. comm.,

Patrick Disterhoft, CUCF). The six lamps procured from

CUCF showed excellent stability during their seasoning at

CUCF, and it was confirmed that they do not exhibit any

anomalous emission lines. These lamps were believed to

be the best quality attainable at the time of purchase.

To add to the lamp library, six lamps were procured

from Gamma Scientific (San Diego, California) who are

one of a few vendors of potted and seasoned FEL lamps.

The procured lamps were seasoned for 20 h before they

were potted, and an additional 10 h after potting before

they were shipped to BSI. Additional lamps from other

vendors are currently being tested for possible inclusion in

the lamp library.

Ohno (1997) stated that new incandescent lamps decrease in luminous intensity by 10% or more in the first few

percent of their life, and that standard lamps must be seasoned at the rated operation current for more than 5% of

the rated life. For FEL lamps, Ohno suggests seasoning at

the rated current for 24 h, followed by more than 48 h at the

operating current. The CUCF lamps were seasoned at the

CUCF facility for more than 20 h before they were shipped

to BSI. Seasoning times of the “V” and “GS” lamps are

shorter than those recommended by Ohno (1997).

All of the uncalibrated lamps (starting with “V” or

“GS”) were operated for periods ranging from 4–35 h using the software described in Sect. 6.3.1. Lamp current

and voltage were recorded and lamp irradiance was monitored with either the XGUV or OXR (Sect. 6.4). A summary of this lamp validation activity is provided in Fig. 25

and Table 8, which show a comparison of changes in irradiance (“drifts”) that were calculated for all lamps from

the radiometric measurements. In the visible, lamp drifts

ranged between approximately −0.03% and +0.03% per

hour, whereas in the UV, the drifts ranged between about

−0.04% and +0.01% per hour. Although all lamps were

† Additional information concerning the CUCF and their joint

mission with NIST is available on the following Web site:

http://www.srrb.noaa.gov/calfacil/cucfhome.html.

seasoned, drifts were typically larger during the first hours

of testing. These results indicate some lamps should be

seasoned for another 10–30 h before a calibration transfer.

G G

G

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C

C CC

C

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A

A

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AA

AAA A A AAA AAA AA

S S S SS

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SSSSSS S SS SSS

J J

J

J J

J J

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G G

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A A A A

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AAAA

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S S S S S S

S

SSS

SS

-0.16

-0.06

0.04

0.14

290 490 690 890

Drift per hour [%]

Wavelength [nm]

G 018 (1-4)

E 019 (1-4)

C 020 (1-4)

A 021 (1-4)

S 022 (1-4)

J 1027 (1-4)

E 1027 (10-35) 

G 1025 (2-25)

C 1024 (3-6)

F 1026 (1-4)

A 1026 (10-25)

S 1028 (1-4)

Fig. 25. The drifts in the uncalibrated “V” and

“GS” lamps (blue and red, respectively) that are

part of the OSPREy lamp library. Lamps that were

tested twice are denoted with a solid symbol.

Table 8. A summary of lamp output drifts (in units

of percent change per hour) for the uncalibrated

lamps in the lamp library as a function of the UV

and visible spectral domains.

Serial Time Drift

Number On [h] UV Visible

V-017†

V-018 4 0.011 −0.001

V-019 4 −0.006 −0.007

V-020 4 0.007 −0.001

V-021 4 −0.031 −0.042

V-022 4 0.014 0.005

GS-1019†

GS-1024§ 4

GS-1025 25 0.034 0.009

GS-1026 25 0.027 0.010

GS-1027 35 0.027 0.008

GS-1028 4 0.015 −0.011

† Not tested.

§ Requires additional seasoning before establishing the

long-term performance.

NIST asserts that well-seasoned FEL lamps should be

stable to within 0.3% over a 24 h period. This translates to

drifts less than 0.0125% per hour. This drift rate compares

well to the drift rate of lamps of the “V” series. Lamps of

the “GS” series show somewhat larger drifts, in particular

below 350 nm. It appears prudent to season these lamps

for an additional 10–30 h before calibrating them.

40
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

6.3 Lamp Operation

Operating FEL standards of spectral irradiance at the

highest level of accuracy entails demanding requirements

for lamp setup and operation. Important factors to address include accurate control over the drive current for

the lamp, meticulous lamp alignment, and good stray light

suppression in the calibration dark room.

6.3.1 Control of Lamp Current

The output of an FEL lamp at 300 nm changes by about

1% per 0.1% change in the current used to power the lamp

(Kostkowski 1997). To achieve the desired accuracy of better than 0.1% in the output of the lamp, the current has

be controlled to better than 0.01%. This is not achievable

with COTS digitally-controlled power supplies, because of

the low resolution of these devices. Consequently, BSI developed a customized control system for powering a lamp,

which consists of the following components:

• Power supply with analog control input (Agilent

6654A);

• High-precision voltage source (National Instruments

NI-9263);

• High-quality digital multimeter (Agilent 34401A)

for measuring the voltage drop across the shunt;

• High-accuracy shunt (Isabellenhuette ISA-PLAN

Precision Resistor Type RUG-Z) and;

• Custom LabVIEW software (National Instruments)

to set, monitor, and control the lamp current.

Current is supplied to the lamp posts, and lamp voltage is

monitored at the opposite (kinematic) contacts. A highcapacity uninterruptible power supply (UPS) is integral to

the system to prevent sudden power losses or fluctuations

at the lamp in case of a power outage, brownout, or surge.

With this system, it is possible to set and maintain the

lamp current to within a precision of ±50 μA (0.0006% for

a target current of 8.2 A). The accuracy of the current is

only limited by the calibration uncertainty of the shunt

of less than ±0.002%. LabVIEW software was developed

that allows the system to execute the following:

1. Linearly ramp up the lamp current over several minutes using the digital input of the power supply to

a point 25 mA below the specified current.

2. Finely tune the lamp current to within ±50 μA using the analog programming terminals of the power

supply and a 16-bit ADC reading the voltage across

the shunt.

3. Monitor the voltage at the lamp terminals, plus the

temperatures of several key components (multimeter, laboratory, and shunt).

4. Display the lamp current, voltage, and power plus

deviation from established lamp voltage.

5. Write all measurements and ancillary information

(e.g., cumulative lamp usage time) into databases.

A screenshot of the software in operation is provided in

Fig. 26, which is divided into three columns. The left column is used to select the shunt and lamp, to turn on the

lamp, and to actuate the shutter used for dark current

measurements. The center panel gives an overview of the

lamp current, voltage, and power, and indicates whether

the lamp has reached a stable state. The current and voltage reported by the power supply, plus lamp usage times

are also displayed. The right column provides time-series

plots of temperature at several locations in the laboratory,

as well as lamp voltage, current, and power.

Fig. 26. The software control panel for operating

FEL lamps.

6.3.2 Laboratory and Lamp Setup

The BSI calibration laboratory was upgraded in 2009 to

meet the requirements for high-accuracy calibration transfers. Materials (e.g., paints, walls, and curtains) with low

reflection in the infrared were selected to reduce uncertainties from stray light in the SWIR wavelengths. The

laboratory is temperature stabilized to within 1◦C. The

temperature and humidity are measured at several locations including the lamps, bases, and radiometers; and air

flow disturbance from air conditioning vents is minimized.

6.3.2.1 Irradiance Bench

A new irradiance optical bench was designed and constructed. Using occulting devices placed in the direct optical path between the lamp and collector, stray light contributions at all wavelengths was confirmed to be less than

0.1%. Transfer radiometers are positioned in kinematic

mounts, which allow reproducible instrument removal and

reinstallation. Lamps are mounted in a kinematic lamp

socket designed by NIST (Zalewski et al. 1972), which is

attached to a stack of linear and tilt stages allowing precise alignment with respect to six degrees of freedom. Baffles between the lamp and radiometer were designed using

NIST guidelines (Yoon and Gibson 2011) to further minimize stray light. The laboratory back wall is covered with

black fabric tested for minimum reflectivity to reduce onaxis reflections and is 2 m away from the lamp.

41
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

A computer-controlled shutter was installed between

the lamp and radiometer for automated dark-current measurements. A laser alignment system was added to allow

fast and reliable alignment of lamps and transfer radiometers. Correct alignment of a radiometer can be verified

by placing a mirror placed in front of the radiometer and

confirming that the laser beam reflects back on the laser

aperture. Similarly, a standard lamp alignment jig, having a window with etched crosshairs to mark the location

of the lamp, can be inserted in the lamp holder to verify

the lamp is correctly positioned (Fig. 27). The distance

between the lamp and radiometer is adjusted with the aid

of an aluminum rod that is precisely machined to 50 cm.

Lamp Alignment

Jig with Crosshair

Kinematic

Lamp Socket

Knife-edge

Baffle

Lamp Alignment

Stages

Fig. 27. The irradiance bench lamp alignment assembly. The red lines are generated by the alignment laser, which defines the optical path and is

used to center the crosshair of the alignment jig.

6.3.2.2 Radiance Bench

The BSI radiance optical bench was also improved. The

lamp is mounted 290 cm away from a Spectralon plaque

made by Labsphere, Inc. (North Sutton, New Hampshire).

The bidirectional reflectance distribution function (BRDF)

of the plaque is regularly calibrated by Labsphere. Black

baffles held in place with flat-black frames are mounted

between the lamp and plaque to reduce stray light. Black

curtains, which were selected to have low reflectivity in

the visible and infrared, were installed to block light paths

other than the direct path from lamp to plaque.

Dual mounts were designed and installed, which enable

reproducible radiometer alignment and accurate pointing

to the center of the plaque from opposite sides at 45◦ angles. The setup allows for the installation of two radiometers at the same time wherein one radiometer can be a

monitoring device, which stays in place during an entire series of calibration transfers. The second holder can accommodate radiometers to be calibrated or recalibrated. The

radiance test bench is also equipped with a laser alignment

system and a computer-controlled shutter for automated

dark-current measurements.

6.4 Lamp Transfer Radiometers

The individual lamp library lamps were characterized

with the XGUV and the OXL instruments. These radiometers can also be used to transfer irradiance scales from one

lamp to another. The XGUV has been in service at the BSI

calibration facility for several years, is optimized for UV

transfers with a 290–875 nm spectral range, and is used on

the irradiance optical bench. The OXL instrument spans

340–875 nm with microradiometers and 325–790 nm with a

spectrograph, which is normally mounted on the radiance

calibration bench; and the OXE instrument spans 320–

1,640 nm with microradiometers and 250–785 nm with a

spectrograph.

The OXE instrument was not used for the lamp characterizations and is presented to complete the description

of the OXR instrumentation developed for the OSPREy

activity (it is the companion sensor to the OXL). The centroid wavelengths for the XGUV and OXL instruments are

presented in Table 9.

Table 9. Nominal (left column) and centroid wavelengths of the XGUV and OXL sensors used as lamp

transfer radiometers.

λ [nm] XGUV [nm] OXL [nm]

289 291.29

300 301.13

313 311.24

320 319.18 318.19

340 339.12 339.12

380 379.92 379.33

395 395.64

412 411.06

443 442.62 441.92

465 464.07

490 489.08 488.96

510 509.26

532 530.40

555 554.43 553.21

589 588.55

625 624.46

665 665.46 663.87

683 682.98

710 708.06

780 779.46 777.63

875 875.07 873.42

6.4.1 The XGUV

The XGUV is based on PRR electronics and GUV2511 radiometers, and has 12 channels. Spectral response

functions of each channel were measured with the BSI

spectral tester (Bernhard et al. 2005) and their centroid

wavelengths λc

i were calculated. Nominal and centroid

wavelengths are summarized in Table 9. The XGUV is

42
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

equipped with a cosine collector and temperature stabilized to ±0.1◦C.

6.4.2 The OXL

The OXL is a laboratory instrument designed to monitor and transfer radiance calibrations. It combines filterphotodetector technology at 18 discrete wavelengths (Table 9) with a high-resolution spectrograph, Hamamatsu

model C9407MA (Bridgewater, New Jersey). The OXL is

temperature stabilized to about ±0.1◦C, and the radiance

fore optics have a 17◦ FVA. The spectrograph spans 325–

793 nm, with bandwidths of 7 nm in the UV and 5 nm in the

visible, and has a complementary metal oxide semiconductor (CMOS) detector with 256 pixels and 16 bit digitization. The OXL is a very stable, hybridspectral radiometer;

ideal for radiance measurements of calibration sources such

as a 1,000W FEL irradiance standard used in conjunction

with a calibrated reflectance plaque.

6.4.3 Software for Lamp Spectra

Data measured by transfer radiometers are written to

a centralized Structured Query Language (SQL) database.

Software was developed to parse this database and calculate a summary of a measurement sequence. The results

include the means and standard deviations of light and

dark data sequences. These measurements are also compared with the previous usage of a given lamp, and the ratio of the two measurements is graphically displayed. This

feature allows real-time assessment of lamp drifts while the

lamps are still being used. Queries of the databases can

also be used to retrieve the lamp usage history, current and

voltage stability, and laboratory conditions (temperature

and humidity) during calibration activities.

6.5 Lamp Transfer Uncertainties

Comparisons of lamp library FEL standards, as well as

the transfer of an irradiance scale between lamps, should

ideally be performed with a radiometer that has an infinitesimally small bandwidth. From a practical point of

view, such a radiometer cannot be designed and manufactured. Instead, this section discusses uncertainties associated with using moderate-bandwidth radiometers, such as

the XGUV and OXR. The channels of these radiometers

have approximately a rectangular (box-shaped) slit function with a nominal bandwidth of about 10 nm.

6.5.1 Setup of Analytical Functions

Systematic uncertainties from a moderate-bandwidth

instrument depend mostly on differences in the shape of

the spectrum associated with the FEL lamp†. For this

† If two lamps with different brightness, but identical spectral

shape are compared, the bandwidth of the instrument would

not affect the transfer.

analysis, analytical functions Φ(λ) were fitted to the irradiance values E(λ) of several FEL lamps from various manufacturers (Table 10). These functions formed the basis of

the analysis presented in the following subsections.

Table 10. The lamps used for ucertainty estimates.

Lamp Manufacturer Amps Origin

F-614 Osram

Sylvania 8.2 NIST

F-615 Osram

Sylvania 8.2 NIST

F-616 Osram

Sylvania 8.2 NIST

91537 General

Electric 7.9 GammaScientific

BSI-1 Ushio 8.2 Gamma

Scientific

BSI-2 Ushio 8.2 Gamma

Scientific

HEC-1631 Unknown 8.0 Hofmann

HEC-1632 Unknown 8.0 Hofmann

0.8

0.9

1.0

1.1

250 750 1250 1750

Ratio

Wavelength [nm]

Fig. 28. The ratio of irradiance calibration values

for NIST lamp F-616 to a black-body fit (blue). The

red line is the inverse of the fit function f(λ).

To determine Φ(λ), black-body (or Planck) functions,

P(λ), were fitted to the lamps’ irradiance tables. In a

second step, functions of the form

f(λ)=1+ η1e−η2(λ−η3) + η4 + η5λ + η6λ2

1 + e−(λ−η7)/η8

(5)

were fitted to the ratio of P(λ) and E(λ), where λ is wavelength, and ηi are eight fit coefficients. Figure 28 shows

43
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

-0.3

-0.1

0.1

0.3

260 340 420 500

Rectangular Slit Function RPD [%]

Wavelength [nm]

a

0

-0.3

-0.1

0.1

0.3

260 340 420 500

Triangular Slit Function RPD [%]

Wavelength [nm]

b

0

Fig. 29. The systematic uncertainties involved when using a hypothetical spectroradiometer for lamp transfers

that has two different slit functions of 10 nm FWHM: a) rectangular (or box-shaped), and b) triangular. The

uncertainties are computed with NIST lamp F-614 as the reference in the RPD calculation (Sect. 1.1.2). The

lamps involved are shown in groups. The real lamps are NIST FELs 614, 615, and 616 (black); 91537 (green);

BSI lamps 1 and 2 (blue); HEC-1631 (violet); and HEC-1632 (purple). The black-body functions are shown

as a function of temperature ranging from 2,800–2,900 K (orange), 3,000 K (gray), and 3,100–3,300 K (red).

the ratio E(λ)/P(λ) and the associated inverse of the fit

function f(λ) for NIST lamp F-616. The fit was equally

good for all lamps, indicating that functions of the type

Φ(λ) = P(λ)/f(λ) are an excellent analytical representation of FEL irradiance tables.

6.5.2 Effect of Bandwidth

Figure 29a shows the effect of using a hypothetical

spectroradiometer that has a rectangular (box-shaped) slit

function of 10 nm full-width at half-maximum (FWHM).

The first eight data sets were calculated based on the real

lamps described above. The remaining data sets are based

on black-body functions with color temperatures ranging

between 2,800–3,300 K. All data sets are with respect to

NIST lamp F-614. Figure 29b shows a similar figure for

a hypothetical instrument with a triangular slit function

of 10 nm FWHM (20 nm at the base). In both figures,

the maximum uncertainty at 300 nm is smaller than 0.3%,

and smaller than 0.1% for wavelengths larger than 370 nm.

These uncertainties are considerably smaller than the uncertainty of lamp irradiance tables issued by NIST. It can

therefore be concluded that moderate-bandwidth radiometers such as the OXR radiometers are more than adequate

for the transfer of calibrations from one FEL lamp to another.

6.5.3 Calibration Transfer Simplifications

The signal (amplitude) A of channel i of a moderatebandwidth radiometer measuring a lamp is proportional

to

A(λi) = 

γ(λi) E(λ) dλ, (6)

where γi(λ) is the spectral response function of channel

i and E(λ) is the spectral irradiance of the lamp. When

comparing two lamps with irradiance E1(λ) and E2(λ), the

ratio Υ of the signals is:

Υ(λi) =

 γ(λi) E1(λ) dλ

 γ(λi) E2(λ) dλ. (7)

In practice, this ratio is not evaluated. Instead the simplified ratio Υ is calculated, which is defined as:

Υ

(λi) = E1(λc

i)

E2(λc

i)

, (8)

where λc

i is the centroid wavelength of channel i calculated

from the response function γ(λi).

An analysis of the systematic uncertainty introduced

by this simplification was made by computing the ratio

of Υ

(λi) to Υ(λi). The data were once again referenced

to NIST lamp F-614. The uncertainty was found to be

largest at the shortest wavelengths. For the comparison of

real lamps, the uncertainty was less than 0.2% at all wavelengths. The uncertainty only exceeded 0.3% when lamps

with color temperatures below 2,900 K or above 3,300 K

were used. The latter is likely not an issue when comparing FEL lamps, but could become an issue when lamps

of another type are used in the lamp library in the future

44
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

(recalling that the lamp library cannot remain a static inventory, because lamps have finite lifetimes and inevitably

are replaced). It was concluded that the centroid method

was adequate for lamp comparisons.

6.5.4 Uncertainties

The measurement of response functions is affected by

uncertainties, and this may also lead to some uncertainty

in the calculation of the centroid wavelength for each instrument channel. To study this effect, spectra of all test

lamps were shifted by 1 nm and compared to the unshifted

spectra, and following the procedure used in earlier (Sect.

6.5.2), the computations are with respect to NIST lamp

F-614. The results are presented in Fig. 30 following the

presentation scheme established for Fig. 29 (but note the

change in scales). For wavelengths above 300 nm, systematic uncertainties due to 1 nm wavelength shifts are smaller

than 0.5% in all cases. For the subset of real lamps, uncertainties are smaller than 0.15%.

-1.0

-0.5

0

0.5

260 340 420 500

RPD [%]

Wavelength [nm]

Fig. 30. The uncertainty (expressed as the RPD

with respect to NIST lamp F-614) caused by a 1 nm

shift in the centroid wavelength.

An uncertainty of 1 nm in the centroid wavelength for

a particular channel is, therefore, adequate. The BSI spectral tester allows measurements of spectral response functions of the multichannel instruments with uncertainties

of approximately 0.1 nm. Uncertainties resulting from the

wavelength mapping of spectral response function measurements are, therefore, a negligible contribution to the

overall lamp transfer uncertainty.

6.6 Lamp Usage Protocol

Prior to using a lamp, the correct alignment of the test

setup is verified using the laser alignment system (Sect.

6.3.2.1). The FEL to be used is inserted into the lamp

holder, with its identification tag facing away from the

sensor. The computer-controlled power supply is turned

on and slowly ramped up (to avoid thermally shocking

the filament) until the proper operating current for the

particular lamp is achieved.

Following a warm-up time of at least 15 min, the shutter of the test bench is closed and dark-current measurements are taken for a 1 min period. The shutter is then

opened and light measurements are recorded. Lamp currents, voltages, and other parameters provided by the LabVIEW software (Sect. 6.3.1), as well as measurements of

the transfer radiometer are written to SQL databases. On

completion, the lamp current is slowly ramped down (to

avoid thermally shocking the filament), and the lamp is

removed from the holder only after it has cooled down

completely.

6.7 Lamp Comparisons

All lamps of the OSPREy lamp library that have a calibration certificate were compared on both the radiance

and irradiance optical benches. Lamps were powered using the LabVIEW software and allowed to warm up for at

least 20 min. After the warm-up period, the dark currents

of the transfer radiometers were measured for 1 min, followed by 1 min of light measurements. Lamp V-020 was

measured on both calibration benches at the beginning and

end of the comparison sequences to verify that the calibration setup (transfer radiometers, lamp power, alignment,

and stray light in the laboratory) remained stable. These

measurements indicated that the system did not change by

more than ±0.15% over the course of the experiment.

As an example comparison, all of the measurements

with lamp V-020 that were performed on the radiance

bench are considered. The lamp was measured five times:

in the morning and evening of the first day of measurements, and then three times on the following day. Ratios of all measurements with the OXR relative to the

first measurement show the OXR microradiometer channels changed by less than ±0.1%, with the exception of the

710 nm channel, which had one outlier at 0.15%.

Measurements with the spectrograph were consistent

at the same level, however, some data were affected by the

spectrograph’s hot pixels (i.e., pixels with locally higher

dark value than their neighbors), most notably at 374.4,

406.5, and 656.5 nm. Spectrograph data were also affected

by considerably more signal noise in the UV compared to

the microradiometer channels. The relative uncertainty

u

(λ), which is caused by signal noise, is shown in Fig. 31,

and is determined by

u

(λ) =

σ2(λ) + σ2(λ)

μ(λ) − μ(λ) , (9)

where μ(λ) and μ(λ) are the mean light and dark signals,

respectively, and σ and σare the corresponding standard

45
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

deviations. For the microradiometer channels, u

(λ) is

smaller than 0.1%, except for the 380 nm channel, whose

filter has lower transmission than that of other channels.

For the spectrograph, u

(λ) exceeds 1% for wavelengths

smaller than 380 nm. This demonstrates that the spectrograph is less suitable for performing accurate lamp transfers in the UV at these radiance levels.

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0.0001

0.001

0.01

0.1

300 500 700 900

Relative Uncertainty [%]

Wavelength [nm]

Fig. 31. The relative uncertainty of measurements

in the OXR microradiometer channels (open circles) and the spectrograph (solid circles) determined

from five measurements (different colors).

Lamps were compared relative to the NIST standard

F-616, which is considered to be the most trustworthy lamp

of the lamp library. First, it is traceable to the NIST

2000 scale, and second, the voltage drop when powered up

agrees best with the value specified by NIST. The lamps

were compared by calculating the so-called Γl values, which

are ratios defined as

Γl(λi) = μl(λi) − μl(λi)

Φl(λc

i )



μr(λi) − μr(λi)

Φr(λc

i )

	−1

, (10)

where μl and μl are the 1 min means of light and dark measurements, respectively, of the transfer radiometer when

measuring lamp l with channel λi; Φl(λc

i ) is the value of

the fit function of lamp l at the centroid wavelength that

is associated with channel i; and r denotes the reference

lamp (F-616). The denominator (the terms in brackets) of

Γl includes similar quantities for the reference lamp.

Ten-parameter functions of the type introduced in Sect.

6.5.1 were fitted to the irradiance tables of all lamps. Figure 32 shows the residuals to these fits, expressed as the

ratio of the fit functions, Φ(λ), to the irradiance values

that are tabulated in the lamp certificates. Residuals are

typically smaller than 0.25%. There is some variability at

the shorter wavelengths in Fig. 32, which is due to noise

in the tabulated values. Because the fit functions smooth

this noise, it is believed that these functions provide values

closer to the actual spectral irradiance of the lamps than

the values of the certificates.

Fig. 32. The residuals of the 10-parameter fit, expressed by the ratio of fit functions Φ(λ) to the tabulated irradiance values E(λ) of all lamps.

6.7.1 Irradiance Bench Comparison

Figure 33 shows Γl values determined from measurements using the irradiance bench and the XGUV as the

transfer radiometer, but expressed as RPDs, by subtracting 1 from the ratio in (10) and multiplying by 100. There

is excellent (better than 0.3%) agreement between lamps

F-615 and F-616. Measurements of lamp F-614 are 0.5–

1% too high. These high values were expected because the

voltage drop across the contacts of the lamp was 108.107 V,

which is 1.2% larger than the value reported by NIST

(106.83 V). It is likely the lamp changed during transport

from NIST to BSI (although the lamps were hand transported on an airline, not shipped by common carrier).

Fig. 33. The Γl(λi) values for seven lamps expressed as an RPD and determined with irradiance

bench comparisons using the XGUV.

46
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

The calibrations of all other lamps are with respect to

the NIST 1990 scale. As expected, these lamps are lower

in the UV by about 1.5% (see also the black line labeled

NIST1990/NIST2000 in Fig. 33). The two measurements

of lamp F-473 are very consistent. Lamp GS-1024 was calibrated against F-473 in August 2008 and not used since.

The figure indicates that the irradiance scales of the two

lamps were still in very good agreement on 7 January 2010.

Measurements of lamp GS-1019 were high, even though it

was also calibrated against F-473 in August 2008. In contrast to lamp GS-1024, it was used for 18 hours and the

difference likely reflects its aging over time.

6.7.2 Radiance Bench Comparison

Figure 34 shows a similar comparison for measurements

performed on the radiance bench using the OXR. Measurements for all lamps agree to within ±2%, except lamp

F-137, which was not run on the irradiance bench. This

lamp is very old; it was calibrated in 1982 against a DXW

lamp, and some time ago during an intercomparison exercise, another laboratory wrapped the lamp in plastic while

it was still hot. Some of the plastic melted on the glass envelope. When used for the trials presented here, no plastic

was visible, but it is possible that the glass envelope was

permanently damaged. It was included in the lamp library

to set an end-member state as to what can be expected

from a mishandled lamp.

QQ

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F FFF F F

PP P

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PPPPPPPP P PP SS S P P P SSSSSSSSS S SSS S S

BBB

B

BBBBBBBBBBBB B B

-2.3

-0.3

1.7

3.7

250 500 750 1000

RPD [%]

Wavelength [nm]

F-182

GS-1019 F-550

F-614

F-473

NIST

1990/2000

F-615

F-474

F-137

F-527

0

Fig. 34. The Γl(λi) values for nine lamps expressed

as an RPD and determined with the radiance bench

using the OXR. Measurements of OXR microradiometer channels are indicated by symbols, and

measurements of the spectrograph are indicated by

the color-matched lines.

Lamp F-550 has the highest irradiance of all undamaged lamps (excluding F-137). The spectrograph saturated

between 530–580 nm when measuring this lamp (light blue

line in Fig. 34). The hot spectrograph pixel at 656.5 nm

is visible for most lamps as a notable spike in the data.

Because of the many data sets plotted in Fig. 34, it is difficult to compare measurements of microradiometer channels and the spectrograph. Subsets of the figure were therefore redrawn, and are shown in Fig. 35.

Figure 35a shows the Γl values expressed as RPDs for

lamps F-137, F-182, and F-527. The Γl values for microradiometer channels and the spectrograph generally agree

well, with the exception of the UV wavelengths of lamp

F-527 for which the spectrograph measurements are lower

than the corresponding microradiometer measurements by

up to 2%. This difference is likely caused by changes in

the dark current for the spectrograph. The spectrograph

is close to its detection limit at these wavelengths, and

even small changes in dark current can have a significant

relative effect.

Also note that there is a dip of about 0.5% in the Γl

values for all three lamps at 395 nm, which is seen in both

the microradiometer channels and the spectrograph. This

dip is caused by an emission line of aluminum that is affecting lamp F-616, according to the lamp certificate issued

by NIST. Disterhoft et al. (2005) reported that aluminum

emission lines at 308, 309, 394, and 396 nm have become

common in recent FEL lamps, while they were mostly absent in older lamps, such as F-137, F-182, and F-527. The

lines are caused by aluminum that has been added to the

tungsten alloy during production to improve its anti-sag

properties.

Figure 35b shows the Γl values expressed as RPDs for

lamps F-474, F-615, and GS-1019. The Γl values for the

microradiometer channels and the spectrograph are very

consistent for lamps F-615 and GS-1019. There is considerable variability in the measurements of the microradiometer channels for lamp F-474, which is not apparent in

the spectrograph measurements. The reason for this variation is unknown, but it is possible the feature is caused by

a combination of anisotropic lamp output and the fact that

OXR channels do not point to the same spot of the plaque.

The sensitivity of OXR measurements to the pointing direction is further discussed in Sect. 6.7.4. The effect of the

aluminum line is also visible in the Γl values of the three

lamps.

Figure 35c shows the Γl values expressed as RPDs for

lamps F-473, F-550, and F-614. For lamp F-614, Γl values

for the microradiometer channels and the spectrograph differ sharply at wavelengths below 380 nm. This difference is

caused by dark-current drifts of the spectrograph. While

for all other lamps “dark” and “light” currents were measured immediately after the other, measurements of lamp

F-614 were 1.5 h apart. The Γl values of lamp F-614 does

not indicate a dip from an aluminum emission line. Lamps

F-614 and the reference lamp F-616 are likely affected by

this line equally, and the effect cancels when forming the

ratio. Spectrograph measurements of lamp F-550 saturated as discussed earlier.

47
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

QQ

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R R

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1.7

3.7

300 500 700 900

RPD [%]

Wavelength [nm]

F-182

F-137

F-527

JJ

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300 500 700 900

Wavelength [nm]

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300 500 700 900

Wavelength [nm]

GS-1019

F-615

F-474

F-550

F-614

F-473

abc

Fig. 35. a) Same as Fig. 34, but for subsets of the lamps: a) F-137, F-182, and F-527; b) F-474, F-615, and

GS-1019; and c) F-473, F-550, and F-614.

6.7.3 Comparison of Measurements

Figure 36 compares Γl(λi) values expressed as RPDs

determined with both the irradiance and radiance benches.

The pattern is generally similar, for example, Γl values for

lamps F-473 and F-474 show a comparable increase with

wavelength on both benches. The Γl values determined

on the radiance bench tend to be higher by 0.5–1.2% than

those for the irradiance bench.

BBB

BB

B

B B B B B B

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JJ

J

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PP P P P P P P P

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G

G

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EE

E

EE

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E EEE E

E

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C C

C

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S S S

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-2.0

-0.5

1.0

2.5

250 500 750 1000

RPD [%]

Wavelength [nm]

F-182

F-615

GS-1019

F-614

F-473

F-474

0

Fig. 36. A comparison of Γl(λi) values expressed

as RPDs determined with the irradiance (solid symbols) and radiance (open symbols) benches. Measurements with the same lamp are shown in the

same color.

The reason for the higher values on the radiance bench

is likely rooted in the common reference, lamp F-616. The

voltage drop across the lamp terminals was monitored with

the LabVIEW software on both benches and agreed to

within 11 mV (or 0.01%). It is believed that the radiative output was virtually identical during both uses of the

lamp. One explanation of the discrepancy is a possible

anisotropic output of the lamp. After the measurements

were completed, it was discovered that the lamp holder

was rotated by 1◦. If the radiant intensity of lamp F-616

were different by 0.5–1% at 1◦, compared to its normal orientation while other lamps have a more isotropic output,

the difference could be explained.

The excursion from the aluminum line at 395 nm is only

apparent in OXR measurements. The XGUV used on the

irradiance bench does not have a channel at 395 nm (Table 9), so the aluminum line cannot be detected.

6.7.4 Effect of OXR Pointing Direction

The microradiometer channels of the OXR are arranged

within a hexagonal grid, so each channel points to a slightly

different spot on the plaque. Channels on the outer rim are

approximately 2 cm away from the channel in the center,

and point to a spot of the plaque that is approximately

3 cm away from its center. It can be expected that signals

change when the instrument is rotated. First, the plaque

should be brightest in the center because this point is closest to the lamp. The distance between lamp and plaque

is approximately 280 cm. The center of the plaque should

be a factor of (2802 + 32)/2802 = 1.00011 brighter than a

spot 3 cm away from the center. The difference of 0.011%

can be considered negligible. Second, if the radiant intensity of a lamp is not isotropic, the illumination pattern of

the plaque differs from that expected from a point source.

Finally, the BRDF of the plaque may not be completely

homogeneous.

To measure the effect of the pointing direction, the

OXR was rotated in its holder in steps of 90◦, and measurements at 0◦, 90◦, 180◦, and 270◦ were compared. Results indicate that rotation changes the instrument’s signal

48
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

by up to 1.7%. This is much larger than the change expected from the variation in plaque brightness calculated

from a point source. This indicates that the radiant intensity of the test lamp (V-020) is indeed anisotropic. This

anisotropy contributes to uncertainties of lamp transfers

using the radiance bench. These uncertainties can be reduced by reducing the distance between transfer radiometer and plaque, or by reducing the FVA of the transfer

radiometer.

6.8 Usage of OSPREy Lamp Library

Lamps of the OSPREy lamp library have to be intercompared at regular intervals (e.g., annually) to confirm

that the irradiance preserved by these standards is constant in the long term. Some lamps of the library are

used regularly to validate the calibration of EMR sensors

in OSPREy systems, and it is particularly important to

ensure that these lamps are stable. The frequency of lamp

intercomparisons is based on the following:

• NIST standards should be operated as infrequently as

possible to preserve their calibration over the long term

(e.g., 15 or more years), so the annual operating time

should ideally be not more than 2 h (thereby not exceeding their recommended calibration lifetime of about

50 h).

• Lamps that are used to calibrate radiometers used in

the OSPREy activity should be intercompared with

each other and NIST lamps after 20 h of usage or less

(more frequent checks may be necessary if a lamp’s voltage changes by more than 0.3%).

• Lamps should ideally be used in pairs for radiometer

calibrations so that any inconsistency becomes immediately obvious.

• Whenever lamps are intercompared, the lamp that is

run at the beginning of the test series should also be

run at the end to confirm stability of the transfer radiometer.

A complete operation of a lamp—including ramp up, measurement, and cool down—takes about 1 h. It is, therefore,

not practical to compare more than 10 lamps in one day.

Based on these considerations, the following “OSPREy

Lamp Library Usage Protocol” was established and used

for all lamps in the lamp library:

1. Operate every uncalibrated lamp of the OSPREy

lamp library (“V” and “GS” lamps) for another 10–

30 h to confirm their stability with either the XGUV

or OXR. This is necessary because preliminary tests

reported in Sect. 6.2 suggest some lamps are still

drifting at a rate larger than typical for this lamp

type.

2. Compare all lamps using the OXR radiometers on

the irradiance and radiance benches, and transfer

calibrations to the “V” and “GS” lamps. This establishes a baseline value for each lamp over the full

wavelength range (300–1,600 nm). This also allows

for a comparison of the NIST SIRCUS irradiance

scale that will eventually be transferred to OXR instruments with the NIST FASCAL scale of the FEL

standards.

3. Divide the “V” and “GS” series of lamps into three

categories:

Category 1 lamps are routinely used to check the

radiometers used in the OSPREy activity.

Category 2 lamps are only used if measurements

of “Category 1” lamps are inconsistent.

Category 3 lamps are considered long-term standards and should only be used every five years or

if “Category 2” lamps become inconsistent.

Note: “Category 1” lamps should be used in pairs

such that inconsistencies that would require double

checking with “Category 2” lamps become immediately apparent.

By using this protocol and its hierarchical approach, the

amount of time a NIST standard is powered on can be

reduced considerably. The goal is to compare lamps only

when necessary to minimize lamp usage.

6.9 Conclusions

Twenty-one lamps were identified to become part of the

OSPREy lamp library. This library, in combination with

the OXR instruments, helps maintain the spectral irradiance scale for a time period of 15 years or more. Some

lamps of the “V” and “GS” series should be seasoned for

some additional hours until drift rates are within the expected range of this lamp type. Systems for powering and

operating lamps, and the radiometers used, proved more

than adequate to reliably transfer irradiance scales from

one lamp to another. Problems in the existing setup, such

as the rotation-dependence of OXR measurements, were

identified, and experience gained from operating and comparing lamps helps to further improve the setup.

49
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 7

Spectrograph Testing and Review:

An Engineering Analysis of COTS Spectrographs

Germar Bernhard, Vi Quang,

Thomas Comer, Charles R. Booth, and John H. Morrow

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

EMR sensors are hybridspectral instruments with 19 fixed wavelength microradiometers plus an integrated

spectrograph. Requirements for these devices are challenging, because they represent two sensing technologies

in one housing, which must both sample a very wide dynamic range—the very bright Sun and the relatively much

darker ocean. Candidate devices must be sufficiently sensitive to detect the low signals inherent in OSPREy

work in the red region of the spectrum above seawater, exhibit sufficiently accurate spectral selection, stable

dark noise, and good temperature stability. A review of commercial spectrograph manufacturers identified a

large number of instruments, from which 10 spectrographs were obtained and systematically tested. The latter

included two from Hamamatsu, three from Avantes, four from Zeiss/Tec5, and one from B&W Tek. Testing

protocols included the analysis of the following: a) wavelength range, b) spectral resolution, c) slit function, d)

dynamic range, e) out-of-band rejection, f) stray light, g) saturation, h) change of dark signal with integration

time and temperature, i) spectral responsivity, j) noise equivalent irradiance or radiance, and k) linearity. The

test results indicate that an ideal instrument does not exist, but workable candidates are available. For example,

all instruments suffer from stray light and nonlinearity to some degree, which limits their usable dynamic range

and measurement accuracy. After considering all tests results and other factors relevant for operation and

system integration, it was determined that the MMS UV-VIS II and MMS1 spectrographs from Zeiss/Tec5 were

the most suitable devices for OSPREy applications.

7.1 Introduction

The radiometers used in the OSPREy activity are hybridspectral instruments with fixed wavelength microradiometers plus an integrated spectrograph. The addition

of the spectrograph permits sampling of spectra in regions

not covered by filtered detector channels. Spectrograph

data can be used to account for any spectral features in

measurements of water-leaving radiance that are caused by

absorbing and scattering compounds in the water, which

cannot be spectrally resolved by the microradiometer channels. The spectrum can then be convolved with the spectral response of the satellite channels, and the resulting

values can be compared with satellite measurements. Furthermore, the addition of a spectrograph allows for the

detection of unwanted emission lines in spectra of calibration sources. The advantage of the higher resolution of

the spectrograph can be combined with the superiorities of

the filter radiometers—greater dynamic range, lower stray

light, better SNR, and higher sampling speed—to provide

a sensor combination superior to either of the individual

constituents alone.

Spectrograph requirements for OSPREy applications

are challenging, because they must sample a very wide dynamic range—the very bright Sun and the relatively much

darker ocean. Candidate devices must be sufficiently sensitive to detect the low signals inherent in OSPREy work

in the red region of the spectrum above seawater, exhibit

sufficiently accurate spectral selection, stable dark noise,

and good temperature stability. This chapter presents the

results of a detailed engineering analysis of candidate spectrographs available for integration into OSPREy.

A review of spectrograph manufacturers identified a

large number of instruments, from which 10 spectrographs

50
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

were obtained and systematically tested. The list includes

two from Hamamatsu (models C9407MA and C9408MA),

three from Avantes (AvaSpec models 1024, 2048×14, and

2048), four from Zeiss/Tec5 (MCS PDA, MCS CCD, MMS

UV-VIS II, and MMS1), and a BTC112E from B&W Tek.

Because some instruments were only available for a limited amount of time (e.g., one week), not all tests could

be performed with all instruments. A photograph of a

Zeiss/Tec5 MMS spectrograph with the fiber optic bundle

(i.e., the “fiber optics”) is shown in Fig. 37.

Fig. 37. The Zeiss/Tec5 MMS spectrograph with

the fiber optics shown alongside a microradiometer

for scaling purposes. A fully assembled microradiometer, with metal sleeve and front-end optics,

has a dimension of 0.435 × 3.79 in2.

7.2 Test Protocols

The instruments were tested in the BSI calibration facility. Wavelength range was first established by mapping

wavelength versus pixel and then determining the wavelengths of the first and last pixel. This was done by using

polynomial mapping functions provided by the manufacturer or by establishing these functions through scanning

the spectrum of a mercury wavelength standard.

The spectral resolution of a spectrograph depends on

the number of rules per millimeter of the grating, the width

of the entrance slit, and the number of adjacent pixels of

the array that are averaged. Slit functions were determined from scans of mercury and argon lines of a lowpressure wavelength standard. Gaussian functions of the

type a exp − b(λ − c)2

were fitted to the measured data

points for comparison. Bandwidth (FWHM) of all instruments was calculated from available mercury and argon

lines, as well as the 633 nm line of a HeNe Laser.

Out-of-band rejection is defined as the background radiation level when measuring a spectral line at wavelengths

far from that line. It is quantified here as the ratio of

the far-field background signal to that of the spectral line.

When measuring a light source with a continuous spectrum

(e.g., a tungsten lamp or the Sun), the background signal

results from the combined contributions of a large wavelength band. If the radiation level at a given wavelength is

very small, the out-of-band stray light contribution can become as large as the signal. This is a common occurrence

for solar measurements in the UV-B, because absorption

by atmospheric ozone causes a very rapid decrease of spectral irradiance for shorter wavelengths. Stray light can also

cause large calibration uncertainties.

The out-of-band stray light for each spectrograph was

evaluated using the 632.816 nm line of a HeNe laser. Side

modes were cleaned up by pointing the laser beam on a

grating and directing the beam that was diffracted towards

a slit. The beam exiting the slit was directed onto a diffuser made of PTFE that was mounted in front of the

entrance optics of the instrument to be tested. For each

instrument, these laser scans were stitched together from

measurements at two integration times to extend the dynamic range of the units. For example, a short integration

time is needed close to the peak of the laser line to avoid

saturation, while a long integration time is required away

from the peak to measure stray light with sufficient detail.

Saturation and stray-light levels for solar measurements

were determined by pointing the optical fiber connected to

the candidate spectrographs directly at the Sun. No attempt was made to calibrate these spectra, because of the

difficulties in obtaining an accurate irradiance calibration

to fiber fore optics not equipped with a cosine diffuser.

Measurements were performed with different integration

times. When the signal of a spectrograph saturated at

the shortest integration time possible, measurements were

repeated by placing an ND filter of optical depth (OD)

between 0.5–3.0 in front of the fiber optics.

At wavelengths below 320 nm, the solar irradiance is

effectively absorbed by Earth’s ozone layer and no signal

is detectable below about 290 nm. The cutoff provided by

ozone absorption can therefore be used to quantify stray

light that is detected below 290 nm, but originates from

photons with wavelengths in the visible and infrared.

The dark signal (i.e., no light enters the sensor aperture) generally depends on the array pixel and integration

time, and is temperature dependent. Drifts in dark signal affect the detection limit of radiometers equipped with

these detectors. Consequently, in addition to recording the

dark values as a function of integration time, the temperature sensitivity of the dark signal of all spectrographs was

characterized. Most test devices were not equipped with

internal temperature sensors and an external sensor was

mounted as closely as possible to the detector.

The spectral responsivity for each of the candidate spectrographs was determined both for irradiance and radiance

calibrations. Spectral responsivity was determined by dividing net signals with the irradiance produced by the FEL

lamp. It is important to note that spectral responsivity

calculated this way is only accurate if the stray-light contribution to the net signal is negligible. As is shown below,

this is generally not the case for any of the test instruments in the ultraviolet range. At short wavelengths, the

stray-light contribution can be more than two orders of

51
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

magnitude larger than the signal resulting from photons

of the desired wavelength. This problem makes the calibration a challenge and requires the use of cut-on filters

to determine the spectral dependence of stray light. If the

stray-light contribution is large (e.g., greater than 10% of

the net signal), uncertainties of the stray-light correction

may prevent accurate determination of the responsivity.

Radiance responsivity was determined using the candidate device’s bare fiber (no fore optics attached), oriented

towards the center of a Spectralon plaque with Lambertian

characteristics, or with an FOV-limiting baffle arrangement. Bare fibers typically have a numerical aperture of

0.22, which translates into an FVA of about 25◦. The baffle arrangement had an FVA of 2.5◦, which is the designed

FVA for radiometers used in the OSPREy activity. The

plaque was illuminated by a calibrated FEL lamp mounted

287.1 cm away.

To determine responsivity for measuring irradiance, flat

PTFE diffusers were fitted to the instrument’s fore optics

and placed a distance of 50 cm from a calibrated 1,000W

FEL lamp. Net signal was determined by subtracting dark

measurements where any light reaching the diffuser was occluded and light measurement, where the entire lamp was

visible from the diffuser. Measurements were performed at

integration times ranging between several milliseconds and

several seconds. Several light and dark scans were averaged

together to reduce noise when calculating responsivity and

its standard deviation. At integration times smaller than

10 ms, typically 100–200 samples were averaged. For integration times larger than 1,000 ms, 20 samples were averaged. Spectral responsivity was determined by dividing

net signals with the irradiance produced by the FEL lamp.

Following (1), noise equivalent irradiance (NEI) of the

spectrograph, NE(λ), determines the smallest spectral irradiance that can be measured with a radiometer. NEI is

defined here as the standard deviation of the dark signal,

σ, relative to the irradiance responsivity:

NE(λ) = σE(λ, ti)

γE(λ, ti)

, (11)

where λ is wavelength, ti is the integration time, γ is the

responsivity, and the E subscript designates irradiance.

NEI was calculated for all candidate spectrographs, and

was not corrected for stray light. Noise equivalent radiance (NER) of the spectrograph, NL(λ), is defined as the

standard deviation of the dark signal to radiance responsivity (expanded here for completeness):

NL(λ) = σL(λ, ti)

γL(λ, ti)

, (12)

where the L subscript designates radiance. The wavelength

range was also assessed for all instruments for which NER

is sufficiently small to allow accurate calibrations with and

without FOV-limiting fore optics.

Linearity of the candidate instruments was tested using

a variety of approaches, some specific only to individual

candidates. Because of the instrument-specific nature of

the approach, the testing protocol is presented with the

specific result for each spectrograph.

7.3 Candidate Instruments

The results from a market survey to select the best

spectrograph for integration with OXR and EMR instruments resulted in the following potential COTS sources:

• Avantes (www.avantes.com) provides an extensive

lines of fiber optic spectroradiometers using a symmetrical Czerny-Turner design. Six different detector arrays (photodiode, CMOS, and CCD†), and six

gratings can be chosen. All models (except those

equipped with Peltier coolers) have the same size,

form factor, and software interface.

• B&W Tek (www.bwtek.com) offers a variety of array spectroradiometers equipped with CCD detectors. The most suitable model for OSPREy is the

BTC112E series of spectrometers, equipped with a

2,048 pixel Peltier-cooled CCD array built into a

small housing of 108×95×42 mm3.

• Hamamatsu (www.hamamatsu.com) makes so-called

mini-spectrometers, which cover a wavelength range

from 200–2,200 nm with a spectral resolution ranging from 1–9 nm. The available sensors include linear CMOS image sensors for the UV and visible,

back-thinned CCD, and InGaAs linear sensors for

wavelengths between 900–2,200 nm.

• Horiba/Jobin Yvon (www.horiba.com) makes the

model VS-140 linear array spectrometer, which is

a high-throughput f /2.4 system. The VS-140 features an aberration-corrected concave holographic

grating and can be equipped with either a CCD

or photo-diode array (PDA) detector for the wavelength range of 190–800 nm with 2.3 nm bandwidth.

• Ocean Optics (www.oceanoptics.com) supplies a

variety of turnkey universal serial bus (USB) systems for a variety of applications ranging from absorbance, fluorescence, and Raman spectroscopy to

spectroradiometric measurements.

• Labsphere (www.labsphere.com) markets a minispectrometer similar to the USB4000 spectrometer

from Ocean Optics. This recently introduced unit

uses a Sony linear silicon CCD array with 2,048 pixels and covers the wavelength range 200–1,100 nm.

• StellarNet (www.stellarnet-inc.com) builds several different ruggedized miniature fiber optic spectrometers, and the model EPP2000C would be the

† CCD is defined as charge-coupled device.

52
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

most suitable for OSPREy. It uses a concave grating, provides a CCD array detector with 2,048 pixels, and allows measurements between 280–900 nm

with a resolution of about 1 nm.

• Zeiss/Tec5 (www.tec5usa.com) spectrographs are

based on a monolithic body made of a patented

ceramic structure, and they are all equipped with

an aberration-corrected concave grating. The MCS

and MMS models would be the most suitable for

OSPREy. The MCS is available with a thermoelectrically cooled CCD array from Hamamatsu. MMS

models are attractive because of their small size of

70×60×40 mm3.

In addition to the market survey, a literature search was

conducted regarding the use of miniature spectroradiometers in atmospheric research. For example, Herman et

al. (2006) used an Avantes AvaSpec-1024 spectrometer to

measure atmospheric trace gases, and Kouremeti et al.

(2008) built a spectroradiometer based on a Zeiss/Tec5

MCS module to measure solar irradiance and sky radiance

in the UV spectral domain.

The specifications of the various models were subsequently compared to determine which units were the most

promising for OSPREy. The following 10 demonstration

models were acquired for testing, and are presented in Table 11:

Hamamatsu models C9407MA and C9408MA;

Avantes AvaSpec models 1024, 2048×14, and 2048;

Zeiss/Tec5 models MCS PDA, MCS CCD, MMS

UV-VIS II, and MMS1; and

B&W Tek model BTC112E.

The two models from Hamamatsu are attractive because

of their small size and comparatively low price. The three

models from Avantes have almost identical optics, but are

equipped with different detectors, either a CMOS linear

image sensor (AvaSpec-1024) or CCD detectors (AvaSpec2048x14 and AvaSpec-2048). While CMOS sensors are less

sensitive than CCD arrays, they offer a considerably better

SNR and can be used at higher light levels. One objective

of the tests was to determine the better technology for OSPREy applications. Instruments by Zeiss/Tec5 promised

the best wavelength stability and ruggedness, because of

their monolithic design; the MMS UV-VIS II and MMS1

models were particularly attractive, because of their small

size. The BTC112E from B&W Tek looked promising because of its integrated Peltier cooler.

7.4 Results

Table 11 presents the determinations for spectral range

(λR) of each of the candidate instruments. Note that detectors based on silicon are relatively insensitive beyond

1,150 nm, and the usable wavelength range may, therefore,

be smaller than shown.

7.4.1 Resolution and Slit Function

The Avantes AvaSpec models 1024 and 2048×14 spectrographs had 50 μm entrance slit widths. The spacing of

array cells (i.e., the pixel pitch) was 25 μm for the model

1024 and 14 μm for the 2048×14. In order to get slit functions with the desired triangular or gaussian shape, the effective width of the exit slit of a spectroradiometer should

match that of the entrance slit. Following the advice of

the manufacturer, two pixels were averaged when using

the AvaSpec-1024, three pixels for the AvaSpec-2048, and

five pixels for the AvaSpec-2048×14. Measurements of all

other units were not averaged.

Determinations of the slit functions for the Zeiss/Tec5

MCS CCD at 296.728, 435.833, 546.074, and 912.297 nm

are shown in Fig. 38, which indicates good agreement between the measurements and the matching gaussian function. The slit functions are symmetrical, but the bandwidth increases substantially with wavelength. Slit functions of all other instruments, except those of the Avantes

AvaSpec-2048 and the B&W Tek BTC112E, could also

be well characterized with gaussian functions. The slit

function of the BTC112E unit was very asymmetrical, in

particular in the visible. It is possible the test unit was

misaligned, but this could not be confirmed.

G

G

G

G

G

G

G E

E

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0.4

0.8

1.2

-6 -2 2 6 

Relative Wavelength [nm]

G 296.728

E 435.833

C 546.074

A 912.297

0

Normalized Slit Function

Fig. 38. The determinations of the slit functions

for the Zeiss/Tec5 MCS CCD at four different wavelengths (in nanometers).

The bandwidths for the Avantes AvaSpec-2048 and the

Zeiss/Tec5 MCS PDA units vary from 1.7–3.6 nm. The

bandwidth of the Zeiss/Tec5 MCS CCD unit has a peculiar pattern, with a local maximum at 546 nm and a

large increase towards longer wavelengths in the infrared.

This pattern is consistent with test results of a similar

unit reported by Kouremeti et al. (2008). The Hamamatsu

53
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Table 11. The specifications of candidate spectrographs tested at BSI for the OSPREy activity. The Zeiss/Tec5 MCS PDA unit is referred to by themanufacturer as MCS; the MCS PDA designation used here is for better differentiation from the MCS CCD unit. The complete model name for theUV-VIS II unit is MMS UV-VIS II. Blank entries indicate a specification is either unknown or not specified by the manufacturer. The wavelength rangeis denoted

λ

R and the wavelength resolution is denoted δλ.

Unit Hamamatsu Avantes (AvaSpec) Zeiss/Tec5 B&W Tek

Specification C9407MA C9408MA 1024 2048×14 2048 MCS PDA MCS CCD UV-VIS II MMS1 BTC112E

Layout Czerny- Turner Czerny- Turner Symmetrical CzernyTurnera Symmetrical Czerny- Turnera Symmetrical Czerny- Turnera Concave Grating Spectrometer Concave Grating Spectrometer Concave Grating Spectrometer Concave Grating Spectrometer Crossed Czerny- Turner

TE Cooled No No No No No Optional Yes No No 10–15◦C

λ

R Avail.b 340–780 nm 640–1,050 nm 200–1,100 nm 200–1,100 nm 200–1,100 nm 190–1,015 nm 190–1,015 nm 250–785 nm 300–1,150 nm 300–850 nmc

λ

R Testedd 340–780 nm 640–1,050 nm 200–1,100 nm 200–1,100 nm 200–1,100 nm 300–720 nm 190–995 nm 250–785 nm 300–1,150 nm 300–780 nm

δλ Avail.b 9 nm 9 nm 0.15–20 nm 0.04–20 nm 0.04–20 nm 2.4 nme 2.4 nme 7 nm 10 nm 0.3–20 nm

δλ Testedd 9 nm 9 nm 2.9–3.5 nm 2.9–3.5 nm 1.7–2.3 nm 2.4 nm 2.5–6 nmf 6–8 nm 9–10 nm

∼1.5 nm

Stray Light

<0.5%

<0.5%

<0.1%

<0.1%

<0.1% 0.1% 0.1%

<0.3%

<0.8% 0.05%g

CMOS CMOS CMOS CCDh CCD NMOS CCD NMOS NMOS CCD

Detector Hamamatsu Hamamatsu Hamamatsu Hamamatsu Sony Hamamatsu Hamamatsu Hamamatsu Hamamatsu

S8378-256N S8378-256N S3904-512 S7031-1006 S3904-256Q S3904-256Q

Pixels 256 256i 1,024 2,048×14 2,048 512j 1,048×64 256 256 2,048

Sensitivityk 120 16,000 20,000 1,000–10,000l 10,000l 10,000l

Signal

to Noise 2,000:1 500:1 200:1

ADC 16 bit 16 bit 16 bit

m 16 bit 16 bit 16 bit 16 bit 15 bitn 15 bitn 16 bit

Integration

Time 5 ms–10 s 5 ms–10 s 2.2 ms–10 min 2.2 ms–10 min 1.1 ms–10 min 1 ms–6 s 1 ms–6 s 2 ms–6.5 s 2 ms–6.5 s 5 ms–17 min

USB

Interface 1.1 1.1 2.0 2.0 2.0 1.1. or 2.0 1.1. or 2.0 2.0 2.0 2.0

Dimensions

[mm] 75×53×46 75×53×46 175×110×44 175×110×44 175×110×44 140×105×75o 140×105×75o 67×60×40o 70×60×40o 108×95×42

Estimated

Weight 400 g 400 g 716 g 716 g 716 g 2,500 g 2,500 g 125 g 125 g 500 g

OEM Unit

Available Yes Yes Yes Yes Yes Is An OEM Is An OEM Is An OEM Is An OEM Yes

Estimated

Cost $1,850 $1,850 $4,200 $5,000 $3,500 $7,582 $12,000 $4,271 $4,271

a With a 75 mm focal length. b Can be provided by the manufacturer. c For a unit equipped with the NIR option. d The demonstration unit as tested by BSI. e Specification is 3.0 nm in the UV-NIR. f About 2.5 nm for λ < 800 nm; 6 nm for

λ = 950 nm. g At a wavelength of 600 nm. h A back-thinned CCD. i Infrared enhanced. j A unit with 1,024 pixels is available as an option. k In units of counts per microwatt per millisecond. l With 14 bit ADC.

m The unit tested at BSI had a 14 bit ADC. n Plus a sign bit. o Dimensions do not include the electronics module.

54
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

C9407MA and the two MMS units from Zeiss/Tec5 have

bandwidths ranging between 5 and 11 nm. The bandwidth

of the C9408MA varies between 8.5 nm at 650 nm to about

6.5 nm at 1,000 nm.

7.4.2 Out-of-Band Rejection

A comparison of measurements of the 632.816 nm line

of a HeNe laser using several candidate spectroradiometers is presented in Fig. 39. The out-of-band rejection of

the spectrographs at 100 nm away from the laser line is between 5×10−4 and 3×10−5. For comparison, a scan of the

325 nm line of the HeCd laser using a BSI high-resolution

SUV-150B spectroradiometer is also shown in Fig. 39 (but

shifted by 308 nm for clarity). This instrument is based on

a scanning double monochromator.

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XXXXXX 10-6

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1

150 450 750 1050

Normalized Signal

Wavelength [nm]

XHamamatsu

C9407MA

XB&W Tek

BTC112E

XSUV-150B

XMCS PDA

XMCS CCD

XMMS UV-Vis II

XMMS1

Zeiss/Tec5

Fig. 39. A comparison of measurements of the

632.816 nm line of a HeNe laser using several candidate spectroradiometers.

In terms of stray-light rejection, the Zeiss/Tec5 MCS

CCD and B&W Tek BTC112E units are the best, and

smaller units are poorer (e.g., the Hamamatsu C9407MA

and the two Zeiss/Tec5 MMS devices). Some Zeiss/Tec5

units show secondary peaks, and according to the manufacturer, these features are caused by recycled light that

is reflected by the detector array back to the grating, and

then diffracted a second time by the grating and measured

by the sensor.

Spectrograph units with similar optical layouts, nonetheless had different levels of out-of-band rejection. For

example, the stray-light rejection of the MMS UV-VIS II

is significantly better than the MMS1, and the stray-light

level of the MCS CCD is below that of the MCS PDA,

but all these devices are from the same manufacturer. It is

not clear from the experiments whether these differences

are caused by the small changes in the optical layout of

the units or some variation between individual units of the

same model. For example, contamination during the manufacturing process could conceivably raise the stray-light

level. Measurements of the three devices from Avantes fall

within the range of the other units. Notably, the straylight levels of all instruments tested were better than the

specifications provided by the manufacturers.

The out-of-band rejection of the SUV-150B device is

at least 5 × 10−8. Some fluorescence from (or caused by)

PTFE contamination is indicated five orders of magnitude

below the level of the excitation line. Note that fluorescence cannot typically be detected with the spectrographs

discussed here, because it is well below the observed straylight levels.

7.4.3 Stray-Light Levels

Stray light was present for all of the spectrographs

when measuring the solar spectrum. Below about 300 nm,

the measured spectra do not decrease exponentially, as

they should, but stay either constant or increase with decreasing wavelength. The stray-light level ranges between

0.1–1% of the maximum signal value and was the smallest for the Zeiss/Tec5 MCS CCD and Avantes AvaSpec

2048×16 units. Curiously, the stray light level is considerably higher, and also spectrally dependent, for the two

other units manufactured by Avantes.

The starting wavelength of the Hamamatsu C9407MA

plus the Zeiss/Tec5 MCS PDA and MMS1 devices are

at 300 nm or higher, so stray-light assessment using the

ozone cutoff is not possible. Repeated measurements with

a Schott GG-385 filter shows stray light becomes apparent

below 353 nm for these instruments, and ranges between

0.2–0.5%. The stray-light level depends on wavelength,

indicating it is not sufficient to subtract a constant value

from a measured spectrum to correct for stray light.

7.4.4 Saturation

Except for the Zeiss/Tec5 MCS PDA, all of the spectrographs saturated—even at the shortest integration times

that the instruments were capable of—when the fiber optic bundle was pointed at the Sun with no ND filter. Instruments equipped with CCD detectors are more sensitive

than those with PDAs and are more affected by saturation.

While the Zeiss/Tec5 MCS PDA could in theory be used

without an ND filter, it is not advisable because the instrument would have to be operated at integration times

between 1–5 ms. Much longer (e.g., 2,000 ms) integration

times are necessary for calibration.

Results discussed below indicate that none of the instruments tested, including the MCS PDA, is linear with

integration time. It would therefore be difficult to operate

the MCS PDA without an ND filter for OSPREy sun photometer applications. These results suggest that an ND

filter is necessary for all instruments.

55
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

7.4.5 Dark Signal

The dark signal characteristics of the test units were

very different. The dark signal data for the Hamamatsu

C9407MA spectrograph consists of two components: a constant component and one increasing strongly with integration time, with additional large pixel-to-pixel variability

that increases with integration time. At 10,000 ms, the

dark signal of some pixels was as high as 40,000, or 61%

of the maximum signal of 65536 (16 bit). The same variability is also present when the unit is exposed to light.

Most of the variability is, therefore, removed when the dark

measurement is subtracted from light measurement to calculate the net current. The large dark signal, however,

substantially limits the dynamic range of the instrument.

The Hamamatsu C9408MA and C9407MA use similar

detectors and have similar dark signals, but the former

has fewer hot pixels. Hot pixels are also a problem for

the Avantes AvaSpec-1024. The two CCD models from

Avantes have no hot pixels, but the AvaSpec-2048 dark

signal shows a general downward trend with pixel number.

The dark signals of all Zeiss/Tec5 units show very little

dependence on pixel number and are more than one order

of magnitude below their saturation threshold, even at the

longest integration time.

The temperature sensitivity of the dark signal for all

spectrographs was also characterized. As an example, the

Hamamatsu C9407MA dark signal increased by about a

factor of 16 over a temperature range of 5–56◦C. The relative increase depends weakly on wavelength. Notably, the

majority of pixels saturate at temperatures higher than

45◦C, and several pixels saturate at lower temperatures.

Spectrographs for the OSPREy activity are heated to a

constant temperature of 40◦C to maintain the temperature stability. At this temperature, several pixels of the

C9407MA are already saturated. Operating the Hamamatsu C9407MA spectrograph at such a high temperature

would severely affect the performance of the device. The

dark signals of the two Zeiss/Tec5 MCS PDAs changed by

a factor of 115 over a 12–60◦C temperature range without

saturating. The change is exponential, which suggests the

instrument should be operated at low temperatures. The

tests indicated that a temperature of 40◦C with a temperature stabilization to within 0.05◦C is acceptable, however.

The large temperature dependence of dark signals observed for all units suggests instrument responsivities are

also affected by temperature. Testing with the Avantes

AvaSpec-2048×14 and the Zeiss/Tec5 MCS PDA as a function of temperature while exposed to a 100W tungsten

lamp showed that the signal varied strongly with temperature, as predicted. The results also indicated, however,

that most of the temperature dependence was the result of

the temperature effect on the dark signal.

Temperature-related drifts in the dark signal can be tolerated if the dark signal is measured frequently (e.g., every

minute). EML radiometers have a computer-controlled filter wheel with an opaque position to allow automated dark

measurements. Such a device is not available for irradiance

radiometers. The dark signal tests show excellent temperature stabilization is necessary to operate spectrographs in

irradiance radiometers to meet the accuracy levels required

by the OSPREy activity. Tests with an analog temperature controller confirmed that temperature stabilization to

within 0.03◦C level is achievable.

7.4.6 Spectral Responsivity

The spectral responsivity of each candidate spectrograph was determined for irradiance and radiance calibrations. The Avantes AvaSpec-2048×14 saturates for integration times larger than 100 ms, and reports a signal even

at wavelengths below 180 nm because of stray light. The

net signal increases linearly with integration time when the

ratio of net signal divided by integration time is between

100–400, but there are differences below and above this

range. Measurements with an integration time of 50 ms are

about 2% smaller in the center of the wavelength range. At

large signal levels, the unit tends to underestimate the actual irradiance. Below 400 or above 1,100 nm, where signal

levels are small, there is a large discrepancy between the

different data sets, which is a clear indication that there

are significant departures from linearity. A similar analysis

was performed for all candidate spectrographs. The relationship between net signal and integration time was nonlinear for all units, but the effect varied in magnitude. For

some units, the effect was barely noticeable because the

signals at short integration times were affected by noise,

which partly obscured the nonlinear effect.

Nonlinear behavior at low signal levels is mostly observed at wavelengths that are also affected by stray light.

Stray light is an optical phenomenon, however, and the signal generated by stray light should scale linearly with integration time. Linearity of the Zeiss/Tec5 MCS CCD determined with a monochromatic light source indicated that

the system is linear to within 1.5%, i.e., within the uncertainty of the experiment. The measurement of monochromatic light sources is not a OSPREy application, however,

so the value of these test results is limited.

The spectral responsivity of all units was determined

by dividing the net signal by the known irradiance of the

FEL calibration lamps. For example, the responsivity of

the Avantes AvaSpec-1024 is about one order of magnitude

greater in the UV than in the NIR, whereas the responsivity of the AvaSpec-2048×14 is relatively uniform across the

entire wavelength range. Generally, spectrographs with

CCD arrays have a much larger spectral responsivity than

those using PDAs.

7.4.7 Dynamic Range

The candidate spectrographs were equipped with either 15 or 16 bit analog-to-digital converter (ADC) capabilities, which is equivalent to a dynamic range of approximately 3.3 × 104 or 6.6 × 104, respectively. Spectrographs

56
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

installed in EML radiometers require a dynamic range of

more than 100 × 104 to accurately measure high-intensity

sources, such as direct sunlight, and low-intensity sources,

such as the radiance of the sea surface or the radiance of

a calibration plaque.

In theory, the dynamic range of a spectrograph can

be increased beyond that offered by the ADC capability

by either measuring at different integration times or using

ND filters to reduce the signal from high-intensity sources.

The nonlinear behavior described above limits the ability

to extend the dynamic range via the use of different integration times. Spectrographs for EML sensors are, therefore, equipped with a filter wheel with two ND filters. The

dynamic range for EME sensors is less demanding than for

radiance sensors. For irradiance sensors, sunlight and calibration sources can be measured at the same integration

time, so the use of ND filters is not necessary.

7.4.8 Noise Equivalent Irradiance

The NEI for the MMS UV-VIS II equipped with a

PTFE diffuser plate that is 0.02 in thick is presented in

Fig. 40. NEI varies between 0.001 μW cm−2 nm−1 at ti =

200 ms and 0.3 μW cm−2 nm−1 at ti = 2 ms. Longer integration times (which would lead to lower NEI) are not

possible because the unit would saturate. For accurate results, NEI ideally has to be lower by at least 1.5 orders

of magnitude than the spectrum to be measured. For the

sample spectra shown in Fig. 40, this can be achieved for

integration times equal to, or longer than, 100 ms and for

wavelengths above 310 nm.

0.001

0.1

10

1000

250 450 650 850 

NEI

Wavelength [nm]

200

100

50

20

10

5

2

FEL

Solar

Irradiance

Fig. 40. The NEI, in units of μW cm−2 nm−1, for

the Avantes AvaSpec-1024 as a function of ti values

from 2–200 ms. The spectrum of a 1,000W FEL

lamp at 50 cm distance and a spectrum of solar

global irradiance at a 45◦ zenith angle are shown

for comparison.

In theory, NEI should decrease proportional to √ti, if

the noise contribution is dominated by photon statistics.

Multiplying all Fig. 40 data sets by √ti shows this is not

the case for the Avantes AvaSpec-1024 spectrograph, for

which the NEI is approximately proportional to ti. The

reason for this unexpected behavior is not known, but was

confirmed by the manufacturer. Similarly, the NEI of all

the other units was proportional to ti rather than √ti. NEI

can either be improved by averaging several spectra at a

given integration time, or measuring one spectrum over a

long integration time. NEI determined with the former

should decrease proportionally to √ti, while the latter is

proportional to ti as the data indicate. Consequently, it

is advantageous to always use the longest integration time

possible.

A comparison of the Avantes AvaSpec-1024 with the

AvaSpec-2048 may suggest that instruments using CCD

detectors have a smaller NEI and are, therefore, preferable

for OSPREy applications. Tests with other units, however, reveal that this is not the case. For example, an NEI

of 0.001 μW cm−2 nm−1 is achievable with the Zeiss/Tec5

MMS UV-VIS II. For this unit, the accuracy of the calibration is limited by dark signal drifts and stray light, rather

than signal noise.

7.4.9 Radiance Responsivity

The spectral pattern of radiance responsivity was similar to that for irradiance responsivity for all instruments,

because the transmission of the diffuser used for the latter

was not highly dependent on wavelength. As in the case

of irradiance, radiance responsivity should change linearly

with integration time. The BSI tests indicate that this is

not the case for all test units, albeit the degree of nonlinearity differs from unit to unit. Ratios of net currents, with

and without the baffle arrangement, varied between 0.015–

0.070, and did not show much dependence on integration

time for most instruments.

7.4.10 Noise Equivalent Radiance

For the Zeiss/Tec5 MCS CCD equipped with a bare

fiber and using a 200 ms integration time, NER is more

than 2.5 orders of magnitude smaller than the radiances

from the sky or a calibration plaque. This indicates that

signal noise is not a limiting factor for accurate calibrations and solar measurements. The minimum NER (at

5,000 ms) when equipped with the 2.5◦ FVA fore optics is

about 0.0001 μW cm−2 nm−1 sr−1. This is the best (lowest) value of all instruments tested. With the fore optics

installed, the radiance of the plaque is more than two orders of magnitude larger than NER for wavelengths longer

than 360 nm. At 340 nm, the radiance of the plaque with

the lamp 287.1 cm away is about 1.5 orders of magnitude

larger than the NER for the longest integration time. Accurate determination of responsivity at this wavelength is,

57
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Table 12. An abbreviated summary of the spectrograph testing performed at BSI. All numerical wavelength range

entries show the reduced wavelength range, with respect to the full range given in Table 11, determined to be usable

for a given characteristic. For stray light, the range is defined as the interval where stray light contributes less than

10% to the total signal. For noise and linearity, the range is defined as the interval for which the error is smaller than

2.5%.

Unit Hamamatsu (MA) Avantes (AvaSpec) Zeiss/Tec5 (MCS) Zeiss/Tec5 (MMS) B&W Tek

Specification C9407 C9408 1024 2048×14 2048 PDA CCD UV-VIS II MMS1 BTC112E

Stray Light 350–

380 nm N/A 378–965 nm

377–

1,100 nm

395–

1,100 nm

Not

Tested

330–

995 nm

348–

785 nm

380–

930 nm

442–

780 nm

Attenuator

Required Yes Yes Yes Yes Yes Maybe Yes Yes Yes Yes

NEI

Calibration

Full

Range

Not

Tested

320–

1,100 nm

Full

Range

Full

Range

Full

Range

Full

Range

Full

Range

Full

Range

Full

Range

NER Calib.

Bare Fiber

Full

Range

Full

Range

350–

1,100 nm

350–

1,100 nm

Not

Tested

340–

720 nm

Full

Range

Not

Tested

Not

Tested

Not

Tested

NER Calib.

2.5◦ FOV

430–

700 nm

Full

Range

500–

600 nm

441–

1,100 nm

Not

Tested

600–

700 nm

Full

Range

Not

Tested

Not

Tested

Not

Tested

Nonlinearity

Irradiance

Not

Tested

Not

Tested

Noise

Limited

470–

1,025 nm

360–

1,100 nm

Noise

Limited

360–

995 nm

350–

785 nm

350–

1,050 nm

340–

780 nm

Quality Slit

Function Yes Yes Yes Yes No Yes Yes Yes Yes No

Satisfactory

Dark Signal No Yes No Yes Yes Yes Yes Yes Yes No

Temp. Stabil.

Required Yes Yes Yes Yes Yes Heating is Sufficient for Quality Data Yes

therefore, challenging. If the lamp is moved to a distance

of 100 cm, however, calibration becomes possible.

The wavelength range for which NER is sufficiently

small to allow for accurate calibrations, with and without

FOV-limiting fore optics, was assessed for all instruments

(Table 12). Without FOV-limiting optics, calibrations are

possible over the full wavelength range for most instruments. Limiting the FOV to 2.5◦ makes calibrations in

the UV challenging.

7.4.11 Linearity

Stray-light tests revealed that signals of all instruments

do not scale linearly with integration time, in particular at short wavelengths (or small signal levels). This

nonlinearity—together with stray light and drifts of the

dark signal—limits the dynamic range of the instruments.

Spectrographs using CCD detectors seem to be more affected, but this may not, in fact, be the case because nonlinear behavior of PDA systems tends to be obscured by

signal noise. The effect was further investigated by repeating the stray-light measurements using PTFE diffusers of

different thicknesses in front of the instrument fiber optics.

If a thicker diffuser is used, a lower signal is expected, but

the ratio of measurements with a thick and a thin diffuser

should be independent of integration time.

The ratios of measurements from the Avantes AvaSpec1024 made with a diffuser 0.03 in thick to that of a diffuser

0.02 in thick are presented in Fig. 41. The responsivity

with the thicker diffuser is 20–30% lower in the UV and

visible, and up to 65% lower in the NIR. The reason for the

wavelength dependence is probably due to the wavelengthdependent scattering properties of PTFE. Measurements

for integration times of 500, 1,000, and 2,000 ms are consistent between 340–1,100 nm (indicating good linearity),

and affected by noise outside this range.

0.0

0.5

1.0

1.5

100 500 900 1300

Ratio

Wavelength [nm]

50

100

200

500

1000

2000

Fig. 41. The ratios of measurements from the

Avantes AvaSpec-1024 made with a diffuser 0.03 in

thick to that of a diffuser 0.02 in thick, as a function

of ti (colored lines) in milliseconds.

58
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

A similar analysis for the Avantes AvaSpec-2048×14 is

presented in Fig. 42. The ratio of the two responsivities

is far less affected by noise. The magnitude of the difference is similar to that determined with the AvaSpec-1024,

but ratios for different integration times are less consistent than they were for the AvaSpec-1024. At short wavelengths, the ratio is smaller for measurements at short integration times. Between 1,050–1,200 nm, the pattern is

reversed. This suggests that the signal at a given pixel

depends on the signal of pixels sampled prior to that pixel

when reading out the array.

0.3

0.5

0.7

0.9

100 500 900 1300

Ratio

Wavelength [nm]

3

5

10

20

50

Fig. 42. An analysis similar to the one shown in

Fig. 41 (note, however, the difference in y-axis scaling), but for the Avantes AvaSpec-2048×14.

The signal dependency as a function of pixel number

leads effectively to nonlinearity, which becomes dependent

on integration time and the spectral pattern of the source

being measured. This artifact is very difficult to correct

and would be a serious obstacle if the unit were to be

used for the OSPREy activity. Measurements with the

Zeiss/Tec5 MCS CCD uncovered a similar nonlinear behavior. On the other hand, measurements with the MCS

PDA for integration times between 50–1,000 ms were consistent to within 0.5% down to 300 nm.

Linearity of the Avantes AvaSpec-2048×14 was also

tested using a purpose-built beam combiner designed and

built by BSI. This apparatus combines the beams of two

light sources using a cubical beam splitter. For testing the

AvaSpec-2048×14, one light source was a bright whitelight LED and the other was a 100W halogen lamp coupled with a fiber optic bundle. The beams of the two light

sources can be blocked independently to measure dark signal, signal of either of the sources, or both sources. If

an instrument is linear, the signal measured with both

light sources unblocked should be identical to the arithmetic sum of the signals of the two sources measured separately. The output of the two sources can be adjusted

independently to achieve the desired signal levels close to

saturation. In the test, the ratio of the arithmetic sum

of the signals of the two sources and the signal measured

with both light sources unblocked deviated by up to 2%

between 500–700 nm. These measurements confirmed the

nonlinear performance of the unit.

All of the tests above were performed with polychromatic light sources, i.e., lamps or LEDs. The Zeiss/Tec5

MCS CCD was also tested with a quasi-monochromatic

radiation at 555 nm, which was produced by the BSI spectral source (Bernhard et al. 2005). This source consists

of a 1,000W Xenon lamp focused on the entrance slit of

a 50 cm double monochromator with prism pre-disperser.

Radiation exiting the system is pure, for all practical purposes, with no measurable contribution of stray light. It

was directed on a diffuser connected to the MCS CCD via

a fiber optic bundle. Measurements were performed at integration times between 3–5,000 ms. The response of the

spectrograph was linear to within 1.5%.

A second experiment with the Zeiss/Tec5 MCS CCD

was designed to test whether detected radiation at a given

wavelength depends on radiation at other wavelengths. For

example, the CCD pixels are read sequentially by the system electronics. If the read-out mechanism was dependent

on the charge of pixels read prior to the pixel in question,

the signal would be biased. This would result in nonlinearity if the bias depended on integration time. The test

involved three monochromatic light sources: in addition

to the BSI spectral source (set to 480 nm), radiation from

a HeCd laser (325 nm) and a HeNe Laser (633 nm) were

directed onto a diffuser connected to the fiber optics. Linearity at 480 nm was quantified depending on whether or

not any (or both) of the lasers were turned on. Results indicated the system was linear to within 0.6%, regardless of

the configuration, suggesting that the CCD read-out mechanism is not responsible for the nonlinearity observed with

polychromatic light sources.

A third test investigated the hypothesis that nonlinearity depends on the light intensity entering the fiber optics.

The test was set up like an irradiance calibration, but with

ND filters involving transmissions ranging between 10−3

and 1 placed in front of the diffuser. These tests indicated

that the observed nonlinearity is not affected by the light

intensity.

A fourth and final test was performed with the use

of cut-on filters, which are opaque at wavelengths below

a certain wavelength. Examples are shown in Fig. 43a

with no filter and Fig. 43b with a GG-400 filter, which is

opaque below 380 nm. In the latter case, signals measured

at wavelengths below 380 nm are entirely caused by stray

light and nonlinearity is almost entirely restricted to this

region.

59
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

0.8

1.2

1.6

2

180 280 380 480

Ratio

Wavelength [nm]

3

5

10

a

0.8

1.2

1.6

2

180 280 380 480

Ratio

Wavelength [nm]

3

5

10

b

Fig. 43. Linearity test results of the Zeiss/Tec5 MCS CCD performed without and with a cut-on filter: a)

no filter, and b) the GG-400 filter, which is opaque below 380 nm. The plots show the net signal measured

by the Zeiss/Tec5 MCS CCD divided by integration time (3, 5, or 10 ms) and normalized to the measurement

with 10 ms integration time. This ratio should be equal to 1 and independent of integration time for a linear

system.

These tests confirmed that nonlinearity is only a problem when polychromatic light sources are measured. They

also suggest that the effects of nonlinearity can be reduced

(if not, perhaps, completely eliminated) if the stray light

contribution to the net signal is removed by post processing the data. It has yet to be shown whether this is true

or not.

7.5 Conclusions

A side-by-side comparison of the spectrographs that

were tested is provided in Table 12, which is organized

as a function of nine unit specifications. Note that the

organization of the table follows the presentation scheme

established with Table 11, although it is partitioned a little

differently.

Wavelength range testing showed the wavelength range

of all test units is sufficient for OSPREy applications. The

wavelength range of most units can be optimized for the

needs of OSPREy by selecting an appropriate grating. The

two Hamamatsu units have fixed gratings, covering the

range of 325–1063 nm by using both units together.

Spectral resolution and slit function testing showed the

bandwidth of the 10 test units varied between 2–10 nm.

The Zeiss/Tec5 MMS UV-VIS II and MMS1 models plus

the Hamamatsu C9407MA and C9408MA models represent the four smallest units, and they have bandwidths

ranging between 6–10 nm. The comparatively low spectral

resolution of these units may not be sufficient for some OSPREy applications. All spectrographs have symmetrical

gaussian-shaped slit functions, with the exception of the

Avantes AvaSpec-2048 and the B&W Tek BTC112E. The

optics of these two test units may have been misaligned.

Out-of-band rejection and stray light testing showed

the far-field out-of-band rejection of the test units varied

between 0.04% and 0.0004%. Characterizing out-of-band

rejection with a monochromatic light source is not sufficient to characterize stray light characteristics relevant for

solar measurements. The dynamic range of solar measurements is typically limited by stray light to 2.5–3.0 orders

of magnitude. Stray light is also a problem for calibration scans and limits the dynamic range to between 1.5

(AvaSpec-1024) and 3.0 (MCS CCD) orders of magnitude.

The spectral distribution of stray light can be determined

with cut-on filters, and a correction can be applied. This

correction extends the usable dynamical range for calibrations by more than one order of magnitude.

Saturation testing showed that with the exception of

the Zeiss/Tec5 MCS PDA spectrograph, all instruments

saturate when their fiber optics are pointed at the Sun.

While the MCS PDA does not saturate at 1 ms integration time, other data suggest that the instrument is not

linear at this short integration time. This means that ND

filters have to be used to measure direct sunlight for all

instruments.

Change of dark signal with integration time testing

showed the dark signal increases substantially with integration time for all instruments. The Avantes AvaSpec-1024,

the B&W Tek BTC112E, and the two Hamamatsu units

exhibit a large pixel-to-pixel variation in the dark signal,

60
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

which increases with integration time. Most of this variability is removed when subtracting “dark” from “light”

measurements, however, the dynamic range for long integration times is limited by these “hot” pixels. The pixelto-pixel variability of the two CCD-equipped Avantes units

and the four Zeiss/Tec5 units is very low in comparison.

Change of dark signal with temperature testing showed

the dark signal of all instruments depends strongly on temperature. Changing the temperature from 10◦C to 60◦C

increased the dark signal by factors between 16 and 115.

For long integration times, the dark signal of some pixels of

the Hamamatsu units and the Avantes AvaSpec-2048x14

saturated for temperatures above 45◦C. These results show

that all instruments should be operated in a temperaturestabilized—preferably cooled—housing. The detectors of

the B&W Tek BTC112E and the Zeiss/Tek5 MCS CCD

units are thermo-electrically cooled. The testing showed,

however, that the instruments are not insensitive to variations in ambient temperature. Consequently, it is necessary to temperature stabilize the enclosure where these

instruments would be installed. This is a challenge, because the excess heat of the thermo-electric coolers would

have to be properly dissipated.

Irradiance responsivity and NEI testing showed all instruments exhibited some nonlinear behavior when measurements at different integration times were compared.

Stray light prevented determination of responsivity at short

wavelengths. NEI was calculated by dividing the standard

deviation of dark current measurements by the responsivity. When using the longest integration time that does

not lead to saturation, the NEI of the test units ranged

between 0.0006 and 0.01 μW cm−2 nm−1. For some instruments, NEI is not small enough to calibrate these units

with sufficient accuracy in the UV.

Radiance responsivity testing confirmed problems with

nonlinearity and stray light. When limiting the field-ofview to 2.5◦ full-angle, it became a challenge to determine

responsivity for several instruments. This problem could

be alleviated by moving the lamp closer to the plaque.

Linearity testing showed all instruments suffer from

some nonlinearity. The problem is most severe for instruments equipped with CCD detectors, e.g., the Avantes

AvaSpec-2048 and AvaSpec-2048x14. The testing indicates that departures from linear behavior of these two

instruments may exceed 5% at large signals and 40% at

low signals. The Zeiss/Tec5 MCS CCD is also affected

by nonlinearity when tested with a polychromatic light

source. It is linear to within 0.6% (i.e., within the measurement uncertainty) when tested with a monochromatic

light source. The reason for the conflicting results is not

understood. As calibrations are performed with polychromatic light sources, nonlinearity remains a challenge.

The primary conclusions of the spectrograph testing,

organized in order of importance to OSPREy objectives,

are as follows:

1. Of the instruments tested, the two Zeiss/Tec5 MCS

units have the best optical properties and operational characteristics. The main disadvantages of

the instruments are their large size and high price.

Like all other instruments tested, the two instruments are affected by nonlinearity when exposed to

polychromatic radiation, which limits the usable dynamic range of the instruments.

2. The Zeiss/Tec5 models MMS UV-VIS II and MMS1,

as well as the Hamamatsu C9407MA and C9408MA

(used together) units, are also possible options for

OSPREy. The main advantage of the four units is

their small size while still providing acceptable optical characteristics. Their main disadvantage is their

comparatively large, wavelength-dependent bandwidth of 5–9 nm. The two Hamamatsu units also

suffer from an excessively high dark current with

large pixel-to-pixel variability.

3. All Zeiss/Tec5 spectrographs are made from a monolithic body, which provides superior ruggedness and

wavelength stability.

4. The two Hamamatsu units are only equipped with

the USB 1.1 interface and two spectrographs cannot

be operated at the same time on one computer.

5. Instruments equipped with CCD detectors have favorable sensitivity. Unfortunately, the signals of

these units change in a nonlinear way with integration time and flux level. These nonlinearities

are difficult to correct and pose a challenge for OSPREy integrations.

6. Good temperature stabilization is necessary for all

units because of the large temperature dependence

of the dark offset with the spectrograph component.

This is a challenge considering space and power are

recurring limitations.

7. None of the spectrographs are able to cover the dynamic range required for direct observations of the

solar disk, calibration scans, and measurement of

other natural targets (e.g., radiance emanating from

the ocean). Possible solutions to this problem are

to a) use ND filters mounted on a filter wheel under computer control to attenuate the signal when

viewing the Sun, b) use a fixed ND filter in combination with a large field-of-view (e.g., 17◦ instead of

2.5◦), or c) to not use spectrographs for Sun measurements. For the latter, EML radiometers use a

filter wheel.

61
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Chapter 8

The Integrated OSPREy System

Charles R. Booth, Randall N. Lind, John H. Morrow, and Germar Bernhard

Biospherical Instruments Inc.

San Diego, California

Stanford B. Hooker

NASA Goddard Space Flight Center

Greenbelt, Maryland

Abstract

The previous chapters describe the major elements in the radiometers used in an OSPREy system: a microradiometer cluster with necessary modifications to support OSPREy design criteria, a spectrograph, optical

collectors (both radiance and irradiance), primary (housing) and secondary (spectrograph) thermal regulation,

and accessories like the tracker and shadowband. This chapter describes how these components—plus housing

design, primary and secondary temperature control, and other support electronics—are integrated to make the

radiometers used in OSPREy systems. These include radiance and irradiance field sensors, and a similar pair

designated as transfer radiometers. The fully integrated system provides an unprecedented capability in a single

housing. The spectrograph provides hyperspectral resolution over a subset of the complete spectral range, while

the microradiometers provide a larger dynamic range in responsivity, higher sampling speeds, better sensitivity,

and sampling across the entire OSPREy spectral range (290–1,670 nm). The two sensor technologies supplement each other. For example, spectrograph data can be used to detect potential degradation of the interference

filters used by the microradiometer channels while the microradiometers help to correct dark-current drifts and

nonlinearity in spectrograph measurements. The capability of radiance sensors is further enhanced by a nineposition filter wheel and integrated camera. In the standard configuration, the filter wheel permits hyperspectral

polarimetric measurements, direct-Sun viewing, stray-light correction, dark current measurements, and a home

position. The video camera is used for locating the Sun and verifying the condition of all targets (cloud-free

solar and lunar disks, cloud presence in sky data, and sea surface debris or foam detection). The components

of each radiance and irradiance sensor type are integrated in a common housing that is environmentally sealed,

nitrogen purged, and temperature controlled. Synchronous and asynchronous sampling modes measure the sea,

Sun, and sky, across a wide spectral range (UV–SWIR). The OSPREy architecture is modular and scalable,

which permits the configuration (sensor inventory) and complexity (sampling redundancy) to be matched with

science objectives and resource allocations. The modularity allows the observing system to expand or contract as mission requirements evolve. These measurements support an unprecedented number of current and

next-generation satellite missions involving both atmospheric and oceanic data products.

8.1 Introduction

OSPREy systems use EMR sensors composed of a cluster of fixed wavelength microradiometers and a spectrograph. The sensors include radiance and irradiance versions, with a similar pair designated as transfer radiometers. Previous chapters presented major elements in the

hybrid designs: microradiometers and necessary OSPREy

modifications (Chap. 2); optical collectors, for both irradiance (Chap. 3) and radiance (Chap. 4); the tracker used

with the radiance sensors (Chap. 5); and selection of a

spectrograph (Chap. 7). This chapter describes how these

components—plus housing design, primary and secondary

temperature control, and other support electronics—are

integrated in OSPREy systems built with EMR sensors.

The spectrograph component provides hyperspectral

resolution over a subset of the complete spectral range,

while the microradiometers provide a larger dynamic range

in responsivity, higher sampling speeds, better sensitivity, and sampling across an observational spectral range

of 340–1,640 nm. The two sensor technologies supplement

each other through intracomparisons. For example, spectrograph data can be used to detect potential degrada62
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

• 8–19 channels

• One radiance sensor

 (SeaPRISM analog)

• Manual or fixed options

Starter System

• Radiance and irradiance

 (16–37 channels)

• Some redundancy

• Shadowband optional

Minimum System

• Two irradiance sensors

 with shadowbands

• One radiance sensor

• Improved accuracy

Spectral System

• Up to 74 channels of

 radiance and irradiance

• Synchronous and asyn-

 chronous data products

Operational System

• Two complete triads

• Maximum redundancy

 and spectral coverage

• Maximum data quality

Maximum System

• Sun, sea, sky, and Moon radiance measurements (290–1,670nm)

• Thermal regulation, hyperspectral, video camera, and 9-position

 filter-wheel assembly (3-axis polarimetry, cut-on filter, etc.)

• QA and QC from microradiometer-spectrograph intracomparison

Measurements, Data Products, and Mission Advantages

• Global irradiance plus diffuse component (using shadowband)

• Direct-to-global irradiance ratio (used for cosine-error correction)

• Improved data products plus cloud detection and optical depth

• Enhanced QA and QC from two (redundant) solar measurements

All of the Above, and in Addition:

• Two optimized cosine collectors for high irradiance accuracy from

 UV to SWIR (290–1,100 nm and 1,000–1,670nm)

• Up to 36 channels for irradiance or enhanced redundancy

• Synchronous and asynchronous shadowband operation

All of the Above, and in Addition:

• Redundancy minimizes risk (data loss from sensor malfunction)

• Synchronous sampling enhances QA, QC, and data products

• Asynchronous sampling also enhances data products (e.g., the

 detection of thin cirrus clouds)

All of the Starter and Minimum Systems, and in Addition:

• Maximum risk reduction (full instrument redundancy)

• Maximum number of synchronous and asynchronous scenarios

• Maximum QA and QC (faulty sensor or device quickly identified)

• Maximum number and quality of data products

All of the Above, and in Addition:

a

b

c

d

e

Fig. 44. The SHALLO architecture applied to the EMR sensor suite to produce the following field systems

(in order of increasing complexity and capability): a) starter system, b) minimum system, c) spectral system,

d) operational system, and e) maximum system. The wavelength ranges are examples and can be configured

to the research objectives—they are not predetermined.

tion of the interference filters used by the microradiometer

channels while the microradiometers can help to correct

dark-current drifts and nonlinearity in spectrograph measurements, while greatly extending the dynamic range.

The capability of EML (radiance) sensors is further enhanced by a filter-wheel assembly and integrated camera.

The nine-position filter-wheel assembly is mounted in line

with the spectrograph fiber optics and can be custom populated. In the standard configuration, the filter wheel

permits hyperspectral polarimetric measurements (three

polarized filters), bright-target viewing (two ND filters),

stray-light correction (395 nm cut-on filter), dark current

measurements (opaque disk), dim-target viewing (open),

and a home position. The video camera is used for locating the Sun (in lieu of a quadrant detector) and verifying

the condition of all targets, i.e., cloud-free solar and lunar

disks, cloud presence in sky data, and sea surface debris or

foam detection (although an irradiance sensor can confirm

cloud-free solar and lunar disks).

The OSPREy field radiometers are EMR sensors, and

the laboratory sensors are from the OXR instrument class.

A fully supported deployment of an OSPREy system involves radiance and irradiance sensors from both instrument classes being used in the field and in a calibration

facility. Although the sensors are similar, there are differences, as summarized in the following:

1. OXR sensors are anticipated to be used exclusively

in the laboratory (calibration transfer), while EMR

sensors are anticipated to be used only in the field.

2. OXR sensors have a maximum of 18 fixed wavelengths, because the spectrograph fiber replaces one

microradiometer for both radiance and irradiance

instruments; for EMR sensors, this is also true for

EME sensors—EML sensors have 19 channels.

3. EML sensors have a nine-position filter wheel and

a video camera.

Although designed for laboratory use only, OXR sensors

are nonetheless designed to be rugged and can be shipped

to remote calibration facilities.

An important aspect of EMR sensors is their scalability. One part of this unique functionality results directly

from the modularity of microradiometers, but the principal

scalability comes from the Scalable Hydro-optical Applications for Light-Limited Oceanography (SHALLO) design

philosophy established for all instrument classes built with

microradiometers, including above-water sensors (Morrow

et al. 2010a). This philosophy recognizes that there is always a part of the spectrum that is light limited for all

water masses, although the portion of the spectrum involved likely changes with water type. Consequently, a

high-quality sensor technology that can be easily and cost

effectively reconfigured—i.e., microradiometers—is needed

to span and adapt to the dynamic range of the problem.

The SHALLO architecture codifies this philosophy by

establishing a sequence of modular capabilities and a stepwise upgrade pathway for the instruments built with microradiometers (Fig. 44). For EMR sensors and their antic63
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Fig. 45. The testing of EMR sensors on the BSI rooftop facility: a) an EML sensor (without a shroud) in

solar-tracking mode, and b) an EME sensor with the shadowband deployed and shading the cosine collector.

The customized bracket holding the radiance sensor fastens to the arm of the PTU-D300 tracker.

ipated use in the OSPREy activity, five system configurations are available. The five systems establish a hierarchy

in the level of accomplishment that can be achieved , both

in terms of the accuracy and diversity of the resulting data

products. The five systems also establish a range in complexity and, thus, a range in resources needed to deploy

and support the systems. Within this matrix of functionality and cost, the starter system requires the least, and

the maximum system provides the most.

The ensuing sections introduce the common design features for EML and EME sensors (Fig. 45) followed by the

specifics of what is needed to produce each system configuration. To ensure all systems are completely commercial

products, all the radiometers and necessary support electronics or mechanisms are constructed with COTS components. Some of these components are discussed in detail

in prior chapters of this document or in Morrow et al.

(2010a) and are mentioned only briefly here. The shortand long-term stability of an EMR sensor is of great importance to OSPREy applications. It is achieved primarily

through the selection of stable components, thermal regulation, nitrogen-purged and sealed housings, plus rugged

designs that can withstand potential shocks during transport.

8.2 Common Design Features

All EMR and OXR sensors, whether built to measure

radiance or irradiance, have three common design features:

a fixed wavelength microradiometer cluster, a hyperspectral spectrograph, and a support electronics component.

Radiance sensors are further distinguished by having a

filter-wheel assembly and a video camera. All radiometric

components are mounted inside a nitrogen-purged sealed

inner housing, which is temperature regulated to within

40 ± 0.1◦C using a primary heater element and analog

proportional-integral (PI) controller. The housing is an anodized aluminum cylinder with an outer diameter of 6.0 in

(15.2 cm) and a length of 22.9 in (58.2 cm) for EML sensors

and 19.7 in (50.0 cm) for EME sensors.

The spectrograph fiber-optic bundle is 9.4 in (24.0 cm)

long and enters the inner housing via a sealed coupling.

The tip of the fiber optics is in the same plane as the

microradiometer photodetectors such that the fiber optics

and the photodetectors have the same view of the back

of the irradiance collector. Custom temperature regulation from a secondary heater element integrated with the

spectrograph supports stable temperatures to better than

±0.03◦C.

An EMR sensor set is defined as a single radiometer

(Fig. 44a), a radiance and irradiance pair (Fig. 44b), or a

radiance radiometer with dual irradiance radiometers (Fig.

44c). Each sensor set plus accessories and ancillary sensors

are connected to a Power and Component Scheduler (PCS)

unit (Sect. 8.2.4), which provides power and houses the

needed support electronics for instrument scheduling and

data acquisition. Consequently, the redundant configurations shown in Figs. 44c and 44d, require two PCS units.

A separate Archive and Communications Master (ACM)

coordinates the measurements of all sensors in the system

configuration and archives the data collected by the PCS

units (Sect. 8.2.4).

8.2.1 Microradiometer Component

The microradiometer section of EMR sensors consists

of the fore optics to support irradiance (Chap. 3) or radiance (Chap. 4) measurements, the cluster of microradiometers with integrated filters for wavelength selection,

and the aggregator. The waveband set used to initiate the

OSPREy activity was based on a variety of factors. Because the fixed-channel wavelengths of EMR instruments

are based on microradiometer technology, it is easy to

change the set of wavelengths in response to requirements

for a specific satellite mission or research requirement, so

the initial configurations are easily modified if necessary.

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

The selected wavelengths for the OXR and EMR sensors

produced for the OSPREy development activity are presented in Table 13.

Table 13. The wavelengths (10 nm bandwidths,

except as noted) used in the OXR and EMR sensors

for the OSPREy development activity (L denotes

the radiance sensor and E the irradiance sensor).

Nominal Center OXR EMR

Wavelength [nm] L E L E

320 ×

340, 380 × × × ×

395 × ×

412, 443 × × × ×

465 ×

490, 510, 532, 555 × × × ×

589 × × × ×

625, 665, 683, 710, 780, 875 × × × ×

1,020, 1,245†, 1,640‡ × × ×

† 15 nm bandwidth. ‡ 30 nm bandwidth.

The criteria used to select the wavelengths in Table 13

were based on the following considerations:

• Because the primary objective of the OSPREy activity

is to validate satellite measurements of water-leaving

radiance, filters were selected at wavelengths where absorption by atmospheric trace gases such as oxygen and

water vapor is minimal. This is particularly important

because the oceanic signal is an order of magnitude less

than the total radiance observed by a satellite sensor.

Selecting bands void of atmospheric absorption is also

important for accurate retrievals of aerosol parameters.

• Wavelengths were selected to match current and nextgeneration ocean color satellite missions.

• SWIR wavelengths were included to improve atmospheric correction algorithms. The ocean is radiometrically black in the SWIR domain, so the contribution

of the atmosphere to the backscattered signal can be

accurately measured and extrapolated to the visible domain.

• In anticipation of a future focus on coastal zones, UV

wavelengths were included because they might be used

to distinguish the absorption signals of CDOM, Chl a,

detritus, and minerals. UV bands may also promote

the detection of harmful algal blooms, such as red tides,

because they produce UV absorbing compounds known

as mycosporine-like amino acids (Laurion et al. 2003).

Furthermore, UV bands are helpful for flagging data

affected by absorbing aerosols, which are a challenge

for atmospheric correction.

• The spacing of the chosen wavelengths is approximately

equal throughout the UV and visible domains.

• OSPREy systems are composed of as many COTS elements as possible. To keep costs down, wavelengths

were selected from a pool of wavelengths commonly

stocked at BSI.

The OXR sensors include a 320 nm channel to allow for

comparisons of standards of spectral irradiance below the

shortest wavelengths of the EMR field instruments as initially configured (340 nm). This is important, because the

spectra of the calibration lamps may deviate significantly

from a black-body function for wavelengths in the UVB. The spectrum of a lamp does not change linearly with

wavelength, so knowledge of the spectral irradiance below

340 nm is needed to accurately interpolate lamp spectra

between the two shortest wavelengths used by the field instruments (i.e., 340 and 380 nm).

Each microradiometer is assembled with custom, iondeposited, five-cavity, interference filters with 6 OD blocking over the detector range, and is designed for minimum

fluorescence. Additional broad-band blocking filters are

included in most microradiometer assemblies to provide

additional out-of-band blocking. These are selected after

reviewing the interference filter performance and the target

source spectral distributions. Each EMR sensor is spectrally measured to verify blocking and center wavelength

(Fig. 46). All data were deconvolved to correct for the finite bandwidth of the slit function for the spectral tester,

as described by Bernhard et al. (2005). The centroid wavelength λc of each channel is calculated as

λc =

 γ(λ)λ dλ

 γ(λ) dλ , (13)

which is then used in the data analysis.

0.001

0.01

0.1

1

300 1000 2000

Normalized Spectral Response

Wavelength [nm]

500

Fig. 46. The normalized spectral response functions of the OXE sensor (Table 13). Note the logarithmic x-axis.

8.2.2 Spectrograph Component

The inclusion of a spectrograph permits sampling of

the spectrum in regions between the filtered detector channels. The advantage of the higher resolution of the spectrograph can be combined with the superiorities of the filter radiometers—greater dynamic range, lower stray light,

65
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

better SNR, and higher scan speed—to provide a sensor combination superior to either of the individual constituents alone. Based on a detailed engineering analysis

(Chap. 7) the COTS models MMS UV-VIS II and MMS1

UV-VIS from Zeiss/Tec5 were selected for OSPREy. The

MMS UV-VIS II has a spectral range of 245–785 nm and

is used with the OXE and EME instruments. The MMS1

has a spectral range of 300–1,150 nm and is used for the

EML instruments.

The irradiance and radiance radiometers use different

spectrographs, because of differences in how dark corrections are made. Radiance sensors have a filter-wheel assembly for which one position contains an opaque disk for

measuring the dark current. Irradiance sensors do not have

a filter-wheel assembly, and it would have been both challenging and cost prohibitive to integrate a mechanical shutter in this design for automated dark measurements of the

spectrograph. Consequently, a different technique for applying the dark correction was necessary.

For irradiance radiometers, fixed wavelength channels

and the fiber optics of the spectrograph share common fore

optics (Fig. 47), including the cosine diffuser. In this design, one microradiometer of the fixed wavelength cluster is

replaced by a pass-through of the spectrograph fiber optics.

Although the spectrograph is temperature stabilized with

an analog controller to better than ±0.03◦C when used in

the field, data analysis indicates that the remaining variation in temperature still leads to noticeable variation in

the dark current of the spectrograph.

Fig. 47. The front (aperture) section of an OXE

or EME radiometer showing how the spectrograph

fiber optic (pink) replaces one of the microradiometers, so both sensing technologies view the cosine

collector.

Because the atmosphere is opaque below 290 nm, spectrograph data from 245–290 nm can be used to monitor

variations in the dark offset, which can then be used to

correct the observational data. This correction is possible because tests indicate that changes in the dark offset

are nearly independent of the spectrograph pixel, which

means that information from the 245–290 nm range can

be used to correct measurements in the UV-A and visible

wavelengths.

If the MMS1, which does not measure below 300 nm,

had been selected for irradiance radiometers, corrections

for drifts in the dark offset would have been challenging,

perhaps not even possible. The use of the MMS UV-VIS

II in irradiance units is, therefore, necessary to meet the

accuracy requirements for OSPREy applications. An additional advantage of the MMS UV-VIS II is its smaller

bandwidth of 7 nm provides superior spectral resolution

compared to 9 nm for the MMS1.

In radiance instruments, fixed wavelength channels and

the fiber optics of the spectrograph use independent Gershun tubes defining their FOV. This design allows a physical separation of the two components and the implementation of a filter wheel between the spectrograph fiber optics

and the Gershun tube for the spectrograph (Fig. 48). The

filter wheel also includes an opaque disk position for automated dark current measurements. Drifts in dark current

can be corrected by moving the filter wheel periodically to

the opaque disk position, and measurements below 290 nm

are not needed. Consequently, the MMS1 is used for radiance instruments to take advantage of their ability to

measure at wavelengths beyond 785 nm.

a

b

c

c

d

e

e

f

Fig. 48. The front (aperture) section of an OXL radiometer with the environmental housing removed

(right), and the cover plate with all apertures visible

(left). The exposed components include a) the primary instrument heating element (red), b) the microradiometer Gershun tubes, c) the video camera

exit aperture, d) the array of 19 microradiometers

on a hexagonal grid, e) the spectrograph exit aperture, and f) the filter-wheel assembly (with separate

Gershun tube).

8.2.3 Support Electronics Component

All sensors and controls are accessible via a single allweather connector on the end cap of the radiometer, which

is used to route the spectrograph data acquisition and control functions via a Tec5 interface to the Zeiss spectrometer. This connection also provides communications with

the microradiometers and their aggregator, secondary temperature control for the spectrograph, and a flash drive for

storing calibration data. In the case of the EML (radiance)

sensor, control of the filter wheel and telescopic camera

are also routed through the connection. The internal electronics and spectrograph temperature control use 12 VDC

power; the primary instrument temperature control uses a

separate 15 VDC power source.

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

A commonly used device for instrument temperature

stabilization is the digital proportional-integral-derivative

(PID) controller, which switches a heater on and off at

high frequency. Rapid switching can cause electrical interference that may cause noise in measurements made

by sensitive devices. To prevent any adverse effects, the

spectrographs in OXR and EMR sensors are temperature

stabilized using an analog proportional-integral (PI) controller, which smoothly adjusts the current to the heater

strip attached to the device without switching.

Measurements of the spectrograph temperature of an

OXR sensor that was tested in the laboratory over a time

period of 10 h showed variations in temperature had a standard deviation of 0.0011◦C, indicating the excellent performance of the controller. Temperature variations of a system installed outside were larger, about ±0.03◦C, because

solar heating caused temperature gradients across the radiometer. Gradients across the spectrograph component

are minimized by thermal insulation, but cannot be completely avoided and have an effect on the spectrograph’s

dark current. For the most accurate measurements, it is

therefore necessary to measure the dark current several

times throughout the day.

The nine-position filter wheel (Fig. 49) is mounted in

front of the spectrograph fiber and uses an index (home)

position to establish the following hyperspectral measurements: three axes of polarization, dark offsets (opaque

disk), bright-target (Sun) viewing (two different ND filters), dim-target (Moon) viewing (open), and stray-light

correction (395 nm cut-on filter).

a

b

c

d

e

f

g

h

i

Fig. 49. The EML sensor filter wheel: a) index

(home) position, b) cut-on filter, c) 90◦ polarizer,

d) 45◦ polarizer, e) 0◦ polarizer, f) opaque disk, g)

3.0 ND filter, h) 1.5 ND filter, and i) open.

The wheel measures 30 mm in diameter and is driven

by a high resolution stepping motor controlled by the aggregator electronics. Recent testing has shown that the

components are sufficiently light tight that high-quality

dark measurements can be obtained by making the dark

measurement in between two disk positions. This frees up

a position in the filter wheel for another purpose, if needed.

The integrated video camera is a USB Webcam fixedfocus camera modified with the addition of telescopic optics and ND filters optimized for direct viewing of the Sun.

The video camera is used for locating the Sun (in lieu of a

quadrant detector) and verifying the condition of all targets, i.e., cloud-free solar and lunar disks, cloud presence

in sky data, and sea surface debris or foam (although an

irradiance sensor can confirm cloud-free solar and lunar

disks).

External to the instrument housing, located a short

distance away (less than 5 m) in an all-weather enclosure is

an acquisition control computer based on a low-power Intel

Atom processor, solid state disk drive, and high-efficiency

AC-to-DC power supplies for the computer and the remote

field radiometer. Also in this enclosure is an Ethernet hub

allowing the computer to connect to the Internet, other

field radiometers, and field laptops, which may be brought

to the site for calibration and other maintenance duties.

Other interface modules for connecting additional sensors

(meteorological sensors, for example) can also be provided.

Typically, this enclosure would be mounted at the base of

the pedestal mounting the radiometer.

8.2.4 System Scheduling and Archiving

In an observational system built with EPIC radiometers (Fig. 44), each EMR sensor, as well as ancillary external devices that do not connect directly to an EMR

sensor, connects to an automated Power and Component

Scheduler (PCS), which is housed with additional support

electronics (described below) in a stainless steel control

box for long-term weather resistance. The enclosure was

selected with an emphasis on maintaining a reasonable internal thermal environment for the electronics in all seasons, as well as ease of field maintenance in the event of a

component failure.

The enclosure is a National Electrical Manufacturers

Association (NEMA) 4X type, which provides certified

protection from the worst environments with an ingress

protection (IP) rating for the connectors (IP67) and suitable cables. The control box is designed to be located up

to 5 m from the external devices, and is resistant to the

external formation of ice on the enclosure. It is also rated

for protection against corrosion, falling dirt, rain, sleet,

snow, windblown dust, and splashing water. PCS power is

supplied from 85–264 VAC at 47–63 Hz (200W maximum).

Options are available for DC power from solar panels or

other power sources (e.g., a wind turbine).

Custom OSPREy software written as Microsoft .NET

Framework modules control the system and provides autonomous operations under a user-programmable schedule.

Included in the PCS are high stability, low-noise power

supplies, thermal control circuitry, an integrated GPS receiver, and auxiliary sensors (e.g., a rain detector) as desired. The PCS design is predicated on adaptability; for

67
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

example, radiance instrument position is controlled by the

tracking system, and the operation of the shadowband is

likewise controlled by an automated positioning system,

either of which is powered by a Phoenix TRIO power supply mounted on a standard mounting rail†. The internal

components were carefully selected for reliability in each

purpose. OSPREy system operations are controlled by an

Intel DW525 Atom dual core imbedded PC with 4 GB random access memory (RAM) plus a 120 GB solid-state disk

(SSD), under Windows Embedded 7, as configured for OSPREy. A block diagram overlaid on a picture of control

box internal components is provided in Fig. 50 (the optional surge protector and Ethernet hub are not shown).

a

b

c

d

e

f

g

h

i

j k

Fig. 50. The control box internal components for

an EMR observational system, like OSPREy (the

heat sink and GPS antenna are not shown, because

they are mounted on the top exterior of the enclosure), grouped into functional units: a) primary

housing temperature controller (Wavelength Electronics); b) power switch and USB expansion hub;

c) DIN rail with terminal blocks; d) power supply (Phoenix) for the embedded PC and tracker

or shadowband accessory; e) 110 VAC bus; f) circuit breaker; g) 120 GB SSD (Intel); h) D525MW

Atom dual-core embedded PC (Intel); i) secondary cooling fan; j) ultra-low-noise power supply for

main instrument power and spectrograph secondary

temperature controller (Daitron); and k) ultra-lownoise power supply for primary housing temperature controller (Daitron).

Data collection software running on each PCS is driven

by a scheduler (task), which specifies the component and

† A Deutsches Institut f ̈ur Normung, or German Institute for

Standardization, (DIN) metal rail widely used for mounting circuit breakers and industrial control equipment inside

equipment racks is used.

mode of data collection as a function of time. The scheduler is implemented as a table in American Standard Code

for Information Interchange (ASCII) format and is regularly updated by the Archive and Communications Master

(ACM), which coordinates the measurements of all EMR

sensors. Because all computer clocks are synchronized,

measurements can be performed in synchronous and asynchronous modes as directed by the ACM.

If the connection between a PCS and the ACM is severed (e.g., because the communications connection is lost

or there is a failure with the ACM), the affected PCS system will run the schedule it last received from the ACM

until new communications establish otherwise. The scheduler specifies all parameters relevant for system operation including the mode of the shadowband (e.g., stowed

shadowband, shadowband in front of Sun, or shadowband

sweeping between predefined angles), the mode of the solar

tracker (e.g., Sun tracking using ephemeris algorithm, Sun

tracking using video camera, Moon tracking, sky scan, sea

surface viewing, etc.), the position of the filter wheel in

EML (radiance) sensors, the integration time of the spectrograph, and others.

All data records are time stamped, and acquired in an

ASCII comma-separated format in the measurement units

reported by the sensors (e.g., volts, counts, or pixel number). Separate files are produced for system logs, the spectrograph (if present), and microradiometer components.

Data are recorded on the SSD, and are intended to be ingested daily by the ACM on a defined, but programmable,

schedule (most likely at night when system activity is usually at a minimum).

The ACM is a computer located close to the EMR sensors, or remotely situated, depending on the bandwidth

of the available communications channels to the deployment site. A variety of tools for system monitoring, QA

and QC, as well as data analysis are under development.

These tools are being designed to apply calibrations and

produce a variety of data products, with the initial set of

tools based on an operational system and its resulting data

products (Fig. 44d).

8.3 Starter System

The simplest OSPREy configuration—or starter system—uses a single EML radiance sensor as a starting point

for automated above-water radiometry and sun photometry, as well as an advanced replacement for a SeaPRISM

unit (Fig. 44a). With respect to the latter, SeaPRISM

units are not hyperspectral, have many fewer channels

(eight), are not capable of intracomparisons for QA and

QC (unless duplicate filter channels are installed, which

further reduces their limited spectral resolution), do not

have a video camera, and cannot measure channels simultaneously. In addition, any polarization capability also

reduces the spectral resolution.

The starter system is a low-cost, entry system into the

OSPREy suite of instruments, which can be incrementally

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

improved as resources or objectives evolve. For example, a

single EML sensor can be used as an algorithm validation

system or a monitoring device, for atmospheric, terrestrial,

and oceanic applications. The front end of an EML radiometer is shown in Fig. 48, and a cutaway drawing is

presented in Fig. 51. The narrow FOV of the instrument

determines the length of the Gershun tubes and results in

a slightly longer housing than an irradiance instrument. A

customized FOV for different sampling objectives is possible and would change the overall length of the instrument.

Similarly, customized lengths of the fiber optics can alter

the length of the instrument.

Fig. 51. A simplified technical drawing of an EML

radiometer. The core of the design is the cluster

of microradiometers (brown) left of the aggregator

stack (green) with filter-wheel assembly above, fiber

and spectrograph (pink) to the right, and camera

below. The electronics positioned near the end cap

primarily support the spectrograph. Some details

are omitted (e.g., wiring and insulation) for clarity.

A sampling scenario for a starter system may include

measurements of direct solar irradiance, E(λ), followed by

Li(λ) and LT (λ), to derive LW (λ). Because of the high

angular velocity of the tracker (up to 50◦ s−1), a complete

sequence can be executed within 30 s and may be repeated

several times per hour. Direct solar measurements allow

the determination of the AOD, which is needed for computing the normalized water-leaving radiance (Zibordi et

al. 2004b), LW (λ)



N. Once or twice per hour, almucantar

and principal plane scans can be performed for characterizing additional aerosol properties, e.g., the aerosol SSA

and phase function.

During the night, the measurement scenarios can include direct measurements of the Moon. A time series of

such measurements permits a Langley calibration of the

sensors and derivation of the AOD. The sequence of measurements can be reconfigured and tailored to the specific

research objectives. For example, a starter system can replace sun photometers used in the AERONET work and

sampling scenarios can be adapted to the AERONET protocol.

8.4 Minimum System

The addition of an EME sensor with a shadowband accessory to a starter system defines a minimum system configuration (Fig. 44b). The front end of an EME (or OXE)

sensor is shown in Fig. 47 and a cutaway depiction is provided in Fig. 52. An EME sensor consists of a cluster of 18

microradiometers with fixed wavelengths and the fiber of

the Zeiss/Tec5 MMS UV-VIS II spectrograph occupies the

position normally used by the nineteenth microradiometer.

The microradiometer cluster is coupled to the irradiance

collector via a plano-convex lens specially designed for use

with the parallel geometry of microradiometers (Booth et

al. 2010).

Fig. 52. A simplified technical drawing of an EME

(or OXE) following the approach in Fig. 51. The

primary new component is the plano-convex lens

(white) immediately left of the microradiometers

(brown) and the cosine collector on the aperture

end plate (blue).

The benefits of the minimum system configuration are

the enhanced QA and QC capabilities, which is provided

by having two (radiance and irradiance) independent measurements of the Sun and Moon plus the intracomparisons

between the microradiometers and spectrograph in each

sensor. By itself, the irradiance radiometer provides measurements of the global solar and lunar irradiance, which

can be used to detect the presence of clouds across the

solar and lunar disks. The shadowband accessory permits

the measurement of the diffuse component of the global

irradiance, which is used to establish the direct-to-global

irradiance ratio. The greater diversity in measurements

provides improved data products (e.g., better cosine-error

correction), as well as new data products (e.g., cloud optical depth).

A variety of sampling scenarios can be implemented

with a minimum system. For oceanic observations, the

EME sensor typically measures Ed(0+, λ) while the EML

sensor alternates between LT (λ) and Li(λ) measurements.

The Ed(0+, λ) data are used to convert LW (λ) derived from

the EML sensor to LW (λ)



N. Measuring Ed(0+, λ) directly, rather than estimating it from E(λ), as is done for

the starter system (or a SeaPRISM unit), is more accurate and this is a fundamental advantage of the minimum

system configuration.

A typical sampling scenario for atmospheric observations includes EML measurements of E(λ) while the EME

sensor measures Ed(0+, λ) and Ei(λ) in an alternating sequence using the shadowband. The direct irradiance computed from the Ed and Ei measurements can be used to

validate the data from the EML sensor. As an alternative,

the EME sensor can be making shadowband measurements

to determine the direct-Sun irradiance, while the EML sensor performs almucantar and principal plane scans. An

additional feature of the minimum system is its ability to

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Table 14. The sampling modes for the OSPREy operational system. The first column refers to the two redundant

EMR dyads, labeled “A” and “B”. Mode 1 is the standard mode for measuring LW (λ) and is distinguished by two

different (“a” and “b”) versions, wherein the role of the two dyads is reversed. Mode 2 has three versions, each of

which has both dyads making the same measurements: Sun, sky, and sea. Mode 3 is for sky radiometry and Mode 4

is stowed. The ⊥ symbol denotes viewing perpendicular to the solar plane.

Instrument Mode 1a Mode 1b Mode 2a Mode 2b Mode 2c Mode 3 Mode 4

A: Radiance Li LT Direct-Sun† Li LT Direct-Sun Stowed, dark

A: Tracker Sky, ⊥ Sun Sea, ⊥ Sun Tracks Sun Sky, ⊥ Sun Sea, ⊥ Sun Tracks Sun Stowed

A: Irradiance Ed, Ei Ed, Ei Ed, Ei Ed Ei Ed, Ei Ed, dark

A: Shadowband Cycling Cycling Cycling Stowed Active Cycling Stowed

B: Radiance LT Li Direct-Sun† Li LT Li Stowed, dark

B: Tracker Sea, ⊥ Sun Sky, ⊥ Sun Tracks Sun Sky, ⊥ Sun Sea, ⊥ Sun Sky scans Stowed

B: Irradiance Ed, Ei Ed, Ei Ed, Ei Ed Ei Ed, Ei Ed, dark

B: Shadowband Cycling Cycling Cycling Stowed Active Cycling Stowed

Duration [min] 15 15 15 5 5 15 > 60

† Or direct-Moon measurements.

estimate cloud optical depth by comparing measurements

of Ed during overcast illumination with reference data for

clear-sky conditions. As with the starter system, lunar

data collection scenarios are also possible.

8.5 Spectral System

A refinement to the minimum system is accomplished

by having two EME sensors. This so-called spectral system (Fig. 44c) uses two individually optimized cosine collectors to ensure the lowest cosine errors over the two spectral regions. The two regions are established by the cosine

collectors and the accompanying selection of the spectrograph. The two cosine collector designs are optimized for

the 290–1,100 nm and 1,000–1,670 nm spectral ranges, and

the corresponding wavelength ranges for the spectrographs

are 250–780 nm and 300–1,150 nm, respectively.

The overlap in wavelengths of the two spectrographs

provides redundancy in the measurement suite across a

subset of the full spectral range. The microradiometer

components of the two irradiance sensors can be set up

to add to, or complete, the desired level of redundancy—

the complete extent of which establishes how much minimization of risk is built into the system. Dual irradiance

sensors allow more sophisticated sampling scenarios using synchronous and asynchronous protocols, which further enhances data products and the number and types of

QA and QC products. The latter are an important part

of managing the uncertainty budget for the system.

In synchronous operation, the two irradiance sensors

work in tandem and the spectral system is essentially equal

to a minimum system with a larger number of wavelengths.

In this configuration, all sampling scenarios of the minimum system can also be applied to the spectral system.

In asynchronous operation, one irradiance sensor is measuring Ed while the other measures Ei using the shadowband. For channels common to both sensors, the ratio of

diffuse-to-global irradiance can be measured directly. This

method has smaller uncertainties compared to the alternative approach where this ratio is determined from sequential measurements of diffuse and global irradiance.

8.6 Operational System

Balanced proportions of enhanced accuracy and risk

minimization are achieved with an operational system (Fig.

44d), which is composed of two EML and EME dyads.

This system configuration was built as part of the OSPREy

development activity. Although each sensor type could be

configured slightly differently, the perspective here is that

the radiance sensors are duplicates as are the irradiance

sensors. The use of two identical dyads (recalling that

a radiance and irradiance sensor pair must differ by one

fixed wavelength channel) provides maximum redundancy,

which minimizes risk and maximizes enhanced data products from the use of synchronous and asynchronous sampling scenarios. Consequently, the operational system is

anticipated to be suitable for the highest-quality validation exercises, as well as for vicarious calibration.

Within the hierarchy of the most simple to the most

complex system configurations (Figs. 44a–44e), the operational system is the first system to provide the greatest diversity in sampling modes, as shown in Table 14). This diversity also provides the most extensive QA and QC opportunities, through redundancies in equipment (two copies of

one instrument type) and data products (alternative measurement approaches for the same data product). Ultimately, the diversity is primarily due to the fact that the

dual EML and EME sensors permit synchronous and asynchronous sampling for both sensor types, during the day

and night.

Modes 1a and 1b are the usual modes for LW (λ) measurements with one radiance sensor viewing the sky and

the other viewing the water at the correct angles with respect to the Sun and the platform-perturbation avoidance

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

criteria. The shadowband accessories cycle through measurements of global irradiance (Ed), diffuse irradiance (Ei),

and special measurements, wherein the shadowband is either positioned at 10◦ on either side of the Sun or slowly

sweeps over the collector (Bernhard et al. 2010). The latter are used to correct for the partial shading of the sky

when Ei is measured with the shadowband occulting the

Sun. The shadowbands of the two dyads operate asynchronously such that there is always a measurement of Ed.

Modes 2a–2c are designed primarily for sensor intercomparisons. In Mode 2a, both EML instruments measure

direct-normal irradiance and either track the Sun (day)

or Moon (night). The EME sensors cycle through independent measurements of direct-normal irradiance. In

Mode 2b, the tracked systems make synchronous measurements of sky radiance (Li) while the EME sensors measure

Ed. In Mode 2c, the EML instruments point at the sea and

the EME sensors measure Ei. These modes allow for the

intercalibration of both radiometer types, with the EML

sensors exposed to flux levels representative of Modes 1

and 3.

Mode 3 is designed to characterize the sky radiance field

for sun photometry, and is used for retrieving more comprehensive data products, such as the SSA. This is done

with one EML sensor scanning the sky at a constant solar

zenith angle and varying the azimuth (almucantar scan),

or by scanning the sky in a vertical plane containing the

Sun and the radiometer (principal plane scan). During

the latter, the second sensor is pointing at the Sun. Two

modes could be used here for redundancy, but given the

redundancy in the second set of modes, this seems unnecessary. During sky-radiance characterizations, the shadowband devices are cycling. There can also be an alternative

scan wherein one EML sensor scans the entire sky.

Mode 4 is a night mode and is used primarily to determine the dark offsets. During this mode, the radiometers

are exercised at each of the three gain settings while measuring the dark signals. Mode 4 is also executed during

severe weather for safeguarding the sensors.

8.7 Maximum System

The culmination of redundancy and sampling opportunities occurs with the maximum system, which uses two

identical triads (Fig. 44e). The triads are formed by using one EML sensor and two EME sensors to ensure the

highest accuracy in the irradiance measurements. Once

again, spectral diversity can be optimized by using different spectral configurations in the multiple sensor systems, while remembering that common wavelengths provide redundancy for the most important wavelengths and

enhance QA opportunities. The use of a maximum system

is anticipated for vicarious calibration activities requiring

the highest accuracy possible, and for specialized exercises

wherein a portion of the spectral domain requires a unique

configuration.

8.8 Transfer Radiometers

Although a separate class in the architecture of instruments built with microradiometers (Morrow et al. 2010c),

OXL and OXE instruments are of a similar design to their

EMR equivalents, and in fact, the irradiance sensors in

both product lines are the same. The principal differences

between the two are in the radiance sensors: compared to

an EML, an OXL unit does not have a video camera nor

a filter-wheel assembly, and has one less microradiometer

(18). Although built and envisioned as laboratory devices,

OXR sensors can collect data outdoors. The OXL spectrograph, however, saturates if pointed at a very bright target

(e.g., the Sun), because of the absent ND filter (due to the

missing filter wheel).

For the OSPREy activity, the main purpose of OXR

sensors is to a) ensure a high-accuracy transfer of the radiance and irradiance scales established by the NIST SIRCUS facility (Brown et al. 2000 and Eppeldauer et al. 2000)

to the BSI calibration laboratory, b) preserve these scales

for the long term, and c) transfer these scales to OSPREy

field sensors and the OSPREy lamp library (Chap. 6).

OXR sensors are compatible with the kinematic mounting

fixtures used in the BSI calibration laboratory to ensure

reproducible positioning.

The long-term stability of OXR units is very important.

For the OSPREy activity, the instruments are anticipated

to remain in the BSI calibration facility under controlled

environmental conditions (temperature and humidity) at

all times with the exception of travel to NIST for SIRCUS

calibration. The OXR radiance instrument is also used

for monitoring the stability of the BRDF of the reflectance

plaque used for radiance calibrations (App. I). Because the

BSI radiance calibration bench (Sect. 6.3.2.2) has fixtures

on both sides of the reflectance plaque, the OXR radiance

sensor can be used for direct comparison with other radiance sensors (Fig. 53). In this case, the calibration of the

lamp illuminating the plaque is not critical.

Fig. 53. A view from the plaque of the radiance

bench toward the calibration standard (dimly lit for

clarity). The OXL prototype is on the left side and

an EML sensor is on the right side with the spectrograph aperture oriented downward (6 o’clock position). Both instruments are positioned with kinematic mounts. All reflections are caused by the

camera flash.

71
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

8.9 Radiometer Performance

An OXE and an EML sensor were calibrated in the

BSI calibration laboratory. The OXE sensor was set up

on the irradiance bench (Sect. 6.3.2.1) and illuminated

by a calibrated FEL lamp 50 cm from the cosine collector (as measured from the lamp posts). The EML sensor

was set up facing the center of a Spectralon reflectance

plaque, which was illuminated by a calibrated FEL lamp

positioned 287.1 cm away from the center of the plaque.

Because both of the OXR and EMR instruments are

nontraditional—hybridspectral—devices, a new lexicon incorporating a unique symbology and vocabulary is needed

to provide the specificity for the calibration and the resulting data products that can be produced from the instrument measurements. This new lexicon is important

and becomes even more important once the radiometers

are exposed to the diversity of targets in the field, wherein

data products can be produced from different instrument

types (radiance or irradiance).

8.9.1 Iconographic Symbology

The so-called iconographic symbology presented here

is based on providing accents on variables, both above and

below, to denote the important aspect of data acquisition,

e.g., sea viewing, shadowband, FEL calibration, etc. In

most cases, the accents are designed to be visual clues regarding what was recorded. The simplest variable is associated with recording a signal amplitude, denoted A, and

is used to introduce the symbology. In most cases, A is

recorded from either fixed wavelength microradiometers or

hyperspectral spectrographs, and the spectral channel for

the former or pixel number for the latter is denoted λi. The

center wavelength associated with either is λc

i. To simplify

the ensuing presentation, any spectral dependence is omitted for the time being.

There are two types of optical measurements to distinguish: radiance and irradiance. Radiance measurements

usually involve targeting, and the sensor is pointed at a

light source. Irradiance measurements usually do not involve pointing, except they are usually made with respect

to an established planar geometry, which requires the instrument to be properly positioned or leveled (a form of

pointing). Radiance measurements usually have an arrow

accent, whereas irradiance measurements usually do not.

An exception for the latter is during calibration, wherein

the cosine collectors are pointed at a light source (e.g., an

FEL lamp). Consequently, the only time irradiance measurements have an arrow is to denote calibration (denoted

by leftward overhead arrow accent).

There are four recurring kinds of variables and the presence or absence of the accents provide the needed distinction among the four: a) a calibration recording, b) an ideal

value, c) a true value, and d) a field measurement:

A




A calibration value signal amplitude is identified by

the leftward overhead arrow accent.

AAn ideal value signal amplitude is identified by the

vertical parallel bars accent under the variable.

A

A true value signal amplitude is identified by the

horizontal parallel bars accent under the variable.

A field measurement, which is the most predominant type

of measurement, is identified by the absence of the above

three accents. Whether or not the measurement is radiance

or irradiance, as well as microradiometer or spectrograph,

is established below after more of the distinctive types of

measurements are presented.

A principle distinction in variable type, as established

in Chaps. 6 and 7, is whether the variable represents a light

or dark measurement. For a light measurement, the sensor

aperture is unobstructed with respect to the intended target, whereas for a dark measurement the sensor aperture is

obstructed, occluded, or capped. Following the approach

established above, wherein the most recurring value is not

accented, dark measurements are denoted by the presence

of a filled-in (dark) circle or square:

A

•

The capped dark signal amplitude obtained with an

opaque cover over the sensor aperture.

A




The background dark signal amplitude obtained by

closing a shutter between the lamp (while it is operating) and the radiometer.

A

•

The night (dark) signal amplitude.

A

•




The ambient or occluded calibration dark signal

amplitude.

Consequently, any variable without the filled-in (dark) circle is, by definition, a light measurement.

For irradiance sensors equipped with the BioSHADE

accessory, a unique type of dark measurement can be made:

A

•

The shadowband night (dark) signal amplitude.

This dark value can be subtracted from an irradiance night

(dark) value to establish a QA assessment of the night dark

(which shows how a radiance and irradiance dyad leads to

enhanced QA, because radiance sensors alone cannot make

this measurement).

There is additional nuance in the dark data collected

by microradiometers, which is important for certain analyses. The nuance is a result of microradiometers having

multigain amplifiers. The very first microradiometers had

two-stage amplifiers, and all subsequent models have threestage amplifiers. The type of amplification circuit, i.e.,

two- or three-gain stages, is denoted by the number of the

filled-in (dark) circles:

A•• The two-gain stage sensor dark signal amplitude.

•••

A The three-gain stage sensor dark signal amplitude.

Only one two-gain system was built with microradiometers

(the very first system), so the distinction between two- and

three-gain systems is not expected to be significant, but is

included for completeness.

When dark data are collected, microradiometers are

taken out of autoranging gain control and commanded

72
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

to switch to specific gain stages, so dark values can be

recorded for each gain stage. The particular gain stage

being recorded is denoted by the presence and relative position of the filled-in (dark) circle within a sequence of circles, the number of which indicates the number of stages

in the amplification circuit:

A•◦ The high gain of a two-gain sensor signal amplitude.

A◦• The low gain of a two-gain sensor signal amplitude.

•◦◦

A The high gain of a three-gain sensor signal amplitude.

◦•◦

A The medium gain of a three-gain sensor signal amplitude.

◦◦•

A The low gain of a three-gain sensor signal amplitude.

Combining the gain-stage information for a particular dark

type provides a complete description of the dark measurement. Combining a capped sensor dark with gain information can yield the following, for example:

A

•

◦◦• The low gain (of a three-gain sensor) signal amplitude obtained with a capped sensor.

This level of detail is not needed in all applications. It is

presented here for completeness and to show how a highly

detailed symbology might be produced.

As noted earlier, radiance measurements are targeted,

that is, the sensor is pointed at the light source to be measured. The currently anticipated targets for EMR radiometers include the following:

A




The sky signal amplitude.

A




The sea signal amplitude.

A

∗

The solar signal amplitude.

A

◦

The lunar signal amplitude.

Note that the sky and sea arrows are not horizontal, so

they do not indication calibration; the former is angled

upwards and the latter downwards.

The direct components of the solar and lunar flux can

be measured or derived and are designated as follows:

A

∗

The direct-Sun signal amplitude.

A

◦

The direct-Moon signal amplitude.

Note that two bounding small vertical bars are used in

conjunction with the already established Sun and Moon

accents to denote the value is directional.

For some of the OSPREy system configurations presented in Fig. 44, an irradiance sensor is equipped with a

BioSHADE accessory, so the indirect (sky) component of

the solar (or lunar) global irradiance can be determined.

This diffuse component can be subtracted from the global

measurement to yield the direct-Sun (or direct-Moon) irradiance component mentioned above. The shadowband

variables for OSPREy systems are as follows:

A



The shadowband sky signal amplitude.

A

∗

The shadowband solar global irradiance (Sun and

sky) signal amplitude.

A

◦

The shadowband lunar (Moon and sky) signal amplitude.

Recalling that a fourth shadowband dark measurement, A

•

,

can also be made.

The anticipated calibration scenarios include the following:

A






The FEL lamp calibration signal amplitude.

A

∗




The solar calibration signal amplitude.

A

◦




The lunar calibration signal amplitude.

A






The reflectance plaque calibration signal amplitude.

All of these calibration scenarios can be executed at BSI

or in the field.

8.9.2 Lexicon

Sensor performance was established using the statistics

derived from dark and light measurements plus instrument

characterization parameters, which have a spectral dependence (part of this nomenclature was presented in Sects.

6.7 and 7.2, and is repeated here for completeness):

μ(λ) The mean value of an acquisition sequence,

σ(λ) The standard deviation of an acquisition sequence,

κ(λ) The maximum (or saturation) signal level,

γ(λ) The responsivity (calibration coefficient and applicable terms, e.g., the immersion factor).

The use of light or dark data is indicated by the absence

or presence of a dark accent, respectively. In this case the

capped darks accent is applicable. For example, the mean

value of a dark data acquisition sequence is denoted μ

•

(λ),

whereas the mean value of a data acquisition sequence collected with the aperture exposed to light is denoted μ(λ).

Considering a generalized parameter P, an indexing

scheme is adopted wherein two indices, i and j, provide the

needed specificity to uniquely identify the measurement

and instrument type, respectively, Pj

i , as follows:

i = E denotes irradiance data,

i = L denotes radiance data.

j = M denotes the microradiometer data, and

j = S denotes the spectrograph data.

To continue with the earlier example, the mean value of a

dark data acquisition sequence for the spectrograph data

of a hybridspectral radiance sensor is denoted μ

•S

L(λ). This

nomenclature also anticipates indices assigned for EMR

spectrograph data involving the position of the filter-wheel

assembly. Because they are not needed here, the information is suppressed for brevity. If a radiometer does not

have more than one sensing technology, the superscript

designation is not used (e.g., Sect. 7.2).

There are two other immediately useful parameters that

need to be included, and they both involve sources (or targets), which are identified with the i subscript:

i = F denotes measurements of an FEL lamp, and

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

i = P denotes measurements of a reflectance plaque.

The irradiance from an FEL lamp is designated EF and

the radiance from a plaque is designated LP . In general,

these designations are used with the standard symbology

associated with radiance (L) and irradiance (E) variables.

Note that Ei and Li are the diffuse irradiance and sky radiance, respectively, unless indicated within a generalized

discussion of parameter indices. For generalized parameter

discussions, the radiometric parameter of interest should

be indicated by the fraktur or euler typefaces (e.g., P or

P, respectively) to avoid confusion; the euler typeface is

reserved for hybridspectral sensors, so it is clear that two

different sensor technologies might have been used for the

observation of interest.

Some data products (e.g., direct-Sun irradiance) can

be derived more than one way with more than one sensor,

so accents are likely necessary to make it clear how a data

product was derived. This diversity is part of the power of

the OSPREy architecture, because it provides intrinsic QA

assessments, particularly for autonomous systems. The

level of detail needed to document data products is left

to the user, and the presentation here is designed to show

what a detailed approach might look like.

Ultimately, the variables of central interest with an OSPREy system are radiance (L) and irradiance (E), wherein

the subscript notation i = L and i = E, respectively, become redundant and can be ignored. This frees up the

subscript location for the standard symbology for radiance

and irradiance values, at which point, accents might no

longer be needed for proper distinction and can also be

ignored. For example, the total sea radiance from a hybridspectral sensor can be denoted Lj

T (λ), wherein LM

T (λ)

denotes the microradiometer data and LS

T (λ) denotes the

hyperspectral spectrograph data.

To characterize the performance of the OXE radiometer

and an EML sensor, several dark and light measurements

were performed and their mean (μ) and standard deviation

(σ) values are part of the data products. From these data,

the following three parameters were computed: the noise

equivalent signal, N; the signal noise, S; and the maximum

level of signal saturation, M:

Nj

i (λ) = σ

• j

i (λ)

γj

i (λ)

, (14)

Sj

i (λ) = σj

i (λ)

μj

i (λ)

, (15)

and

Mj

i (λ) = κj

i (λ) − μ

• j

i (λ)

γj

i (λ) . (16)

These three parameters are central to describing instrument performance for hybridspectral instruments (as first

introduced in Sect. 7.2).

8.9.3 OXE (Irradiance) Performance

For the specific case of the OXE sensor,

Nj

E(λ) = σ

• j

E(λ)

γj

E(λ)

, (17)

Sj

E(λ) = σj

E(λ)

μj

E(λ)

, (18)

and

Mj

E(λ) = κj

E(λ) − μ

• j

E(λ)

γj

E(λ) , (19)

where the j index designates the spectrograph or microradiometer channels (S and M, respectively).

The responsivity is calculated as

γj

E(λ) = μj

E(λ) − μ

• j

E(λ)

EF (λ) , (20)

where EF is the spectral irradiance of the FEL lamp at

50 cm distance.

Measurements of the microradiometer channels were

performed at a rate of 5 Hz, while an integration time of

5,000 ms was applied to the spectrograph measurements.

Light and dark measurements were executed over a 1 min

time period. These measurements were used to calculate

μj

E(λ) and μ

• j

E(λ). Data analysis confirmed that individual

measurements have a distribution that is approximately

gaussian.

The standard deviation of the mean of a normal distribution is equal to σ/√Ns, where Ns is the number of

samples. The mean NM

E (λ) is designated NME (λ) and is

computed for microradiometers based on a sampling at

5 Hz with a 60 s sampling period:

NM

E (λ) = NM

E (λ)

√5 · 60

= 5.77 × 10−2 NM

E (λ).

(21)

The corresponding formulation for the spectrograph using

an integration time of 5 s and 60 s sampling is:

NS

E(λ) = NS

E(λ)

60/5

= 2.89 × 10−1 NS

E(λ).

(22)

One advantage resulting from the conversion of Nj

E to

Nj

E is that noise specifications for the filter channels and

the spectrograph become comparable. Furthermore, the

latter is the more relevant quantity to describe the instrument performance, because calibrations applied to solar

measurements are typically based on a 60 s sampling of

the light and dark signals when measuring the calibration

source, as was done here.

74
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

The mean signal noise, S, for 60 s sampling is defined

in a similar way as follows:

Sj

E(λ) = Sj

E(λ)

√Ns

, (23)

where Ns is 300 for the microradiometer channels and 12

for the spectrograph.

Table 15 presents MM

E (λ), NME (λ), and SME (λ) values for the microradiometer channels of the OXE sensor.

The MM

E (λ) and NME (λ) values are considerably larger in

the UV compared to the VIS–SWIR wavelengths. This

is partly a consequence of the transmission of the interference filters used for each microradiometer channel. For

example, the peak transmission of the 380 nm filter is comparatively low, explaining the increased MM

E (λ) at this

wavelength. The SM

E (λ) values are less than 0.01% at all

wavelengths, indicating that signal noise in light data is not

a significant contributor to the overall uncertainty budget.

Table 15. Noise and saturation characteristics for

the microradiometer channels of the OXE sensor.

The EF , MM

E , and NME values are given in units of

μW cm−2 nm−1; the SM

E values are in percent. The

last row gives the scaling factor for the data in each

column.

λ [nm] EF MM

E NME SME

320 0.314 3.99 17.4 0.006

340 0.557 4.09 19.1 0.004

380 1.388 13.58 57.9 0.005

412 2.436 3.68 16.6 0.002

443 3.776 2.37 9.9 0.002

490 6.314 1.04 4.4 0.002

510 7.525 1.25 5.4 0.002

532 8.908 0.91 4.5 0.002

555 10.380 0.70 2.9 0.002

625 14.690 0.43 2.0 0.002

665 16.870 0.31 1.3 0.002

683 17.760 0.45 2.1 0.002

710 18.960 0.40 1.7 0.002

780 21.390 0.29 1.3 0.002

875 22.950 0.58 2.5 0.002

1,020 22.600 0.22 2.8 0.002

1,245 18.870 0.07 6.5 0.002

1,640 11.570 0.03 2.2 0.002

Scaling 1 ×106 ×10−6 1

Figure 54 contrasts the noise and saturation characteristics of the microradiometers to those of the spectrograph

and compares these quantities with a spectrum of global

solar irradiance modeled for θs = 40◦, as well as the spectral irradiance of an FEL lamp at a distance of 50 cm from

the sensor. The irradiance of both sources is more than

four orders of magnitude larger than NM

E (λ), which indicates signal noise is not a significant factor in limiting the

accuracy of the fixed wavelength measurements. The irradiance of both sources is also well below the saturation

level, MM

E (λ).

A A

A

AAAAAAAAA A

AA

AAA

A A A AAAAAAAAA A

AA

AAA

10-7

10-2

103

108

300 800 1300 1800 

Irradiance [W cm-2 nm-1]

Wavelength [nm]

a

b

d c

e

f

Fig. 54. The noise and saturation characteristics

of microradiometer channels and the spectrograph

of the OXE sensor: a) MM

E (λ), b) MSE(λ) for ti =

5,000 ms, c) global Sun irradiance, d) EF (λ), e)

NS

E(λ), and f) NME (λ).

The noise and saturation characteristics of the spectrograph are notably inferior to those of the microradiometer

channels. For example, at 320 nm, the lamp irradiance is

only 1.5 orders of magnitude larger than NS

E(λ), indicating that signal noise limits the precision of lamp transfers

using the spectrograph at this wavelength. The saturation irradiance MS

E(λ) shown in Fig. 54 was calculated for

an integration time of 5,000 ms and is barely larger than

the irradiance of the solar spectrum. It is therefore possible that the spectrograph might saturate under certain

circumstances (e.g., when reflections off of clouds lead to

an enhancement of surface irradiance beyond the clear-sky

limit). In these cases, saturation can be avoided by reducing the integration time. The system operation software

has a build-in feature to automatically optimize the integration time to the radiation level of the source.

8.9.4 EML (Radiance) Performance

Noise and saturation characteristics of the EML sensor

were determined in a similar way as those for the OXE

instrument. The main difference is that the EML sensor

was pointed to the center of a reflectance plaque, which was

illuminated by a calibrated FEL lamp positioned 287.1 cm

away from the center of the plaque. The radiance of the

plaque was calculated based on the BRDF of the plaque.

The Sj

L(λ) and MjL(λ) terms for the EML sensor follow

75
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

from (15) and (16), noting that the radiance responsivity

becomes

γj

L(λ) = μj

L(λ) − μ

• j

L(λ)

LP (λ) , (24)

where LP (λ) is the spectral radiance of the plaque. Following the practices established for the OXE performance

analysis, mean quantities Nj

L(λ) and SjL(λ) were calculated

by scaling with 1/

√Ns. The scaling factors for irradiance

and radiance are identical, because both measurements use

sampling periods of 60 s.

Table 16 presents MM

L (λ), NML (λ), and SML (λ) for the

EML channels. The wavelength dependence of the three

quantities is very similar to those shown in Table 15 for

irradiance. The main difference of the OXE and EML sensors is the irradiance collector used by the former. The

similar wavelength dependence of the two devices confirms

that the collector (specifically the diffuser material) is spectrally flat. The SM

L (λ) values are considerably larger than

SM

E (λ) values, particularly in the UV. This is a consequence of the field-of-view limiting fore-optics of the radiance sensor, which reduces its responsivity considerably

(Chap. 5).

Table 16. Noise and saturation characteristics

for the microradiometer channels of the EML sensor

following the format for Table 15. The units for the

LP , MM

L , and NML values are μW cm−2 nm−1 sr−1;

the SM

L values are in percent. The last row gives

the scaling factor for the data in each column.

λ [nm] LP MM

L NML SML

340 0.005 2.19 9.8 0.165

380 0.014 9.34 40.1 0.310

395 0.018 2.47 11.5 0.062

412 0.024 2.87 13.7 0.052

443 0.037 1.82 7.8 0.024

490 0.061 0.99 4.5 0.008

510 0.073 1.21 5.7 0.008

532 0.086 1.14 5.9 0.007

555 0.100 0.86 3.6 0.006

589 0.121 0.79 3.3 0.005

625 0.142 0.57 2.3 0.005

665 0.163 0.44 2.4 0.005

683 0.171 0.59 2.6 0.005

710 0.183 0.54 2.5 0.005

780 0.206 0.43 1.8 0.004

875 0.221 0.91 4.2 0.004

1,020 0.214 0.34 4.2 0.005

1,245 0.179 0.10 6.2 0.005

1,640 0.109 0.06 4.1 0.005

Scaling 1 ×106 ×10−6 1

Figure 55 contrasts the noise and saturation characteristics of the microradiometer channels to those of the

spectrograph and compares these quantities with the socalled pseudo-radiance of the direct Sun, the sky radiance

Li(λ), the water-leaving radiance LW (λ), and the radiance

of the calibration plaque LP (λ).

E E

E E EEEEEE EEEE EEE

E

E

G G G GGGGGG G

GGGG

GGGG

G

Å Å Å Å ÅÅÅÅÅÅ ÅÅÅÅ

ÅÅÅ

Å

Å

10-7

10-2

103

108

300 800 1300 1800

Radiance [

W cm-2 nm-1 sr-1]

Wavelength [nm]

a

b

c

d

e

f

g

h

Fig. 55. The noise and saturation characteristics

of the spectrograph and microradiometer channels

for the OXE radiometer: a) MM

L (λ); b) MSL(λ) for

ti = 100 ms; c) pseudo-Sun radiance; d) Li(λ) for

θs = 40◦ and no aerosols; e) LW (λ) for θs = 40◦;

f) LP (λ); g) NS

L(λ); and h) NML (λ).

Some of the Fig. 55 data sets require further explanation. The sky radiance data were calculated for θs = 40◦,

a viewing zenith angle of 40◦, and an azimuth angle 90◦

away from the solar azimuth (i.e., perpendicular to the Sun

plane). The direct-Sun radiance was calculated by scaling

the sky radiance by the factor En(λ)/Ei(λ), where En(λ)

is the solar direct irradiance at the surface of Earth for

overhead Sun, and Ei(λ) is the integral of Li(λ) over the

FVA of 2.5◦ of the EML sensor. The factor En(λ)/Ei(λ)

is equal to the expected ratio of signals of the sensor when

pointing at the Sun and the sky. The pseudo-Sun radiance is so designated, because the radiance across the FVA

when pointing at the Sun is not uniform. Consequently,

this pseudo-radiance can be interpreted as a uniform radiance across the FVA that leads to the same signal as that

produced by the direct Sun. The water-leaving radiance is

computed identically to that used in Fig. 15.

The c–f radiances in Fig. 55 are more than 2.5 orders

of magnitude larger than NM

L (λ). Calibrating the filter

channels with a plaque located 287.1 cm away from an

FEL lamp with sufficient precision is therefore possible.

In contrast, NS

L(λ) is less than 2.0 orders of magnitude

smaller than the radiance of the plaque for wavelengths below 400 nm. The calibration accuracy of the spectrograph

is therefore compromised, and it may be necessary to move

the plaque closer to the lamp for calibrating this wavelength range. Measuring water-leaving radiance with the

76
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

spectrograph for wavelengths above 600 nm also leads to

significant uncertainties, whereas accurate measurements

with the microradiometer channels can be performed at

wavelengths beyond 700 nm. Measurements of sky radiance are not compromised by signal noise for either the

filter channels or the spectrograph.

Figure 55 also indicates that pointing the instrument at

the Sun does not saturate the microradiometer channels.

Measurements of the spectrograph do saturate, so it is necessary to attenuate the signal. The Fig. 55b data indicates

the saturation level of the spectrograph when the signal is

attenuated by an ND filter of optical density 3.0 (attenuation by a factor of 1,000), and, in addition, the integration

time is reduced to 100 ms. The filter wheel integral to the

EML sensor includes two ND filters with an optical density

of 1.5 and 3.0, which are rotated in front of the spectrograph fiber optics whenever direct-Sun measurements are

performed.

8.10 Remote Sensing Applications

The marine biosphere is composed of a complex diversity of physical, chemical, biological, and ecological processes. Each process is an integral part of larger planetary biogeochemical cycles (e.g., carbon, nitrogen, phosphorous, silica, iron, etc.). These planetary cycles are coupled to, and influence climate through, feedback mechanisms. Despite significant research accomplishments from

SeaWiFS and the two MODIS instruments onboard the

Aqua and Terra spacecrafts, the oceanic processes, planetary cycles, and feedback mechanisms are insufficiently

understood.

The National Research Council (NRC) Decadal Survey (NDS) emphasized the importance of satellite data

for investigating oceanic processes and recommended three

spaceborne observing systems designed to contribute to the

acquisition of data regarding the distribution of marine

biosphere properties (NRC 2007):

• Geostationary Coastal and Air Pollution Events

(GEO-CAPE),

• Hyperspectral Infrared Imager (HyspIRI), and

• Aerosol-Cloud-Ecosystems (ACE).

The NASA Climate-Centric Architecture (CCA) report

(NASA 2010) added the following:

• The National Polar Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP)

mission, and

• The recently announced Pre-Aerosol, Clouds, and

Ocean Ecosystem (PACE) mission.

Because an OSPREy system can produce multiple (oceanic, terrestrial, and atmospheric) data products, the total number of satellite missions that can be supported—

and made consistent—is necessarily larger. Restricting

the list to example domestic missions, the following can

be added to the above: Aura, Aqua, Terra, and CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO).

The NDS advocates that the “validation of geophysical

products inferred from satellite remote sensing is essential.” Furthermore, for the development of CDRs, “validation should be an almost continuous component, providing an independent check on the performance of spacebased sensors and processing algorithms.” The CCA places

special emphasis on global data sets created from multiple satellite platforms and notes: “it is incumbent on the

providers of satellite data to take particular care that the

consistency between related data sets is well documented.”

For the inevitable need to create comprehensive data products from diverse organizations and instruments, the CCA

requires “calibration and validation throughout all stages

of the process.”

Both the NDS and CCA promote the use of ground networks for calibration and validation activities. The NDS

recommends “the networks should also be expanded in geographic extent and the types of measurements made.”

Specifically, “the panel calls for the development of surfacebased networks focused on climate observations and the development of the associated climate records as set forth in

climate-stewardship principles.” The compact size of even

the most sophisticated OSPREy (maximum) system, and

the availability of lower-cost configurations, makes an OSPREy network easier to implement than a network of traditional in-water moorings (which are typically very large

and more expensive to purchase and maintain). More importantly, an OSPREy system can contribute to both oceanic and atmospheric (or terrestrial and atmospheric) climate records simultaneously.

The CCA recommends expanding ground networks, so

they can be used “in validation activities required to establish inter-consistency between data from NASA and nonNASA satellites.” Expanding the geographic extent of networks implies international partnerships, as does including foreign missions. The NDS recommends international

partnering, because it, “spreads the cost burden, mitigates

risks of gaps in particular data streams, encourages technical innovation by broadening the engineering expertise

base, and increases the number of science users.”

This philosophy of shared international participation

is at the core of the OSPREy activity, which establishes

a COTS software and hardware solution that is available

to the worldwide scientific community. Indeed, the first

exploitation of microradiometers, the recently introduced

C-OPS in-water instrumentation (Morrow et al. 2010b),

followed the same philosophy and is being used by US,

French, Canadian, Polish, Chinese, and South African scientists, to name a few.

Examples of current and next-generation missions that

OSPREy was designed to support, including the international Environmental Satellite (ENVISAT) launched by

77
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Table 17. The applicability of OSPREy data products (derived from an operational system configuration) to representative

domestic and international satellites that are currently operational or that are planned next-generation missions. (The row

numbering is for referencing convenience.)

OSPREy Data Product Aura Aqua

Terra

ENVISATCALIPSOPARASOL NPP PACE GEOCAPEHyspIRI ACE

1 Total ozone column × × 2 Aerosol optical depth (AOD) × × × × × × × × 3 Aerosol absorption × × × × × 4 AOD for fine and coarse mode aerosols × × 5 Aerosol size and effective radius × × × × × 6 Aerosol phase function × × × 7 Almucantar and principal plane scans × × 8 Refractive index (real and imaginary) × × 9 Cloud optical thickness × × 10 Precipitable water vapor (PWV) × × × × × × 11 Global and diffuse spectral irradiance × × 12 Aerosol scattering of spectral flux × × 13 Radiative forcing induced by aerosols × × 14 Degree of polarization, Stokes vector × × 15 LW , Rrs, [TChl a], and turbidity × × × × × × × 16 Suspended or dissolved matter × × × × × × × 17 Terrestrial surface reflectance × × × × × × ×

Notes: 2 With the  ̊Angstr ̈om coefficients. 3 The single scattering albedo. 6 And the asymmetry parameter. 7 Plus full scans at greater angular resolution. 15 Plus normalized and exact forms of LW .

the European Space Agency (ESA), are presented in Table 17. The table summarizes a representative diversity of

oceanic, atmospheric, and terrestrial data products that a

minimum OSPREy system (Fig. 44b) can provide based

on the sensor capabilities of each mission:

Total ozone column is derived from spectrograph

measurements in the UV-B. The standard retrieval

method uses direct-Sun measurements and is the

method of choice for processing observations of Dobson and Brewer spectrophotometers.

All aerosol products can be retrieved with a single

radiance sensor, either by pointing the device at the

Sun or by performing scans in the almucantar and

principal plane directions.

Cloud optical depth is determined from the attenuation of global irradiance by clouds.

Precipitable water is determined from spectrograph

measurements between 900–1,000 nm.

Polarimetric data are provided by the spectrograph

internal to radiance sensors.

For comparison with satellite measurements, LW is

transformed to normalized forms, e.g., the radiance

that would exit the ocean in the absence of the atmosphere and with the Sun at zenith and denoted



LW



N.

The requirements for measuring terrestrial surface

reflectance are similar to those for measuring LW

and its normalized forms.

Note, in particular, the comprehensive number of data

products associated with the PACE and ACE joint oceanic and atmospheric missions.

The CCA also advocates for “opportunities for developing countries to participate more fully with NASA.” In

the not-too-distant past, many aspects of calibration and

validation were very expensive customized solutions that

were not commercially available, which prevented replication by a partner. For example, the high cost and lack of

commercialization of the MOBY instrumentation, which

was the main vicarious calibration source for SeaWiFS and

MODIS (Clark et al. 1997), restricted its use to a single domestic site (off Lanai, Hawaii). The intrinsic vulnerability

of one site results in data gaps, even with multiple copies

of the observing system. More importantly, the utility of

the data is compromised by unavoidable seasonal dependencies (e.g., sun glint, which is a recurring problem for

sensors that do not tilt, like MODIS), as well as geometric limitations that restrict the kinds of on-orbit problems

that can be addressed with the sea-truth observations (e.g.,

trying to understand and correct an inadequate prelaunch

polarization characterization).

The CCA supports climate measurements and the expansion of “validation opportunities that leverage NASA

investments and lower the development risk of key components vital for the instruments needed for climate measurements.” The OSPREy approach presented here embraces

this philosophy, as well as the need for international partnerships. To provide access for all interested partners, all

of the sensor suites are commercially available. In addition,

all major subsystems are COTS technologies (e.g., the sun

78
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

tracker), so the entire measurement suite is subjected to

market forces to ensure cost competitiveness. Relying on

COTS technology is not a detraction. Bailey et al. (2008)

used data from COTS profilers (Werdell and Bailey 2005)

and a buoy with COTS sensors (Antoine et al. 2008) to

show satellite gains from COTS instruments are rather indistinguishable from MOBY.

8.11 Discussion and Conclusions

The satellite missions discussed above and summarized

in Table 17 include both hyperspectral and fixed wavelength sensors. The latter includes individual spaceborne

instruments with an arguably sufficient number of wavelengths to qualify as hyperspectral, and the summation of

all such sensors certainly comprise a hyperspectral superset. This places a unique burden on the technologies used

in the field as part of a comprehensive response to the required calibration and validation exercises to support these

missions. Although individual field units could be deployed

for each mission, such an approach increases the final uncertainty budget, because of sensor-to-sensor differences,

particularly if the underlying technologies or radiometric

scales are considerably different. A single sensor system

that is part of a network of intercalibrated like sensors all

traceable to the same radiometric scale can support the calibration and validation of multiple satellites while offering

the unique opportunity to significantly reduce satellite-tosatellite uncertainties.

Also summarized in Table 17 is how an OSPREy system can produce multiple (oceanic, atmospheric, and terrestrial) data products and necessarily across a wide spectral domain, so the total number of satellite missions that

can be supported spans domestic and international missions. The OSPREy approach fosters international partnerships, providing access to high-quality observations to

all interested partners. As many of the subsystems as

possible are COTS technologies (e.g., the sun tracker, the

spectrographs, and the video camera), and the entire measurement suite is subjected to market forces to ensure cost

competitiveness.

OSPREy systems are configured with hybridspectral

radiometers combining a cluster of fixed wavelength microradiometers with a spectrograph. The spectrograph provides hyperspectral resolution over a subset of the complete spectral range, while the microradiometers provide

a larger dynamic range in responsivity, higher sampling

speeds, better sensitivity, and sampling across the entire

OSPREy spectral range (305–1,640 nm). The two sensor

technologies supplement each other. For example, spectrograph data can be used to detect potential degradation of the interference filters used by the microradiometer

channels while the microradiometers can help to correct

dark-current drifts and nonlinearity in spectrograph measurements, while greatly extending the dynamic range.

The capability of radiance sensors is further enhanced

by a nine-position filter wheel and integrated camera. In

the standard configuration, the filter wheel permits hyperspectral polarimetric measurements, direct-Sun viewing,

stray-light correction, dark current measurements, and a

home position. The video camera is used for locating the

Sun and Moon, as well as verifying the condition of all targets, i.e., cloud-free solar and lunar disks, cloud presence

in sky data, and sea surface debris or foam detection (although an irradiance sensor can confirm cloud-free solar

and lunar disks). The components of each radiance and

irradiance sensor type are integrated in a common housing that is environmentally sealed, nitrogen purged, and

temperature controlled.

OSPREy field sensors are part of the EMR product

line, and the OSPREy laboratory sensors are from the

OXR instrument class. A fully supported deployment of

the OSPREy technology involves radiance and irradiance

sensors from both instrument classes being used in the field

and in a calibration laboratory. An important aspect of

EMR sensors is their scalability, which is derived directly

from the modularity of microradiometers, but the principal scalability comes from the SHALLO design philosophy

established for all instrument classes built with microradiometers (Morrow et al. 2010c). The SHALLO architecture codifies this philosophy by establishing a sequence of

modular capabilities and a stepwise upgrade pathway for

the instrument classes built with microradiometers. This

scalability can be reversed to create a simpler system if

resources or science objectives no longer require or can

support, respectively, a more sophisticated system.

Five configurations are available for OSPREy systems

(Fig. 44): the starter system establishes a significantly

more advanced replacement for SeaPRISM units; the minimum system features radiance and irradiance, with a shadowband capability for the latter; the spectral system optimizes irradiance coverage from 290–1,670 nm; the operational system with dual radiance and irradiance sensors

provides a compact, fully redundant, sampling capability;

and the maximum system features two instrument triads

for maximum spectral coverage, measurement redundancy,

and data products. The five systems establish a hierarchy

in the level of accomplishment that can be achieved for

calibration and validation activities, both in terms of the

accuracy and diversity of the resulting data products.

The upgradability of the OSPREy architecture has already been exploited as part of the development activity.

The linear glass polarizing filters from Edmund Scientific

(Rochester, New York) used to establish and test the filterwheel assembly (Fig. 49) were inexpensive, but spectrally

limited to 400–700 nm. Properly orienting the round filters

in the filter holder was technically challenging. To provide

polarimetry over the spectral range supported by the spectrograph, i.e., 300-1,150 nm an alternative technology and

source for polarizers was needed.

Broadband polarizers (250–4,000 nm) using nanowire

technology have recently become available. A set of Ultra Broadband Nanowire UBB01A polarizers from Moxtek (North Orem, Utah) were procured and the filter wheel

79
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Table 18. The applicability and quality of OSPREy data products to the five SHALLO system configurations (Fig. 44)

using the presentation established for Table 17. The quality is presented on a relative five-star scale, with five stars

being the highest quality and one star the lowest. Data products that do not achieve a five-star rating for a maximum

system configuration have a design component or compromise that requires more comprehensive testing than could be

achieved with the field commissioning part of the OSRPEy development activity. In addition, distinguishing between

four- and five-star systems remains to be completely determined, because the outcome of the cosine correction of the

EME radiometer was better than originally anticipated. The line numbering is for referencing purposes. Note that

the latter does not mean the device is inadequate for the measurement task—it simply means there are higher quality

alternatives (which may or may not be necessary for consideration). A blank entry indicates the data product cannot

be produced directly from the observations, although it might be modeled using one or more available parameters.

OSPREy System Configuration

Data Product Starter Minimum Spectral Operational Maximum

1 Total ozone column 

2 Aerosol optical depth 

3 Aerosol absorption 

4 AOD for fine and coarse mode aerosols 

5 Aerosol size and effective radius 

6 Aerosol phase function 

7 Almucantar and principal plane scans 

8 Refractive index (both  and  parts) 

9 Cloud optical thickness 

10 Precipitable water vapor 

11 Global and diffuse spectral irradiance 

12 Aerosol scattering of spectral flux 

13 Radiative forcing induced by aerosols 

14 Degree of polarization, Stokes vector 

15 LW , Rrs, [TChl a], and turbidity 

16 Suspended or dissolved matter 

17 Terrestrial surface reflectance 

modified to accommodate these components (Fig. 56). The

comparatively large size (0.6×0.6 cm2) and delicacy of the

coatings presented a number of technical challenges. For

example, the filters are so delicate, they cannot be touched

or altered (e.g., cut to size) during installation. Orienting

the filters in the filter holder was not difficult, because they

have an orientation aligned to a square edge.

Cut-on

Filter

Home

90° Pol.

Filter

45° Pol.

Filter

0° Pol.

Filter Opaque

ND 3.0

ND 1.5

Open

Fig. 56. The modified EML sensor filter wheel upgraded with Moxtek polarizers (pink) and following

the presentation established in Fig. 49.

Table 18 provides an overview of the applicability and

quality of OSPREy data products to the five SHALLO system configurations (Fig. 44). Most data products can be

retrieved from measurements of a radiance sensor mounted

on a pointing unit (the starter system). The addition of an

irradiance sensor with the shadowband accessory (a minimum system) provides redundancy, reduced uncertainty,

and the ability to measure additional data products such

as cloud optical depth, and global and diffuse irradiance.

The following are relevant with respect to the perspective

of the data products and sensor configurations:

• Deriving total ozone column from direct-Sun measurements is only possible if the Sun is not obscured

by clouds. When clouds are present, total ozone can

be calculated from measurements of global irradiance, which can be performed with the minimum

system.

• Although aerosol products only require a single radiance sensor, the addition of an irradiance sensor

system provides redundancy and also offers an independent method to derive aerosol absorption properties. For example, the single scattering albedo can

be estimated from the ratio of diffuse to global irradiance. The spectral and maximum systems allow

80
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

more accurate determinations of aerosol properties

in the SWIR domain.

• Cloud optical depth requires at least one irradiance

sensor, and in practice, is estimated by comparing

measurements of global irradiance with results of

a radiative transfer model using different optical

depth values as model input parameters.

• Measurements of precipitable water cannot be made

with irradiance sensors, because the spectrograph

internal to these units has a terminal wavelength of

785 nm.

• Measurements with the three polarizers that are

mounted in the filter wheel in front of the spectrograph fiber optics at orientations of 0◦, 45◦, and

90◦ can only be performed sequentially (unless the

operational system with a second radiance sensor is

used).

• The requirements for measuring terrestrial and sea

surface reflectance are similar, resulting in an increase in data quality progressing from the starter

system to the maximum system.

Because illumination conditions can change during the observation period for a radiance measurement, contemporaneous observations with an irradiance sensor can help to

characterize these changes. A minimum system is, therefore, superior compared to a starter system even though

irradiance sensors do not provide polarimetric measurements.

In general, the confidence in a measurement result can

be improved if the same data product can be achieved

with different methodologies. For example, AOD can either be determined from measurements of the radiance

sensor pointing at the Sun or from data of direct solar

irradiance that have been derived from global and diffuse

measurements from an irradiance sensor. If results of the

two approaches agree, confidence is significantly enhanced

because it is unlikely that the same systematic error is affecting both methods equally.

The uncertainty of most data products can be reduced

further as the sensor suite is expanded, resulting in the

spectral, operational and maximum systems. Such a progression adds redundancy, the ability to measure different

quantities simultaneously, and the use of irradiance collectors optimized for the spectral range of the measurement

(spectral and maximum systems). Although applicable to

almost all data products, the benefits in the ability to expand the sensor suite is well represented in the oceanic

measurement requirements:

1. LW and related data products can be measured

with a starter system in a similar way as with a

SeaPRISM instrument (except the individual channels are acquired simultaneously with OSPREy).

Without an irradiance sensor, the normalization factor to convert LW to 

LW



N must be estimated

from measurements of direct solar irradiance, which

is subject to uncertainty.

2. The irradiance sensor that is part of the minimum

system allows the normalization factor to be measured directly, resulting in a smaller uncertainty of



LW



N. The irradiance sensor is also required for

accurate Rrs values.

3. As in the case of atmospheric data products discussed above, the spectral system can provide more

accurate measurements at SWIR wavelengths.

4. The use of two dyads in the operational system decreases uncertainties in measuring LW ,



LW



N, and

Rrs further, because LT and Li can be measured simultaneously.

5. The use of two triads in the maximum system minimizes uncertainties with more accurate measurements at SWIR wavelengths.

Although the progression to more sophisticated systems provides increasingly powerful capabilities, the level

of accomplishment with a solitary EML sensor is unprecedented, because of the hybridspectral architecture. The

hyperspectral and fixed-wavelength observations of solar

and lunar irradiances during clear-sky conditions with an

EML sensor is presented in Fig. 57. The data were acquired at different zenith angles resulting in an air mass

of about one for the solar data and approximately five for

the lunar data. The two plots include annotations of atmospheric absorption bands from oxygen (O2) and water

(H2O), as well as a calcium (Ca) band in the solar photosphere. The broad reduction in the UV domain from

ozone (O3) is noted on the figure, and the strong effect

of Rayleigh reduction in the lunar observations from the

longer atmospheric path length (large zenith angle and corresponding air mass) is also noted.

X

X

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XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

X

X

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X

X

X

X

XX

X

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XX

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XXXXXX

10-6

10-5

10-4

10-4

250 650 1050 1650

Lunar Irradiance

Wavelength [nm]

1250

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101

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102

Solar Irradiance

4 x

2 x

H2O

O3

Ultraviolet Visible Near-Infrared to Short Wave Infrared

H2O

O2

H2O

O2

Rayleigh

Solar Zenith

Angle = 11°

Air Mass ~ 1

Lunar Zenith

Angle = 79°

Air Mass ~ 5

19-channel

microradiometers

256-pixel

spectrograph

Ca (solar

photosphere)

E

E

E

EEEEEE

EEEEE E E

E

E

E

E

E

E

E

E

EEEEEEEEE E E

E E

E

Fig. 57. EML irradiance observations (in units of

μW cm−2 nm−1) of the Sun and Moon during clearsky conditions and significantly different zenith angles. Note there is a discontinuity in both the xand y-axes (denoted by the zigzags).

81
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

The results presented in Fig. 57 indicate the following

with respect to the performance of EML sensors: a) the

spectral dynamic range of the sensors is excellent; b) the

detail (absorption lines) and consistency in the data suggest good intercalibration (the calibrations are presently

based on a NIST FASCAL traceability with the OSPREy

lamp library); c) the signal dynamic range (about eight

decades) indicates the Sun and the Moon can be used to

monitor sensor performance during clear-sky conditions;

and d) the large lunar zenith angle data suggest Langley

plots from lunar data are possible.

The performance of an EME sensor is presented in Fig.

58, wherein the recorded solar observations (red) are compared to a radiative transfer model (gray) based on the

conditions encountered during the field measurements. In

this case, the spectrograph data have been interpolated to

higher resolution to better match the detail of the model.

The agreement between the spectrograph and the microradiometers is on average to within 2.5%, and the agreement of both with respect to the model is similar over the

300–785 nm spectral range. Although at different scales,

a comparison of the solar observations in Figs. 57 and 58

reveal the strength of the dyad (dual radiance and irradiance sensors) measurement suite, because one sensor can

be compared to the other. The chance that two sensors

would malfunction at exactly the same time or exactly in

the same spectral domain is negligible, so aberrant performance is quantifiable, especially under circumstances

wherein modeling can also be included in the analysis (e.g.,

solar observations).

0

50

100

150

300 550 800 1650

Wavelength [nm]

18-channel

microradiometers

J

J

J

J

J

JJJ

J

J J

JJ

J

J

J

J

J

256-pixel

spectrograph

Radiative transfer

model

Fig. 58. Solar EME measurements (in units of

μW cm−2 nm−1) during clear-sky conditions (recalling that EME sensors have 18 microradiometers,

because one is removed for the spectrograph fiber).

Note there is a discontinuity in the x-axis after the

spectrograph data ends (denoted by the zigzag).

82
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Acknowledgments

Conceived in 2004, the enabling technology for building new

sensors for the OSPREy activity is the microradiometer—a

small, integrated photodetector, preamplifier high resolution

(24 bits) ADC, microprocessor, and an addressable digital port,

all in one small circuit assembly. The microradiometer was developed as a joint activity between BSI and NASA under an

SBIR program entitled “In Situ Radiometers: Smaller, Faster,

and Scalable to Hyperspectral.” The SBIR Phase I contract

NNG05CA40C (2005) resulted in a functioning microradiometer prototype (not required), which served to illustrate the potential for success of the project. The SBIR Phase II contract

NNG06CA03C (2005–2007) moved the prototype instrument

through a complete development cycle, which concluded with

the release of a field-tested device. It was also completed on

time and on budget.

Having proven the design in 2007, the first true microradiometers were successfully machine-manufactured in one lot of quantity 100. NASA contract NNG08HZ17C (2008) for OSPREy is

on schedule and under budget to build the prototype instruments and begin the development of an expandable radiometer system for deployment on above-water platforms. An ACE

project office augmentation (2011) added a nine-position filterwheel assembly in line with the spectrograph fiber optics and a

digital camera to EML sensors.

The preparation of the manuscript and its final level of completeness benefitted significantly from the technical editing and

computer graphics expertise of Elaine Firestone, whose attentiveness to detail, and her good cheer, are greatly appreciated.

Appendices

The appendices provide additional information on various

aspects of the OSPREy activity. The inclusion of the appendices is to anticipate the need for clarification regarding some

technical details that are not summarized in the individual

chapters and to provide a broader perspective of the deployment of the sensors as it is presently envisioned.

A. Above- and In-Water Methods

B. Vicarious Calibration Protocols

C. The BSI Calibration Facility

D. Ancillary Measurements

E. The BioSHADE Accessory

F. Platform Power and Data Telemetry

G. Extended Test Deployments

H. Operational Deployment

I. Absolute Calibration

J. Uncertainty Analysis

K. Platform-Perturbation Mapping

L. The SABSOON Towers

M. BSI Quality Assurance Experience

The last appendix provides an example of a quality assurance

program for a network with similar objectives as the OSPREy

activity.

Appendix A:

Above- and In-Water Methods

The two methodologies for estimating LW (λ) require either

above- or in-water sampling. Above-water methods use direct

observations of the radiance emanating from the sea surface,

which after correction for glint contamination, yields an estimate of LW (λ). In-water techniques, however, use vertical

profiles of upwelled radiance, Lu(z, λ), where z is the vertical

coordinate, to establish a near-surface extrapolation interval

from which LW (λ) is estimated after propagation through the

sea surface.

Although above-water data are part of global bio-optical

databases, the majority are in-water data (O’Reilly et al. 2000).

Part of this disparity is because in-water measurements have a

longer history, and part of it is the consequence of the frequently poor agreement between the two methods (Rhea and

Davis 1997, Fougnie et al. 1999, Toole et al. 2000, and Hooker et

al. 2002a), so in-water methods have dominated. In principle,

there are no a priori reasons to select water-leaving radiances

from an above-water method, LˆW (λ), over an in-water method,

L ̃W (λ), when sampling the optically simplistic environment required for vicarious calibration exercises. Furthermore, satellite

sensors themselves are above-water instruments.

Most in-water methods for estimating LW (λ) are based on

the Smith and Baker (1984) technique for analyzing Lu(z, λ)

profiles. From a near-surface portion of the profile (or all available depths from a buoy), the attenuation coefficient is computed as the local slope of ln [Lu(z, λ)], and is used to extrapolate the upward radiance through the upper layer to determine

Lu(0-, λ) at null depth z = 0-. The water-leaving radiance is

obtained using

L ̃W (λ)=0.54Lu(0-, λ), (A1)

where the constant 0.54 accurately accounts for the partial reflection and transmission of the upwelled radiance through the

sea surface (Mobley 1999). The formulation in (A1) assumes

there are no artificial perturbations to the Lu data (a similar assumption is made for an above-water method), and if

they are (unavoidably) present, corrections are required. Routine corrections include instrument self shading (Gordon and

Ding 1982, and Zibordi and Ferrari 1995) and platform shading (Doyle and Zibordi 2002, and Zibordi et al. 2002a).

Despite the advantages of time series measurements, buoys

have some important deficiencies: a) the sensors are usually

mounted close to the main body and can be negatively influenced by the buoy (mounting the sensors on standoffs can reduce this effect, but not completely eliminate it); b) to minimize

the complexity and vulnerability of moving parts, multiple light

sensors are deployed at a small number of fixed depths, so there

is a spatial resolution problem; and c) because the sensors are

mounted relatively close to the surface, they can be subjected

to significant biofouling, surface effects, and damage, which can

be being difficult to detect without divers.

Sampling problems are primarily engineering challenges, and

if properly solved, good data can be collected. Examples of radiometric buoys that were successfully deployed are as follows:

The Marine Optical Buoy (MOBY), developed in the US

and funded mostly by NASA in support of the SeaWiFS

and MODIS satellite missions (Clark et al. 1997);

The UK Plymouth Marine Bio-optical Data Buoy (PlyMBODy), developed by the Plymouth Marine Laboratory

(PML) as a part of the SeaWiFS Exploitation Initiative

(Pinkerton and Aiken 1999); and

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

The French Bou ́ee pour l’Acquisition de S ́eries Optiques

a Long Terme ` (BOUSSOLE), developed by the Laboratoire d’Oc ́eanographie de Villefranche (LOV) primarily

to support the Medium Resolution Imaging Spectrometer

(MERIS) mission (Antoine et al. 2006 and 2008).

Although these buoy designs differ—the last two were designed

with COTS radiometers—they are sufficiently similar that any

one can be used to summarize the basic aspects of an in-water

mooring. MOBY is selected, because it is the most sophisticated and has the longest deployment record (since July 1997).

MOBY is instrumented with a solar irradiance reference

plus identical pairs of downward irradiance (Ed) and upwelling

radiance (Lu) sensors located at three shallow depths (2, 5, and

9 m). The light sensors are mounted on arms so the perturbative effects of the buoy superstructure are reduced. All of the

light sensors collect data from 380–900 nm using custom-built

hyperspectral sensors with high spectral resolution. Orientation sensors allow the exclusion of data degraded by excessive

tilts or direct shading from the buoy superstructure. Biofouling is mitigated with an approximately monthly interval of diver

visits to keep the optical apertures clean.

The biggest difference between MOBY and other buoy designs is the use of custom-built hyperspectral sensors. This

means that MOBY data can be spectrally combined to match

any remote sensor in the applicable spectral range. In addition,

if the spectral response functions of the satellite channels are

known, the summation process can include this information to

provide a properly weighted in situ observation. The capabilities of an instrument system like MOBY is well established

(McClain et al. 2004); the only question about such an enterprise is whether or not such a costly undertaking is required.

The use of offshore towers as an alternative to moored buoys

for calibration and validation activities was investigated (Zibordi et al. 2002a). An in-water system was deployed close to a

tower, but anchored with cables strung between the sea bottom

and a protruding deck to provide a stable measurement geometry. The difficulty with this arrangement is the proximity of

the tower can produce significant perturbations to the in-water

light field under certain illumination conditions and solar geometries. The stability of the platform, however, permits an

exact identification of the solar geometry needed to accurately

remove shading effects (Zibordi et al. 1999).

Above-water methods are based on pointing a radiance sensor at the sea (at a prescribed nadir viewing angle, θ, of 40 or

45◦), so the total radiance at the surface, LT (λ), is measured.

The acquisition does not disturb the sea surface, so the net effect of the vertical complexity of the water column is precisely

captured. Unwanted radiance contributions must be avoided,

so all methods avoid the glint in the sun plane. This is accomplished by pointing the sensor an angle φ away from the Sun

(90◦ or 135◦), while avoiding any platform perturbations.

The remaining difficulty in above-water methods is to remove the reflected sky light from the LT measurement, and it

is this procedure that distinguishes above-water methods from

one another. For the method presented here, sky glint is removed by measuring the sky radiance, Li(λ), in the same plane

as LT (λ), and at a zenith angle θ equivalent to θ (θ = 180−θ).

These two measurements can then be used to derive the waterleaving radiance (omitting the angles for brevity):

LˆS95

W (λ) = LT (λ) − ρ Li(λ) (A2)

where the S95 notation denotes the SeaWiFS 1995 revision of

the Ocean Optics Protocols (Mueller and Austin 1995), and ρ

is the surface reflectance, which is small (about 3%, so Li is

the important correction term). If the interface was level, ρ

would be the Fresnel reflectance, but the sea surface is usually

wind roughened, so ρ depends on the capillary wave slopes,

and, thus, on wind speed, W (Austin 1974 and Mobley 1999).

An updated version of the S95 method using a more accurate

ρ(W) value derived from the Mobley (1999) results is referred

to as the S01 method (Hooker et al. 2003).

The anisotropy of the upwelled radiance field means aboveand in-water determinations of LW (λ) cannot be intercompared

directly—one observation must be transformed to the geometry

of the other. The transformation equations (Morel and Gentili

1996 and Mobley 1999) are an established part of the Protocols

and were successfully incorporated into above-water methods

(Hooker and Morel 2003, Hooker et al. 2003, and Hooker and

Zibordi 2005b), so only a brief summary is given. The radiance

bidirectionality is parameterized by the so-called Q function,

which takes a particular value, denoted Qn, for nadir-viewing

measurements. For Case-1 waters, the functional dependence of

the variables can be simplified by assuming the IOPs are universally related to the chlorophyll a concentration, Ca (Morel

and Prieur 1977). Because a nadir-transformed, above-water

estimate of LW is equivalent to the in-water value, a formulation can be produced (Morel and Mueller 2002) to improve the

S01 method, and is hereafter referred to as the Q02 method:

LˆQ02

W (λ) = LˆS01

W (λ) 0

(θ, W)

Q(λ, θ, φ

, θ, Ca)

Qn(λ, θ, Ca) , (A3)

where the Q terms are evaluated at null depth, θ is the abovewater viewing angle (θ) refracted by the air–sea interface, and

the  merges all the effects of reflection and refraction (0 is

evaluated at nadir). All the correction terms are computed

from look-up tables (Morel et al. 2002).

The formulation in (A3) allows for a direct comparison between above- and in-water LW values, but only if extraneous

(platform) perturbations are absent. A set of experiments were

conducted to map the above-water perturbation field associated

with a tower (Hooker et al. 2003). Based on the height of the

tower superstructure, H, the tower perturbation analyses were

partitioned into near- and far-field sets (x<H and x>H, respectively, where x is the perpendicular distance from the tower

to the surface spot viewed by the sea-viewing sensor). The primary conclusions (Hooker and Zibordi 2005) were: a) the maximum perturbations occur very close to the tower (x/H  1),

and as x/H → 1 (i.e., as the surface spot becomes as far away

as the main superstructure height), the perturbations converge

towards very small values; and b) within the far field (x>H),

the perturbation is negligible, and a remote sensing 5% absolute accuracy objective can be satisfied (see Appendix K for

more details).

The investigations into above-water measurements and the

tower perturbations contributed to a complete inquiry into the

uncertainty budgets for deriving water-leaving radiances from

above- and in-water sensors. This information was needed to a)

establish that the quality of the data from both measurement

types was in keeping with calibration and validation requirements, and b) determine whether or not a convergence between

the two methodologies to within the calibration uncertainties

of the sensors is possible.

A summary of the total uncertainty budgets derived from

a variety of coastal field campaigns and laboratory exercises is

given in Table A1, with more complete spectral details available

84
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

in Hooker et al. (2004). Although the absolute calibration of

the radiometers is important (Hooker et al. 2002b), other uncertainty sources contribute significantly. The in situ stability

includes sensor decay over time and variations in the calibration coefficients caused by differences in the calibration conditions. The uncertainty for Lu immersion factors are estimated

from the parameters used in the analytical model (Mueller and

Austin 1995). The uncertainty in the proper characterization

of Ed immersion factors is less than 0.5% (Zibordi et al. 2004a),

and although this uncertainty can influence the selection of the

near-surface extrapolation interval and, thus, the LW (λ) values,

this is usually a minor effect (so it is omitted).

Table A1. An averaged summary of the major sources

of uncertainties in the above- and in-water (AW and IW,

respectively) computation of LW for blue–green wavelengths. The last two rows give the net uncertainties

assuming the indicated sources combine in quadrature

(square root of the sum of the squares).

Uncertainty Source IW AW

1. Absolute calibration 2.1 2.5

2. In situ sensor stability 1.2 1.2

3. Lu immersion factor 1.0

3. Surface reflectance† 0.6

4. Instrument self shading 0.8

4. Bidirectional correction† 0.5

5. Platform perturbation ‡ 1.2 0.2

6. Deployment stability 1.0 0.2

7. Environmental variability 3.0 2.2

1–6 Quadrature Sum 3.1 2.9

1–7 Quadrature Sum 4.3 3.6

† Representative of the uncertainty in LˆQ02

W as a result

of typical uncertainties in the input parameters used

to calculate these quantities and not the intrinsic uncertainties in the look-up tables.

‡ Only the in-water observations are corrected for platform perturbations; the above-water measurements

were made under circumstances significantly minimizing this uncertainty.

The uncertainties in computing self- and tower-shading corrections, as well as the surface reflectance and bidirectional correction, are estimated for the former from the magnitude of the

parameters used to correct for their effects, whereas for the

latter two, the net uncertainties are derived from a sensitivity

analysis of the input variables. The in-water uncertainties due

to the instability of the deployment platform were estimated

by Hooker and Maritorena (2000) for an instrument deployed

from a large ship. The corresponding above-water values are

considerably less, because the tilt filtering of the above-water

data retains only those data within 2◦ of the viewing angle.

The environmental variability is mostly uncontrollable, except it can be minimized by collecting all the in situ data under

excellent conditions (which was done for the Table A1 analysis). The in-water component was estimated using successive

casts under different measurement conditions (Zibordi et al.

2002a) and are assumed to be independent of the optical profiling system. For the above-water instruments, the environmental variability was estimated using successive acquisitions in two

coastal campaigns and closely match previous estimates in the

same study area (Hooker et al. 2002a). The quadrature sum of

uncertainties, all assumed independent, for both systems gives

values lower than 4.5%. Assuming half of the remote sensing total uncertainty budget is apportioned to the satellite sensor, the

allowed uncertainty in the in situ data is approximately 3.5%

(

52/2 ). Although the net uncertainties exceed this level, this

is primarily a consequence of environmental variability. If only

the controllable sources of uncertainty are considered, the net

uncertainties are (on average) to within 3.5%.

An intercomparison of above- and in-water techniques for

estimating LW , based on the aforementioned Hooker et al.

(2004) study, is presented in Fig. A1. The comparison is based

on the relative percent difference (RPD) between the nearlysimultaneous (within 3 min) deployments of the two types of

instruments. Because in-water methods are the most prevalent, the in-water data were selected as the reference in the

RPD† calculation.

Fig. A1. A comparison of the above- and in-water

determinations of water-leaving radiances, LˆQ02

W (λ) and

L ̃W (λ), respectively.

The two types of data in Fig. A1 were collected under mostly

excellent conditions: cloud cover less than 4/10, wind speed

less than 5 m s−1, and wave height less than 0.5 m. At the

same time, they were acquired over an appreciable range in seawater properties—in fact, most of the environmental variables

spanned an order of magnitude change that is representative of

the differences between clear and turbid waters (the data set is

approximately 86% Case-1 and about 14% Case-2). The data

show there is a significant convergence between above- and inwater methods over a wide range of conditions: they agree to

within 1.7% on average, which is in keeping with the uncertainty

in instrument intercalibrations (2–3%), as well as the intercomparisons derived from simultaneous in-water deployments (also

2–3%).

† The RPD is defined as ψ = 100(X − Y )/Y , where X is the

above-water observation and Y is the corresponding in-water

(reference) value.

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Appendix B:

Vicarious Calibration Protocols

The fact that low-cost and easily-deployed COTS sensors

can serve as a data source for vicarious calibration (Bailey

et al. 2008) makes it compelling to revisit the tenets established for vicarious calibration in the Protocols and to discuss these within the capabilities of alternative sources of highquality data. The three considered here are a) an ocean-surface

reflectance model (ORM) based on Case-1 parameterizations

(Werdell et al. 2007); b) the NASA Bio-Optical Marine Algorithm Data (NOMAD) archive (Werdell and Bailey 2005),

which is a subset of high-quality in situ optical data from the

SeaWiFS Bio-Optical Archive and Storage System (SeaBASS);

and c) and the Bou ́ee pour l’acquisition de S ́eries Optiques `a

Long Terme (BOUSSOLE) Project (Antoine et al. 2006 and

2008). The latter two constitute a variety of COTS instruments

and different data processors.

Given the recent more expansive inquiry into vicarious calibration data sources, a review discussion of the vicarious calibration procedures currently being used seems warranted. An

item-by-item presentation and subsequent discussion of the original vicarious calibration protocols (shown in slanted typeface)

is as follows:

1. The performance of a satellite sensor must be monitored

at daily-to-weekly intervals by comparing derived normalized water-leaving radiances with contemporaneous seatruth values (both made to within the established uncertainty criteria).

All vicarious calibration methods must comply with this

requirement and about 30 quality-assured matchups are

needed. To understand a new satellite sensor, and to have

scientifically useful data as early in the mission as possible, the 30 good matchups are needed as quickly as possible. Multiple sites (SeaPRISM) or multiple investigators

on ships (NOMAD) are a good way to accomplish this,

although a modeling approach (ORM) will always provide

the greatest number of data points in the shortest time.

2. The most direct way of making the sea-truth measurements on a continuing daily basis over periods of several

years is to utilize a specially-designed array of radiometers

mounted on a moored buoy.

Off-shore structures are an alternative, and an abovewater measurement is more direct than an in-water one.

A large number of investigators equipped with suitable

profilers (NOMAD) can also provide large amounts of

data over extended time periods. A model approach represents a hybrid opportunity wherein a surrogate variable

(e.g., the chlorophyll a concentration), which is much easier to measure, is used (ORM). For the in-water methods,

the distinguishing aspect is the high vertical resolution of

profilers versus the limited vertical resolution of a buoy

(although profiling buoys are possible).

3. The buoy must be designed to mount the optical collectors well away from platform shading and reflections; although, instrument self-shading corrections will be needed

unless the sensors are very small.

Free-fall profilers (NOMAD) satisfy this requirement (assuming a self-shading correction is applied). In addition,

it is rather easy to avoid platform shading and reflections

with an above-water system, and no self-shading correction is needed. A modeling approach (ORM), by definition, will not have any of these problems as long as the

data used to initially build and validate the model are not

contaminated.

4. To minimize uncertainties arising from extrapolating the

upwelling radiance to the sea surface, the buoy must be

moored at a location with consistently transparent Case1 waters and with negligible mesoscale to sub-mesoscale

spatial variability.

The QA criteria of the match-up process forces compliance of this requirement for all vicarious calibration methods. The results from BOUSSOLE and NOMAD suggest

some relaxation in the strictness of this language is appropriate (i.e., allowing the chlorophyll concentration to rise

is not significantly detrimental). In addition, given the

robustness of the Case-1 model, unequivocally clear waters are not such a strict requirement, which is reinforced

by the ORM results.

5. To ensure frequent occurrences of matched satellite and

buoy measurements, the site must be cloud free throughout most of the year.

The QA criteria of the match-up process forces compliance of this requirement for all vicarious calibration methods, even though an easily replicated system that can

be economically deployed could satisfy—and very likely

exceed—this requirement by simply having multiple sites.

6. The mooring must be located close to an island-based sun

photometer and sky radiance sensor to allow concurrent

determinations of aerosol optical thickness and sky radiance distribution.

An above-water system based on a modified sun photometer satisfies this automatically, as would a modeling approach (ORM).

7. The atmospheric conditions at the mooring location must

not be significantly subjected to land-induced (e.g., orographic) effects.

The QA criteria used in the match-up process forces compliance of this requirement for all vicarious calibration

methods. Again, a model (ORM) can satisfy this most

easily.

8. Extraordinary calibration maintenance procedures are

needed to ensure low uncertainties in the radiometric measurements.

Calibration is only one part of the uncertainty in a measurement. Bailey et al. (2008) showed that different approaches can have very similar uncertainties, because of

their different strengths and weaknesses.

9. Comparative shipboard measurements must be made near

the buoy to check the radiometric stability of the buoy

sensors, to determine spatial variability surrounding the

buoy location, and to develop and validate bio-optical algorithms.

All vicarious calibration methods have to comply with

this requirement, and no one method distinguishes itself

with respect to the others, except an offshore structure is

likely to be easier to access.

10. The sea-truth radiometric measurements must reproduce

the spectral response functions of the satellite sensor

bands and this cannot be accomplished using COTS radiometers.

86
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

The results from BOUSSOLE and NOMAD suggest this

is not really true. Furthermore, the results summarized in

App. J, Fig. J1 confirm that measurements with a 10 nm

bandpass are suitable for accurately determining radiometric quantities for a 1 nm bandpass.

11. The need for flexibility in the choice of spectral response

weighting functions used to determine band-averaged

measurements imposes a requirement for full-spectrum

(i.e., hyperspectral) measurements with resolutions less

than 1 nm.

The results from BOUSSOLE and NOMAD suggest this

is not really true, and the emergence of multispectral

sensors with many channels (13 and 14 channels were

common with legacy sensors, and 19 is now common for

current-generation designs) means a significant portion of

the spectrum can be covered with reasonable resolution.

It is important to remember that the ORM method is also

hyperspectral and could be coupled to a fixed-wavelength

approach for certain problems.

12. Provisions to assure radiometric stability throughout the

extended period of operations should include, as a minimum, pre- and post-deployment calibrations of all radiometers, combined with continuous monitoring of onboard light sources of known stability (if possible).

All vicarious calibration methods have to comply with

this requirement. The advantage of an above-water system is it is rather easy to use natural targets (e.g., the

Sun, and even the full Moon, when environmental conditions permit) as a calibration check or to measure a

portable source (the latter can be more easily maintained,

because it is not submerged). As has already been demonstrated (Hooker and Aiken 1998), profiling radiometers

(NOMAD) can be very easily monitored on a daily basis using a portable source and are capable of calibration

monitoring in the field at the 1% level.

13. Instruments suspended in seawater for long periods of

time experience fouling by biological organisms that, if

not countered effectively using antifouling methods and

frequent cleaning by divers, seriously degrade the performance of optical sensors.

Free-fall profilers (NOMAD) do not foul, although they

must be properly cared for in the field. Above-water autonomous systems experience very little fouling, because

the sensor is parked in a downward-viewing orientation

when not in use (this could be almost completely eliminated with a movable housing guard).

Probably the most important point to make about vicarious

calibration is:

There is no absolute truth; truth is defined by the process or processes employed in the vicarious calibration

methodology.

If there are any biases in the vicarious calibration approach,

the biases will be transferred to the remote sensor and the data

products derived from the satellite observations. Given that it

is rather common for the space sensor to have unknown degradations in the prelaunch characterization that can only be determined after launch by using field data as a source of truth,

it is imperative that the in situ observations used for vicarious

calibration strictly adhere to the Protocols and all instruments

are properly characterized, calibrated, sited (notably the solar

reference), and maintained (both in the field and in the laboratory).

Appendix C:

The BSI Calibration Facility

The BSI Calibration Facility (Fig. C1) is equipped with dedicated optical benches for irradiance and radiance calibrations,

an apparatus for the measurements of spectral responsivity

functions, and test benches for angular response and linearity

characterizations. The entire laboratory is painted in flat black

and has additional curtains and baffles to ensure the proper

minimization of stray light.

a

d e

b

c

Fig. C1. The BSI calibration facility showing the following: a) test tank, b) spectral tester, c) directional

tester, d) irradiance calibration, and e) radiance calibration.

The irradiance calibration facility is optimized for the operation of 1,000W tungsten halogen FEL lamps and maintains

precision power supplies, shunts, and voltmeters, which are

regularly calibrated externally. Radiance calibrations are also

based on FEL lamps and performed by pointing the test radiometer at an angle of 45◦ at a Lambertian plaque made of

Spectralon, which is typically located about 2.9 m from the FEL

light source. The bidirectional reflectance distribution function

(BRDF) of the plaque is regularly calibrated by Labsphere,

and the OSPREy project is taking the opportunity to examine plaque uncertainties in greater detail. The facility has been

validated by several calibration intercomparisons sponsored by

NASA (Meister et al. 2003). BSI maintains several FEL standards of spectral irradiance that have been calibrated by the

NIST FASCAL. There are also several working standards that

are regularly calibrated against the NIST FASCAL lamps.

Additional lamps from different sources and manufacturers

were obtained and screened to establish a lamp library of 21

FELs for the OSPREy activity (Chap. 6). In addition, the calibration facility was upgraded to operate lamps at the highest

level of accuracy achievable. Upgrades included a new system

for powering the lamps, which allows regulation of the lamp

current to within a precision of 50 μA (or 0.0006% for a target

current of 8.2 A). Other facilities required for accurate lamp

transfers were also upgraded to reduce uncertainties caused by

stray light, misalignment, and temperature variations.

The device used for the characterization of spectral responsivity consists of a 1,000W xenon arc lamp and a 0.5 m grating double monochromator with prism predisperser. This device was custom designed and built by BSI (Bernhard et al.

2005). The two single monochromators that make up the double monochromator are stacked vertically and share a common

shaft to which the gratings are mounted. This design ensures

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

that the two single monochromators are always synchronized.

Each of these is equipped with three gratings, machined with

2,400, 1,200, and 600 grooves per millimeter, for covering a

wavelength range from 200–2,000 nm.

The angular response tester is equipped with a laser alignment apparatus and a computer-controlled rotary table. Linearity of detectors can be determined either via the inversesquare law using a 3 m rail with precision distance-measurement

capability or an automated lineator, which compares the test

radiometer with a reference radiometer with known linearity

characteristics. This instrument was established as part of the

development of microradiometers (Morrow et al. 2010a).

Other major equipment that is part of the BSI calibration

facility includes the following:

• Several integrating spheres;

• An Aires FF250 imaging, 0.25 m flat-field spectrograph;

• A helium-neon (HeNe) lasser at 633 nm; and

• A helium-cadmium (HeCd) laser at 325 nm.

The latter is part of the equipment used for establishing the

stray-light characteristics of the spectrographs integrated into

EPIC radiometers.

As part of the UVSIMN project, BSI also maintains a solar calibration facility on the roof of the company’s building.

One of the UVSIMN SUV-100 radiometers is permanently located in a dedicated room below the roof and is available for

intercalibration exercises with OSPREy sensors.

Several improvements to the present facility were undertaken to accommodate the development requirements for OSPREy radiometers:

The stray light suppression within the laboratory was improved to accommodate calibrations in the SWIR domain.

The wall paint was tested for reflectivity beyond 1,000 nm,

and a new flat-black paint with the requisite performance

in the SWIR was applied.

Kinematic sensor mounts for reproducible fixation of EPIC

radiometers in both the irradiance and radiance calibration facility were designed, fabricated, and installed. Identical mounts will also be used by the Sun-tracker system.

The radiance calibration setup was modified to permit

simultaneous viewing of the plaque with the OXR and

standard EPIC radiometers.

The apparatus for responsivity characterizations will be

optimized for use in the SWIR domain. This will include

improvements to the wavelength calibration and the reference detector. The software will be modified to allow

rapid scanning over a large wavelength range.

Screening and seasoning of a set of 12 FEL lamps to be

used in calibration transfer exercises. These lamps are

part of what is referred to as the OSPREy Lamp Library

(Chap. 6).

The stability of the OXR and OSPREy technology likely

accommodates measurements historically made with the SeaWiFS Transfer Radiometer (SXR) and the second generation

version called the SXR-II. The number of channels in these heritage instruments is significantly less than an EPIC sensor and

they only cover the visible part of the spectrum. Nonetheless,

they had well-established performance capabilities, particularly

in terms of stability and absolute response (Johnson et al. 1998

and 2003), which can be contrasted to the performance metrics

of the OXR.

Appendix D:

Ancillary Measurements

Environmental instruments are an important adjunct to the

optical measurement systems, including meteorological observations and ocean wave height. Some of these measurements are

crucial inputs to atmospheric models, some describe the state

of the sea or sky being sampled, others warn of weather conditions that could compromise measurements or even the sensors

themselves, and others provide enhanced remote viewing of the

installed system.

While many platforms where OSPREy might be installed

may already be equipped with meteorological instruments, this

is not a certainty; furthermore, the sensors might not be calibrated and in working condition, and their data streams might

not be accessible or compatible with the OSPREy data acquisition architecture. For this reason, a set of environmental sensors will be fully integrated into the OSPREy system and the

resulting data products.

The required ancillary sensors include the following:

1. Barometric pressure, which is required for calculating relevant atmospheric properties and as a warning of impending severe weather;

2. Rain gauge, which is used as one of the indicators that

sampling conditions are unfavorable for the radiance scanning systems (R.M. Young model 55202 heated tipping

bucket);

3. Relative humidity and air temperature (R.M. Young model 41382V);

4. Wind speed and direction will be a part of the sea state

characterization and will be used to determine if it is

prudent to deploy the tracking and shadowband systems

(R.M. Young marine wind monitor model 5106);

5. Global positioning system (GPS) with processing for total

precipitable water;

6. Pyranometer for broadband radiation (Kipp & Zonen

model CMP21 with ventilation);

Future revisions of ancillary sensors could also include imaging technologies, such as the following:

7. All-sky (fisheye) camera using either the Schreder model

VIS-J10060CC2 camera from Austria or the Yankee model

TSI440A (the Schreder camera seems to have advantages,

but it is new to the market); and

8. Network pan-tilt-zoom camera (AXIS model 233D).

The outputs from the meteorological sensors are common signal

sources and easily integrated: rain (pulse output), wind (pulse

output), wind direction (variable resistor), humidity (voltage),

temperature (voltage), barometer (voltage), and other ancillary

voltage sensors are digitized by an Agilent U2300 USB data acquisition module connected to the PC. The wave height sensor

has a digital output.

The wave height (radar-based) sensor, is useful for monitoring the sea state. A lidar system was considered, but rejected,

because of the potential interference with the SWIR optical

channels. A radar system is considered the most appropriate,

and the plan is to use these data with the anemometer measurements to estimate when whitecaps are likely contaminants in

the sea-viewing radiance data (O’Connor FMCW Radar). The

high cost of radar systems necessitates that this component be

added when the field deployments are more established.

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Appendix E:

The BioSHADE Accessory

Shadowband radiometry is provided by the BioSHADE accessory, which is a device that attaches to the OSPREy irradiance sensors (Bernhard et al. 2010). The device uses a microprocessor for command and control, and is compatible with a

GPS receiver option for use on ships. There are three modes of

operation:

• The shadowband can be kept in the stowed (hidden) position below the plane of the irradiance cosine collector

for a global irradiance measurement (Fig. E1a).

• The shadowband can be set to a particular hemispherical

angle with a direct (Go to) command to occult the Sun,

so the diffuse irradiance can be measured (Fig. E1b).

• The device can be commanded to move over a range of

positions and at a programmed rate, for instance, a full

hemispherical sweep over a range of ±90◦ (0◦, which is

straight up towards the sky, is zenith).

BioSHADE appears as just another microradiometer-type device when it is used within the microradiometer architecture of

sensors.

Stowed

Shadowband

Rotated

Radiance

Rotated

Shadowband

Stowed

Radiance

Fig. E1. The BioSHADE mechanism shown attached

to an irradiance sensor and in two modes of data acquisition: a) global irradiance, for which the shadowband

is in the stowed position below the irradiance cosine

collector, and b) diffuse irradiance, for which the shadowband is rotated to occult the solar disk. In the same

respective panels, the radiance sensor is shown rotated

to view the sky, and stowed to protect the optical aperture.

BioSHADE is typically programmed to cycle through measurements of global and diffuse irradiance, plus special measurements, wherein the shadowband is positioned 10◦ on either side

of the Sun, are also possible. The latter can be used to correct

for the partial shading of the sky when the diffuse irradiance

is measured with the solar disk occulted. The shadowbands of

the two dyads operate asynchronously, so the global irradiance

is always measured during a data acquisition scenario. The

position of the shadowband is recorded in the data stream.

Appendix F:

Platform Power and Data Telemetry

Power and communications for the instrument suite may

be available at some deployment structures, but it is expected

in most cases that this infrastructure will be lacking. To design a complete system flexible enough to exploit any kind of

physically suitable platform, power generation will have to be

done onsite, and high-speed data transmission will have to be

facilitated.

Even if a platform already equipped with power is identified and used to deploy an OSPREy system, some portion of a

separate power generation capability will probably be needed

to ensure a suitable backup capability. The latter is needed not

only to safeguard the system, but also to aid in risk assessment

by being able to point and receive data from the cameras that

are part of the system. Consequently, certain aspects of what

is presented here are expected to be a part of every OSPREy

system.

Platform Power

Several power technologies have been considered, including

diesel-electric, solar, wind, fuel cells, and wave power. For most

anticipated platform locations, a hybrid system of solar and

wind-charged battery power was selected as the best solution.

A small (less than 5 kW) diesel generator would be used for

battery charging during platform visit periods, because there

will be a high load demand when people are on-platform and

during radiometer calibrations.

Fuel cells are an emerging technology with few commercial

products available. Given the viable alternatives, it was considered more cost effective and less hazardous if the transportation of compressed gasses (hydrogen) to the platform could be

avoided. Wave power for the requirements of the OSPREy systems is too exotic in its current state; it is also costly and not

well proven for autonomous systems.

The OSPREy system, during autonomous operation, is projected to use or require less than 1 kW peak, 500W during normal daylight operation, and 300W in dormancy (nighttime and

storms, but the radiometers are temperature controlled continuously). The OSPREy system will be battery powered, and all

components will run off of a 24 VDC bus. This voltage choice

is convenient in a number of significant ways:

• It is relatively safe in contrast to operating at 120 VAC

(60 Hz);

• It is more efficient for autonomous local-generation systems, because it avoids the substantial power losses from

inverters to step up to 120 VAC and then back down to

the DC levels OSPREy uses; and

• It is a commonly used industrial control and automation

power level, which provides cost savings, because commercial components are widely available at competitive

pricing.

Battery capacity will be specified to support the system

in its dormant state for 72 h (long duration storm), depleting

the batteries to 50% of their charge in this period. The batteries will be a lead-acid Absorbent Glass Matt (AGM) type

specifically intended for wind and solar charging. They will

be maintenance free, with a completely sealed valve-regulated

construction. This type is classified as nonspillable battery for

transport and complies with the US Department of Transportation (DOT) HMR49, as nonhazardous material.

89
OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

To charge batteries, solar power has the greatest appeal

and will probably be the primary power source. Photovoltaic

(PV) is a clean, silent, and low maintenance solution that is

readily available. Field solutions are well documented (e.g.,

polarpower.org), and easily scalable to address the requirements of different latitudes and climates. PV has limitations,

because it is only effective when sunshine is available (no charging during rain or at night) and the panels take up space. For

a design latitude of 40◦ (New York City) and maximum reserve

capacity, about a 30 m2 array of PV panels (4 kW) would be

needed to supply the daily requirements of OSPREy. Given

this, supplemental power is necessary.

The secondary battery charging technology will probably

be one or more small wind turbines designed for stationary

marine and coastal applications. Two commercially available

three-bladed turbines, approximately 2.7 m in swing diameter,

can provide 400W continuous charging in as little as 5.4 m s−1

(12 mph) wind. These same turbines can provide as much as

2 kW in 13.4 m s−1 wind conditions (30 mph storms). This

potentially facilitates indefinite period charging during times

when solar charging is ineffective (and OSPREy is operating in

its dormant state).

Wind turbines have the added advantage that they can

charge continuously during the day or night, again offsetting

PV in a complementary manner. Because wind turbines have

moving parts, they are generally higher maintenance than solar

systems and this needs to be considered carefully for long-term

deployment scenarios. They also provide no charging in low

wind conditions (less than 3.1 m s−1), so reasonably complete

wind histories for a planned location are needed. In many cases,

offshore structures are already instrumented with meteorological sensors, so detailed wind information is frequently available.

For design purposes, however, wind climatologies are usually

sufficient.

The balance of PV and wind will be tailored to the climate

conditions of the specific platform location. To optimize charging efficiency, the plan is to use Maximum Power Point Charge

Tracking charge controllers, with remote monitoring features.

Charging, battery charge state and health, and OSPREy loading of the power system will be monitored, in an attempt to

prevent data loss from a power system problem. The solar and

wind charging subsystems, as well as battery banks, will be

configured in parallel to the 24 VDC power bus. In this configuration, should a power system component fail, the OSPREy

system will not be completely crippled until the next servicing

opportunity, which means emergency response scenarios (which

might be expensive for some locations) can be kept to a minimum.

The OSPREy power requirements are a small fraction of

the power typically available from diesel generators designed

for continuous unattended operation. This power source is also

a source of particulates with the potential to compromise the

radiometer light collection (optical) surfaces and some of the

atmospheric observations, although proper attention to siting

the generator can greatly minimize this problem. It would also

require supply and storage of fuel at the platform, and the

engine would require periodic maintenance from a mechanic

brought to the site.

It is expected, however, that during platform visits by personnel to service the equipment, particularly during the monthly maintenance activities, power demands could be on the order

of 1.2 kW (continuous). Much of the needed power will be dedicated to radiometer calibrations and system service activities.

It is also possible that remote troubleshooting of a malfunctioning sensor could increase power requirements as other systems

are reprogrammed or exercised to diagnosis the problematic

equipment.

To address the occurrence of any occasional peak demands,

a small diesel generator would be part of an OSPREy power system. The generator would be used for charging during platform

maintenance visits in conjunction with solar PVs and wind, as

well as providing 120 VAC directly from the generator’s integral

inverter. Its occasional use and compact size will require minimal maintenance, little fuel to be transported or stored, and

will not be a continuous polluting source. Diesel is chosen not

only for its efficiency, but also with fuel transportation safety

in mind.

Data Telemetry

The volume of in situ data plus remote system management

communications is expected to require a daily transfer of up to

1 GB of information. To achieve OSPREy objectives, including

diagnostic images, a reliable high-speed data link and static Internet protocol (IP) addressing is needed. At offshore locations,

it is unlikely that the estimated 500 kB s−1 (or faster) data link

will be readily available for dedicated OSPREy use. To optimize costs and the amount of time in a 24 h period available for

communications, commercial bandwidth options are considered

the most appropriate.

It is anticipated that most platform locations will not be so

convenient with respect to the common bandwidth and Internet access options, and cellular telephony cannot provide the

required sustained bandwidth. At this time, the most costeffective solutions for these locations are satellite-based, so this

type of service will be used for OSPREy data communications.

Of the available options, the most readily available and affordable is Very Small Aperture Terminal (VSAT) technology.

Dedicated channel VSAT is high reliability (the bit error rate

is 10−7 or better), small footprint (typical dish diameters are

0.8–1.8 m), and available with a variety of fixed bandwidth rate

options from 300 kB s−1 to greater than 1 MBps (transmit rate

from ground link to receive rates are generally higher). Static

IP addresses are available, and bandwidth can be scaled up or

down as OSPREy requirements change.

Available VSAT coverage includes the contiguous US coasts

(up to 100 km offshore), the coasts of Alaska and Hawaii, the

Gulf of Mexico, the Caribbean Sea, and the northwest coast of

Mexico. VSAT has the potential to provide an affordable singletechnology bandwidth solution for all currently envisioned OSPREy platform locations. Should OSPREy platforms be in

other regions of the globe, VSAT services are available for Europe, most of South America, North Africa and the Middle

East, and many coastal regions of East Asia.

If OSPREy systems are placed on platforms at high latitudes or far offshore, there are other satellite-based solutions

with global, or near-global availability, including broad swath

links more typically employed in the maritime industry (commercial vessels). These services will be substantially more expensive per bit than VSAT, however. There is also the NASA

Tracking and Data Relay Satellite System (TDRSS). While

TDRSS availability is not 24 h per day globally, channel bandwidth is substantial enough to achieve OSPREy data transfer

objectives, at nearly any conceivable OSPREy platform site.

Because of geosynchronous orbits, TDRSS is available at extreme latitudes (the poles).

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Appendix G:

Extended Test Deployments

The OSPREy suite of sensors is designed to operate autonomously in remote, sometimes harsh, environments. Service and maintenance opportunities are normally expected to be

limited to monthly visits, but an emergency servicing capability

is also anticipated (e.g., for unexpected equipment problems or

a safeguard response to a severe weather forecast). Most likely,

the system will be running on power and telecommunications

links for which BSI is responsible. Fortunately, BSI has been

designing and operating complex multisensor optical systems

for over 20 years, some in even more hostile environments than

anticipated for OSPREy systems (the center of the Greenland

Ice Sheet, for example). BSI has typically achieved a greater

than 95% acquisition of all possible data products in these circumstances.

In any newly designed system, a shakedown or commissioning period is required, and the first deployment of an OSPREy

system will be no different. There will be two phases to this

early testing of a new system: the first, will be on the rooftop

optical platform at BSI, which will test all of the individual

components as they are available and characterized; the second

will be a two-week deployment at an offshore site to be selected

early in the project. After the successful completion of these

two tests, the system will be considered ready for operational

deployment (App. H).

Component reliability is an issue, because all components

eventually fail. With the BSI systems deployed in polar environments, this is dealt with first by designing for reliability, and

then by stocking spare components onsite (in rare instances one

of the facility technicians is asked to change a standard lamp

or replace a fuse), and finally with annual visits to each site

with a set of tools, calibration standards, and spares. For OSPREy, there is no capability of onsite assistance, so monthly

visits will include the availability of a complete set of spare,

fully calibrated radiometers in the event one shows degradation problems, or more simply, is scheduled to be rotated out

of operation for refurbishment.

Part of the envisioned operational cycle will include sensor calibrations back at the BSI calibration facility (App. C).

Although calibration monitoring at the platform will be done

monthly using a portable source (App. H), the monthly maintenance plan involves bringing back one of the two radiometer

sets on a regular rotation, perhaps quarterly (to be determined

more exactly once experience with the system has been acquired). In this case, the spare set of radiometers would be

installed and the system would spend a day running in a more

intense intercomparison mode. The advantage of this approach

is that it would periodically freshen the calibration of the full

set of radiometers independently of using the portable calibration source. This provides an alternate operating mode in the

case that the portable calibration source is not as successful as

anticipated.

The BSI corporate facility is located 3.4 mi northeast of

downtown San Diego, California. The facility has had a rooftop

optical observation platform since BSI moved to the location in

1991. The rooftop platform has been host to a UV-Visible Scanning Spectroradiometer installation, which is part of the NSF

Polar Programs UV Monitoring Network. A GUV-511 UV filter

radiometer is also permanently installed, and other instruments

are regularly deployed as various projects are initiated and concluded. After using the rooftop platform to develop and test

the tracking systems, shadowband, and other components, the

entire OSPREy system, including solar power generation and

satellite data communications, will be deployed on the rooftop

platform for several months with all components operating autonomously.

During rooftop testing, OSPREy global irradiance measurements will be compared with the Scanning Spectroradiometer (300–600 nm) permanently installed on the roof. Shadowband measurements, sky radiance, Sun tracking, solar principal

plane, and almucantar sky radiance measurements will all be

made. Although this arrangement does not allow for any seaviewing observations, all of the other sensor systems and resulting data products can be completely tested. The sea-viewing

sampling scenario will be simulated by using series of painted

targets on the roof that can be designed to provide a relatively

stable signal. Of course, these would not be calibration targets,

but targets with reflectances similar to that of the ocean, the

selection of which will be based on the Munsell Color Classification colors used in early remote sensing studies. The objective

here is to subject the system to the most realistic dynamic range

in variables possible.

While testing on the rooftop optical platform at BSI should

provide a convincing demonstration of the ability to routinely

obtain solar irradiance and atmospheric properties, and even

the ability to accurately measure radiance from calibrated targets, it will not completely demonstrate the ability to provide

sea-truth data for ocean color satellite missions. A two-week

deployment of all components, except the ancillary meteorological instruments (App. D) and autonomous power generation,

at a site with a good sea-viewing geometry is part of the first

field commissioning exercise. This deployment will include simultaneous in-water AOP profiles to validate the above-water

determination of water-leaving radiances and the production

of higher order data products (e.g., the derived chlorophyll a

concentration).

The platform to be used for the initial deployment has

not been finalized. NASA has ongoing relationships that may

allow access to a number of coastal observatories and other

locations—all of which have scheduling and logistical advantages and disadvantages. Although each is different in terms

of capability and access, the South Atlantic Bight (SAB) Synoptic Ocean Observing Network (SABSOON) observatory is

documented as an exemplary facility for comparison purposes

(App. L). In the past, BSI has installed solar tracking radiometric systems on the Scripps Institution of Oceanography pier,

which extends far out into the ocean, and certain types of testing might be advantageous at this site. This location would

also permit the deployment of an in-water profiling system for

additional validation data. Recent advances in the use of a telescoping mast to mount solar sensors well clear of local obstructions (Hooker 2010) means deployment opportunities on previously awkward structures like piers are more tenable. When extended, the mast also safeguards the equipment from unwanted

access by other personnel on the structure.

Another option is to charter a boat and deploy for several

days of repeated observation sequences of both above- and inwater optical observations following the methods of Hooker et

al. (2004). An advantage of this approach is that several water

types could be accessed off San Diego, but the disadvantage is

that a moving ship would make Sun tracking very difficult (but

this is rigorously tested on the BSI rooftop facility). A final

decision on the optimum location and deployment method will

be researched during the first year of the project and finalized

before the third year (when the deployment is scheduled to take

place).

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Appendix H:

Operational Deployment

After the extensive test phase and field commissioning deployment (App. G), an OSPREy system will be ready for operational deployment on an ocean platform. An engineer and

optical scientist will be sent to inspect and survey candidate

platforms for suitability. This survey will include meeting with

the custodians of the platforms to preview suitable mounting

locations (for all instruments and solar power panels), and to

assess the availability of pre-existing logistical support. The

latter includes power, communications, storage, and laboratory

space, all of which are not required for successful OSPREy operations, but all of which would enhance the operational reliability of the system.

The possible methods for mounting devices will also be investigated to determine if welding will be necessary, and the

type of tools that will be required for installation. Part of

this assessment will include the mitigation of perturbations to

the observational suite from unavoidable obstructions (some of

which are inevitable). The site will be photographed at different

times of the day to understand and document the solar geometry. When the various mounting locations are determined, cable

lengths and disconnect points will be determined. The mode

of deployment will be reviewed carefully, paying particular attention to vertical distances to be traversed, lifting assistance

(hoists), types of ladders, and other logistical factors.

Approximately six weeks will be needed to fabricate the

necessary mounting hardware and to procure and test all of the

required cabling. Any needed services required for deployment

(e.g., helicopter, boat, electrician, or welder) will be contracted

and scheduled. Based on the deployment vehicles and their

carrying capacity, plus the means of vertical transport on the

platform, shipping containers will be fabricated and made ready

for transport. When the installation opportunity arrives, the

equipment will be shipped and the team will travel to the staging site for the installation. Installation time will range from

3–7 days, depending on weather conditions, as well as the conditions of the platform and the difficulty of working on it. As the

sensors are brought online, data analysts back at BSI will exercise the communications links and start data collection. After

all sensors are functioning nominally, a 24 h undisturbed period

will allow the instruments to come to thermal equilibrium, and

permit the data analysts at BSI to review system performance.

Finally, the engineers will revisit the platform and perform

calibrations using a portable calibration source. After the field

calibrations are performed, an in-water deployment of matching

submersible AOP radiometers (in terms of the fixed wavelength

microradiometers) will be used to characterize the optical properties of the water. Additional field measurements will be made

for IOPs, as well as sampling for the analysis of HPLC pigments

and biogeochemical parameters. At the end of the installation,

the OSPREy system should be fully operational. Based on operational experience with other remote systems, shortly after

midnight each day, all data and logs collected the previous day

will be automatically transferred to BSI. An archived copy will

remain on the data collection computer at the platform. A remote session will be initiated, to inspect all connected sensors

and systems. The remote host software will also have the ability

to generate electronic mail messages and corresponding alerts

for any problems that might demand immediate attention. Finally, a remotely operated digital camera, sited on the platform

to have unobstructed viewing of all important components, can

be used for remote visual inspection and problem diagnosis.

Initially, measurements from the previous day will be processed and compared with historical and modeled data to detect

outliers on a daily basis. The log files will be filtered for unusual

events, and the results of this automated data review will be

used to produce a daily report summarizing system operation.

This review will focus on such factors as temperature regulation and dark offset stability, tracking of redundant sensors

during sampling modes when pairs of radiometers are operating

in the same mode and viewing the same target, monitoring battery power levels, and system power consumption. This type

of functionality will run automatically and will be timed in

keeping with personnel work schedules. For some deployment

locations, time zone differences might increase the desired lag

time between the end of an observational day for an OSPREy

system and the start of a BSI work day.

A second level of monitoring will examine data quality from

the aspect of agreement of various radiometric products derived

from different paths (such as direct solar irradiance derived

from the shadowband radiometer and the Sun-tracking radiometer). The results of this monitoring will be used to build data

reports, including data quality estimates, which will be posted

on the OSPREy Web site (typically with a one day lag). Initially, these reports will be semiautomatic as the formats are

tuned to be the most useful. As the analysts involved become

more accustomed to the data flow and quality, the reports will

become fully automatic and delivered as a portable document

format (PDF) file via e-mail. Unless directed otherwise, the

OSPREy Web site will be public, because this kind of visibility greatly increases the number of people looking at the data,

which significantly increases the chance of detecting problems

and improving the quality of the data products throughout the

lifetime of the activity. Synergistic activities with other customers of OSPREy sampling systems will be pursued where

mutually advantageous and permissible.

Regular platform visits will be scheduled on a monthly basis. These visits will include calibrating each radiometer with

a portable calibration source before and after cleaning the sensors. The latter provides the opportunity to detect any biases

caused either by fouling or sensor drift. The solar panels will

be cleaned and the meteorological sensor suite inspected, along

with all computer and power systems. Water samples will be

collected for HPLC pigment and biogeochemical analyses, and

a C-OPS in-water profiling package will be deployed to collect contemporaneous measurements of the AOPs of seawater

for subsequent comparison to the OSPREy AOP data products. In the event of a system component failure or degradation, a spare component will be available for installation at the

monthly visit. If a major problem is encountered (e.g., responding to a significant power supply problem or the damage from

a severe weather event), the time span of the work may require

more than a one-day visit.

The various sampling systems will be designed such that the

monthly maintenance and sampling visit can be completed in

less than 8 h under normal circumstances. This makes it possible to accomplish the work by helicopter at all times of the

year if the offshore structure has helicopter access. If the only

access is by ship, the transit time will be longer, but more people can be taken to ensure the amount of work can still be done

in the time anticipated. Regardless of helicopter access, a certain number of visits will always be done by ship to ensure the

greatest flexibility in accommodating personnel and equipment.

In particular, the transportation of heavy or bulky items will

be staged for ship transportation (helicopters have restrictive

cargo transport capabilities).

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

Appendix I:

Absolute Calibration

This appendix summarizes the method presently being applied to convert field measurements made with radiometers

built with microradiometers to geophysical units, such as spectral radiance and irradiance. This standard method is based on

the NIST FASCAL scale of spectral irradiance, as detailed in

the Protocols, and is straightforward to implement. This task

is performed in the BSI calibration laboratory (Sect. 6.3.2 and

App. C) using a NIST standard lamp for all calibrations, plus

a reflectance standard for radiance.

The standard method does not provide radiometry at the

1% accuracy level, however, which is one of the goals of the

OSPREy concept. A new, more advanced calibration method

based on a NIST SIRCUS calibration is currently under development that will be published in a subsequent report. This

new method will take several sources of uncertainty into account, which are absent from the standard method, and will

address the calibration of the spectrograph component of OSPREy radiometers, with additional features.

Dark Measurements

Each microradiometer used in OSPREy instruments has

three gain stages (Sect. 2). The ratios between the three gain

values are accurately measured during the manufacturing process of each microradiometer and stored in the nonvolatile memory of each sensor. The outstanding linearity exhibited by all

three gain stages (Sect. 2.3) ensures that a single-point calibration coefficient, determined at any one gain, satisfies the

uncertainty requirements for obtaining calibrated reading at

all gains. The use of high-quality gain resistors having temperature coefficients of less than 20 ppm ensure minimum drift

over time. Each gain stage has a unique dark signal amplitude, or offset, that is somewhat temperature dependent and

determined during calibration.

Dark measurements can be acquired using different procedures (Sect. 8.9) and are usually recorded to track the sensitivity of the dark signal to environmental forces (e.g., temperature). At BSI, the dark measurement for each microradiometer

and gain setting is usually acquired over a 30 s time period at

5 Hz. BSI has three ways to measure the average dark signal

amplitude (μ denotes an average signal amplitude and the accent establishes the way the dark measurement is made):

μ

•

Covering the sensor aperture with an opaque cap that

blocks all the light reaching the aperture (this measurement is the most common, because it directly establishes

the dark offset, and it can be done in the field);

μ

	

Closing a shutter between the compartment of the laboratory that contains the lamp (while it is operating) and the

compartment where the radiometer is mounted, which allows only the background radiation scattered from the

lamp compartment to reach the radiometer (this dark

measurement is unique to calibration and establishes how

good the baffling is for the compartment where the lamp is

operated, although some background radiation that would

pass through the aperture is not measured); and

μ

•

	

Placing an occulting device between the source of direct

radiation (a lamp for irradiance and a reflectance plaque

for radiance) and the radiometer such that the occulting device only blocks the direct radiation across the size

of the aperture but nonetheless allows ambient radiation

scattered from the backside of the lamp compartment and

the walls of the radiometer compartment to reach the radiometer (this dark measurement is also unique to calibration and establishes how good the baffling is for the

entire calibration facility).

Because of the extensive baffling and reflection minimization

procedures used at the BSI calibration facility to suppress stray

light (Sect. 6.3.2 and App. C), the differences in the dark signal

amplitudes determined with the three methods is less than 0.2%

at SWIR wavelengths, and less than 0.1% in the UV, visible,

and NIR domains. Consequently, the first two methods are used

for routine calibrations, because they are the most expedient.

As noted above, the most common method involves covering the sensing aperture with an opaque cap to measure the

average dark signal amplitude. When these data are obtained

in the field close in time to the collection of light data, these

dark measurements are referred to as field darks; if obtained in

the laboratory as a necessary part of completing the calibration

procedure, these dark measurements are referred to as calibration darks and are recorded in the calibration file. For sensors

built with microradiometers, the dark offsets obtained by capping the sensor aperture are also stored in the radiometer’s

nonvolatile memory and used by the firmware to calculate the

signal amplitude when exposed to radiation (these values can

be updated in the field to provide the most accurate real-time

geophysical values).

Responsivity

The next step in the calibration process involves determination of the spectral responsivity, γ(λ), as it pertains to calibration for each microradiometer. The responsivity term converts

a measured signal amplitude to calibrated geophysical units.

For irradiance sensors (identified by the E subscript) built with

microradiometers (identified by the M superscript), responsivity is defined as:

γM

E (λ) = ( μM

E (λ) − μ

•M

E (λ)) − ( μ

	

M

E (λ) − μ

•M

E (λ))

EF (λ)

= μM

E (λ) − μ

	

M

E (λ)

EF (λ) ,

(I1)

where μM

E (λ) is the average light signal amplitude derived from

repeated measurements of the spectral irradiance EF (λ) from

the standard lamp at the calibration distance of 50 cm. The average is usually based on a sampling time of 30 s and a sampling

rate of 5 Hz.

For radiance sensors (identified by the L subscript) built

with microradiometers, responsivity is defined as:

γM

L (λ) = μM

L (λ) − μ

	

M

L (λ)

LP (λ) , (I2)

where LP (λ) is the radiance of a standard (typically Spectralon) reflectance plaque illuminated by a standard FEL lamp,

wherein the instrument to be calibrated is facing the center of

the plaque at an angle of 45◦, and μM

L (λ) and μ

	

M

L (λ) are the

light and dark average signal amplitudes, respectively, measured in a similar fashion as for irradiance radiometers. The

LP (λ) term in (I2) is calculated using the following formulation:

LP (λ) = ρP (λ)

π EF (λ)



r + Δ

c + Δ

	2

(I3)

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

where r is the reference distance for the lamp (50 cm for a NIST

standard lamp and measured from the front of the lamp posts);

c + Δ is the centerline distance between the surface of the

plaque and the center of the lamp filament (in the same units

as r) for which Δ is the offset distance between the center of

the lamp filament and the front of the lamp posts; and ρP (λ)

is the spectral reflectance factor of the plaque for an incidence

angle of 0◦ and a viewing angle of 45◦.

Measurement Equation

The formulation of the measurement equation follows from

the definition established by the National Bureau of Standards

(NBS†) in a series of monographs describing optical radiation

measurements. As part of laying down the foundation for such

measurements, Nicodemus et al. (1976) defined the following:

The measurement equation is the mathematical expression that quantitatively relates the output of a measuring instrument to the radiometric quantity that is being

measured, taking into account all of the pertinent factors contributing to the measurement result. The main

part of that measurement equation relates the radiation

input at the receiving aperture of the instrument to the

resulting output in terms of the instrument responsivity

(output “signal” per unit incident radiation input).

The explicit reference of responsivity being equal to output over

input (I1 and I2) sets the form for the measurement equation,

but there is an added requirement that Nicodemus et al. (1976)

made clear:

The complete equation also accounts, as needed, for the

effects of interactions between matter and radiation at

the source and along the optical path of the radiation

beam as well as at the instrument.

From the generalized perspective of BSI calibrations, the majority of which are for in-water sensors, a principal interaction

effect is the so-called immersion factor.

The immersion factor is a necessary part of the spectral

characterization of an in-water sensor, because when the collector is immersed in water, its light transmissivity is less than

it was in air. In-water sensors are calibrated in air, however, so

a correction for this change in transmissivity must be applied

when the in-water raw data are converted to physical units.

The immersion factor for irradiance must be determined experimentally (Hooker and Zibordi 2005a), whereas for radiance it

can be computed to an acceptable accuracy; by definition, the

immersion factor is unity when the sensor is used in air.

There are other interaction effects that need to be included,

but not all of these are handled explicitly as part of the measurement process, because some of the needed parameters are

typically not available at the time the data are acquired. For

example, a correction for the self-shading effect is frequently applied when the data products are derived from the observations.

Nonetheless, it is useful to be able to consider an expanded multidimensional concept for responsivity wherein the complexity

of the term is built up as the characterization of the instrument

becomes more comprehensive.

The dimensionality of γ is denoted by including arguments

to the responsivity term, wherein each added argument represents a new interaction effect. In other words, if ei represents

a particular interaction effect, then γ(λ, e1, e2) indicates which

two of those interaction effects are included in the definition of

† The NBS was the precursor agency of NIST.

responsivity that is being applied. Note that in the simplest

representation of responsivity (I1 and I2), the term simply represents what is usually called the calibration coefficient.

Considering now the formulation to convert a measured signal amplitude A(λ) to geophysical units as obtained for inwater irradiance (E subscript) and radiance (L subscript) sensors equipped with microradiometers (M superscript), the measurement equations are as follows:

EM(λ) = AM

E (λ) − μ

•M

E (λ)

γM

E (λ,) (I4)

and

LM(λ) = AM

L (λ) − μ

•M

L (λ)

γM

L (λ,) (I5)

where the argument for responsivity accounts for immersion

factor interaction effects. In this case,

γM

E (λ,) = γM

E (λ)

M

E (λ) (I6)

and

γM

L (λ,) = γM

L (λ)

M

L (λ)

, (I7)

where the numerators in (I6) and (I7) are the aforementioned

calibration coefficients and the denominators are the immersion

factors (which for OSPREy sensors are unity).

Note that (I6) and (I7) do not specify the target. For example, the calibration procedure is independent of whether or not

the shadowband of the irradiance unit is in use or whether the

radiance radiometer measures the radiance of the sky, Sun, or

Moon (by pointing up), or the sea surface (by pointing down).

Furthermore, for remotely installed instruments, it is sometimes

possible to utilize ambient darks measurements performed at

night to provide a temporally more representative measure of

the dark offsets.

OSPREy Considerations

The formulations presented above, (I1)–(I7), are not in

agreement with the legacy approach documented in the Protocols. The differences are a result of the Protocols not adhering to the principles first established by the NBS, retained by

NIST (Larason and Houston 2008), and adopted by the wider

community (Boivin 2005). In the Protocols, responsivity is erroneously defined as the radiometric input quantity per unit

output. This inversion is not necessarily a significant source

of uncertainty for simplistic calibration scenarios (e.g., singlepoint calibrations).

The standard calibration procedure outlined above does not

provide radiometry at the 1% accuracy level. The procedures,

therefore, need to be amended to achieve this level of accuracy.

OSPREy technology anticipates development of a new, more

accurate and complete method to calibrate radiometers, which

are presented in detail by Bernhard et al. (2012). The new

method serves to minimize uncertainties in calibrated irradiance or radiance data arising from several sources of error that

are not addressed by the standard method. It also deals with

the special challenges involved in calibrating the spectrograph

component of OSPREy radiometers and the new capabilities

afforded by the filter wheel of the radiance unit.

94
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

OSPREy irradiance radiometers have a state-of-the-art cosine collector (Chap. 3). Although the cosine error of the collector is small, it is not zero, and a correction is required to minimize the impact of this error on calibrated spectral irradiance

measurements. The correction method is based on measurements of the cosine error, which are performed for every OSPREy irradiance radiometer, the ratio of direct to global spectral irradiance measured with the instrument’s shadowband,

and assumptions on the distribution of sky radiance (Bernhard

et al. 2010). The new calibration method will build on these

earlier results. For example, rather than assuming that sky

radiance is isotropic, measurements of the sky radiance distribution provided by the tracker-mounted radiance sensor can

be used to further reduce the uncertainty of the current cosine

error correction scheme.

Spectral Resolution

Microradiometer channels cover a spectral band of approximately 10 nm FWHM, while spectrographs have a bandwidth of

6–10 nm (Table 11). Largely due to absorption processes in the

outer region of the Sun’s atmosphere, the solar spectrum is not

constant over these wavelength ranges, and varies greatly on a

0.001 nm scale. These absorption processes lead to the Fraunhofer lines in the extraterrestrial solar spectrum. These lines

are not resolved by either the micrometer channels or the spectrograph, which cause uncertainties in the measurement when

calibrations are applied.

Although ground-based OSPREy instruments do not measure the extraterrestrial spectrum (ETS) directly, spectral measurements including observations of the direct Sun, sky radiance, or the radiance emanating from the sea surface, can be

considered as the product of the ETS and a transmission spectrum that takes into account absorption and scattering processes in the Earth’s atmosphere. Even though OSPREy microradiometer channels occur at wavelengths where absorption

by the Earth’s atmosphere is minimal, the detailed Fraunhofer

structure of the ETS cannot be neglected because it introduces

calibration uncertainties arising from the finite bandwidth of

the sensors. To determine the magnitude of the effect, a highresolution ETS solar spectrum was compared with two simulated spectra: one from a moderate bandwidth (10 nm boxcar)

radiometer and one from an idealized spectrometer that has a

triangular slit function and a resolution of 1 nm FWHM. The

maximum divergence of the simulated spectra and the ETS

was a factor of 15. These differences can be explained by the

smoothing of the high-resolution ETS by the finite bandwidth

of the hypothetical sensors.

The new calibration method will take into account the relative spectral responsivity functions of OSPREy instruments,

including bandwidth differences between two units and nuances

such as manufacturing tolerances of interference filters and geometric factors such as filter detuning from acceptance cones.

The method will result in a reporting of spectral irradiance or

radiance identically to spectra measured by ideal spectrometers. For example, the 10 nm FWHM 380 nm channel of an

OSPREy irradiance sensor will be calibrated such that the reported spectral irradiance would be identical to that of a hypothetical spectrometer with a triangular slit function and a

bandwidth of 1 nm. With this approach, measurements of all

OSPREy radiometers would be comparable and the quantities

to be measured are unambiguously defined. The method requires accurate knowledge of the spectral responsivity functions

of all microradiometer channels. All instruments are therefore

characterized using the BSI spectral tester (App. C).

Spectrograph measurements for OSPREy radiometers are

calibrated using a similar procedure and gridded to a standard

wavelength interval (e.g., 300, 301, 302 nm, etc.), resulting in

spectra with a defined bandwidth and wavelength interval, regardless of the native bandwidth and pixel wavelength of the

spectrographs. This standardization is particularly important

because spectrographs installed in irradiance and radiance sensors have different bandwidths. By standardizing the calibrated

data product, measurements of the two units become comparable. Standardization is also required for comparison of measurements of microradiometer and spectrograph components and

radiometers that are not OSPREy instruments.

Spectrograph Considerations

Calibration of spectrograph data is subject to unique challenges because the units are affected by dark signal drifts, limited dynamical range, stray light, and nonlinearity. These four

sources of uncertainty will be addressed in the new calibration

method. Although the OSPREy spectrographs are temperature stabilized to better than ±0.03◦C, data analysis indicates

that the remaining variation in temperature leads to noticeable

variation in the dark signal amplitude. For irradiance sensors,

these variations are characterized and corrected by analyzing

variations in spectrograph measurements spanning 245–285 nm.

Because Earth’s atmosphere is opaque to radiation in this wavelength range because of ozone absorption, variations in spectrograph data in this domain can be attributed to the combined

effects of dark current drifts and stray light. Drifts of the dark

signal amplitude of spectrographs used in radiance units are

characterized by turning the filter wheel to the opaque position.

The dynamic range of the spectrograph is limited by the

15 bit ADC capability of the unit (Table 11). The dynamic

range can be extended by two methods: a) measuring at a

different integration time, and b) using the neutral density filters of the filter wheel (Figs. 49 and 55). The first option is

addressed by considering that the spectrograph responsivity is

proportional to the integration time, whereas the second option requires accurate knowledge of the spectral transmission

of the two neutral density filters installed in the filter wheel.

The transmission of each neutral density filter is determined in

the BSI calibration laboratory.

The stray light correction for each spectrograph requires

the measurement of the spectrograph’s slit-scattering function

over the entire wavelength range. The function is determined

using measurements of laser lines (e.g., the measurement of the

632.816 nm line of a HeNe laser, as discussed in Sect. 7.4.2).

From these measurements, a stray-light correction matrix is

determined using a method similar to that suggested by Kreuter

and Blumthaler (2009) and applied to spectra that have been

corrected using the dark signal data. The resulting spectra are

then corrected for nonlinearity. The associated correction factor

is a function of the light signal amplitude and is determined in

the laboratory.

The filter wheel installed in all OSPREy radiance sensors

is equipped with three polarizers, oriented at 0◦, 45◦, and 90◦

(Figs. 49 and 55). From measurements taken at these three

positions, the polarization state of radiance can be determined

in terms of the Stokes vector. The calibration process requires

characterization of the Mueller matrices for each of the three

polarizers, which will be done in the BSI calibration laboratory

using methods developed by Voss and Liu (1997) and Liu and

Voss (1997).

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

Appendix J:

Uncertainty Analysis

Although microradiometers offer a step-function improvement in many practical aspects of design and deployment of

field radiometers, the underlying photodetector technologies remain unchanged from PRR instruments. These legacy systems

were capable of acquiring data over almost the entire performance envelope of the detectors, and remain an excellent proxy

for the ultimate performance characterizations of the OSPREy

EPIC instruments (Chap. 2). The following uncertainty analysis is offered to represent the uncertainty approach, and to a

qualified extent, an excellent first approximation of what is expected from OSPREy.

The uncertainty of SIRCUS responsivity calibrations for the

spectral range 406–920 nm is 0.2% (Brown et al. 2000). The

uncertainty of the calibration transfer from an OXR to an OSPREy EPIC radiometer is mainly influenced by small changes

(0.1%) in the lamp output within the time period needed to execute the calibration and small alignment uncertainties in the

physical setup. The latter will be limited to less than 0.5 mm,

because all OSPREy radiometers are equipped with a kinematic

mount designed for high positioning accuracy.

Repeated lamp calibrations performed on PRR-800 radiometers over the time span of several years have indicated that the

instruments are typically stable to within 1% during one year,

although single channels may change at a somewhat larger rate.

With daily intercomparisons of the various radiometers, uncertainties caused by changes in responsivity can be limited to

approximately 1.0%. The primary source of daily intercomparisons with the OSPREy sensors are natural targets, although

other targets are available at longer time periods (e.g., the

portable source that will be used during monthly maintenance

visits).

Changes in responsivity resulting from collector contamination (e.g., sea spray, air pollution, and birds) are hard to quantify, because they depend on the platform location, position

of the sensors on the platform, and environmental conditions

around the platform. Contamination of irradiance radiometers

is minimized by using a diffuser made of polytetrafluoroethylene (PTFE), an inert material that is easily cleaned by rain

and wind. Fouling of the radiance optics are reduced by stowing the radiometers with the glass apertures protected. Should

this prove to be ineffective, addition of a (distilled) water-spray

system will be considered and has been conceptualized. Contamination may be a problem during significant dust events,

but these periods can be identified by regular intercomparison

of the radiometers. Data with discrepancies larger than 2%

will be flagged as abnormal and will be subjected to additional

scrutiny.

The uncertainty, due to the deviation from an ideal cosine

response of the UV-VIS EPIC irradiance radiometers, will be

similar to the PRR-810 radiometers, which is to within 2% for

zenith angles spanning 0–65◦ and to within 10% for 65–85◦.

Correction procedures developed for the spectroradiometers in

the UVSIMN activity (Bernhard et al. 2004) will be applied to

OSPREy EPIC instruments. The associated uncertainty of 1%

is based on a sensitivity analysis using UVSIMN data (Bernhard

et al. 2004). Accurate knowledge of the ratio of the direct-toglobal irradiance from shadowband measurements will reduce

the uncertainty further. The cosine error for the VIS-SWIR

EPIC irradiance radiometers is larger because of the difficulty

of designing diffusers for the SWIR domain. Global irradiance

in the SWIR during clear skies, however, is mostly from the

direct component, which considerably reduces correction uncertainties.

The uncertainties related to the transfer of an instrument

from the laboratory environment to field measurements arise

from the very different shapes of a standard lamp and the solar

spectra: a solar spectrum provided at a 1 nm resolution may

change by up to a factor of 2.5 within the 10 nm bandpass of

an OSPREy EPIC channel, whereas a lamp spectrum is almost

constant. OSPREy EPIC measurements will be normalized to

a standard bandpass of either 1 nm, or 10 nm using radiative

transfer modeling introduced in Apps. I and M, and which is

expanded in detail in Bernhard et al. (2012). The associated

uncertainty stems from the fact that the shape of the solar

spectrum changes as a function of solar zenith angle (θs) and

environmental factors. This problem is addressed during data

processing by multiplying conversion factors—used to convert

measurements from 10 nm to 1 nm bandpass—with correction

factors.

The magnitude of the correction factors and the resulting

uncertainty were estimated by comparing conversion factors

calculated for different radiometric quantities (Es, Li, and LW ),

solar zenith angles (θs = 40◦ and 80◦), cloud conditions (clear

sky and overcast), and chlorophyll concentrations. The latter is

determined using a Case-1 model with [Chl a]= 0.045 mg m−3

as described by Morel and Maritorena (2001). The results of

these calculations are shown in Fig. J1, which depicts the ratios of the conversion factors determined for various parameter

settings to the factor calculated for Es(λ), θs = 40◦, and clear

sky.

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Correction Factor

Fig. J1. Correction factors for the conversion of OSPREy EPIC measurements from 10 nm to 1 nm bandpass. The results are shown for widely diverse set of

situations (shown with separate symbols as listed at the

top of the plot). OSPREy wavebands are indicated by

the gray vertical lines; the horizontal yellow band denotes a ±1% variation with respect to a correction factor of 1.00.

The correction factors in Fig. J1 are usually smaller than

0.5% for most channels, confirming that measurements with

10 nm bandpass are suitable for accurately determining radiometric quantities for a 1 nm bandpass. Exceptions include wavelengths below 340 nm, where absorption by ozone has to be

considered, and in the vicinity of strong water absorption (e.g.,

between 590–600 nm). The latter is of minor importance, because OSPREy wavelengths were chosen such that interference

96
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

with water absorption is minimal. Differences for LW (λ) (green

circles in Fig. J1) are typically smaller than 0.5%, except at 510

and 589 nm, where the total value of the correction factor is as

high as 1.015, because of the large spectral change of LW (λ)

at these wavelengths. Because the parameters controlling the

total value of correction factors are well known, the uncertainty

of a correction factor is assumed to be 10% of the total value,

which equates to less than 0.5% at all wavelengths under consideration.

Nonlinearity is mostly a consequence of gain changes (OSPREy EPIC sensors have three gain stages) combined with offset drifts. Uncertainties caused by offset drifts are minimized

in the OSPREy radiometers through the use of temperature

stabilization and automated nighttime offset measurements—

so-called dark measurements (which are usually taken with the

caps on the radiometers, but were taken here with the radiometers in their stowed position, so the influence of ambient light

is minimized to the greatest extent possible).

The successful use of nighttime darks has already been demonstrated (Hooker 2010), and the only extra work involves some

additional quality assessment of the data to ensure no contamination from natural and artificial light sources (e.g., the

Moon and navigational lights, respectively). The PRR-810 radiometers are linear to within 1% over their usable dynamic

range. The linearity of OSPREy EPIC radiometers was further

improved to within approximately 0.5% using test equipment

developed as part of the NASA SBIR project titled, “In Situ

Microradiometers: Smaller, Faster, and Scalable to Hyperspectral” (Contract Number NNG06CA03C).

The uncertainties unique to deriving the principal data product, LW (λ), are independent of the specifications for the radiometers, and the values in Table 2 are adopted from Appendix A. The uncertainty in computing the surface reflectance

and anisotropy correction were derived from a sensitivity analysis of the input variables used by the correction methods. Uncertainties due to perturbation from the observation platform,

such as tower shading, were assumed to be 25% of the associated correction factor. The influence of wave effects and similar

environmental factors was estimated from a statistical analysis

of nearly simultaneous above- and in-water measurements of

LW (λ).

One source of uncertainty in the calculation of surface reflectance that has not been considered here is polarization. Sky

radiance is polarized and the reflectance of radiation from the

water surface depends on the polarization state of the incoming

radiation. The LT (λ) values will, therefore, depend on the degree of polarization of the sky. The polarization of sky radiance

depends in turn on various factors such as aerosol loading, the

presence of clouds, and the scattering angle between the Sun

and the direction of sky viewing.

While the effect of polarization can be partially corrected

using a radiative-transfer modeling approach, an accurate determination is not possible because of the many factors involved. A sensible solution consists of measuring the degree

of polarization of skylight directly. The EPIC radiance sensors

have a nine-position filter-wheel assembly permitting polarization measurements with the spectrograph. The filter wheel has

nine positions (Sect. 8.2), so three components of polarization

will be measured.

Appendix K:

Platform-Perturbation Mapping

Hooker and Zibordi (2005b) quantified how significant platform perturbations can be when using an above-water method

on an offshore structure, and also showed they are avoidable

(or can be minimized) using some simple metrics associated

with the sampling protocol. Regardless of the environmental

variability, the primary avoidance principle for a sea-viewing

sensor mounted on the illuminated side of a platform is that it

must be pointed to a spot on the sea surface that is at least

as far away (perpendicular to the structure, x), because the

platform is high (H). If this rule is followed, the platform perturbation will be negligible, that is, less than the repeatability

of so-called far-field measurements (defined as those measurements for which x/H > 1); whereas, near-field measurements

(x/H < 1) will be contaminated. Although this rule is sufficient

for many purposes, such as test deployments, the uncertainty

requirements for calibration and validation activities require a

detailed platform perturbation mapping.

The principal objective of a platform perturbation study

is to determine at what viewing angles and solar geometries

will the surface spot (sampled by a sea-viewing sensor) not be

contaminated with platform perturbations. The surface spot

is the cross-sectional area on the sea surface intersected by the

FOV of the radiometer pointed at the sea surface. The sea

surface is usually perturbed by wind, so the roughness of the

surface is a source of oblique wave facets that can reflect light

from a variety of directions into the view of the radiometer.

The platform can also block light that would normally reach

the surface spot. In either case, the farther the surface spot

is from the platform, the less likely unwanted perturbations

caused by the platform can contaminate the natural light field.

The perturbation analysis is based on the spatial characteristics of a diagnostic variable, r:

r(x, λr) = LT (x, λr)/Li(λr)

ρ(W) , (K1)

where λr is a reference wavelength in the NIR domain (e.g.,

865 nm). Under natural circumstances (i.e., in the absence of

platform perturbations) and in Case-1 water conditions, ρ(W)

= LT (λr)/Li(λr), within the accepted variance and provided

ρ(W) is given a correct value, and r(x, λr) = 1. Any other

reflected radiation added to the sky-reflected radiation leads to

an increase in LT (x, λr), and r(x, λr) > 1.

The most important aspects of r(λr) as an analytical variable are as follows:

1. It intrinsically includes the effects of changing solar illumination, because the sea-viewing observations are normalized by the sky radiance; and

2. It is a severity index, in the sense that the stronger the

artificial increase in LT (x, λr), the larger the increase in

r(x, λr), and the magnitude of the departure from unity

(or an appropriate reference value) is an estimate of the

severity of the contamination.

3. It is completely insensitive to bottom perturbations, because of the high attenuation of NIR wavelengths.

In Case-2 water conditions, or if the water type is close to the

threshold of Case-1 and Case-2 conditions, r(x, λr) is not expected to be unity even at far-field distances, so the last point

requires some qualification. The time needed to make a sequence of horizontal displacement system (HDS) measurements

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

is less than 1 h (on average) and covers 1–20 m or more in sampling distance from the platform. This is with using a movable

boom with the sensors at one end from the near field to the far

field at a particular solar geometry. In the absence of a source

of artificial reflections, r(x, λr) is expected to remain essentially

constant over this time. In other words, if the tower were not

present, r(λr) might not be unity, but it would remain constant

over the short time period of a single experiment. Multiple experiments over a variety of solar geometries are needed to map

out the perturbation field.

An example platform-perturbation mapping (Hooker et al.

2003) is presented in Fig. K1. The data show far-field observations are not significantly influenced by platform reflections,

which lead to positive RPD values, but the near-field data are

(shading produces negative RPD values). Near-field reflection

contamination was confirmed by a) comparing LW (λ) values

from above-water data from the near and far field with an independent set of simultaneous (to within 5 min) in-water observations, and b) above-water normalized water-leaving radiances

spanning all of the near field and part of the far field, with one

observation in the latter used as the reference in the perturbation analysis. The inset panel in Fig. K1 shows a schematic of

the localized (x,y) coordinate system, along with the geometry

for the pointing angles with respect to the Sun (β) and the surface spot viewed by the sea-viewing sensor (α). The a–d arc

shows the transit of the Sun from early morning to late afternoon, respectively (the concomitant change in the solar zenith

angle is not depicted and is also important to reflection contamination). Note the origin of the localized coordinate system

(denoted by the intersection of the +x and +y axes) is a point

at the northwest corner of the tower within the area associated

with a squared-off extension to the platform.

Fig. K1. An example perturbation mapping experiment based on r(865) RPD values (crosses), with their

maximum and minimum extents also shown. The binaveraged values (solid circles and associated curve) as

a function of x/H give the principal characterization of

the perturbation field.

Appendix L:

The SABSOON Towers

The South Atlantic Bight (SAB) Synoptic Ocean Observing

Network (SABSOON) is a good example of the level of sophistication available at some offshore towers, as well as the extent

of available partners for enhancing scientific activities. SABSOON was a prototype ocean observatory based on an array of

offshore fixed structures that operated from the spring of 1999

to the fall of 2009. During operation, the platforms are part of a

U.S. Navy combat flight training range managed by the Naval

Surface Warfare Center, Marine Corps Air Station (MCAS),

Beaufort Detachment (Beaufort, South Carolina). Through the

cooperation of the Beaufort Range Manager, the Skidaway Institute of Oceanography (SkIO) provided access to the towers to

make year-round atmospheric and oceanographic observations.

The SABSOON tower array is located about 60–110 km

off the Georgia coast (Fig. L1a). The three central towers

(M1R1, R2, and M2R6) have onsite power generation from solar panels, wind turbines, and backup diesel generators, with a

climate-controlled enclosure. The outer five towers are somewhat smaller, with only solar panels for power generation, and

without climate control for the instrumentation enclosure, which

is smaller. Additional power generating capability has been

added to R8 to ensure sufficient power for SABSOON research.

In the eight-tower array, there are four- and three-legged

designs (Fig. L1b). The former (R2, M2R6, M1R1) are larger

and equipped with higher-capacity power systems. All towers

have a helicopter landing pad (Fig. L1b), a ship docking area

(Fig. L1c), and an antenna truss platform for communications

antennas, which was made available for scientific instruments

(Fig. L1d). The water depth across the range varies from about

25 m (R5 and R7) to 43 m or more (R3 and R8, respectively).

The network supported continuous time series and near-real

time data delivery from a variety of sensors. Developmental

funds were provided by the National Oceanographic Partnership Program (NOPP) in 1998 (Seim 2000). Scientific investigations operated on a not-to-interfere basis with respect to

Navy activities, with all installations submitted to the Range

Manager for approval. Three towers had meteorological and

oceanographic sensors (R2, M2R6, and R8), and a fourth (R4)

had only a meteorological package. The ocean sensors included

conductivity, temperature, and depth (CTD) sensors, chlorophyll fluorometers, bottom-mounted acoustic doppler current

profilers (ADCPs), plus above- and in-water photosynthetically

available radiation (PAR) sensors. At the larger R2 and M2R6

platforms, SABSOON was allocated 360W (48 VDC) from the

Navy power system (solar and wind power generation, with

diesel generator backup). At R8, the Navy power capacity was

considerably lower, and SkIO installed a separate power system

(solar panels, wind turbine, liquid propane gas backup generator, batteries, controller) providing 250W (24 VDC) of power.

Data telemetry bandwidth within the Navy microwave communications system was equivalent to a T1 line, which together

with a T1 land line connecting to SkIO provided two-way, realtime communications at 1.472 Mbps. The SABSOON data system operated as a wireless local area network (LAN) with offshore computers being nodes on the SkIO network. For routine

operation, most data were logged to offshore computers at 6 min

intervals and retrieved hourly. Offshore data logging was used

to avoid data loss during microwave communication downtimes.

Transportation for servicing the SABSOON tower systems was

by helicopter, the SkIO research vessel (R/V Savannah), and

by smaller vessels operated by GRNMS. The GRNMS program

provided considerable logistic support for SABSOON through

an agreement with SkIO.

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

-81.5 -81.0 -80.5 -80.0 -79.5

32.0

31.5

31.0

b

c d

a

Fig. L1. The SABSOON offshore tower array: a) the location of the tower network superimposed on the local

bathymetry and with respect to the National Oceanic and Atmospheric Administration (NOAA) Gray’s Reef National

Marine Sanctuary (GRNMS) site, b) the large and small (inset panel) tower designs, c) the ship docking facilities at

M2R6 (after refurbishment), and d) the antenna truss deck at R8 (with the helicopter pad below).

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Appendix M:

BSI Quality Assurance Experience

BSI has been operating the UV Spectral Irradiance Monitoring Network (UVSIMN) for the National Science Foundation

(NSF) since 1988†. The network was established in 1987 by the

NSF Division of Polar Programs in response to serious ozone

depletion reported in Antarctica. Seven sites are involved and

the instrumentation provides global irradiance measurements

between 280–600 nm, and secondary data products, such as,

total column ozone, effective albedo, and cloud optical depth.

The tasks BSI has undertaken include hardware and software

development, oversight of daily operations, data processing, QA

and QC of data products, data distribution, documentation,

and publication in peer-reviewed journals. The complexity of

the instrumentation and the level of QA and QC BSI has developed are good indicators that BSI has the relevant experience

for designing, building, and managing the OSPREy system.

Network data are routinely used by the research community for the validation of satellite observations, the verification

of models describing radiative transfer through the atmosphere,

and the preparation of assessment reports, such as the Scientific Assessments of Ozone Depletion published by the World

Meteorological Organization (WMO 2007). Experience gained

during almost 20 years of operation will be highly beneficial for

OSPREy. This includes familiarity in handling large data volumes, management of automated procedures for data screening,

quality control implementation of radiative transfer codes for

data correction and interpretation, and data distribution.

One of the more important accomplishments of the UVSIMN

activity that BSI is directly responsible for, in terms of the requirements of the OSPREy project, is the quality control plan.

The plan consists of a wide diversity of elements executed over

significantly different time scales—spanning daily checks to annual activities—which require a large variety of skills and expertise:

• Automatic quality checks (every few seconds) in which

all spectroradiometers sample ancillary data (such as system temperatures at high frequency) and if these measurements deviate from control limits, remedial action is

initiated.

• Daily checks wherein the proper functioning of the system

is checked by research associates (who also clean the instrument collectors), and measurements of irradiance and

wavelength standards are used to determine instrument

stability or uncover instrument problems.

• Weekly data processing and QC for which raw data are

processed, preliminary data are posted, and the following

steps are executed: a) review of weekly briefs from the

research associates, b) application of preliminary wavelength and irradiance calibration to raw data, c) generation of a quality report and review, d) posting of new

data, and e) initiation of remedial action(s) if needed. As

an example of the weekly quality review, Fig. M1 shows

an automatically generated report comparing instrument

parameters measured within the previous seven days with

pre-established control limits. Out-of-limit parameters

are highlighted in red to facilitate inspection. Further

† Detailed information regarding UVSIMN and the type of

work BSI does for this activity is available at the following

Web site: www.biospherical.com/nsf/.

analysis may initiate corrective action such as adjustment

of instrument settings or followup with instrument operators.

• Biweekly calibrations wherein the spectroradiometers are

calibrated by research associates with standards traceable

to the NIST spectral irradiance scale, the calibration data

are reviewed during the weekly data processing, and during the austral spring, a UV Bulletin is posted on the

aforementioned BSI Web site for the UVSIMN activity.

• Radiometric intercomparisons for which data from multichannel radiometers are compared with data from collocated spectroradiometers several times during the year.

• Annual activities wherein the following tasks are conducted: a) training of research associates at BSI; b) visits

of network sites by BSI personnel (for end-of-season calibrations; comparison of onsite standards with traveling

standards; inspection, maintenance, repair, and upgrade

of instruments; and start-of-season calibrations); and c)

preparation of final Version 0 data.

Following a review of the data obtained during the site visit,

all solar data recorded between two annual site visits are reprocessed and published using the following procedures: a) review

of all calibration scans performed during the last year; b) application of the final wavelength correction to solar data; c)

calculation of calibration factors for ancillary sensors; d) QC of

final data, which involves a comparison of measured data with

target values, comparison of new data with data from previous years, and external (remote sensing) data; e) dissemination

of final Version 0 data; f) documentation of QC results in reports; and g) publication of final data on compact disk–read

only memory (CD-ROM).

There are also a number of activities that fall into a variety

of longer-term accomplishments, which are detailed as follows:

• Comparison of standards of spectral irradiance wherein

the lamp standards of spectral irradiance used in the

UVSIMN, which are traceable to the NIST irradiance

scale, are sent out for recalibration at regular intervals.

In addition, calibration lamps are compared with standards of the NIST/NOAA Central UV Calibration Facility (CUCF).

• Participation in intercomparisons wherein UVSIMN spectroradiometers regularly participate in national and international intercomparisons. Results have been published

in peer-reviewed journals and have been used to improve

instrumentation, measurement protocols, and data analysis procedures. Figure M2 shows some of the instrument

types (installed in the field) involved in the radiometric

intercomparisons.

• Comparison with radiative transfer models wherein spectral data of the UVSIMN are compared in regular intervals with results of radiative transfer models.

• Publication of results in scientific journals wherein data

from the UVSIMN are regularly published by either BSI

personnel or researchers not associated with BSI.

• Re-evaluation of network data, because Version 0 data of

the UVSIMN exhibits some known and well-documented

systematic errors, a new data version (denoted Version

2), is being produced.

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Fig. M1. Weekly quality control chart of NSF UVSIMN. Measured instrument parameters from five network sites are

compared with pre-set control limits to identify instrument and data problems. Out-of-limit parameters are highlighted

in red.

Fig. M2. The NSF UVSIMN network site at Summit

Station, located in the center of the Greenland ice sheet.

Shown in the foreground is the collector of a BSI SUV150B scanning spectroradiometer. Farther back are a

GUV-511 UV filter radiometer and a PSP pyranometer. The system was installed in 2004 and is remotely

controlled by BSI.

Since 1988, BSI has collaborated with the Los Angeles Department of Water and Power (LADWP) to design and deploy

a series of water-quality monitoring systems in five reservoirs

(Morrow et al. 2000). These systems represent the earliest industrial application of the bio-optical instruments that were

originally designed for oceanographic and remote sensing applications. Matched pairs of sensors located on a minimal-shadow

mooring provide in situ measurements of spectral downward irradiance and upwelling radiance at six SeaWiFS satellite bands.

A radiometrically matching reference provides incident irradiance at the outlet tower of each reservoir. Multiple algorithms using derived reflectance, diffuse attenuation, and solarstimulated fluorescence allows for calculation of Chla concentration over a range of 0.02–40.0 mg m−3, and a nephelometric

turbidity equivalent based on PAR. Uncontrolled algal growth

can quickly compromise the taste, odor, and appearance of impounded water.

The monitoring systems were designed to provide reservoir

managers with the daily data needed to recognize and react

to incipient algal blooms before water quality is degraded. In

particular, water operators can control the delivery of disinfection agents to the water system, minimizing disinfection byproducts, and potential taste and odor, at minimal expense.

The near-real time (30 min averages) reporting of data supports

early intervention of nuisance algal blooms and complements

grab sample data acquired during manned reservoir surveys.

High temporal resolution data also provides useful information

on short time scale processes such as algal blooms, thermal destratification, and rain runoff events.

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Frequently Asked Questions (FAQs)

1. What are the basic differences between OXR and EMR

sensors?

An OXR is designed and built to be a transfer radiometer that is used exclusively in the laboratory and

not in the field, whereas EMR sensors are designed and

built for field work (Sect. 1.3). Consequently, an OXL

(radiance) sensor does not have a filter-wheel assembly,

because it does not need to view bright targets, and it

does not have an integrated camera, because it does

not need to track a target or be autonomously pointed.

If there were an application wherein an OXL needed to

track a target, it is compatible with the tracker used in

the OSPREy activity (FAQ 24).

In addition, the spectrograph fiber in an OXL (radiance) radiometer is not placed outside the microradiometer cluster as it is in an EML (radiance) sensor.

Instead, one microradiometer is removed and the spectrograph fiber in an OXL sensor is fed through the missing microradiometer position, which is the same as is

done with all OXE and EME sensors. This means that

the interior design of OXE and OXL sensors are more

similar than the interior design of EME and EML sensors. Both OXE and OXL sensors have a maximum

of 18 microradiometers, whereas EML sensors have a

maximum of 19 microradiometers and EME sensors

have a maximum of 18 microradiometers (like the OXR

sensors).

In summary, OXL and EML sensors are rather different

(and have different wavelength configurations as shown

in Table 13), whereas OXE and EME sensors are more

similar. The basic difference between the two types of

irradiance instruments is the color: the OXE sensor is

black for darkroom use and the EME sensor is white

for outdoor use.

2. Why is the so-called “operational” OSPREy system

(Fig. 44d), which has redundant radiance and irradiance instruments (i.e., two dyads), an advantage?

The presence of duplicate (or redundant) sensors in an

operational system (Sects. 1.2 and 8.6) allows for synchronous and asynchronous sampling with those sensors, which has several advantages:

• With two radiance sensors, both the sea surface

and sky can be measured simultaneously. This synchronous sampling eliminates any temporal evolution in one or the other, which can occur if measured

sequentially.

• With two irradiance sensors fitted with shadowband

accessories, one can be measuring the global solar

irradiance while the other measures the sky irradiance. This asynchronous sampling allows the global

irradiance to be available for normalizing measurements subjected to small (linear) changes in atmospheric conditions.

• Each pair of instruments can be used to measure the

same source simultaneously. This synchronous sampling provides the opportunity to detect calibration

drift and other factors that degrade the measurements.

• The independence of two systems—including data

acquisition computer, GPS, and tracker—provides

increased resistance to hardware failure. This is

particularly important because the system is designed to be operated in harsh environments with

minimal support personnel.

• Two independent systems allows one to be removed

for calibration, while the other maintains the measurement time series. When the first instrument

is returned, its calibration can be compared with

the instrument that remained on station. This is

particularly important when the remoteness of the

location means extended shipping times for calibration.

3. What kind of maintenance is required for an OSPREy

system?

Ideal radiometric measurements depend on invariance

in the properties of the radiometer. The least constant component is normally the optical aperture with

the external environment, which in an OSPREy system is the quartz window on the radiance sensor and

the cosine collector on the irradiance sensor. The shadowband accessory, if run on a regular cycle, is a bird

deterrent. The outer layer of the cosine collector is

made from PTFE (Teflon), which greatly resists the adherence of deposits, and the surrounding surfaces are

designed to shed particles when washed by rainwater

(Fig. 14). The radiance aperture is also subject to the

deposition of contaminants, which can increase scattering at this surface, thereby degrading solar trackingdependent measurements. Unlike an irradiance sensor,

a radiance sensor is mounted on a tracker and can be

stowed in a downward-pointing orientation to minimize

the opportunities for deposition.

In all cases, dust, grime, and salt spray deposits gradually build up and degrade the signal at the affected

aperture. The rate of this reduction depends on the

environment in which the OSPREy system is installed,

and the impact differs depending on the data product

being generated. Although an OSPREy system is designed to be continuously operated remotely, periodic

manual cleanings of the radiance windows and irradiance collectors is required.

The interval between cleaning is highly dependent on

the deployment site; ideally, daily cleaning is advised.

Much less frequent cleaning, i.e., weekly or even monthly, may be acceptable in some conditions or for some

science objectives. A cleaning cycle requires approximately 10 min time per sensor, and should be done

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only by someone who is properly trained. As an aid

to determining the need for cleaning, a remote camera system can be deployed to allow inspection of the

sensor windows and collectors. Current testing of such

a system indicates it is helpful in examining radiance

windows when the radiometer is pointed at the remote

camera.

If the remote camera can be mounted above the plane

of the irradiance radiometers, the collectors can be inspected using the camera. In particular, large contamination events from animals (specifically birds) are also

easily detected. The remote camera is very helpful in

verifying operation of other OSPREy system components, and can be used to diagnosis other mechanical

issues or can function as an aid to allow a remotely

located engineer to assist personnel servicing the installation.

4. What are the types and recommended frequencies of

radiometer calibrations for an OSPREy system?

The types and frequencies of calibrations for an OSPREy system depend on the sampling and research objectives established for the system. For example, if the

system is used for algorithm validation, research applications, or water-mass monitoring, a standard calibration is advised annually or every six months, depending on the desired quality level for the measurements.

This recommendation is based on a weekly-to-monthly

cleaning regimen.

For vicarious calibration systems, the recommendation

is a combination of standard and a so-called characterization calibration. If the vicarious calibration work

involves significant sun photometry components, a solar (Langley) calibration is available and is anticipated

in combination with the standard and characterization

calibrations. The frequency of the combination of calibration types is expected to be discerned from monitoring with a portable source, e.g., PURLS (Sect. 1.5.4),

plus daily sensor intracomparisons using the spectrograph and the microradiometers in each EMR sensor

and intercomparisons using at least a Minimal System

(Fig. 44).

All calibrations include a thorough inspection of the instrument, cleaning, and any required software updates.

Longer servicing intervals are also anticipated. The

specific concern here is that the risk associated with intrusive maintenance may outweigh the reward when it

comes to disassembling and reassembling the seals on a

properly functioning and stable unit. For example, the

replacement of most O-rings is presently scheduled for

a 3–5 yr interval, but only experience with how EMR

sensors age, which is presently unknown, will determine

if that interval is appropriate.

A standard calibration for irradiance instruments is

performed on the irradiance bench and a radiance calibration is done on the radiance bench (Chap. 6). These

calibrations should be done at least annually, and more

frequently if intercomparisons with other instruments

(if applicable) indicate a problem. It is not necessary

to perform the more elaborate irradiance calibration of

radiance radiometers annually, so this calibration is not

considered part of the standard calibration. For example, if the responsivity of a particular detector changed

by 2%, both the signal obtained from the radiance and

irradiance calibration of that instrument should change

by 2%. Consequently, the irradiance calibration could

be tied to the radiance calibration, which is much easier

to perform.

A solar calibration is performed following the Langley

method, and is part of the protocol to track instrument

stability. The advantage of this method is that the instruments can stay in place at the deployment site and

do not have to be brought back to the BSI calibration

laboratory. The problem is that the uncertainty of Langley calibrations at a marine site with marine aerosols

is comparatively large. Consequently, changes in the

calibration at the 1% level is hard to detect. Significant problems (e.g., a defective channel) can be readily

discovered, however.

A comprehensive calibration involves the following:

• Determination of spectral responsivity functions of

filter channels;

• Radiance optical bench calibration of EML (radiance) sensors;

• Irradiance calibration of EML (radiance) sensors using an x–z stage and determination of filter transmission function;

• Spectrograph slit function, including determination

of stray light correction matrix;

• Determination of the Mueller matrix for polarimetry;

• Irradiance optical bench calibration of EME (irradiance) sensors;

• Angular response characterization (FVA of radiance

optics or cosine response of irradiance collector);

• Linearity characterization of spectrograph component;

• Wavelength-to-pixel mapping of spectrograph component; and

• Assembly and QC of all calibration files and parameters.

Changes in many of these instrument parameters, e.g.,

the angular response and the slit function, are less

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

likely. Consequently, all characterizations that are part

of the characterization calibration are anticipated to be

done every 2–3 yr. More complete details about BSI

calibrations are available in Bernhard et al. (2012).

5. How can the broad sampling capability of an OSPREy

system—that is the pointing and tracking associated

with viewing the sea surface, the sky, the Sun, and the

Moon—be achieved with a less costly configuration?

There are several ways to reduce the cost of an OSPREy system, but still exploit the unique capabilities

of autonomous sampling that OSPREy systems offer.

Some possibilities are only applicable to systems with

redundant sampling opportunities, so not all options

are available for all system configurations. From that

larger perspective, cost savings are available as follows:

The number of microradiometers in each sensor can

be reduced to the minimum required.

With respect to a maximal perspective wherein two

irradiance sensors are used to cover the full spectral range that OSPREy is capable of (Fig. 44c),

the number of irradiance sensors can be reduced to

one, while maintaining a broad UV-SWIR spectral

coverage, as long as the compromise in accuracy is

acceptable.

Redundant sensors in the system can be removed,

as long as the resulting increase in risk is acceptable.

If hyperspectral observations are not required, a

custom instrument patterned after the EMR can

be built without the spectrograph or filter wheel

(which also removes the present implementation of

polarimetric measurements). Alternatively, XTRA

sensors (Morrow et al. 2010c) can be used rather

than EMR sensors (which removes thermal regulation as well as spectrograph components).

If the data products associated with the shadowband accessory are not needed, the shadowband can

be eliminated.

The important point to remember is an OSPREy system can be custom configured in terms of the instrument suite (the number of sensors) and the sensor capabilities (the individual specifications of each sensor).

6. Why is the spectral range of an EME (irradiance) sensor different from an EML (radiance) sensor?

EMR sensors are designed and built to function autonomously in the field. Unlike the OXR instruments,

which are used in the laboratory, EMR sensors can generally not be capped for the measurement of the dark

offsets of both the microradiometers and the spectrograph. Of the two types of dark measurements, the

spectrograph dark offsets are the most important, because the spectrograph is more temperature sensitive

(Sect. 7.4.5), which is a principal reason why EMR and

OXR sensors are thermally regulated.

To solve the dark measurement problem, and to provide

other functionalities (e.g., polarization, improved straylight correction, and bright target viewing), EML (radiance) sensors have a nine-position filter wheel (Figs.

49 and 56) with an opaque disk in one position. The

opaque disk position permits the measurement of dark

offsets for the spectrograph, although the entire filterwheel assembly is sufficiently light tight that dark offsets can be measured in the half interval between any

two filter positions. The microradiometer darks are acquired during the night when conditions are optimal

(e.g., overcast sky), which has been shown to provide

sufficient quality measurements over extended periods

of time (Hooker 2010). With the tracker, an EML

sensor is stowed by pointing it towards nadir, which

further improves the night darks acquired for radiance

sensors.

EME sensors do not have a filter-wheel assembly, so the

spectrograph darks must be established using a different technique. Because the atmosphere is opaque below 290 nm, spectrograph measurements spanning 245–

290 nm can be used to monitor variations in dark current and correct the data accordingly. This correction

is possible because spectrograph testing showed that

changes in dark current are nearly independent of the

spectrograph pixel, which means that information from

the 245–290 nm range can be used to correct measurements in the other UV and visible wavelengths. Consequently, EME sensors have to have a spectrograph

with a spectral range below 290 nm (Sect. 8.2.2).

7. Because OXR sensors are laboratory devices, which can

be capped, why were they not equipped with a spectrograph that covered a larger spectral range like their

EMR counterparts?

The shorter wavelength range used in OXR sensors is

advantageous to their role as transfer radiometers, because it allows more accurate measurements in the UV

where lamp standards have the largest variability and

may suffer from emission lines (Sect. 6.7.2). In contrast,

the lamp-to-lamp difference at SWIR wavelengths can

be approximated with a second-order fit function, so

high spectral resolution data are not necessary in this

part of the spectral range of OXR sensors.

8. How do the design (theoretical) wavelength ranges established for EMR and OXR sensors compare with the

typical performance values observed during commissioning the new sensors for the OSPREy activity?

The design specifications for the wavelength ranges used

with the four types of radiometers in the OSPREy activity are as follows:

EME 290–1,670 nm;

EML 300–1,670 nm;

OXE 244–1,670 nm; and

OXL 300–1,670 nm.

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These end-member values are based on the combined

specifications of the microradiometer and spectrograph

components. For an OSPREy system configuration

wherein two irradiance sensors are used to establish a

sensor triad (rather than a dyad), e.g., the spectral or

maximum systems (Fig. 44c and 44e, respectively), the

two wavelength ranges for the irradiance sensors are

290–1,100 nm and 1,000–1,670 nm. The standard diffuser for EME and OXE sensors cover the 244–1,670 nm

wavelength range.

The typical performance specifications for the wavelength ranges used with the four types of radiometers

in the OSPREy activity are as follows:

EME 305–1,640 nm;

EML 320–1,640 nm;

OXE 305–1,640 nm; and

OXL 320–1,640 nm.

These end-member values are based on the typical specifications of the microradiometer and spectrograph components as experienced in commissioning the first operational system in support of ACE and PACE.

The individual microradiometer specifications for the

wavelength ranges used with the four types of radiometers in the OSPREy activity are as follows:

EME 340–1,640 nm;

EML 340–1,640 nm;

OXE 340–1,640 nm; and

OXL 320–875 nm.

These end-member values are based on the manufacturer’s specifications and all the individual microradiometer wavebands are presented in Table 13.

The individual spectrograph specifications for the wavelength ranges used with the four types of radiometers

in the OSPREy activity are as follows:

EME 245–785 nm (Zeiss/Tec5 MMS UV-VIS II;

EML 300–1,150 nm (Zeiss/Tec5 MMS1);

OXE 244–785 nm (Zeiss/Tec5 MMS UV-VIS II; and

OXL 325–792 nm (Hamamatsu C9407MA).

These end-member values are based on the manufacturer’s specifications. The OXL was the first sensor

built for the OSPREy activity. The Hamamatsu spectrograph was used in the OXL, because at the time the

OXL was built alternatives were either not available or

were still undergoing testing.

9. What are the advantages and disadvantages of the microradiometer component of EMR and OXR sensors

compared to their spectrograph component?

Microradiometers offer a larger dynamic range, better

SNR, and higher sampling rates than the spectrograph

component. The main advantage of the spectrograph

is its higher spectral resolution. For EMR sensors,

the spectrograph filter-wheel assembly provides the additional advantages of polarization measurements and

improved stray-light correction. Spectrograph measurements, however, must be corrected for dark offset drifts,

stray light, and nonlinearity. Uncertainties of these corrections make measurements of the spectrograph component in general, less accurate than those of the microradiometer component, particularly nearing the lower

and upper ends of the spectral range. By combining the superiorities of microradiometer measurements

with the added spectral information obtained from spectrograph measurements, a superior sensor combination

is attained compared to either of the individual components alone (Chap. 8). For example, the spectrograph

measurements can be vicariously calibrated against the

microradiometer measurements (making the former as

accurate as the latter), while also providing spectral

information in regions of the solar spectrum where absorption by trace gases occurs.

10. How is the temperature of OXR and EMR sensors maintained?

There are two heating elements and temperature controllers in OXR and EMR sensors, which are designated

“primary” and “secondary.” The primary temperature

regulation is for the entire housing, so all components

benefit, and the secondary regulation is just for the

spectrograph. The instrument housing temperature is

maintained with a primary heater strip attached to the

inner microradiometer sleeve in the main housing (Fig.

3). The secondary heater element is integrated with

the spectrograph.

The primary temperature control uses an ultra-lownoise 15 VDC switching power source located in the

PCS; the internal electronics and spectrograph secondary temperature control uses a separate 12 VDC power

(Fig. 50). Rapidly switching power on and off using

a customary PID approach with the heater strip can

couple electrical noise into the optical measurements.

To preclude any adverse effects, the OXR and EMR

primary instrument housing temperature is stabilized

using a precision temperature controller operating in

an analog PI mode. This approach smoothly adjusts

the current to the heater strip without switching, ensuring temperature regulation of the main housing to

within 40◦C ±0.1◦C.

A similar arrangement for a secondary heater element

integrated with the spectrograph supports stable temperatures to better than ±0.03 ◦C. Gradients across the

spectrograph component are minimized by thermal insulation, but cannot be completely avoided and have

an effect on the dark offset for the spectrograph. Consequently, for the most accurate measurements, it is

necessary to measure the spectrograph dark offset several times throughout the day.

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

11. Are the spectral characteristics of OXR and EMR sensors fixed or predetermined?

No, the spectral characteristics of all OXR and EMR

sensors are neither fixed nor predetermined. There are,

however, size and communications protocol limitations

in choosing alternative spectrographs. Zeiss/Tec5 spectrographs are presently being used, although a Hamamatsu spectrograph was selected for the very first instrument that was built, which was the OXL. Consequently, these manufacturers and models that were selected are the easiest to consider for alternatives.

The microradiometer component of OXR and EMR

sensors can be populated with whatever filters the researcher desires (recalling that there are cosine response

specifications as a function of wavelength), but the cost

of the filters are less if they are selected from the existing BSI inventory (the current inventory of filters is

available at http://www.biospherical.com).

12. Why do all OXR sensors (OXE and OXL) and the

EME sensors have a maximum of 18 microradiometers,

whereas EML sensors can have 19 microradiometers?

OXR sensors are a class of laboratory irradiance (OXE)

and radiance (OXL) instruments designed in parallel

with the EMR field instruments. The OXR class shares

many of the same features and components with their

EMR equivalents. The OXE laboratory instrument

is functionally identical to the EME field instrument

(Chap. 8). The OXE and EME both replace one microradiometer position with the entrance optics of the

spectrograph, reducing the microradiometer complement to 18.

An important distinction between an OXL and EML

sensor is that the OXL lacks the spectrograph filterwheel assembly and integrated video camera that are

installed in the EML. The OXL replaces one microradiometer position with the entrance optics for the spectrograph, again reducing the microradiometer component to 18. For the EML, the spectrograph is external to the microradiometer cluster, and the maximum

number of microradiometers is 19 (Sect. 6.4.2).

13. What is the advantage of two irradiance sensors (Fig.

44c) with two different cosine responses rather than

one covering the combined range of the two (and vice

versa)?

The standard EME (irradiance) radiometer has a cosine response spanning 290–1,670 nm. This allows the

wide spectral range needed for next-generation missions

(e.g., ACE and PACE) to be satisfied in a single sensor.

Although this is a state-of-the-art accomplishment, the

cosine error is elevated in the SWIR domain, which

might not be acceptable for certain applications. To

make sure a highest-quality option is nonetheless available, two optimized cosine collectors can be used, but

this requires two sensors (Sect. 8.5).

14. What are the advantages of using an EML (radiance)

sensor as a sun photometer compared to other commercial alternatives?

An EML sensor has a large dynamic range of 10 decades,

a wide spectral range of 290–1,670 nm, and a high data

rate for the microradiometers (15 Hz). The large dynamic range allows sky, solar, and lunar measurements

across an unprecedented diversity of wavelengths. For

the spectrograph, the large dynamic range is achieved

by combining the ADC 15 bit dynamic range with the

option to change the integration time and use one of

two ND filters installed in the filter-wheel assembly,

which is in front of the spectrograph fiber. The AOD

can also be measured at night using the Moon.

The built-in (or added as a second device on a tracker)

video camera allows accurate Sun (Moon) tracking (to

better than ±0.1◦) and detection of clouds passing in

front of the solar (lunar) disk. The cloud detection can

also be accomplished using an EME (irradiance) sensor,

if it is part of the OSPREy system configuration, which

it is except for the starter system (Fig. 44a).

Commercially available sun photometers are typically

less capable by having one or more deficiencies with

respect to the following (Table 3):

a) Less than 10 fixed-wavelength channels, whereas

EML sensors have 19 fixed-wavelength channels;

b) No hyperspectral capability, whereas EML sensors

have a 256-pixel spectrograph;

c) No thermal regulation, whereas EML sensors are

thermally regulated;

d) No integrated camera, whereas EML sensors have

an integrated camera and can be used in conjunction with other camera configurations;

e) No easily accommodated polarization measurements

across a wide spectral range, whereas EML sensors

use a filter-wheel assembly to provide hyperspectral

polarization observations for three axes of polarization; and

f) No sensor networking (i.e., the instruments are standalone units), whereas EML sensors can be part of

a network or system configuration (Fig. 44) and the

tracker allows a second device to be pointed with

the EML instrument.

15. From the perspective of using an EML (radiance) sensor as a sun photometer, why is the FVA 2.5◦ with a

0.7 ◦ slope angle?

An EML radiometer is designed for multiple purposes,

one of which is to function as a sun photometer. When

viewing the Sun, the instrument should ideally only see

the solar disk, and not any scattered radiation originating from points close to the Sun, i.e., the aureole. From

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

this perspective alone, the FOV should be as small as

possible, but this must be considered with respect to

the angular size of the Sun when viewed from Earth

(0.527–0.545◦, over the course of the year), compensation for the pointing accuracies of the sun tracker,

and compliance with the recommendations and specifications for sun photometers as issued by cognizant

authorities (e.g., the WMO). The FVA of an EML

radiometer must also be large enough to allow accurate measurements of all sources considered by the OSPREy activity, including low-light applications (e.g.,

the Moon, which has a size when viewed from Earth

that is similar to the Sun).

Given these considerations, the specifications of most

COTS sun photometers (Table 3), and the multipurpose measurement objectives of EML (radiance) sensors (sea, sky, Sun, and Moon), the FOV for an EML

sensor was set to 2.5◦ FVA (Sect. 4.2). One advantage

regarding this specification is there are many sun photometers that use this specification (Table 3), although

the CE-318 sun photometer used with AERONET has

a 1.2◦ FVA.

As part of the work the OSPREy team did in selecting

the FVA for EMR and OXR sensors, a careful investigation of the resulting increases in uncertainty in using

a 2.5◦ versus 1.2◦ FVA was undertaken and the following conclusions were obtained:

For a 1.2◦ FVA, the measurement uncertainty is

smaller than 0.005 optical depth units for an AOD

value of up to 4.4.

For a 2.5◦ FVA, the measurement uncertainty is

smaller than 0.005 optical depth units for an AOD

value of up to 2.2.

In most environments, the AOD is not larger than

1.0, thus a 2.5◦ FVA is sufficiently small to calculate AOD with good accuracy for all but the most

extreme environments (e.g., Mexico City).

The effect of wavelength on the AOD uncertainty is

small.

Because the systematic error resulting from the finite FOV can be calculated, direct measurements

with the EML (radiance) sensor can be corrected

for this error before the AOD is retrieved. Such

a correction would increase the complexity of the

AOD retrieval, but it is a tractable calculation.

16. What data products are supported by EMR (radiance

and irradiance) sensors, and why is it advantageous to

derive one data product with more than one instrument?

Data products that can be retrieved by EMR sensors

are summarized in Table 17. Some data products can

be derived from measurements of more than one sensor, providing redundancy in case of equipment failure

and options for intercalibration. The latter is effective in detecting sensor drift and mechanical problems

in the tracking mechanisms. The ability to derive one

data product from two different methods (e.g., AOD

can be retrieved from measurements of the EML (radiance) sensor pointing at the Sun and from an EME

(irradiance) sensor equipped with a shadowband accessory) provides intercomparison opportunities, thereby

establishing additional confidence in the results and an

opportunity to detect problems as they occur, rather

than long after (the chance that two sensors would malfunction or degrade in exactly the same manner simultaneously is remote).

17. What OSPREy configuration can be used to replace a

SeaPRISM unit?

The simplest OSPREy configuration is the so-called

Starter System (Sect. 8.3), which uses a single radiance sensor to provide a starting point for automated

above-water radiometry or an advanced replacement

for a SeaPRISM unit (Fig. 44a). With respect to the

latter, a SeaPRISM unit is not hyperspectral, has many

fewer fixed-wavelength channels (eight), does not have

a video camera, and cannot measure channels simultaneously. In addition, any polarization capability reduces the number of unpolarized channels, and the

tracking ability of a SeaPRISM unit does not support

two devices at once.

The starter system is envisioned as a low-cost entry system, which can be incrementally improved as resources

or science objectives evolve. For example, a single radiance sensor can be used as an algorithm validation

system or a monitoring device, for atmospheric, terrestrial, and oceanic applications. An even lower cost,

and functionally more equivalent, SeaPRISM replacement can be constructed using an XTRA sensor and a

tracker.

18. Are radiance polarization measurements restricted to

the EML (radiance) spectrograph?

No, individual microradiometers can be fitted with glass

polarization filters. The disadvantage of this approach

is if multiple axes of polarization need to be measured,

then the number of microradiometers needed to accomplish the task is rather high, leaving fewer and fewer

unpolarized channels for those measurements. Because

Moxtek filters are too large and cannot be cut to fit

microradiometer fore optics, the most efficient way to

obtain high-quality polarized data is with the combination of using the spectrograph and filter-wheel assembly.

A SeaPRISM replacement using an XTRA sensor with

some polarization capabilities can be built by assigning 10 microradiometers for unpolarized observations

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

(SeaPRISM units have 8 wavelengths), and then having three wavelengths with three polarization axes each

(for a subtotal of 9 microradiometers used for polarization measurements, plus 10 making unpolarized observations, for a grand total of 19 microradiometers).

19. Can an OXR instrument be used in the field?

Yes, but there are limitations in what measurements

can be made with an OXL (radiance) sensor. Because

an OXL instrument does not have a filter-wheel assembly, there are no ND filters for the spectrograph, so it

saturates if pointed at a very bright target (e.g., the

Sun). OXL sensors do not have an integrated camera,

which compromises the built-in capability to track, but

a camera can be mounted on a tracker to provide this

missing capability.

There are, however, almost no limitations for OXE (irradiance) sensors. The only problem is that an OXE

is black and may overheat in direct sunlight. If it is

necessary to use an OXE outside, this problem can be

mitigated by wrapping the instrument housing with reflective material (e.g., aluminum foil), which has been

demonstrated to be effective.

20. Can an OSPREy system be used for terrestrial applications?

Yes, an OSPREy system appropriately mounted (e.g.,

perhaps on a tower) to view terrestrial targets can be

autonomously pointed to make appropriate radiance

and irradiance measurements to produce a reflectance

for terrestrial applications (Chap. 5). The advantage of

the OSPREy system is the excellent pointing accuracy

permits measurements at multiple nadir and azimuth

angles, thereby providing the opportunity for a more

complete description of the BRDF of the target.

21. Can an EMR (radiance or irradiance) sensor be used

as a transfer radiometer?

Yes, because for lamp transfers, the radiometer only

has to be stable over the period of the experiment (typically hours to days) and EMR sensors are stable over

a longer time period. The capabilities of an EMR sensor as a transfer radiometer are best retained over time

if the radiometer is used exclusively in the laboratory

and not subjected to the additional stresses of repeated

transportation, more extreme environmental cycling,

harsh weather, etc. In fact, there is no reason why

an OXR sensor should be more stable than an EMR

sensor, if both are kept in the laboratory.

One difficulty with an EML (radiance) sensor is the

physical separation of the spectrograph outside the cluster of microradiometers, so the spectrograph cannot

view the same spot on the target as the microradiometers. This problem requires two separate measurement

activities whereby the instrument has to be moved in

one measurement sequence, so the same target registration is achieved in both measurements. The OXL

sensor does not have this difficulty.

22. Can the wavelength filters used with the microradiometers in OXR and EMR sensors be changed?

Yes, the microradiometers in both OXR and EMR sensors can have the filters in the fore optics changed (Fig.

4). One of the advantages of instruments built with microradiometers is this procedure is greatly simplified in

comparison to legacy radiometers.

23. Can OXR and EMR sensors be built with microradiometer clusters that are not fully populated (i.e., less

than 18 or 19 microradiometers, depending on the sensor type), and then be upgraded later?

Yes, both OXR and EMR sensors can be cost effectively built with as few as eight microradiometers; a

fewer number of microradiometers would be a custom

configuration. Figure 6 (right) shows a full complement of 19 microradiometers, which plug in as whole

subunits, so reducing the number installed is trivial at

the construction stage. The number of microradiometers can be increased at any time up to the allowed

maximum for the radiance or irradiance sensor type

(FAQ 1). One of the advantages of sensors built with

microradiometers is they are rather modular and this

procedure is comparatively easy to accomplish (especially with respect to legacy sensors).

24. Can an OXL (radiance) instrument be used on a tracker

even though it does not have an integrated camera?

Yes, as long as an appropriate camera is available. The

tracker used in the OSPREy activity (the PTU-D300)

supports the mounting of devices on both sides of the

pedestal (Chap. 5). This means an OXL radiometer

can be mounted on one side and an appropriate camera on the other. The OSPREy data acquisition and

control software supports this configuration for having

the instrument track a target.

25. What is the advantage of the video camera when using

the tracker?

The angular variation when tracking with the video

camera is about ±0.03◦, although refinements to the

algorithm could theoretically improve this to ±0.02◦.

When using the ephemeris algorithm alone (no video

camera, and no adjustments as described in Chap. 5

and Fig. 22) an accuracy of ±0.2◦ is achievable, as long

as the tracker is perfectly level and the zenith and azimuth offsets are applied without error. In practice,

±0.3◦ is more realistic. So the camera that is currently

integrated into EML sensors improves the tracking accuracy by about an order of magnitude.

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

26. What are the advantages of being able to mount two

devices on a tracker?

One advantage is unique to the application of viewing the sky and sea surface to derive the water-leaving

radiance. For this measurement, the sky- and seaviewing radiometers use fixed-angle offsets with respect

to zenith and nadir (e.g., 40◦). This means a single

tracker can be used to point the two fixed-angle radiometers azimuthally with respect to the Sun (usually

90◦ or 135◦ away from the Sun plane).

Another opportunity is to mount a camera in the second position and point it in accordance with how a radiometer mounted in the first position is pointed. This

is an advantage if the radiometer does not have an integral camera or if the integrated camera is configured

for viewing an alternative target. For example, the

integrated camera in EML sensors are configured for

viewing the Sun and have an ND filter. This makes

the camera difficult to use when viewing the Moon, so

a second camera mounted on the tracker can facilitate

this problem.

27. Why does an EML (radiance) sensor have a shroud?

As noted in Sect. 4.2 (and FAQ 15), when viewing the

Sun, an EML sensor should ideally only see the solar

disk, and not any scattered radiation originating from

points close to the Sun, i.e., the aureole. The CE-318

sun photometer used by AERONET has a 1.2◦ FVA,

so the effect of the aureole is necessarily smaller than

for an EML sensor (2.5◦ FVA). In the direct viewing of

the Sun, there is no mitigation that can be applied to

overcome the larger FVA of an EML sensor, which was

a compromise value selected to satisfy the multipurpose sampling objectives of OSPREy systems. There

is another aspect to the aureole problem, however, that

can be mitigated.

The other issue is the effect of direct sunlight when

looking at the sky. Any contamination on the front

window scatters direct sunlight on the detector when

pointing at the sky, and this is an important source of

uncertainty. The problem is greater for an EML (radiance) sensor than a CE-318, because the front window

of the former is close to the top of the instrument. In

contrast, the Gershun tube of the CE-318 extends well

beyond the front window. Consequently, a shroud is

mounted at the front of the EML (radiance) sensor to

shade the window from this contamination when viewing the sky (Sect. 4.5).

28. What is the advantage of the BioSHADE (shadowband) accessory?

The shadowband accessory (App. E) allows the measurement of the diffuse (sky) irradiance, which complements the measurement of global irradiance provided

by the EME (irradiance) radiometer (Fig. 45). From

the two components, the direct irradiance can be calculated, which in turn allows the retrieval of AOD,

aerosol size distribution, and calibration of the sensor

from the Langley technique. Direct irradiance measurements and related data products can be compared

with similar data products obtained when the EML

(radiance) sensor views the Sun.

29. What is a NEMA 4X rating and why is it used in an

OSPREy system?

NEMA 4 enclosures are specified for use in applications where an occasional wash down of the enclosure

occurs or where exposure to pressurized water is possible. NEMA 4 enclosures have doors with gasket seals,

and the door is clamped for maximum sealing. The

4X rating specifies the use of stainless steel or plastic

(noncorrosive materials) for all exterior enclosure components, and are typically used in harsh environments

(e.g., the marine environment). NEMA 4X enclosures

are used with the OSPREy system, specifically the PCS

unit, to ensure proper protection of PCS components

against the harsh marine environment (Sect. 8.2.4).

Glossary

AC Alternate Current

ACE Aerosol-Cloud-Ecosystems

ACM Archive and Communications Master

ADC Analog-to-Digital Converter

ADCP Acoustic Doppler Current Profiler

AERONET Aerosol Robotic Network

AGM Absorbent Glass Matt

AOD Aerosol Optical Depth

AOPs Apparent Optical Properties

ASCII American Standard Code for Information Interchange

BioSHADE Biospherical Shadowband Accessory for Diffuse Irradiance

BioSORS Biospherical Surface Ocean Reflectance System

BOUSSOLE Bou ́ee pour l’acquisition de S ́eries Optiques `a

Long Terme

BRDF Bidirectional Reflectance Distribution Function

BSI Biospherical Instruments Inc.

CALIPSO Cloud-Aerosol Lidar and Infrared Pathfinder

Satellite Observations

CCA Climate-Centric Architecture

CCD Charge-Coupled Device

CDOM Colored Dissolved Organic Matter

CDR Climate-quality Data Records

CD-ROM Compact Disc-Read Only Memory

CMOS Complementary Metal Oxide Semiconductor

C-OPS Compact Optical Profiling System

COTS Commercial-Off-The-Shelf

CTD Conductivity, Temperature, And Depth

CUCF Central UV Calibration Facility

CZCS Coastal Zone Color Scanner

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

DC Direct Current

DIN Deutsches Institut f ̈ur Normung (German Institute for Standardization)

DOT Department of Transportation (US)

DXW Not an acronym, but a lamp code.

ENVISAT Environmental Satellite

EME EPIC Multitarget Irradiance (radiometer)

EML EPIC Multitarget Radiance (radiometer)

EMR EPIC Multitarget Radiometer

EOS Earth Observing System

EPIC Enhanced Performance Instrument Class

ESA European Space Agency

ESRL Earth System Research Laboratory

ETS Extraterrestrial Spectrum

FAD Fish Attraction Device

FAQ Frequently Asked Question

FASCAL Facility For Spectroradiometric Calibrations

FEL Not an acronym, but a lamp code.

FLIR Not an acronym, but part of the name of FLIR

Motion Control Systems, Inc.

FMCW Frequency Modulated Continuous Wave

FOV Field of View

FVA Full View Angle

FWHM Full Width at Half Maximum

GAW Global Atmosphere Watch

GEO-CAPE Geostationary Coastal and Air Pollution

Events

GMD Global Monitoring Division

GPS Global Positioning System

GRNMS Gray’s Reef National Marine Sanctuary

GSFC Goddard Space Flight Center

GUV Ground-based Ultraviolet

HDS Horizontal Displacement System

HEC Hoffman Engineering Corporation

HPLC High Performance Liquid Chromatography

HyspIRI Hyperspectral Infrared Imager

InGaAs Indium Gallium Arsenide

IOPs Inherent Optical Properties

IP Internet Protocol or Ingress Protection if appearing with a numeric value (e.g., IP67)

JGOFS Joint Global Ocean Flux Study

LADWP Los Angeles Department of Water and Power

LAN Local Area Network

LED Light-Emitting Diode

LOV Laboratoire d’Oc ́eanographie de Villefranche

MCAS Marine Corps Air Station

MERIS Medium Resolution Imaging Spectrometer

MFRSR Multi-Filter Rotating Shadowband Radiometers

MMS Multiple Microradiometer System (from BSI),

or Monolithic Miniature-Spectrometer (from

Zeiss/Tec5), depending on usage.

MOBY Marine Optical Buoy

MODIS Moderate Resolution Imaging Spectroradiometer

MODIS-A MODIS Aqua platform

MODIS-T MODIS Terra platform

NAS National Academy of Sciences

NASA National Aeronautics and Space Administration

NBS National Bureau of Standards

ND Neutral Density

NDS NRC Decadal Survey

NEI Noise Equivalent Irradiance

NEMA National Electrical Manufacturers Association

NER Noise Equivalent Radiance

NIR Near Infrared

NIST National Institute of Standards and Technology

NMOS Negative Metal Oxide Semiconductor

NOAA National Oceanic and Atmospheric Administration

NOMAD NASA Bio-Optical Marine Algorithm Data

NOPP National Oceanographic Partnership Program

NPOESS National Polar Orbiting Environmental Satellite System

NPP NPOESS Preparatory Project

NRC National Research Council

NSF National Science Foundation

OBB Ocean Biology and Biogeochemistry

OD Optical Depth

OEM Original Equipment Manufacturer

ORM Ocean-Surface Reflectance Model

OSPREy Optical Sensors for Planetary Radiant Energy

OXE OSPREy Transfer Irradiance (radiometer)

OXL OSPREy Transfer Radiance (radiometer)

OXR OSPREy Transfer Radiometer

PACE Pre-Aerosol, Clouds, and Ocean Ecosystem

PAR Photosynthetically Available Radiation

PARASOL Polarization and Anisotropy of Reflectances

for Atmospheric Sciences Coupled with Observations from Lidar

PC Personal Computer

PCS Power and Component Scheduler

PDA Photo-Diode Array

PDF Portable Document Format

PI Proportional-Integral

PID Proportional-Integral-Derivative

PlyMBODy Plymouth Marine Bio-optical Data Buoy

PML Plymouth Marine Laboratory

PMOD Physikalisch-Meteorologisches Observatorium

Davos

pPTFE Porous PTFE

PRR Profiling Reflectance Radiometer

PTFE Polytetrafluoroethylene

PTU Pan Tilt Unit

PURLS Portable Universal Radiometer Light Source

PV Photovoltaic

PWV Precipitable Water Vapor

Q02 An above-water method formulated using the

Morel and Mueller (2002) bidirectional correction.

QA Quality Assurance

QC Quality Control

RAID Redundant Array Of Independent Drives

RAM Random Access Memory

RPD Relative Percent Difference

RS Recommended Standard

RT Radiative Transfer

R/V Research Vessel

S01 An above-water method formulated using the

Mobley (1999) determination of ρ and including wind effects (Hooker et al. 2003).

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S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

S95 An above-water method formulated using the

SeaWiFS 1995 revision of the Ocean Optics

Protocols.

SAB South Atlantic Bight

SABSOON South Atlantic Bight (SAB) Synoptic Ocean

Observing Network

SBIR Small Business Innovation Research

SeaBASS SeaWiFS Bio-Optical Archive and Storage

System

SeaPRISM SeaWiFS Photometer Revision for Incident

Surface Measurements

SeaWiFS Sea-viewing Wide Field-of-View Sensor

SHALLO Submersible Hydro-optical Applications for

Light-Limited Oceanography

SIRCUS Spectral Irradiance and Radiance Responsivity Calibrations using Uniform Sources

SkIO Skidaway Institute of Oceanography

SNR Signal-to-Noise Ratio

SQL Structured Query Language

SQM SeaWiFS Quality Monitor

SSA Single Scattering Albedo

SSD Solid-State Disk

SuBOPS Submersible Biospherical Optical Profiling

System

SWIR Short-Wave Infrared

SXR SeaWiFS Transfer Radiometer

TDRSS Tracking and Data Relay Satellite System

TE Thermoelectric

UPS Uninterruptible Power Supply

USB Universal Serial Bus

USDA United States Department of Agriculture

UV Ultraviolet

UV-B Ultraviolet-B

UVSIMN Ultraviolet Spectral Irradiance Monitoring

Network

VIIRS Visible and Infrared Imaging Radiometer Suite

VIS Visible

VSAT Very Small Aperture Terminal

WMO World Meteorological Organization

WRC World Radiation Center

XGUV GUV-based Transfer Radiometer

YES Yankee Environmental Systems

Symbols

A The signal amplitude.

A




A calibration value signal amplitude.

A

•

The night (dark) signal amplitude.

A

•




The ambient or occluded calibration (dark) signal amplitude.

A




The background or shutter (dark) signal amplitude.

A

•

The dark signal amplitude that is obtained with

a capped sensor.

A

•

The shadowband night (dark) signal amplitude.

AAn ideal value signal amplitude.

A

A true value signal amplitude.

A•• The two-gain stage sensor dark signal amplitude.

•••

A The three-gain stage sensor dark signal amplitude.

A•◦ The high gain of a two-gain sensor signal amplitude.

A◦• The low gain of a two-gain sensor signal amplitude.

•◦◦

A The high gain of a three-gain sensor signal amplitude.

◦•◦

A The medium gain of a three-gain sensor signal

amplitude.

◦◦•

A The low gain of a three-gain sensor signal amplitude.

A

•

◦◦• The low gain (of a three-gain sensor) signal amplitude obtained with a capped sensor.

A




The sky signal amplitude.

A




The sea signal amplitude.

A

∗

The solar signal amplitude.

A

◦

The lunar signal amplitude.

A

∗

The direct-Sun signal amplitude.

A

◦

The direct-Moon signal amplitude.

A



The shadowband sky signal amplitude.

A

∗

The shadowband solar global irradiance (Sun

and sky) signal amplitude.

A

◦

The shadowband lunar (Moon and sky) signal

amplitude.

A






The FEL lamp calibration signal amplitude.

A

∗




The solar calibration signal amplitude.

A

◦




The lunar calibration signal amplitude.

A






The plaque calibration signal amplitude.

Ca The chlorophyll a concentration.

dp The distance between the aperture and the photodetector.

ei An indexed term to establish a particular interaction effect.

e1 The first interaction effect.

e2 The second interaction effect.

E Irradiance.

E(λ, ti) Net irradiance detected by the radiometer while

exposed to light.

E0(λ) The irradiance at the top of the atmosphere.

Ed(λ) In-water spectral downward irradiance.

Ed(0+) The downward irradiance above the water surface (the global solar irradiance).

Ed(0-) The downward irradiance at null depth).

EF The spectral irradiance from an FEL lamp.

Ei(λ) The diffuse irradiance.

El(λ) The (unknown) spectral irradiance of a lamp.

En(λ) The solar direct irradiance at the surface of the

Earth for an overhead Sun.

Es(λ) The spectral global irradiance from the Sun.

Es(λi) The spectral global irradiance at λi referenced

to a bandpass of 1 nm.

Eu(0-) The upward irradiance at null depth.

Eu(λ) The in-water spectral upward irradiance.

F The measurements of an FEL lamp.

f(λ) The fit function.

H The height of the tower superstructure.

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OSPREy: Calibration and Validation of Current and Next-Generation NASA Missions

k The coverage factor.

L Radiance.

c The centerline distance between the surface of

the plaque and the front of the lamp posts.

Li(λ) The sky radiance.

LP (λ) The radiance of the plaque.

r The reference distance for a standard lamp measured from the front of the lamp posts (50 cm for

a NIST standard lamp).

LT (λ) The total radiance emanating from the sea surface.

Lu(0-) The upwelling radiance.

Lu(z, λ) The vertical profiles of upwelled radiance.

LW (λ) The water-leaving radiance.

LˆW (λ) The water-leaving radiances from an abovewater method.

L ̃W (λ) The water-leaving radiances from an in-water

method.



LW (λ)



N The normalized water-leaving radiance.

Lj

T (λ) The total sea radiance from a hybridspectral instrument, wherein LM

T (λ) denotes the microradiometer data and LS

T (λ) denotes the hyperspectral spectrograph data.

M A superscript to indicate the microradiometer

data.

M The maximum level of signal saturation.

Ns The number of samples.

N The noise equivalent signal.

NE(λ) The NEI of the spectrograph.

NL(λ) The NER of the spectrograph.

NM

E (λ) The NEI computed for the microradiometers.

NM

E (λ) The mean NEI computed for the microradiometers.

NS

E(λ) The NEI computed for the spectrograph.

NS

E(λ) The mean NEI computed for the spectrograph.

P The measurements of a Spectralon plaque.

P(λ) The Planck functions.

P A radiometric parameter of interest.

P A radiometric parameter of interest for a hybridspectral sensor.

Q The bidirectional function for the radiance field,

which is expressed as an irradiance-to-radiance

ratio.

Qn The Q function for nadir-viewing measurements.

R(0-) The irradiance reflectance, Eu(0-)/Ed(0-).

r(x, λr) A diagnostic variable expressing departures in

the spatial distribution of the radiance field, specifically departures caused by platform perturbations.

ra The radius of the front aperture.

rp The radius of the circular opening of a photodetector mount.

Rrs The remote sensing reflectance.

 The merged effects of reflection and refraction.

0  evaluated at nadir.

S A superscript to indicate the spectroradiometer

data.

S The signal noise.

S The mean signal noise.

ti The integration time.

u

(λ) The relative uncertainty.

W Wind speed.

X The above-water observation.

x The generalized horizontal direction.

xa The horizontal position of the Sun converted to

angular variation.

xo The observation.

xp The horizontal position of the center pixel.

Y The in-water (reference) value.

x The generalized meridional direction.

ya The vertical position of the Sun converted to

angular variation.

yp The vertical position of the center pixel.

yr The reference value.

z The vertical (depth) coordinate, where the depth

is the height of water above the cosine collectors.

z = 0- A depth immediately below the sea surface (the

null depth).

z = 0+ A height immediately above the sea surface.

α The surface spot viewed by the sea-viewing sensor.

β The pointing angle with respect to the Sun.

γ The responsivity.

γ(λ) The responsivity defined with the calibration

coefficient.

γ(λ, ) The responsivity defined with the calibration

coefficient and the immersion factor.

γi(λ) The spectral response function of channel i.

Γl(λi) The lamp comparison ratio at channel λi.

(λ) The immersion factor interaction effect.

δ Difference.

Δ The offset distance between the center of the

lamp filament and the front of the lamp posts.

ΔL The simulated radiance.

δλ The wavelength resolution.

ηi A fit coefficient (for i = 1, 2,... , 8).

θs The solar zenith angle.

θ The above-water viewing angle (θ) refracted by

the air–sea interface.

θ The nadir viewing angle.

θ A zenith angle.

κ(λ) The maximum (or saturation) signal level.

λ Wavelength.

λi A particular wavelength (or channel).

λc The centroid wavelength.

λc

i The centroid wavelength of channel i.

λR The spectral range.

λr A reference (NIR) wavelength.

112
S.B. Hooker, G. Bernhard, J.H. Morrow, C.R. Booth, T. Comer, R. Lind, and V. Quang

μ A mean value.

μ(λ) The mean value of light data.

μ

•

(λ) The mean value of (capped) dark data.

μ(λ) The mean value of dark data.

μM

E (λ) The average light signal amplitude.

μl(λi) The 1 min mean of light data for the transfer

radiometer when measuring lamp l with channel

λi.

μM

L (λ) The light average signal amplitude.

μr(λi) The 1 min mean of light data for the transfer

radiometer when measuring reference lamp r

(F-616) with channel λi.

μl(λi) The 1 min mean of dark data for the transfer

radiometer when measuring lamp l with channel

λi.

μr(λi) The 1 min mean of dark data for the transfer

radiometer when measuring reference lamp r

(F-616) with channel λi.

μS

L(λ) The mean value of dark data for the spectrograph data of a hybridspectral radiance sensor.

ρ The surface reflectance.

ρ(W) The surface reflectance when dependent on wind

speed.

ρP (λ) The spectral reflectance factor of the plaque (for

an incidence angle of 0◦ and a viewing angle of

45◦).

σ A standard deviation.

σ(λ) The standard deviation for light data.

σ

•

(λ) The standard deviation of the (capped) dark

data.

σ(λ) The standard deviation of the dark data.

Υ The ratio of the signals when comparing lamps.

Υ The simplified lamp ratio.

φ The azimuth angle.

φ The sensor pointing angle away from the Sun

(90◦ or 135◦).

Φ(λ) The analytical fit function.

Φl(λc

i ) The value of the fit function of lamp l at the centroid wavelength that is associated with channel

i.

Φr(λc

i ) The value of the fit function of reference lamp

r (F-616) at the centroid wavelength that is associated with channel i.

ψ The RPD.

Ω A solid angle.

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31-07-2012 Technical Memorandum

Optical Sensors for Planetary Radiant Energy (OSPREy):

Calibration and Validation of Current and Next-Generation

NASA Missions

Stanford B. Hooker, Germar Bernhard, John H. Morrow, Charles R. Booth,

Thomas Comer, Randall N. Lind, and Vi Quang

NASA Goddard Space Flight Center

Code 616.2

Greenbelt, Maryland 20771

National Aeronautics and Space Administration

Washington, DC 20546-0001

TM-2012-215872

Unclassified-Unlimited, Subject Category: 25, 48

Report available from the NASA Center for Aerospace Information, 7115 Standard Drive, Hanover, MD 21076. (443)757-5802

Germar Bernhard, John H. Morrow, Charles R. Booth, Thomas Comer, Randall N. Lind, and Vi Quang; Biospherical Instruments

Inc., San Diego, CA

A principal objective of the Optical Sensors for Planetary Radiance Energy (OSPREy) activity is to establish an above-water radiometer system as

a lower-cost alternative to existing in-water systems for the collection of ground-truth observations. The goal is to be able to make high-quality

measurements satisfying the accuracy requirements for the vicarious calibration and algorithm validation of next-generation satellites that make

ocean color and atmospheric measurements. This means the measurements will have a documented uncertainty satisfying the established

performance metrics for producing climate-quality data records. The OSPREy approach is based on enhancing commercial-off-the-shelf

fixed-wavelength and hyperspectral sensors to create hybridspectral instruments with an improved accuracy and spectral resolution, as well as a

dynamic range permitting sea, Sun, sky, and Moon observations. Greater spectral diversity in the ultraviolet (UV) will be exploited to separate the

living and nonliving components of marine ecosystems; UV bands will also be used to flag and improve atmospheric correction algorithms in the

presence of absorbing aerosols. The short-wave infrared (SWIR) is expected to improve atmospheric correction, because the ocean is

radiometrically blacker at these wavelengths. This report describes the development of the sensors, including unique capabilities like three-axis

polarimetry; the documented uncertainty will be presented in a subsequent report.

OSPREy, AOP, light sensor, radiometer, microradiometer, COTS, C-OPS, solar reference, optically complex water

 Unclassified Unclassified Unclassified

Unclassified

117

Stanford B. Hooker

(301) 286-9503