NASA Technical Memorandum 104566, Vol. 25

SeaWiFS Technical Report Series

Stanford B. Hooker, Elaine R. Firestone, and James G. Acker, Editors

Volume 25, Ocean Optics Protocols for SeaWiFS

Validation, Revision 1

James L. Mueller and Roswell W. Austin

February 1995
NASA Technical Memorandum 104566, Vol. 25

SeaWiFS Technical Report Series

Stanford B. Hooker, Editor

NASA Goddard Space Flight Center

Greenbelt, Maryland

Elaine R. Firestone, Technical Editor

General Sciences Corporation

Laurel, Maryland

James G. Acker, Technical Editor

Hughes STX

Lanham, Maryland

Volume 25, Ocean Optics Protocols

for SeaWiFS Validation, Revision 1

James L. Mueller and Roswell W. Austin

Center for Hydro-Optics and Remote Sensing

San Diego State University

San Diego, California

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

1995
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Preface

This document stipulates protocols for measuring bio-optical and radiometric data for Sea-viewing Wide Fieldof-viewSensor (SeaWiFS) algorithm development and system validation. The protocols begin in Chapter 2,

with specifications of the measured variables which are to be included in data sets for validation of the SeaWiFS system’s radiometric performance, algorithm development, and algorithm validation. The protocols in

Chapter 3 specify the engineering performance characteristics required of radiometers, optical instruments, and

other instrumentation used to measure these variables at sea. Chapter 4 details laboratory and field protocols

for characterizing and calibrating each type of instrument. Procedures for actually measuring the validation

variables are given in Chapter 5, and protocols for both data processing and methods of analysis are described

in Chapter 6.

This volume, Revision 1, supersedes the earlier version (Mueller and Austin 1992) published as Volume 5 in the

SeaWiFS Technical Report Series. Instrument performance specifications have been modified slightly from the

previous version (e.g., radiometric saturation levels have been increased, and there are wavelength changes for

some channels). Pigment protocols have been strengthened [R. Bidigare]† primarily to discriminate divinyl and

monovinyl chlorophyll a. Spectrophotometric absorption protocols have also been expanded and reorganized [C.

Trees, B. Mitchell, J. Cleveland, C. Roesler, C. Yentsch, and D. Phinney]. Newprotocols have been added for

in situ measurements of spectral absorption and backscattering [R. Zaneveld], for above-water measurements

of water-leaving radiance from ships and low-flying aircraft [R. Doerffer, K. Carder, and C. Davis], and for

sampling in Case-2 water [R. Doerffer, K. Carder, C. Davis, and R. Arnone].

In general, the specifications and protocols set forth here simply describe and adapt instrument specifications

and procedures that are common practice in the ocean optics community. In several areas, however, protocols

call for significant improvements over today’s instruments and practices; these very challenging protocols should,

at least for the present, be regarded more as goals than as strict requirements. The motives for adopting these

goals as protocols are that the improvements called for are necessary to meet the rigorous SeaWiFS uncertainty

goals, and that the community feels these standards can be closely approached with a significant but affordable

effort. Areas in which new research and development must be done to satisfy challenging protocols, and those

areas in which there has been recent progress, are summarized below.

1. Model sensitivity studies and experimental verification are needed to develop methods for adjusting

in situ radiometric measurements at a given wavelength to correspond to SeaWiFS measurements at

a wavelength as much as 4 nm away, and with a different spectral response function (Sections 3.1.1

and 6.1.7).

2. Laboratory research is needed to improve absolute standards of irradiance and radiance, and associated

absolute calibration procedures, to achieve or approach 1% internal consistency in the responsivity

calibrations of radiometers to be used in SeaWiFS validation experiments (Section 4.2). The SeaWiFS

Intercalibration Round-Robin Experiment (SIRREX) program has made significant progress in this

area (Mueller 1993 and Mueller et al. 1994).

3. Radiometric linearity test procedures must be improved to extend linearity characterizations over the

full operating dynamic ranges (Table 4) of the various irradiance and radiance sensors (Section 4.1.7).

This is especially critical for downwelling irradiance measurements at the sea surface, where irradiances

of laboratory irradiance standards are only 2–15% (depending on wavelength) of saturation irradiance.

4. Instrument self-shading effects are a significant, but probably correctable, source of error (Sections 3.1.8, 5.1.6, and 6.1.7). The diameter of a radiometer determines whether or not self-shading

error can be corrected to within less than 5%. The maximum diameter which enables such a correction varies with the absorption coefficient, and is therefore a function of wavelength, water mass, and

the solar zenith angle. For oligotrophic to moderately turbid coastal water masses, wavelengths less

† Names in brackets are the principal contributors to the revised protocols.

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Mueller and Austin

than 600 nm, and solar zenith angles greater than 30◦, upwelled irradiance and radiance data from

many of the currently popular radiometers having diameters of 20–40 cm can be adequately corrected.

In more general conditions, however, new instruments must be developed to minimize self-shading

effects, particularly for near-infrared wavelengths and in Case-2 waters. Self-shading corrections have

been partially verified in recent experiments and a provisional protocol is included in this revision.

5. Measurements following the stringent protocols for avoiding ship shadows and reflections will require

exclusive use of profiling radiometer configurations which are not widely used today (Section 5.1.1).

Tethered free-fall systems appear to offer the most economical approach to meeting these requirements.

More sophisticated and expensive approaches include optical systems on either remotely operated

vehicles (ROVs), or on small surface platforms with self-contained winches.

6. Quantitative characterization of polarization sensitivity is critical for any airborne radiometer to be

used for SeaWiFS radiometric validation, or algorithm development and validation. Protocols and

procedures for polarization sensitivity characterization must be developed in more specific detail than

was accomplished here because of time constraints (Sections 3.3 and 4.3).

7. The uncertainties specified here for cosine responses of irradiance collectors are significantly better

than is typically realized in commercially available radiometers (Section 3.1.5). Moreover, the specified uncertainties may challenge the precision of the laboratory procedures used to characterize an

instrument’s cosine response (Section 4.1.5). Error in cosine response almost directly translates to an

equivalent error in downwelling irradiance for the clear-skies case so critical to the SeaWiFS validation. Therefore, a significant effort to carefully characterize the effect, and to work with instrument

manufacturers to approach or achieve the specific uncertainties, is an important factor in our strategy

for reducing the overall error budget for water-leaving radiance measurements to less than 5%.

8. The use of a portable standard to trace a radiometer’s performance stability during the course of

a field deployment is called for in the present protocols (Section 4.2.5). Several manufacturers offer

reasonably portable radiometric sources, which may be suitable for this purpose, but laboratory

and field evaluations must be carried out to prove their suitability and to develop newand detailed

procedures for their use in the field. The SeaWiFS Project Office (SPO) has sponsored work at the

National Institute of Standards and Technology (NIST) to develop a prototype system.

9. The present protocols for deploying and analyzing data from moored and free-drifting optical systems

are tentative, preliminary, and incomplete. Although moored and drifting optical systems have been

used successfully in several oceanographic experiments, there are no previous examples of their use

for ocean color remote sensing algorithm development, or for radiometric validation of airborne or

satellite radiometers. Newmoored and drifting optical systems are currently being developed and

tested in preparation for applications to SeaWiFS validation; significant progress has been made under

the Marine Optical Buoy (MOBY) program (D. Clark). As results from this effort become available,

new and detailed protocols for making these measurements will be developed and distributed with

the next revision.

The protocols and recommendations in this document attempt to represent and consolidate the contributions

of both the workshop participants and of many other individuals who participated in the review process. The

final document, however, has by necessity been interpreted and rewritten by the authors, who accept full

responsibility for any remaining mistakes and misrepresentations. As can be readily deduced from the above

list of critically needed improvements, this document is an unfinished work in progress to establish protocols

for ocean optical measurements. It will be appropriate to develop and issue a further revised set of protocols

reflecting our collective experience in post-launch algorithm development and validation activities after the first

year of operation of the SeaWiFS instrument.

San Diego, California — J. L. Mueller

December 1994

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Table of Contents

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

1. Overviewof SeaWiFS Bio-Optical Requirements .................................................... 3

1.1 Objectives ......................................................................................... 3

1.2 Sensor Calibration ................................................................................. 4

1.3 Bio-Optical Algorithms ............................................................................. 5

1.4 Community Participation ........................................................................... 5

1.5 Vicarious Calibration ............................................................................... 5

2. Data Requirements .................................................................................7

2.1 Definitions ......................................................................................... 7

2.2 Biogeochemical Data ...............................................................................9

2.3 Above-Water Techniques ..........................................................................11

2.4 Ancillary Measurements .......................................................................... 11

2.5 Optical Moorings ................................................................................. 11

2.6 Drifting Optical Buoys ............................................................................12

3. Specifications ..................................................................................... 13

3.1 In-Water Radiometers ............................................................................ 13

3.1.1 Spectral Characteristics .......................................................................... 13

3.1.2 Responsivity, SNR, and Resolution ............................................................... 14

3.1.3 Linearity and Stability ........................................................................... 16

3.1.4 Sampling Resolution ..............................................................................16

3.1.5 Angular Response Characteristics .................................................................16

3.1.6 Operating Depth ................................................................................. 16

3.1.7 Instrument Attitude .............................................................................. 16

3.1.8 Red and Near-Infrared Wavelengths .............................................................. 16

3.2 Surface Irradiance ................................................................................ 17

3.2.1 Surface Radiometer Characteristics ............................................................... 17

3.3 Above-Water Radiometry ......................................................................... 17

3.4 IOP Instruments ..................................................................................18

3.5 Atmospheric Aerosols .............................................................................19

3.6 Spectral Sky Radiance ............................................................................ 19

3.7 Phytoplankton Pigments ..........................................................................19

3.8 Hydrographic Profiles ............................................................................. 19

4. Sensor Characterization ...........................................................................20

4.1 Radiometry .......................................................................................20

4.1.1 Absolute Radiometric Calibration .................................................................20

4.1.2 Spectral Bandpass Characterization ...............................................................21

4.1.3 Temporal Response ...............................................................................22

4.1.4 Radiance Field-of-View ........................................................................... 22

4.1.5 Collector Cosine Response ........................................................................ 22

4.1.6 Immersion Factors ................................................................................24

4.1.7 Linearity and Electronic Uncertainty ..............................................................25

4.1.8 Temperature Characterization .................................................................... 25

4.1.9 Pressure Effects .................................................................................. 26

4.1.10 Pressure Transducer Calibration .................................................................. 26

4.2 Radiometric Standards ........................................................................... 26

4.2.1 Lamp Irradiance Standards ....................................................................... 26

4.2.2 Radiance ......................................................................................... 26

4.2.3 Radiance Standardization ........................................................................ 27

4.2.4 Traceability and Comparisons .................................................................... 27

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Mueller and Austin

Table of Contents cont.

4.2.5 Portable Standards ............................................................................... 27

4.3 Above-Water Radiometry ......................................................................... 28

4.4 Calibration of IOP Meters ........................................................................ 29

4.5 Sun Photometers ................................................................................. 29

4.6 Sky Radiance Cameras ........................................................................... 30

4.7 Pigment Calibrations ............................................................................. 30

4.8 CTD Calibrations ................................................................................ 30

5. Measurement Protocols ........................................................................... 31

5.1 Irradiance and Radiance .......................................................................... 31

5.1.1 Ship ShadowAvoidance .......................................................................... 31

5.1.2 Depth Resolution in Profiles ...................................................................... 32

5.1.3 Instrument Dark Readings ........................................................................32

5.1.4 Surface Incident Irradiance ....................................................................... 32

5.1.5 Instrument Attitude ...............................................................................33

5.1.6 Instrument Self-Shading .......................................................................... 33

5.1.7 Airborne Ocean Color Radiometry ................................................................33

5.1.8 Shipboard Radiance Measurements ............................................................... 34

5.2 Ancillary Profiles ................................................................................. 35

5.2.1 Beam Transmittance ............................................................................. 35

5.2.2 Chlorophyll a Fluorescence ....................................................................... 36

5.2.3 CTD Profiles ..................................................................................... 36

5.2.4 Spectral Absorption Profiles ...................................................................... 36

5.2.5 Backscattering Profiles ........................................................................... 38

5.3 Atmospheric Radiometry ......................................................................... 38

5.3.1 Sun Photometry ..................................................................................38

5.3.2 Sky Radiance Distribution ........................................................................39

5.4 Water Samples ................................................................................... 39

5.4.1 Pigment Analysis .................................................................................39

5.4.2 Spectrophotometric Absorption ................................................................... 40

5.4.3 Total Suspended Matter .......................................................................... 42

5.5 Ancillary Observations ............................................................................42

5.6 Prototype Optical Buoy .......................................................................... 42

5.7 Drifting Optical Buoys ............................................................................43

5.8 Sampling and Validation ..........................................................................43

5.8.1 Initialization and Validation ...................................................................... 45

5.8.2 Case-1 Water Protocols ...........................................................................45

5.8.3 Case-2 Water Protocols ...........................................................................46

5.8.4 Case-2 Sampling Strategy ........................................................................ 46

5.9 Vicarious Calibrations ............................................................................ 47

6. Analytical Methods ............................................................................... 48

6.1 In-Water Radiometry ............................................................................. 48

6.1.1 Instrument Calibration Analysis .................................................................. 49

6.1.2 Raman Corrections ............................................................................... 49

6.1.3 Normalization by Surface Irradiance .............................................................. 49

6.1.4 K-Analysis .......................................................................................49

6.1.5 Finite Bandwidth Correction ..................................................................... 52

6.1.6 Extrapolation to the Sea Surface ..................................................................52

6.1.7 Instrument Self-Shading Corrections .............................................................. 52

6.1.8 Spectral Adjustments .............................................................................53

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Table of Contents cont.

6.1.9 Normalized Water-Leaving Radiance ..............................................................53

6.2 Above-Water Radiance ........................................................................... 54

6.3 Moored Radiometry .............................................................................. 55

6.4 Aerosol Optical Depth ............................................................................ 55

6.5 Sky Radiance .....................................................................................55

6.6 Phytoplankton Pigments ..........................................................................56

6.6.1 HPLC Pigment Concentration .................................................................... 56

6.6.2 Fluorometric Determination ...................................................................... 56

6.6.3 In Situ Chlorophyll a Fluorescence ............................................................... 56

6.7 Beam Attenuation ................................................................................ 56

6.8 Spectral Absorption .............................................................................. 56

6.8.1 Reflective Tube Measurements .................................................................... 56

6.8.2 Analysis of Absorption Spectra ................................................................... 58

6.9 CTD Profile Analyses .............................................................................59

Acknowledgments .................................................................................... 60

Glossary ...............................................................................................60

Symbols ................................................................................................ 61

References ............................................................................................ 63

The SeaWiFS Technical Report Series ............................................................ 66

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Mueller and Austin

Abstract

This report presents protocols for measuring optical properties, and other environmental variables, to validate the

radiometric performance of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and to develop and validate

bio-optical algorithms for use with SeaWiFS data. The protocols are intended to establish foundations for a

measurement strategy to verify the challenging SeaWiFS uncertainty goals of 5% in water-leaving radiances and

35% in chlorophyll a concentration. The protocols first specify the variables which must be measured, and briefly

reviewthe rationale for measuring each variable. Subsequent chapters cover detailed protocols for instrument

performance specifications, characterizing and calibrating instruments, methods of making measurements in the

field, and methods of data analysis. These protocols were developed at a workshop sponsored by the SeaWiFS

Project Ofice (SPO) and held at the Naval Postgraduate School in Monterey, California (9–12 April 1991). This

report began as the proceedings of the workshop, as interpreted and expanded by the authors and reviewed by

workshop participants and other members of the bio-optical research community. The protocols are an evolving

prescription to allowthe research community to approach the unprecedented measurement uncertainties implied

by the SeaWiFS goals; research and development are needed to improve the state-of-the-art in specific areas.

These protocols should be periodically revised to reflect technical advances during the SeaWiFS Project cycle.

The present edition (Revision 1) incorporates newprotocols in several areas, including expanded protocol

descriptions for Case-2 waters and other improvements, as contributed by several members of the SeaWiFS

Science Team.

Prologue

The NIMBUS-7 Coastal Zone Color Scanner (CZCS)

introduced ocean color remote sensing as a powerful new

tool for observing ocean bio-optical properties. Through

the early 1980s, CZCS data were exploited by a growing

number of scientists studying marine phytoplankton, ocean

productivity, and ocean optical properties. Practical applications to marine fisheries were also demonstrated. Unfortunately, a successor ocean color imaging system was

not developed before the CZCS ceased operating in mid1986. At present, therefore, research in these areas is limited to retrospective, albeit productive, investigations of

the CZCS historical database. In mid-1995, the launch of

the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the

next generation ocean color sensor, will bring a welcomed

and improved renewal of ocean color time-series observations to the ocean research community.

The National Aeronautics and Space Administration

(NASA) SeaWiFS Prelaunch Science Working Group

(SPSWG) has recommended baseline satellite ocean color

products consisting of:

1) normalized water-leaving radiance (LWN ) at five

wavelengths;

2) aerosol radiance at three wavelengths;

3) chlorophyll a concentration;

4) a chlorophyll-like pigment (chlorophyll a plus

phaeopigment a) concentration;

5) the diffuse attenuation coefficient (K) at 490 nm,

K(490); and

6) calibrated radiances observed at the satellite.

The primary SPSWG goals for product uncertainty are

derived water-leaving radiances to within 5% and chlorophyll a concentration to within 35% in Case-1 waters, both

globally and throughout the projected five-year mission.

These goals have been endorsed by the SeaWiFS Science

Team and accepted by NASA. NASA has the responsibility

to lead the product assurance, calibration, and validation

program. NASA is also required to determine the degree to

which the commercially procured ocean color data fulfills

the contractually stated NASA requirements.

The CZCS mission was unquestionably a scientific success, but it also taught the participants that the satisfactory performance of a remote sensing satellite system cannot be taken for granted. Immediately after launch, and

periodically throughout its five-year mission, the SeaWiFS

system performance—including algorithms—must be independently verified using in situ optical measurements of

the ocean and atmosphere. It is imperative that these supporting optical measurements meet a uniform standard of

quality and accuracy if the primary SeaWiFS goals of 5%

uncertainty in water-leaving radiance and 35% uncertainty

in chlorophyll a concentration are to be met, or even closely

approached. To that end, the NASA Goddard Space Flight

Center (GSFC) SeaWiFS Project convened a workshop to

draft protocols and define standards for optical measurements to be used in SeaWiFS radiometric validation, and

algorithm development and validation. The original version of this document (Mueller and Austin 1992) reported

the protocols agreed to by the participants, as expanded

by the authors, made in consultation with both the workshop participants and other members of the ocean biooptics community. The present revision incorporates the

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

expanded protocols and revisions contributed by several

members of the SeaWiFS Science Team and other colleagues.

This report specifies the type and quality of supporting in situ optical measurements and analytical protocols

that will be required to develop bio-optical algorithms and

validate the SeaWiFS calibration. Economics dictate that

these observations and data will accrue over several years

from a variety of sources, using different instruments and

approaches. These data must be internally consistent, of

known and documented uncertainty, and in a form readily

accessible for analysis by the SeaWiFS investigators.

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Mueller and Austin

Chapter 1

Overview of SeaWiFS Bio-Optical Requirements

Introduction

The Ocean Optics Protocols for SeaWiFS Validation, Revision 1 are intended to provide standards, which if

followed carefully and documented appropriately, will assure that any particular set of optical measurements

will be acceptable for SeaWiFS validation and algorithm development. It is true that in the case of ship shadow

avoidance, for example, there are some circumstances in which acceptable radiometric profiles may be acquired

considerably closer to a ship than is specified here (Section 5.1.1). When the protocols are not followed in such

cases, however, it is incumbent upon the investigator to explicitly demonstrate that the actual error levels are

within tolerance. The most straightforward way for an investigator to establish a measurement that is both

accurate enough to meet the SeaWiFS standards and uncontaminated by artifacts, such as ship shadow, will be

to adhere closely to the protocols.

1.1 OBJECTIVES

Immediate concerns have focused this document on specific preparations for the SeaWiFS mission. A longer-term

intention is the development of bio-optical databases that

are relevant to future needs, and therefore, this document

also recognizes the capabilities of other planned or potential ocean color sensors, including:

a) the Japanese Ocean Color Temperature Sensor

(OCTS);

b) the Moderate Resolution Imaging Spectroradiometer (MODIS);

c) the Medium Resolution Imaging Spectrometer

(MERIS); and

d) the German Reflecting Optics System Imaging

Spectrometer (ROSIS).

The key objective of the working group was to recommend protocols and standards for supporting in situ

optical measurements. These objectives addressed the following subject areas:

1. The required and useful optical parameters to be

used for validation of SeaWiFS normalized waterleaving radiances and atmospheric correction algorithms, and for monitoring the satellite sensor’s calibration and stability, will be defined.

2. The instrumentation requirements, and standards

for measuring the parameters in item 1, including definitions of measured quantities, wavelengths,

field-of-view(FOV) and band specifications, sensitivity, uncertainty and stability, will be delineated.

3. The optical instrument characterization, intercalibration standards, and related protocols will be defined. This objective includes the following subjects:

a) laboratory calibration and characterization

measurements, uncertainties, and procedures

to be applied to instruments used in SeaWiFS validation and algorithm development

activities;

b) pre- and post-deployment measurements and

procedures to be followed with moored instrumentation; and

c) methods for instrument calibration and characterization, and the requirements for record

keeping and traceability, including intercalibrations of radiometric and optical standards

between participating laboratories.

4. The at-sea optical sampling strategy and protocols

will be standardized. This objective includes such

considerations as:

a) the rationale and justifications for moored,

underway, drifting, shipboard, and airborne

measurements;

b) ship shadowavoidance, depth resolution in

optical profiles, and total sampling depths;

and

c) time of day, sky conditions, season, and geographic considerations.

5. The analysis approaches to be used shall be refined.

This objective includes procedures and methodologies recommended for generating variables from in

situ observations, e.g., LWN (z) from Lu(z), K(z),

remote sensing reflectance, etc., as well as error

analysis.

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

6. Protocols for ancillary measurements, data archiving, database population, and access to data will be

standardized.

7. The required atmospheric measurements will be defined, and the degree to which standard methodologies are available will be evaluated.

The development and validation of bio-optical algorithms for SeaWiFS will be addressed by a separate working group, and thus, these topics are briefly examined in

this report. Nonetheless, the SPSWG was charged with

identifying data requirements and sampling strategies for

bio-optical support measurements in the context of the optical and radiometric measurements. This topic includes

the following subjects:

1. Discrete chlorophyll a and pigment concentrations will be measured using the US Joint Global

Ocean Flux Study (JGOFS) program’s protocols and standards for high performance liquid

chromatography (HPLC) pigment sampling and

analysis, which are adopted by reference to the

JGOFS Core Measurement Protocols (JGOFS

1991), Chapter 9, “Pigments and Chlorophyll.”

2. An assessment will be made of the roles of underway, moored, and discrete chlorophyll a fluorescence measurements, howsuch measurements

are calibrated, and their usefulness for satellite

data product validation.

3. The need for biogeochemical measurements of

colored dissolved organic material (CDOM), coccoliths, suspended sediment, detritus, etc., will

be examined on the basis of baseline product

requirements. This subject will also the address the extent to which standards and protocols have been defined for such biogeochemical

measurements.

This report is complementary to anticipated reports of US

and International JGOFS working groups, which are concurrently evaluating bio-optical needs and sampling strategies for their respective science programs.

1.2 SENSOR CALIBRATION

The SPO must make every effort to track the sensor’s

performance throughout the duration of the mission. Since

the instrument will be designed for a five-year mission, it

is certain that the sensor calibration at each wavelength

will change in some unpredictable manner as a function

of time. Experience with CZCS has shown it is very difficult to determine a sensor’s calibration once it has been

launched (Viollier 1982, Gordon et al. 1983, Hovis et al.

1985, Mueller 1985, and Gordon 1987). Similar problems have been encountered with other Earth observing

systems, such as the National Oceanic and Atmospheric

Administration (NOAA) Advanced Very High Resolution

Radiometer (AVHRR) (Brown and Evans 1985 and Weinreb et al. 1990). Because of the large atmospheric contribution to the total observed radiances (Gordon 1981) and

the great sensitivity of the bio-optical algorithms to the

estimated water-leaving radiances (Clark 1981), small errors in the calibration can induce sizable errors in derived

geophysical products, rendering them useless for many applications.

By processing large quantities of so-called “clear water” imagery, i.e., water with pigment concentrations less

than 0.25 mg m−3 (Gordon and Clark 1981), Evans and

Gordon (1994) were able to develop a vicarious calibration

that was used in the global processing of the entire CZCS

data set (Esaias et al. 1986 and Feldman et al. 1989). The

approach, however, requires assumptions that may limit

the scientific utility of ocean color imagery. Specifically,

the normalized clear water-leaving radiances, LWN (443),

LWN (520), and LWN (550), were assumed to be 1.40, 0.48,

and 0.30 mW cm−2 μm−1 sr−1, respectively. The  ̊Angstr ̈om exponents were assumed to be zero and certain geographical regions such as the Sargasso Sea were assumed to

be clear water sites at all times. Under these assumptions,

analyses of the derived (LWN ) values were used to calculate

calibration adjustment coefficients to bring CZCS derived

(LWN ) values into agreement for these regions. The vicarious calibration of the 443 nm band is tenuous because

of the great variability in LWN (443) even in clear water.

Additionally, certain command and engineering data from

the NIMBUS-7 platform were not archived, so that a detailed analysis of possible effects related to the spacecraft

environment and the effects of spacecraft operation on the

calibration could not be performed.

Unlike CZCS, SeaWiFS will routinely produce geophysical fields in a near-real time, operational mode for distribution to the science community. This aspect of the mission necessitates constant evaluation of the sensor performance and the derived products. Therefore, a multifaceted

approach to address the problem of sensitivity degradation

and sensor characterization is required during both the preand post-launch phases. The goal is to ensure that SeaWiFS level-1 radiances are accurately known and meet the

specifications of the SPSWG.

The plan includes both onboard and vicarious calibration approaches. SeaWiFS will have a solar measuring

diffuser plate to reference the response to the sun (Gordon

1981) and also will be capable of periodically imaging the

moon by maneuvering the spacecraft. The vicarious calibration program will incorporate measurements of waterleaving radiances and other related quantities, from ships,

drifting buoys, and fixed moorings, to develop time series

and geographically diverse samples of oceanic and atmospheric data sets. Each approach has advantages and disadvantages, but when combined, they should provide a complementary and comprehensive data set that will be sufficient to monitor short-term changes and long-term trends

in the sensor’s performance.

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Mueller and Austin

1.3 BIO-OPTICAL ALGORITHMS

The SPO will be responsible for producing a standard

set of derived products and will produce both CZCS-type

products and baseline products. The CZCS-type products

will consist of pigment concentration, K(490), five normalized water-leaving radiances, and three aerosol radiances

based on constant default wavelength dependence (epsilon)

coefficients in aerosol corrections. The proposed baseline

products will include five normalized water-leaving radiances, K(490), chlorophyll a concentration, three aerosol

radiances, and one or more error analysis products.

The basic quantities to be computed from the sensor

radiances are the water-leaving radiances, from which all

other derived products except the aerosol radiances are

computed. Every effort must be made to ensure these radiances meet the specifications of the SPSWG, i.e., ±5%

in Case-1 waters. This requires the atmospheric correction

algorithms to be considerably more sophisticated than the

current CZCS algorithms.

The baseline bio-optical products must meet the accuracy requirements established by the SPSWG over a

variety of water masses. The current CZCS algorithms

were based on a data set consisting of fewer than 50 data

points (only 14 observations were available for the band2-to-band-3 ratio algorithm) and performed poorly in regions of high chlorophyll a concentration, high suspended

sediment concentration, high CDOM concentration, and

coccolithophorid blooms (Groom and Holligan 1987). Accurate estimates of the baseline products are essential if

SeaWiFS is to be useful in programs such as the Global

Ocean Flux program [National Academy of Science (NAS)

1984].

SeaWiFS will have the capability, due to improvements

in the signal-to-noise ratio (SNR), digitization, dynamic

range, and wavelength selection, to increase the accuracy

of these products and to flag areas where anomalies or

lowconfidence conditions exist. Clearly, a much larger

database will be needed for developing a broader variety

of bio-optical algorithms, some of which will be region specific. The radiometric, optical, and chemical field observations used in deriving bio-optical algorithms and for vicarious calibration of the sensor must, therefore, conform to

stringent requirements with respect to instrument calibration and characterization, and must also conform to the

observation protocols which have been specified to take

advantage of SeaWiFS capabilities.

The SPO will manage a program to compare the various atmospheric correction and bio-optical algorithms proposed by the science community. The purpose of this program is to independently evaluate suggested improvements

or additions to the SeaWiFS products. This component of

the calibration and algorithm development program will

run in parallel with, but off-line from, operational processing and will provide an essential mechanism for incorporating data and analyses from the community at large.

1.4 COMMUNITY PARTICIPATION

The SPO will rely on the oceanographic community to

perform field research for atmospheric and bio-optical algorithm development, and for all of the in situ data collection for the vicarious sensor calibration. A minimal subset

of these observations will be sponsored by the SPO, but

many projects sponsored by the NASA Research and Application Program and other government agencies are expected to make major contributions to the global five-year

effort. This requires close coordination of the various programs involved and a clear definition of the observations,

accuracies, and data collection protocols required for each

type of activity. The purpose of this document is to clarify

these requirements.

1.5 VICARIOUS CALIBRATION

For ocean observations, it is easy to show(Gordon

1987 and Gordon 1988) that satellite sensor calibration

requirements based on the quality of the existing CZCS

pigment algorithms exceed currently available capabilities.

Furthermore, the sensor calibration is unlikely to remain

unchanged through launch and five years of operation in

orbit. The only foreseeable way of approaching the ocean

calibration needs is through vicarious calibration, i.e., fine

tuning the calibration in orbit.

The methodology used to achieve vicarious calibration

for CZCS was described in detail by Gordon (1987). First,

the calibration was initialized after launch by forcing agreement between the sensor-determined radiance and the expected radiance based on radiometric measurements made

at the surface under clear atmospheric conditions. Next,

since the CZCS responsivity was observed to be time dependent, the algorithms were applied to other scenes characterized by bio-optical surface measurements and more

typical atmospheres, and the calibration was adjusted until the measured water-leaving radiances were reproduced.

Finally, the surface measurements of pigments were combined with satellite pigment estimates for a wide variety of

atmospheric conditions, and the radiance calibration was

fine tuned until the best agreement was obtained between

the retrieved and true pigments.

The CZCS vicarious calibration was not radiometric.

It was a calibration of the entire system—sensor plus algorithms. To predict the radiance measured at the satellite, Lt, the water-leaving radiance, the aerosol optical

thickness, and the aerosol phase function are all required.

Also needed are ancillary data such as the surface pressure, wind speed, and ozone optical thickness. These data

for vicarious calibration and validation will be obtained

by measuring the upwelling radiance distribution just beneath the surface, along with the aerosol optical thickness

and the sky radiance, at the time of the satellite overpass.

The sky radiance will be used to deduce the required information about the aerosol phase function (Voss and Zibordi

5
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

1989). The data set will be used to deduce Lt, at the top of

the atmosphere, coincident with a SeaWiFS overpass from

which the calibration will be initialized.

It must be stressed that this exercise is absolutely essential for calibrating the SeaWiFS system, i.e., sensor plus

algorithms, and that it cannot be effected without a high

quality surface data set obtained simultaneously with the

satellite imagery.

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Mueller and Austin

Chapter 2

Data Requirements

Introduction

The prime objective of in-water optical measurements for SeaWiFS is to derive accurate normalized waterleaving radiances that will be used both for direct validation comparisons with those derived from SeaWiFS

data, and to develop and validate in-water bio-optical algorithms. Therefore, a comprehensive field program to

measure optical and biogeochemical state variables will be required.

2.1 DEFINITIONS

The required and useful variables to be measured for

SeaWiFS validation are listed in Table 1, classified into

two discrete sets. The first set comprises variables that

can be used for radiometric initialization and ongoing validation. The second set encompasses those variables that

will be used for bio-optical algorithm development and validation.

Surface incident spectral irradiance, Ed(0−, λ); downwelled spectral irradiance, Ed(z, λ); and upwelled spectral

radiance, Lu(z, λ), are the fundamental measurable quantities needed to derive normalized water-leaving radiances

in most circumstances. Other ambient properties, like sky

radiance, sea state, wind velocity, etc., are also useful initialization and calibration measurements and are discussed

below.

Surface incident spectral irradiance, Ed(0−, λ), is usually derived from surface irradiance, Es(λ), measured on

a ship well above the water, but the use of a radiometer

floated just beneath the surface (z = 0−) may provide a

better approach (Sections 3.2.1 and 5.1.4). Ed(0−, λ) varies

due to fluctuations in cloud cover and aerosols, and with

time of day, i.e., solar zenith angle. Profiles of Ed(z, λ)

and Lu(z, λ) must be normalized to account for such variabilities during a cast.

Downwelled spectral irradiance, Ed(z, λ), is required to

compute the diffuse attenuation coefficient, K(z, λ), which

in turn, is needed for diffuse attenuation coefficient algorithm development (Austin and Petzold 1981), and for

optically weighting the pigment concentrations to be estimated from remotely sensed ocean color (Gordon and

Clark 1981). Ed(z, λ) is also required to compute the spectral (remote sensing) reflectance, RL(z, λ), which is used

to normalize Lu(z, λ) when developing and validating biooptical algorithms. The need for this normalization arises

because the spectrum of incident irradiance varies with

changing solar zenith angle and atmospheric conditions.

Ed(0−, λ) can then be used, through RL(z, λ), to convert

Lu(0−, λ) measured under a given set of illumination conditions, e.g., overcast skies, to LWN (λ), which would be

measured under the restricted illumination and viewing

conditions associated with SeaWiFS measurements. As

with Lu(0−, λ), Ed(0−, λ) must be determined by extrapolation from a profile of Ed(z, λ) over the upper fewoptical

depths and reconciled with the direct surface measurement

of Es(λ). [Optical depth, τ (z, λ), in the context of this

report is the integral of K(z, λ), for either radiance or irradiance, depending on the context, from the surface to a

given depth z.]

Upwelled spectral radiance, Lu(0−, λ), is the in-water

variable which, when propagated upward through the sea

surface, leads to the measured value of LW (λ). LW (λ)

is, in turn, adjusted using Ed(λ) to derive the normalized

water-leaving radiance, LWN (λ), for a clear-sky zenith sun

at the mean Earth-sun distance. Unfortunately, it is not

practical to measure Lu(0−, λ) precisely at an infinitesimal

depth belowthe surface. Therefore, the profile of Lu(z, λ)

must be measured over the upper fewoptical depths with

sufficient accuracy to determine KL(z, λ) for Lu(z, λ), and

to propagate Lu(z, λ) to the surface. At near-infrared (IR)

wavelengths, the first optical depth is confined to the upper

fewtens of centimeters. Determination of Lu(0−, λ) in this

situation is more challenging and will require special instruments and experiment designs to accommodate the effects of instrument self-shading, wave focusing, small-scale

variability, possible fluorescence, Raman scattering, and

extremely small working volumes. Careful measurements

of inherent optical properties (IOPs), including a(z, λ),

c(z, λ), and bb(z, λ), and spectral fluorescence, may be

useful, in addition to Ed(z, λ) and Lu(z, λ) measurements

made with specially designed radiometers.

Sky radiance is required to enable estimation of the

aerosol phase function through inversion of the radiative

transfer equation. It is also useful for estimating the mean

cosine of the transmitted light field in the water. The sky

radiance should be measured directly; for the latter application, however, it need only be estimated by occulting the

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Table 1. Required observations for initialization and system calibration for satellite product verification and radiative

transfer (also ongoing calibration and atmospheric algorithm validation studies) and bio-optical algorithm development

and validation.

Product Radiative Bio-optical

Verification Transfer Algorithms

Primary Optical Measurements

Incident Spectral Irradiance, Ed(0−, λ) × × ×

Downwelled Spectral Irradiance, Ed(z, λ) × × ×

Upwelled Spectral Radiance, Lu(z, λ) × × ×

Spectral Solar Atmospheric Transmission, τs(λ) × × ×

Submerged Upwelled Radiance Distribution, L(z, θ, φ) × × ×

Spectral Sky Radiance Distribution × × ×

Upwelled Spectral Irradiance, Eu(z, λ) × ×

Calculated or Derived Variables

Water-leaving Radiance, LW (0−, λ) × × ×

Attenuation Coefficient Downwelled Irradiance, Kd(z, λ) × × ×

Attenuation Coefficient Upwelled Radiance, KL(z, λ) × × ×

Spectral Reflectance, RL(z, λ) × × ×

Ambient Properties

Sea and Sky State Photographs × × ×

Wind Velocity × × ×

In Situ Fluorescence Profiles × ×

Aerosol Samples × ×

Temperature and Salinity Profiles ×

Secchi Depth ×

Primary Biogeochemical Measurements

Phytoplankton Pigments (HPLC Technique) × ×

Phytoplankton Pigments (Fluorometric Technique) × ×

Total Suspended Material (TSM) Concentration × ×

Colored Dissolved Organic Material (CDOM) × ×

Inherent Optical Properties

Spectral Beam Attenuation Coefficient, c(z, λ) × ×

Spectral Absorption Coefficient, a(z, λ) × ×

Spectral Backscattering Coefficient, bb(z, λ) × ×

Spectral Volume Scattering Function, β(z, λ, θ) × ×

Red Beam Attenuation, c(z, 660 nm) × ×

Algorithm Specific Research Measurements

Airborne Fluorescence and Radiances × ×

Coccolith Concentration ×

Detritus Absorption Coefficient × ×

Humic and Fulvic Acids ×

Inorganic Suspended Material ×

Organic Suspended Material ×

Particle Absorption Coefficient × ×

Particle Fluorescence ×

Particle Size Spectra × ×

Particulate Organic Carbon (POC) ×

Particulate Organic Nitrogen (PON) ×

Phycobilipigments Concentration ×

Phytoplankton Species Counts ×

Primary Productivity (14C) ×

Total Dissolved Organic Carbon (DOC) ×

× = Needed for the indicated effort.

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Mueller and Austin

sun’s image on a deck cell measuring the incident spectral

radiance from the sun and sky. The mean cosine at the

surface can be used with profile measurements of Ed(λ),

Eu(λ), and c(λ) to estimate bb(λ) (Gordon 1991). An ability to exploit this and similar relationships will greatly

enhance both development and verification of bio-optical

algorithms. The spectral sky radiance distribution over

zenith and azimuth angles is required to determine the

aerosol scattering phase functions at radiometric comparison stations during the system initialization cruises and

will be very useful if measured at all validation stations

throughout the mission.

Upwelled radiance distribution measurements just beneath the sea surface will be required for quantifying the

angular distribution of water-leaving radiance at stations

used for system calibration initialization and long-term

system characterization. These measurements will also be

useful in relating radiance and irradiance reflectance, and

K profiles, to IOPs and biogeochemical substances, e.g.,

chlorophyll a and CDOM, during bio-optical algorithm development and validation.

Atmospheric transmittance spectra should be measured

using a sun photometer in order to determine aerosol optical depths at each station. These data are particularly

needed to verify the atmospheric corrections in direct comparisons between SeaWiFS LW (λ) estimates and those determined from in-water Lu(0−, λ).

Sea state photographs are required to document surface

wave conditions during radiometric measurements. This

information is essential for identifying measurements made

under questionable environmental conditions.

Wind velocity is required to generate, through models, estimates of the surface wave slope distribution, which

will be used to calculate reflected skylight and sun glint

in radiative transfer models (Cox and Munk 1954). Surface wave models driven by wind velocity may also be used

to provide quantitative estimates of surface wave induced

radiometric fluctuations. Qualitatively, wind velocity, and

photographs or videotape recordings of sea state, will be

useful for assessing station data quality.

Upwelled spectral irradiance, Eu(z, λ), is a useful measurement, in addition to Ed and Lu, because there exist both empirical and theoretical relationships between

IOPs, phytoplankton pigments, TSM, and irradiance reflectance. Lu(0−, λ) and Eu(0−, λ) are related by the factor Q(λ), which is not well determined at present, and has

been shown to vary with solar zenith angle (Morel and

Gentili 1993). Combined measurements of Lu(0−, λ) and

Eu(0−, λ) will be extremely useful in determining Q(λ),

which will, in turn, allow traceability of SeaWiFS measurements to previously derived irradiance reflectance relationships and algorithms.

IOPs must be measured for development and validation of the SeaWiFS semi-analytic Case-2 chlorophyll a

algorithm. This algorithm is based on an explicit theoretical function of the ratio of backscattering to absorption, bb(λ)/a(λ). In the first implementation, however,

bb(λ)/a(λ) is modeled statistically as a polynomial function of chlorophyll a concentration. This will introduce a

strong, empirical component to the algorithm, suppressing the physical links between RL(λ) and bb(λ)/a(λ) and

between bb(λ)/a(λ) and phytoplankton pigment concentration. A more robust algorithm would be based on direct

measurements of absorption, scattering, pigments, and reflectance. Due to recent advances in instrumentation, it

is nowpractical to routinely measure profiles of a(z, λ)

(Section 5.2.4) and backscattering variables (Section 5.2.5)

from which bb(z,λ) may be approximated. Future development and validation experiments involving this algorithm

must, therefore, include absorption, beam attenuation, and

scattering measurements.

Red beam attenuation coefficient, c(660), and in situ

chlorophyll a fluorescence measurements are exceptionally

useful in analyzing profiles of Ed(z), Lu(z), and Eu(z) to

derive profiles of Kd(z), KL(z), and Ku(z), respectively.

If these profiles are viewed in real time, they are also useful guides for taking water samples at depths that allow

the vertical structure of chlorophyll a and suspended particles to be accurately resolved in the top optical depth.

Finally, the chlorophyll a fluorescence profile is used to interpolate HPLC and extracted fluorescence measurement

of chlorophyll a concentrations from water samples at discrete depths. It is desirable to make these measurements

simultaneously with irradiance and radiance profiles, if it

can be done in a way to avoid self-shading of the instrument (Section 5.1.6).

Secchi depth measurements are required for real-time

assessment of water transparency during a station and as

a quality check during analysis of radiometric profiles.

Aerosol concentration samples using high volume techniques will be useful, in conjunction with aerosol optical

depth spectra determined from sun photometer measurements, for chemical, size, and absorption characterization

of aerosols, especially in studies of the effects of Saharan

and Asian dust clouds on atmospheric corrections.

2.2 BIOGEOCHEMICAL DATA

Pigment concentrations will be determined using HPLC

and fluorometric methods to develop and validate chlorophyll a algorithms, and to assess the effects of accessory pigment concentrations on water-leaving spectral radiances. These data will also be used to calibrate continuous profiles of chlorophyll a fluorescence (Section 2.1).

Phytoplankton pigment concentration will also be determined using classical chlorophyll a and phaeopigment fluorescence techniques that were used for CZCS pigment

validation and algorithm development. The HPLC technique provides more accurate and precise information for a

greater number of pigments, but gives different values than

does the fluorescence method for various species compositions and chlorophyll a-to-phaeopigment ratios. While the

HPLC method is the primary pigment technique required

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

for SeaWiFS, the classical technique is still required to allowthe CZCS and SeaWiFS data sets and algorithms to

be compared.

Phycobilipigments, present in cyanobacteria and cryptophytes, are treated separately from the HPLC fat soluble pigments. Phycoerythrin and phycocyanin are the

two major groups of phycobilipigments found in the marine environment. The concentration of these water soluble pigments is important due to the contribution of solar

stimulated phycoerythrin fluorescence to the underwater

light field, and also to characterize the phytoplankton population. At times, species which contain phycobilipigment

can account for a large fraction of the primary productivity

(especially in oligotrophic waters) and have been difficult

to quantify due to their small size. These measurements

are not required because SeaWiFS does not contain bands

at their absorption or fluorescence peaks. The measurements are desirable, however, since several aircraft sensors,

e.g., the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS), Airborne Oceanographic Lidar (AOL), the

Multispectral Airborne Radiometer System (MARS), and

future satellite sensors, e.g., MODIS and MERIS, do possess bands at the absorption or fluorescence peaks of phycobilipigments. If such pigment information is required for

a particular study, it is recommended that the glyceroluncoupling technique described by Wyman (1992) be used

to determine phycoerythrin concentrations.

TSM measurements are required to assess the effect of

suspended sediment on the derived products. TSM is of

primary importance in coastal waters, where simple radiance ratio algorithms for TSM have uncertainties equivalent to, or better than, those for estimating chlorophyll-like

pigment concentration. Organic suspended matter and inorganic suspended matter concentrations are subfractions

of TSM; this partitioning of TSM is particularly useful in

process studies.

Particulates, both POC and PON, are required for process studies to help characterize the adaptive state of phytoplankton and to inventory critical biogeochemical elements.

DOC has been shown to be a major pool of carbon

in the oceans. Quantification of the transformations of

this pool is crucial to understanding the marine carbon

cycle. The colored fraction, CDOM, of the DOC is highly

absorbent in the blue range, thus decreasing blue waterleaving radiances, and it must be taken into consideration

for pigment concentration algorithms. DOC measurements

are needed to develop robust relationships between CDOM

and DOC, which are needed to evaluate the usefulness of

ocean color observations for estimating DOC concentrations.

CDOM concentrations are required to assess the effect of Gelbstoff on blue water-leaving radiances and chlorophyll concentration. This is of primary importance in

Case-2 waters, but is also relevant to phytoplankton degradation products.

Humic and fulvic acids comprise the bulk of CDOM

and have different specific spectral absorption coefficients.

Their concentrations are useful for determining the correction used for phytoplankton pigment concentration algorithms in Case-2 waters and for estimating CDOM from

ocean color observations.

Coccolith concentration, which is the number density

of small plates (coccoliths) composed of calcium carbonate (CaCO3), is very important to light scattering. Coccoliths are produced in copious amounts by marine phytoplankton called coccolithophores. Scattering of light by

coccoliths is highly apparent in visible wavelength satellite imagery, because they perturb the usual relationships

between water-leaving radiances and chlorophyll a concentration and adversely impact atmospheric corrections. Additionally, coccolith formation, sinking, and dissolution are

significant factors in the ocean carbon flux budget. It

is, therefore, necessary to measure coccolith concentration, both as number density and CaCO3 concentration,

to aid in 1) the correction of chlorophyll a concentration

algorithms, 2) coccolith algorithm development, and 3) atmospheric correction development and validation.

The particle absorption coefficient, which is comprised

of absorption by living, dead, and inorganic particles, is

a useful variable for modeling the portion of solar energy

that is absorbed by phytoplankton and bacteria.

Detritus (or tripton) absorption coefficient, i.e., absorption of light by detritus, represents a major loss of light

which would otherwise be available to the phytoplankton

component of the marine hydrosol. In many cases, absorption by detritus is a significant term in the marine radiative

transfer processes, and its determination is useful for phytoplankton production models and for modeling the light

field.

Particle size spectra are very useful for in-water radiative transfer calculations, particularly if measurements

include particles smaller than 1 μm.

Particle fluorescence, measured using laser sources on

single-cell flowsystems, may be used to calculate particle

scattering-to-fluorescence ratios for evaluating the population structure of the plankton (both phyto- and zooplankton).

Phytoplankton species counts are important because

species-to-species variability in optical and physiological

properties represents a major source of variability in biooptical algorithms and primary productivity models. This

has been recognized, but it is generally ignored in remote

sensing algorithms due to the tedious nature of species

enumeration, the small sizes of many species, and the large

number of species involved. This information, however, at

various levels of rigor, is useful in evaluating the population

and pigment composition. This is especially important for

some groups, such as coccolithophores.

Primary productivity, using the radioactive isotope 14C

estimation method, is not strictly required for validation of

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Mueller and Austin

water-leaving radiances or system initialization. Furthermore, primary productivity is not a standard derived SeaWiFS product, owing to the complexity of relating ocean

color to production. It will, however, be extremely useful

for process study applications of ocean color data if these

measurements are made at the same time that the water

column optical properties are determined. These data will

aid in the development of models of primary production

using satellite ocean color observations, a goal which is central to the overall SeaWiFS science mission. Of special importance are determinations of key photo-physiological parameters derived from production measurements as functions of irradiance. If 14C productivity measurements are

made, they should conform to the JGOFS Core Measurements Protocols (JGOFS 1991).

2.3 ABOVE-WATER TECHNIQUES

Above-water ocean color radiance measurements from

aircraft and ships can augment in-water measurements of

Lu(z, λ) made to compare directly with SeaWiFS measurements for validation of its radiometric performance and

algorithms. Above-water radiance measurements can, if

they are accurately made, contribute an additional useful constraint in defining internally consistent sun-oceanatmosphere-sensor models that will comprise the essence

of SeaWiFS radiometric validation. For this application,

above-water radiometers must meet the SeaWiFS specifications for radiometric uncertainty, SNR, and spectral resolution at a spatial resolution that will permit direct comparisons with in-water measurements, and with SeaWiFS

measurements by means of spatial averaging. Conversely,

above-water radiance measurements made with less accuracy than the SeaWiFS prelaunch specifications would introduce an unacceptable error source into the validation

models and cannot be used for this purpose.

Airborne ocean color data may also be used to determine spatial variability in ocean optical properties during

shipboard algorithm development and validation experiments. In this context, airborne ocean color measurements

will be especially valuable in productive Case-1 and Case2 waters, where variability in ocean optical properties can

be large over mesoscale and smaller distances. Synoptic

maps of ocean color distributions can be advantageously

utilized to guide sampling by ships. It can also be used

to place in-water data from an individual station in context with respect to nearby variability, and thus provide

a basis for spatial interpolation and averaging when comparing in-water bio-optical measurements with SeaWiFS

image data. This application can be accomplished using

aircraft radiometers meeting somewhat less stringent performance specifications than is demanded for direct validation comparison between SeaWiFS and aircraft radiance

measurements.

Airborne measurements of fluorescence by chlorophyll,

CDOM, and phycoerythrin, both by laser and solar excitation, are useful to evaluate spatial and temporal variability

near ship and mooring stations and to provide independent

assessments of bio-optical algorithms.

2.4 ANCILLARY MEASUREMENTS

Hydrographic data, water temperature (T), and salinity (S), derived from conductivity, temperature, and depth

(CTD) profiles, are useful for characterizing the physical

water mass regime in which an optical profile is measured.

A T-S characterization is especially important near ocean

fronts and eddies where interleaving water masses of very

different biogeochemical composition, and therefore fundamentally different bio-optical properties, can produce complex spatial and temporal patterns of near-surface optical

properties. In these circumstances, T-S profiles can provide an indication of whether a station location is suitable

for reliable remote sensing validation and algorithm development comparisons.

2.5 OPTICAL MOORINGS

Optical moorings will be maintained in one or more regions of lowoptical variability to provide long-term time

series comparisons between in situ and SeaWiFS measurements of normalized water-leaving radiance. Moored optical systems will also be extremely useful in a variety of

oceanographic studies. For example, global satellite observations of ocean pigment biomass and estimates of phytoplankton production are essential to achieve the objectives

of the JGOFS program (NAS 1984); SeaWiFS will play a

key role in this effort.

The oceans exhibit physical and biological variability

over a wide range of space and time scales. This variability, and the need to synoptically measure distributions of

physical and biological properties over large areas and long

time periods, has motivated recent developments utilizing

contemporaneous buoy, ship, aircraft, and satellite sampling strategies (Smith et al. 1987). In addition, long-term

mooring data are required to provide continuous observations and permit an optimization of the accuracy of the

derived satellite products (Booth and Smith 1988).

There are two sources of systematic error in estimates

of phytoplankton pigment biomass derived from satellite

ocean color data. First, errors in satellite estimation of

pigment biomass arise because physical forcing, biological properties, and ocean optical properties all vary systematically with depth, and the upper layer optical signal

observed by satellites may not adequately represent structure deeper in the water column. In many circumstances,

subsurface changes may go undetected unless contemporaneous water column profile data from either shipboard

or moored sensors is available. Second, visible wavelength

sensor systems do not obtain data when the atmosphere

is cloudy. Air-sea interactions giving rise to cloudiness are

often closely linked to biological processes. For example,

Michaelsen et al. (1988) showed that episodic wind events,

11
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

which give rise to coastal upwelling and subsequent phytoplankton production along the California coast, cause

cloudiness that will bias the statistics of pigment concentrations derived from ocean color imagery. Similar biases

of a factor of 3–4, due to wind mixing during cloudy periods, were observed by Muller-Karger et al. (1990). In

circumstances of this nature, visible and infrared satellite

observations of the ocean are not random samples. Moored

optical sensors can measure systematic temporal variability in the vertical distribution of pigment biomass and,

at the same time, provide the continuous time series that

may be used to remove the sampling bias associated with

cloudiness.

The detection and verification of intra- and interannual fluctuations in productivity and associated bio-optical

variables are key goals of programs focused on studying

global change. These goals place stringent requirements

for long-term accuracy and precision on the measurement

systems to be employed. The monitoring of bio-optical parameters to resolve variability at global and decadal scales,

as proposed by the SeaWiFS and MODIS missions, will

require that moored in situ optical instruments be maintained to supplement and support the satellite data sets.

For example, the CZCS sensor degradation and the difficulties encountered in attempting to characterize that degradation, strongly point out howvaluable in-water optical

measurements would have been to that program.

2.6 DRIFTINGOPTICAL BUOYS

Drifting optical buoys, which are expendable and analogous to the ARGOS sea surface temperature (SST) drifters, represent a viable, cost-effective way to obtain significant numbers of daily optical observations to validate

global data sets of water-leaving radiance. Due to high

cost, there will probably never be more than a few permanent optical moorings. Shipboard observations provide

only a fewmeasurements on any given day, due to both the

cost of at-sea research and investigator availability. Optical data from drifting buoys, while less complete than

measurements from ships and fixed optical moorings, can

potentially surpass both in terms of global coverage and

the number of near-real time comparisons with SeaWiFS

observations. Judicious seeding of inexpensive drifters provides one means of sampling conditions and regions critical

to SeaWiFS product verification. For example, chronically

high levels of aerosols caused by desert dust storms constitute a regional condition that will affect atmospheric

corrections. These instruments may also allowstudy of

possible variations in SeaWiFS performance as a function

of latitude, due to orbital variations in sensor performance

and sun angle dependency of algorithms.

Optical drifter development activities occuring at Dalhousie University intend to develop instruments to measure

seven and three upwelling spectral radiances, respectively,

and a single downwelling irradiance. Along with temperature and barometric pressure, these data are transmitted

over an ARGOS link. Storage procedures are designed

to make maximum use of the limited ARGOS bandwidth.

(An interrogating store and forward satellite system with

greater bandwidth would be beneficial for this purpose.)

The upwelling radiance data are obtained at a depth of

approximately 0.5 m and must be propagated through the

surface using KL(λ) estimated from the relative spectral

shape. These water-leaving radiance estimates will, therefore, be inherently less accurate than surface reflectance

observations made together with optical profiles and more

complete ancillary observations.

Both of these systems are in the test and evaluation

phases. High risk areas which are being examined include long-term stability, identification of bio-fouling effects, operating lifetime, and validation of the techniques

used for calculating the water-leaving radiance from the

simple drifting sensors. The accuracy of the ARGOS system for drifter location is sufficient for global area coverage

(GAC), but experience needs to be gained in analysis of

the data to demonstrate the feasibility of using ARGOS

positioning (150 m to 1 km uncertainty) for system calibration and validation work in water mass regimes where

mesoscale variability is significant.

The cost of optical drifters will limit the number deployed. Proponents envision 50 such buoys adrift at any

one time throughout the world—a number sufficient to provide a large enough sample size to support viable global

validation. In such a scenario, typically 60% of the drifters would be obscured by clouds during a SeaWiFS pass

(those in some areas will have a much greater probability

for clouds). Furthermore, current divergence areas will be

systematically undersampled by drifters.

The uncertainty of calculated LW derived from drifter

data has been estimated to be of the order of 15%, even

though at the time they are deployed, the calibrated uncertainty of the instruments will be less than 5%. This

estimate may be pessimistic, based on:

1) the untestable possibility of drifts in radiometric responses during long-term deployment of an

expendable instrument, and

2) errors associated with propagating Lu(0.5 m, λ)

through the water column and interface to estimate LW (λ) without benefit of measurements of

K(z, λ), surface roughness, and other ancillary

measurements to be carried out at corresponding ship stations.

If LWN from drifters is only good to 15%, then they cannot be used to verify SeaWiFS radiometry within 5%, no

matter howmany drifter comparisons are made. Uncertainties must be less than 5% if this technology is to be

used for SeaWiFS radiometric validation. Uncertainties

of 15% may, however, be useful for validating SeaWiFS

and derived products, and for interpolating SeaWiFS data

through periods of extensive cloud cover.

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Mueller and Austin

Chapter 3

Specifications

Introduction

This report describes measurements of optical properties, and other variables, necessary for validating data

obtained with the SeaWiFS instrument, and for the development of in-water and atmospheric algorithms. The

specifications herein are those required of instruments used on ships, or other platforms, to acquire that optical

data. In some cases, the specifications have been selected to allowuse of instruments that are affordable

and that either currently exist, or that can be developed without major improvements in today’s state-ofthe-art technology. In a fewcases, newor improved instruments must be developed to realize the specified

performance characteristics. The data uncertainty requirements for this program are more severe than those

for a general ocean survey. Here, various investigators will use a variety of instruments that will be calibrated

independently at a number of facilities, and contribute data to a common database which will be used to validate

SeaWiFS measurements. The resulting radiometric and bio-optical database will provide an essential means

of detecting and quantifying on-orbit changes in the SeaWiFS instrument relative to its prelaunch calibration

and characterization. This chapter specifies instrument characteristics and data uncertainties thought by the

SPSWG to be necessary, as well as sufficient, for this task. The validation analysis would be significantly

degraded should calibration errors or differences of even a fewpercent, or wavelength errors or differences of a

fewnanometers, occur in (between) the instruments used to acquire the SeaWiFS bio-optical database.

3.1 IN-WATER RADIOMETERS

This section specifies radiometric characteristics for instruments that are used to measure Ed(z, λ), Eu(z, λ), and

Lu(z, λ). The specifications are applicable to filter radiometers and to spectroradiometers based on monochromators. Minimum performance characteristics are specified for spectral resolution, radiometric responsivity and

resolution, SNRs, radiometric saturation and minimum detectable values, angular response, temporal sampling resolution, linearity, and stability.

3.1.1 Spectral Characteristics

In-water radiometers shall be capable, as a minimum,

of making measurements at the wavelengths shown in Table 2. The table presumes the use of properly blocked interference filters to provide the required spectral bandpass

and out-of-band rejection (10−6 or better). Care must also

be taken to avoid possible out-of-band leakage due to fluorescence by filter, or other optical component, materials.

Filter radiometers should have channels with center wavelengths, as measured in the assembled instrument, matching those given in Table 2 to within ±1 nm for 410 and

443 nm, and within ±2 nm for all other spectral bands.

Shifts of these magnitudes in center wavelengths will result in changes in measured radiometric values of approximately ±1% or less (Booth pers. comm.) and this specification should be met if possible.

Table 2. Recommended spectral bands for discrete

wavelength filter radiometers using 10 nm full-width

at half-maximum (FWHM) bandwidths. In addition, out-of-band blocking in the far tails of the instrument response functions should be at least 10−6.

SeaWiFS Wavelengths Ed, Eu, Lu Es

Band [nm] [nm] [nm]

1 402–422 412 1 412

2 433–453 443, 435 2 443

3 480–500 490 490

4 500–520 510 510

5 545–565 555 555

6 660–680 665, 683 665 3

7 745–785 4 780

8 845–885 4 875 5

1 A preferred option is to replace two separate 10 nm

FWHM bands centered at 406and 416nm, with a

single 412 nm channel. The two channels would allow more accurate modeling of LWN (412) matching

SeaWiFS characteristics.

2 An optional extra band is used to improve modeling

of LWN (λ) radiances to match the SeaWiFS 443 nm

channel.

3 Es deck, only one channel in this band is necessary.

4 Due to the specialized nature of infrared in-water

measurements, specialized sensors will be needed.

5 Optional for Es.

13
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

It is recognized, however, that enforcing a ±1 nm hardand-fast specification could be prohibitively expensive, and

this tolerance should be regarded as a goal. With knowledge, to less than 0.2 nm, of the actual center wavelengths

and complete spectral response functions, corrections probably can be made to infer effective radiometric quantities

for the SeaWiFS channels, when the spectral characteristics of SeaWiFS channels have also been measured, shortly

before launch. Bandwidths must be 10 nm ±2 nm FWHM.

They are made narrower than the SeaWiFS channels to reduce the skewing of the parameters derived from underwater irradiance or radiance profiles in spectral regions where

absorption by natural sea water may exhibit rapid variation with wavelength.

To maintain the above tolerances, it is anticipated that

filters will be ordered to a center wavelength with a tolerance of λ0 ±1 nm and a FWHM bandwidth of 8.5 ±1 nm.

When the filter is installed in a radiometer with a 10◦ (halfangle) FOV, however, the spectral bandpass will broaden

by 2–3 nm, and the center wavelength will shift. Furthermore, as a filter ages in use, its transmission curve may

undergo changes to further broaden the FWHM bandpass

and shift the peak. The tolerances specified above include

an allowance for some degradation before expensive filter

and detector changes must be done.

Table 3. High resolution spectroradiometric specifications.

Optical Sensors

Spectral Range: 380 to 750/900 nm

Spectral Resolution: 5 nm (or less FWHM)

Wavelength Accuracy: 10% FWHM of resolution (0.5 nm)

Wavelength Stability: 5% FWHM of resolution (0.25 nm)

Signal-to-Noise Ratio: 1,000:1 (at minimum)

Stray Light Rejection: 10−6

Radiometric Accuracy: 3%

Radiometric Stability: 1%

FOV Maximum: 10◦ (for radiance)

Temperature Stability: Specified for 0–35◦ C

Linearity: Correctable to 0.1%

Ancillary Sensors

Temperature: 0.2◦ C

Pressure: 0.1% (full scale)

Horizontal Inclination 1◦ over 40◦ range

In a single instrument, all channels at a given nominal

wavelength should match within 1 nm, if possible. It is

desirable, therefore, to obtain all of the filters used by an

investigator for measurements at any nominal wavelength

(λn) from a single manufacturing lot when possible. If this

is done, Es(λn), Ed(λn), Eu(λn), Lu(λn), and any atmospheric radiometric quantities measured with that investigator’s systems, would all have a greater likelihood of being measured over the same range of wavelengths, for each

nominal wavelength (λn). In any event, the actual spectral response function of each instrument channel must be

measured and known to be accurate to less than 0.2 nm.

High resolution monochromator-based spectroradiometers, with adequate sensitivity and stray light rejection

characteristics, are also suitable instruments and are recommended for many algorithm development studies. Suitable specifications for such instruments are given in Table 3. (These instruments must also meet the specifications

summarized in Tables 2 and 4.)

3.1.2 Responsivity, SNR, and Resolution

The expected operating limits for radiometric responsivities, SNR, and digital resolution are specified in Table 4, the limits for which were derived as follows:

1. An Ed saturation value of 300 μW cm−2 nm−1 is

assumed at all wavelengths.

2. Implicit, but not stated, in Table 4 is that the minimum required Ed(0) is 20 μW cm−2 nm−1; it will

not be appropriate to occupy validation stations

when illumination is less than this minimum.

3. The minimum Ed(0) implies a minimum detectable

Ed(z) value of 1 μW cm−2 nm−1 at 3 optical depths

(3/K).

4. Digital resolution must be less than or equal to

0.5% of the reading to maintain a 100:1 SNR. To

permit a 1% uncertainty in absolute calibration, if

that goal can be met in the calibration laboratory,

the instrument must digitally resolve 0.1% of the

irradiance (radiance) produced by the laboratory

standards used; typical irradiance (radiance) values

for calibration using 1,000 W FEL standard lamps

traceable to the National Institute of Standards and

Technology (NIST), and required digital resolutions

at these signal levels, are given in Table 4 as “Calibration Irradiance” and “Digital Resolution (cal.),”

respectively. A SNR of 100:1 requires a resolution

in Ed(z) at three optical depths to 0.005 μW cm−2

nm−1 per count, i.e., 2.5 digit resolution. At the

surface, Ed(0) should be resolved to 0.05 μW cm−2

nm−1 per count.

5. The Case-1 saturation values of Eu(0) represent

the Instrument Specification Subgroup’s estimate of

maximum reflectances to be expected in ordinary

Case-1 waters: 12.5% at 410 nm, 7.5% at 488 nm

and 0.5% at 670 nm. These saturation values will be

too lowfor measurements in Case-2 waters or coccolithophore blooms. In these situations, a maximum

expected reflectance of 40% for λ < 660 nm and

20% for λ ≥ 660 nm is assumed. This implies that

the expected maximum irradiance in Eu(0) should

be 80 μW cm−2 nm−1 for λ < 660 nm and 40 μW

cm−2 nm−1 for λ ≥ 660 nm.

14
Mueller and Austin

Table 4. Required instrument sensitivities for SeaWiFS validation and algorithm development as a function of

radiometric measured variable and wavelength.

Property Variable 410 nm 488 nm 665 nm Comment

Ed(z, λ), Ed(0)max 300 300 300 Saturation Irradiance

Downwelled Ed

3

Kd



1 1 1 Minimum Expected Irradiance

Irradiance dE

dN 5 × 10−3 5 × 10−3 5 × 10−3 Digital Resolution (profiles)

dE

dN 5 × 10−2 5 × 10−2 5 × 10−2 Digital Resolution (surface unit)

Eu(z, λ), Eu(0)max 120 120 60 Saturation Irradiance (Case-2/coccoliths)

Upwelled 37 22 1.5 Saturation Irradiance (Case-1)

Irradiance Eu

3

Kd



1 × 10−2 2 × 10−2 1.5 × 10−3 Minimum Expected Irradiance

dE

dN 5 × 10−4 5 × 10−4 5 × 10−5 Digital Resolution (surface unit)

dE

dN 5 × 10−5 5 × 10−5 5 × 10−6 Digital Resolution (profiles)

Lu(z, λ), Lu(0)max 24 24 8 Saturation Radiance (Case-2/coccoliths)

Upwelled 7.5 4.5 0.3 Saturation Radiance (Case-1)

Radiance Lu

3

Kd



2 × 10−3 4 × 10−3 3 × 10−4 Minimum Expected Radiance

dL

dN 5 × 10−4 5 × 10−4 5 × 10−5 Digital Resolution (surface unit)

dL

dN 5 × 10−5 5 × 10−5 5 × 10−6 Digital Resolution (profiles)

Ecal, Source Ecal 2 5 15 Calibration Irradiance

Irradiance dE

dN 2 × 10−3 5 × 10−3 1 × 10−2 Digital Resolution (Ed, Es, Eu cal.)

Lcal, Source Lcal 0.6 1.5 4.5 Calibration Radiance

Radiance dL

dN 6 × 10−4 1 × 10−3 4 × 10−3 Digital Resolution (Lu cal.)

Notes: 1. Eu and Ed are in units of μW cm−2 nm−1 and Lu is in units of μW cm−2 nm−1 sr−1.

2. Responsivity resolution in radiometric units per digital count at the minimum required signal level.

3. Specified ranges should maintain a 100:1 SNR.

6. The minimum required irradiances at three optical depths (as given in Table 4) assumes minimum

reflectances of 1% at 410 nm, 2% at 488 nm, and

0.15% at 670 nm.

7. The saturation and minimum radiances, and radiance responsivity resolutions, for Lu(0) and Lu(z)

at three optical depths are 0.2 times the corresponding specification for Eu(0) or Eu(z). This assumes

Eu/Lu = Q = 5 at all wavelengths and depths.

The specifications in Table 4 are meant as guidance to

interpret the following required performance requirements:

a) The instrument must maintain a 100:1 SNR at every

operating range encountered, during field measurements.

b) The data for measurements obtained in the field

must be recorded with a digital resolution less than

or equal to 0.5% of reading.

c) The dynamic range of the instrument’s linear sensitivity must extend to include the signal levels encountered during laboratory calibrations, and the

calibration signals must be recorded with a digital

resolution of 0.1% of reading to permit 1% uncertainty in calibration.

In general, the above performance specifications do not

pose exceptionally difficult engineering challenges, with the

possible exception of the full dynamic range implied by

Case-2 or coccolith saturation radiance Lu(665) to minimum expected Lu(665). In any event, this situation will

require specially designed radiometers (Section 3.1.8). It

is not necessary that every radiometer used for SeaWiFS

validation operate over the full dynamic ranges given in

Table 4. A radiometer is merely required to maintain the

above performance specifications over the dynamic ranges

of irradiance and radiance existing at locations and associated illumination conditions where it is used for SeaWiFS

validation or algorithm development.

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

3.1.3 Linearity and Stability

Errors attributable to linearity or stability should be

less than 0.5% of the instrumental readings over the dynamic ranges specified in Table 4. This is a challenging

goal, but one which must be met if the equally challenging

goal of achieving 1% uncertainty in absolute calibration is

to be meaningful.

3.1.4 Sampling Resolution

Sampling frequency should be compatible with the profiling technique being used. For the preferred multispectral

filter radiometers and spectroradiometric (dispersion) instruments using array sensors, the minimum sampling frequencies are determined by the profiling rate and the depth

resolution required. In general, five or more samples per

meter should be obtained at all wavelengths. All channels of Ed(z, λ), Eu(z, λ), and Lu(z, λ) at all wavelengths

should be sampled within 10−2 s at each given depth.

The time response of the instrument to a full-scale (saturation to dark) step change in irradiance should be less

than one second to arrive at a value within 0.1%, or one

digitizing step, whichever is greater, of steady state. In

addition, the electronic e-folding time constant of the instrument must be be consistent with the rate at which the

channels are sampled, i.e., if data are to be acquired at

10 Hz, the e-folding time constant should be 0.2 s to avoid

aliasing. Individual data scans may be averaged to improve

signal-to-noise performance, provided adequate depth resolution is maintained.

3.1.5 Angular Response Characteristics

The response of a cosine collector to a collimated light

source incident at an angle θ from the normal must be such

that:

1) for Eu measurements, the integrated response

to a radiance distribution of the form L(θ) ∝

1+4 sin θ should vary as cos θ accurate to within

2%; and

2) for Ed measurement, the response to a collimated source should vary as cos θ accurate to

less than 2% for angles 0◦ < θ ≤ 65◦ and 10%

for angles 65◦ < θ ≤ 85◦.

Departures from cos θ will translate directly to approximately equal errors in Ed in the case of direct sunlight.

The in-water FOV for upwelled radiance bands should

be approximately 10◦ (half-angle). The resulting solid angle FOV (approximately 0.1 sr) is large enough to provide

reasonable levels of flux, using silicon detectors, yet small

enough to resolve the slowly varying (with θ, for θ < 30◦)

field of upwelled radiance. Smaller FOV sensors are appropriate, of course, if all of the other performance specifications are satisfied.

3.1.6 Operating Depth

The instruments shall be capable of operating to depths

of 200 m. Depths should be measured with an uncertainty

of 0.5 m and a repeatability of 0.2 m for profiles in bands

1–6.

3.1.7 Instrument Attitude

The orientations of the instrument with respect to the

vertical shall be within ±10◦, and the attitude shall be

measured with orthogonally oriented sensors from 0–30◦

with an uncertainty of ±1◦ in a static mode; it is not intended that this uncertainty be maintained while an instrument is subject to large accelerations induced by surface

waves. These data shall be recorded with the radiometric

data stream for use as a data quality flag.

3.1.8 Red and Near-Infrared Wavelengths

The fact that the SeaWiFS red and near-IR channels—

bands 6, 7, and 8 at wavelengths of 665, 780, and 865 nm,

respectively—have such short attenuation lengths in water

requires that special attention must be paid to these measurements. Problems due to instrument self-shading (Gordon and Ding 1992) and very rapid attenuation of Lu(z, λ)

must be considered at these wavelengths. Large instruments, such as the standard Marine Environmental Radiometer (MER) packages from Biospherical Instruments,

Inc. (BSI), are not adaptable to these measurements.

Suggested procedures for making the measurements are

to use either fiber optic probes carrying light back to a remote instrument, or very small single-wavelength discrete

instruments. Each of these concepts is adaptable to deployment from a small floating platform. Care must be

taken to avoid direct shading by the supporting platform,

but at these wavelengths, the large attenuation coefficients

of water makes shadowing by objects more than a few meters away irrelevant.

The minimum measurement scheme would be two discrete (10 nm FWHM) channels at 780 and 875 nm. Additional channels at 750 and 850 nm, or more elaborately,

high resolution spectroradiometry, would be useful in determining the spectral distribution of the upwelling light

field in these bands.

These measurements should be performed as part of

the standard validation data acquisition, because of their

importance in the atmospheric correction algorithms. It is

anticipated that in the majority of cases, and particularly

in most Case-1 waters, these measurements will show negligible upwelling light. In Case-2 waters, cases of extremely

high productivity, or in coccolithophore blooms, LWN (λ)

at these wavelengths may be significant, and these measurements will become very important.

When in-water measurements are performed at these

wavelengths, the deck cell channels should be expanded to

include bands at 750 and 875 nm (Table 2).

16
Mueller and Austin

3.2 SURFACE IRRADIANCE

The spectral irradiance at the ocean surface shall be

measured at wavelengths which correspond to the SeaWiFS spectral bands (Table 2), but with 10 nm FWHM

bandwidth. A total radiation pyranometer may provide

helpful ancillary information, but this is not a required

instrument.

Instruments mounted aboard ships must be positioned

to viewthe sky with minimum obstruction or reflections

from the ship’s superstructure, antennas, etc. Particular

care must be taken to prevent sun shadows from antennas

falling on the irradiance collecting surface. Gimbal mounting of the deck sensor may be helpful to keep the surface

of the sensor horizontal. Improperly designed gimbal systems, however, can accentuate fluctuations caused by ship

motion, and if there is obvious oscillation in the measured

irradiance, the gimballing should be improved to eliminate

the problem.

An intuitively attractive technique is to measure irradiance with a sensor floated a fraction of a meter below

the sea surface, far enough away from the ship to avoid

ship shadows. The flotation assembly should be designed

to avoid shadowing the radiometric FOV and to damp

wave-induced motions. This type of arrangement has an

additional potential for supporting a small sensor to also

measure upwelling radiance, Lu(λ), just belowthe surface.

Unfortunately, the oceanographic community has only had

very limited experience with this approach for measuring

Es(λ) (Waters et al. 1990) and its attendant difficulties

with wave-induced fluctuations in near-surface Ed. Additional research should be performed to evaluate the use of

a floating surface unit as the potentially preferred method

for measuring Es(λ) in future revisions to these protocols.

3.2.1 Surface Radiometer Characteristics

The specified number of channels and spectral characteristics of deck cells are the same as those for subsurface

irradiance measurements as shown in Table 2. Saturation

irradiances are the same as for Ed(λ) (Table 4). The dynamic operating range for these sensors needs to only be

25 db, with a SNR of 100:1 but must include the nominal

calibration irradiance (Table 4). Linearity must be within

±0.5%. Sampling frequency should match the frequency

of the underwater radiometer, which should be 1 Hz or

faster, and all wavelengths should be sampled within an

interval less than or equal to 10−2 s. Cosine response characteristics should give relative responsivity to a collimated

source (in air) which matches cos θ, accurate within 2%

for 0◦ ≤ θ < 65◦, and within 10% for 65◦ ≤ θ ≤ 90◦. If

a floating surface radiometer is used, its cosine response

and immersion characteristics must meet the same specifications as those for profiling irradiance meters.

For some oceanographic process studies, it may be acceptable to use a radiometer system measuring Es(λ) at

only a single wavelength. If only a single channel deck

radiometer is available, its spectral characteristic should

closely match one of channels 2–5 with a 10 nm FWHM

bandwidth. A broad-band, or photosynthetically available

radiation (PAR), radiometer should never be used for this

purpose.

3.3 ABOVE-WATER RADIOMETRY

The performance characteristics to be specified for an

above-water ocean color radiometer will vary, depending

on howa particular instrument is to be employed in SeaWiFS validation experiments. For radiometric comparisons with SeaWiFS and in-water measurements, the fundamental criterion to be met is that estimates of spectral

normalized water-leaving radiance derived from shipboard

or airborne measurements must have the same uncertainty

specified for those derived from in-water measurements of

Lu(z, λ) (Table 4). A less accurate radiometer may be used

to semi-quantitatively characterize spatial variability near

ship stations.

In general, the spectral characteristics of above-water

radiometers should match those specified for Lu(λ) in Table 2. In some cases, however, it may be acceptable for

a radiometer to match the SeaWiFS specifications, which

specify center wavelength within 2 nm and 20 nm FWHM

bandwidth. Recalling the sensitivity of solar radiometry to

the exact center wavelength and detailed spectral response

function (Sections 3.1.1 and 4.1.2), any use of airborne

radiometers must quantitatively account for the different

spectral responsivity functions between measurements of

radiance by SeaWiFS, in-water radiometers, and abovewater radiometers at each channel’s nominal center wavelength.

A high-altitude imaging radiometer must have a radiometric uncertainty and SNR in all channels equal to those

of the SeaWiFS instrument if its imagery is to be used

for direct radiometric verification of SeaWiFS radiometric

performance. In some cases, the requisite SNR may be

realized through pixel averaging to a 1 km spatial resolution commensurate with that of SeaWiFS. Direct radiometric comparisons between aircraft and SeaWiFS radiances, however, also require that the different atmospheric

path effects be carefully modeled, and that the uncertainty

in those modeled adjustments be independently estimated.

This can be done most effectively when the aircraft measurements are combined with the full suite of shipboard

in-water, atmospheric, and ancillary measurements (Table 1). In this case, direct comparisons between aircraft

and ship radiometry may require that both the SNR and

the uncertainties realized in combined analyses of the two

data sets will represent a smaller spatial resolution than

the nominal 1 km instantaneous field-of-view(IFOV) for

SeaWiFS.

Performance characteristic specifications are similar for

ocean color radiometers used to measure water-leaving radiance from either the deck of a ship or an aircraft flown

17
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

at lowaltitude, i.e., 200 m altitude or lower. Radiometric characteristics should match the criterion set forth for

in-water Lu(λ) radiometers in Sections 3.1.1–3.1.4 and Tables 2–4. The instrument FOV should be between 5◦ and

10◦ (full angle), and all wavelengths must be coregistered

within 10% of the IFOV. All channels must be scanned

simultaneously, or within less than 10−2 s (depending on

the digitizing design), to avoid aliasing due to varying wave

reflectance in shipboard measurements, and to avoid timespace aliasing in airborne measurements. This constraint

precludes use of filter wheel radiometers and others which

scan channels sequentially over a time interval greater than

10−2 s. Sampling over longer periods of time may be done

by either electronic integration of all channels simultaneously, or by averaging multiple scans.

A radiometer’s sensitivity to the polarization of aperture radiance is critical for ocean color remote sensing applications. Polarization sensitivity is likely to be present

in any radiometer having mirrors, prisms or gratings in

its optical path. To measure accurate water-leaving radiances using instruments of these types, it is necessary to

depolarize aperture radiance using either fiber-optics or a

pseudo-depolarizer. Shipboard and airborne ocean color

radiometers must have a polarization sensitivity of less

than 2% in all channels. The sole exception to this rule

will occur in the case of instruments designed to actually

measure the polarization components of aperture radiance,

e.g., the polarization channels of the French Polarization

and Directionality of the Earth’s Reflectances (POLDER)

instrument.

Each application of a particular above-water radiometer system, if it is proposed for SeaWiFS validation, must

be evaluated on its own merits. The instrument’s responsivity, uncertainty, stability, FOV, and spectral characteristics must be evaluated in the context of the models to be

used to compare its radiance measurements to in-water, or

SeaWiFS, radiance measurements. The suitability of spatial averaging to improve SNRs must be evaluated in terms

of the spatial variability prevailing in the experiment site,

particularly when in-water and aircraft radiances are to

be directly compared. Finer resolution aircraft imagery,

or low-altitude trackline data, will often be essential for

determining the validity of attempts to directly compare

in-water and SeaWiFS radiances measured at a particular

site.

In summary, airborne and shipboard above-water radiometry can obviously contribute extremely valuable data

for validating the radiometric performance of the SeaWiFS

instrument and the algorithms employed with SeaWiFS

data. There is, however, a wide possible range of radiometer characteristics that can be applied to this program, and

detailed specification of required characteristics can only

be done in the context of each particular experiment’s design. Only the guiding principals and desired end-to-end

performance are specified here.

3.4 IOP INSTRUMENTS

The IOPs are:

1) the beam attenuation coefficient, c(z, λ), in units

of m−1;

2) the absorption coefficient, a(z, λ), in units of

m−1; and

3) the volume scattering function, b(z, λ0, θ), in

units of m−1 sr−1.

The integral of the volume scattering function over 4π

steradians is the total scattering coefficient, b(z, λ), with

units of m−1. The integral of the volume scattering function over the back hemisphere is the backscattering coefficient, bb(z, λ), with units of m−1.

It will be possible to measure the spectral attenuation

and absorption coefficients in situ at the time of SeaWiFS

deployment. The instruments for the measurement of the

spectral absorption and attenuation coefficients should, at

a minimum, have the characteristics given in Table 5.

Spectral resolution at more than SeaWiFS wavelengths

would be desirable to deduce pigment concentrations. In

the case of beam attenuation coefficients, the requirements

for uncertainty and precision correspond to changes in c(λ)

resulting from changes in concentration of approximately

5 and 2 μg l

−1 of suspended mass, respectively. Stability

should be tested with instruments connected to the data

acquisition system. Stability with time should be better

than 0.005 m−1 between calibrations.

Table 5. Minimum instrument characteristics for

the measurement of the spectral absorption and attenuation coefficients.

Instrument Characteristics

Spectral Resolution: 410, 443, 490, 510,

555, and 670 nm

Bandwidth: 10 nm

Uncertainty: 0.005 m−1

Precision for λ < 650 nm: 0.002 m−1

Precision for λ ≥ 650 nm: 0.005 m−1

Stability with 0.005 m−1 over

Temperature: 0–25◦ C

Sampling Interval: ≥ 4 samples m−1

Source Collimation Angle: ≤ 5 mrad

Detector Acceptance Angle: ≤ 20 mrad

Depth Capability: 200 m

The spectral total scattering coefficient cannot be measured directly. It can be obtained from b(λ) = c(λ − a(λ),

provided c(λ) and a(λ) are determined with the appropriate uncertainty. The spectral backscattering coefficient,

bb(λ), has the same requirements for spectral resolution,

bandwidth, and linearity as a(λ) and c(λ). Since bb(λ) is

not a transmission-like measurement, however, the uncertainty of its determination will be approximately 10%.

The shape of the volume scattering function can, at

present, be determined in situ only crudely with devices

18
Mueller and Austin

like the ALPHA and Scattering Meter (ALSCAT) and the

General Angle Scattering Meter (GASM), which were built

more than a decade ago at the Visibility Laboratory of

the Scripps Institution of Oceanography. These are single

angle measurement devices, which must be scanned as a

function of angle and wavelength. Because measuring scattering with these instruments is a slow process, they do not

lend themselves readily to incorporation into other instrument platforms. Since it will be possible to independently

determine b(λ) and bb(λ) when SeaWiFS is deployed, the

determination of the shape of the volume scattering coefficient could possibly be determined with acceptable uncertainty by means of measurement of a fewmoments of the

scattering function. A newinstrument development effort

would have to be initiated to pursue this approach.

3.5 ATMOSPHERIC AEROSOLS

Sun photometers should be used to measure atmospheric aerosol optical thickness. These sun photometers

should have specifications in agreement with the World

Meteorological Organization (WMO) sun photometer specifications (Frohlich 1979). Specifically, the instruments

should have a 2◦ FOV, temperature stabilization, and a

precision of ±0.01%. The specific wavelengths of channels

should correspond to the recommended WMO wavelengths

of 380, 500, 675, 778, and 862 nm. For SeaWiFS validation, additional channels at 410, 440, 490, 510, and 555 nm

should be added to the WMO set.

3.6 SPECTRAL SKY RADIANCE

Measurements of spectral sky radiance distribution

should be made using a photoelectric all-sky camera. Spectral characteristics of the sky radiance camera channels

are those specified for Es(λ) (Table 2). Data should be

in a format such that absolute radiance values can be obtained with an uncertainty of 5% and sky irradiance can

be determined from integrals of the data to within 10%. If

the dynamic range of the camera is insufficient to capture

both the sun and sky distribution, neutral density filters

(or some other method) should be used so that radiance

from both the sun and sky can be measured.

3.7 PHYTOPLANKTON PIGMENTS

HPLC equipment and associated standards must conform to protocols specified in Chapter 9 of the JGOFS

Core Measurement Protocols (JGOFS 1991). In situ chlorophyll fluorometers should have a resolution of at least

0.001 mg of chlorophyll a per m3.

3.8 HYDROGRAPHIC PROFILES

A calibrated CTD system should be used to make profiles to maximum depths between 200 and 500 m. The

instrument should meet the minimum specifications given

in Table 6.

Table 6. The minimum instrument characteristics

for the measurement of hydrographic profiles are

listed.

Parameter Range Uncer- Resolutainty tion

Pressure [dbars] 0–500 0.3% 0.005%

Temperature [◦C] −2–35 0.015◦ C 0.001◦ C

Salinity [PSU] 1–45 0.03 PSU 0.001 PSU

19
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Chapter 4

Sensor Characterization

Introduction

This chapter details procedures to characterize the sensor performance specifications prescribed in Chapter 3.

Procedures for characterizing environmental radiometers are presented in Section 4.1, including special characteristics of underwater radiometers. Section 4.2 describes radiometric standards used as a basis for absolute

responsivity characterization of radiometers. Special consideration for radiometers measuring LW (λ) above

water, either from a ship or aircraft, are discussed in Section 4.3. The remaining Sections, 4.4–4.8, address calibrations of IOP instruments, sun photometers, radiance distribution cameras, HPLC and fluorometric systems,

and CTD profiles.

4.1 RADIOMETRY

The characterization of radiometric instruments used

for the acquisition of field data for SeaWiFS validation and

algorithm development shall include the determination of

those instrument characteristics that affect its calibration

as used in the field environment. In addition to the obvious radiometric calibration, it is therefore necessary to

determine:

a) the spectral sensitivities of the various measurement channels;

b) the angular sensitivities of an irradiance or radiance sensor in the medium, i.e., air or water,

in which it is to be used;

c) the temporal response of the system;

d) the effects on responsivity caused by water immersion; and

e) the effects of temperature and pressure on the

above characteristics.

The elements of radiometer characterization and calibration are outlined schematically in Fig. 1.

For any instrument to provide suitable data for SPO

use, the investigator must be certain that the instrument

characterization has not changed beyond accepted limits

and that the time history of the calibration is traceable.

Certain attributes, e.g., angular response characteristics,

are sufficiently constant that they only need to be determined once, unless the instrument is modified. The exact nature of instrument modifications during maintenance

will determine which characterization procedures must be

repeated. On the other hand, radiometric calibrations and

the assessment of system spectral characteristics of filter

radiometers, must be repeated before and after each major

field deployment.

4.1.1 Absolute Radiometric Calibration

Determination of the absolute radiometric responses of

the irradiance and radiance sensors requires the availability

of a properly manned and equipped radiometric calibration

facility. Such a facility must be equipped with suitable

stable sources and sensors, e.g., lamp standards of spectral irradiance and flat response radiometers, respectively.

Either the sources or the sensors must have defined spectral radiometric characteristics that are traceable to NIST

(Section 4.2). The calibration facility must also have a variety of specialized radiometric and electronic equipment,

including: reflectance plaques, spectral filters, integrating

spheres, and highly regulated power supplies for the operation of the lamps. Precision electronic measurement capabilities are also required, both for setting and monitoring

lamp current and voltage and for measuring the output of

the radiometer.

It is not expected that every investigator will be able

to perform his own radiometric calibrations; because of

this, a fewcentrally located facilities will be equipped and

staffed to perform these calibrations as a routine service for

the community. The facilities will perform frequent intercomparisons to assure the maintenance of the radiometric

traceability to the NIST standard of spectral irradiance.

The goal shall be to provide reproducible calibrations from

400–850 nm to within better than ±1%; the minimum requirement for radiometric data to be used in SeaWiFS validation is for repeatable calibrations within less than 5%.

Radiometric calibrations of irradiance sensors will be

performed after it has been ascertained that: the conformity of the sensor angular response to the required cosine

function is satisfactory, the sensor linearity is satisfactory,

and the spectral sensitivity, including out-of-band blocking, is known and satisfactory.

Radiometers shall be calibrated using a 1,000 W FEL

standard of spectral irradiance, with calibration traceable

20
Recurring

Characterizations

Initial System

Characterizations

Instrument Class

Characterizations

Radiometric

Sensitivity

Spectral

Bandpass

Central λ

FWHM

Radiance

Calibration

Scan/Array Irradiance

Calibration

Stray

Light

Signal-toNoise Ratio

Electronic

Interface

Pressure

Sensor

Radiometric

Linearity

Temperature

Sensitivity

Ancillary

Sensors

Immersion

Factors

Collector

Pressure

Sensitivity

Orientation Geometric

Mueller and Austin

Fig. 1. Elements of radiometer characterization and calibration.

to NIST and lamp operation in accordance with Walker

et al. (1987). The irradiance collector is placed normal to,

and at the prescribed distance from, a working standard

lamp of spectral irradiance. The lamp should be of appropriate size to provide an irradiance at the sensor that will

be at least 30%, and preferably above 50%, of full-scale for

the sensor channel being calibrated, although this is not

always achievable in practice (Table 4). The lamp-sensor

space shall be appropriately baffled and draped so that occulting the direct path between lamp and sensor will result

in a response of less then 0.1% of the response to the lamp

flux.

For multispectral instruments, all channels may be calibrated simultaneously if sufficient flux is available at all

wavelengths. The instrument response is recorded for all

channels together with associated dark responses. Ambient and photosensor temperatures are recorded, where

available. For characterization, the radiometric calibration

should be performed at temperature extremes of −2◦ C and

40◦ C for in-water sensors, and at −10◦ C and 45◦ C for

irradiance sensors used above the surface. If responses differ significantly at temperature extremes, responses should

also be determined at intermediate temperatures.

The portable irradiance and radiance reference standard to be used to trace instrument stability during field

deployments (Section 4.2.5) should be placed in position

on the sensor immediately following the calibration to establish the instrument response to this reference unit.

Radiance calibration activities require a uniform source

of known radiance that will fill the angular field of view of

the radiance sensor. The two procedures that may be used

are given below.

Calibration Methods

1. A working lamp standard of spectral irradiance is

placed at the prescribed distance from a plaque of

known Lambertian reflectance. The plaque is normal to, and centered on, the lamp calibration axis.

The radiance sensor is positioned to viewthe plaque

at an angle of 45◦ from the plaque normal (any other

angle at which the diffuse reflectance of the plaque

is known is acceptable also). It must be established

that the plaque fills the sensor’s FOV and that the

presence of the sensor case has not perturbed the

irradiance on the plaque. The instrument response

and dark signal is recorded. It must be verified

that the plaque fills the FOV with uniform radiance for each channel of a multichannel radiance

sensor. Separate calibration setups may be required

for different channels and the lamps may have to

be moved as much as 3 m away from the plaque to

assure uniform illumination. This procedure is difficult to apply to sensors with a large FOV.

2. An integrating sphere with an exit port of sufficient

size to fill the FOV of the radiance sensor may be

used if the radiance of the exit port, at the channel wavelengths, can be determined with sufficient

uncertainty.

These methods are discussed more fully in Section 4.2.2.

4.1.2 Spectral Bandpass Characterization

These instruments should be characterized to define the

nominal wavelengths and bandwidths, defined as the full

width of the passband as measured to the FWHM intensity

points. The nominal, or center wavelength, will usually be

defined as the wavelength halfway between wavelengths at

which the normalized response is 0.5, and the channel is

characterized by this wavelength and the FWHM bandwidth. The determination of the spectral response function, i.e., the passband, will be made for each channel with

21
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

a scanning monochromatic source, with a bandwidth less

than 0.2 nm; the source output must be normalized to a

detector of known spectral sensitivity. The response function thus measured is then normalized to the maximum

(peak).

Although the results of this characterization are usually

represented by only the nominal wavelength and FWHM

bandpass, the full normalized response function should

be recorded for use in detailed wavelength adjustments

and comparisons with the SeaWiFS channel response functions, which will not be known until shortly before launch.

It is further recommended that the internal instrument

temperature be monitored during these tests, and that

the test be repeated at two temperatures at least 15◦ C

apart, e.g., 10◦and 25◦ C. If a significant shift, greater than

1.0 nm, with temperature of either the center wavelength

or bandwidth is detected, then additional temperature calibration points are recommended. Dark offsets must be

recorded during each test.

For spectral characterizations of irradiance diffusers,

the entire surface of the diffuser should be illuminated by

the monochromator’s output. In the case of radiance detectors, a diffuser should be used to diffuse the monochromator slit image and uniformly fill the instrument’s FOV.

The wavelength response of a monochromator-based

radiometer is calibrated by scanning over line sources, with

sharp peaks at well known wavelengths. Suitable spectral

calibration sources, such as, mercury, cadmium, and neon

lamps, are provided by several vendors, together with tabulations of the wavelengths of the emission lines generated

by each source.

The width of the slit function of a monochromator may

be estimated by scanning over a laser line, e.g., heliumneon, at a very small wavelength interval. The instrument

FOV must be filled during the test.

It is anticipated that the monochromator-based spectral characterization will not be able to adequately measure

leakage of broadly distributed out-of-band radiation; therefore, blocking of blue light in channels longer than 540 nm

must be routinely tested. Where continuous wave (CW)

argon lasers are available, out-of-band response should be

measured at 488 nm. One recommended test that can be

performed during the absolute calibrations at λ ≤ 640 nm

is the sequenced measurement of three Schott BG-18 filters, each 1 mm thick, using an FEL-type light source. The

procedure is to measure the channel signal using each filter

separately, then in combination, and comparing the computed and measured transmissions. If a significantly higher

combined transmission of the three filters, when they are

used in combination, is measured relative to the calculated transmittance, then spectral leakage is present. At

wavelengths greater than 640 nm, other filters that attenuate the wavelength of interest, with a transmission value

of less than or equal to 0.1 and which pass shorter wavelength light with significantly greater transmission, should

be substituted for the BG-18.

Consideration must also be given to unblocked fluorescence by the filters, or other optical elements, as a possible source of light leaks. Methods to test for fluorescence

contamination specifically, are not well established at this

time.

While leakage of blue light into red channels is the most

significant oceanographic optical problem, the leakage of

red and IR light into blue channels can cause significant

errors when the instrument is calibrated using a red-rich

source. A convenient way to measure this leakage is to

place a long wavelength-pass, sharp-cut, absorbing glass

filter that does not exhibit fluorescence between a broad

band (e.g., incandescent) source and the sensor. A nonzero response indicates unwanted out-of-band red response

and the need for improved red blocking.

4.1.3 Temporal Response

The temporal response of a spectrometer may be examined by introducing a step function of near full-scale

flux to the system using an electrically operated shutter

and measuring the system’s transient response at 0.1 s, or

shorter, intervals. The response should be stable within

one digitizing step, or 0.1%, whichever is greater, of the

steady state value in one second or less.

4.1.4 Radiance Field-of-View

It is required that the radiance FOV of the instrument

be known. The FOV should not normally enter into the

absolute calibration, however, if the FOV is fully filled by

a calibration source of uniform radiance.

In this test, the instrument is placed on a rotational

stage with the entrance aperture of the radiometer over the

rotation axis. A stable light source with a small filament

is placed several meters in front of the instrument, which

is then scanned from −30◦ to +30◦ in 2◦ increments. The

angle positioning should be within ±0.1◦. The on axis, 0◦,

mechanical alignment is made using the window surface

as reference, by adjusting to get the reflection of the lamp

filament to return on axis. The error in this alignment

is approximately ±0.1◦. The in-air measurement angles,

θa, are converted to corresponding angles in seawater, θw,

using the relation θw = θa/nw, where nw is the index of

refraction of seawater at the particular wavelength of each

channel.

4.1.5 Collector Cosine Response

The directional response of cosine collectors must be

characterized. The directional response of the deck cell is

determined in air, and the in-water instruments are measured immersed in water. Full spectral determinations are

required. For instruments measuring upwelling irradiance

Eu(z, λ), it is recommended that the cosine response of

each instrument be measured individually. For downwelling irradiance Ed(z, λ) instruments, checking a production

22
Mueller and Austin

run may be satisfactory if the vendor’s material and design

are demonstrated to be uniform throughout the duration

of the run.

Absolute responsivity calibration of an irradiance meter is done in air, using light incident normal to the collector. To properly measure irradiance incident on the plane

at all angles θ (relative to the normal), the instrument’s

response should followa cosine function. In other words,

for an instrument response V (0) to a given collimated irradiance incident at θ = 0, if the instrument is rotated

to the angle θ away from the original normal axis, the response should be V (θ) = V (0) cos θ. If this requirement is

met, then the on-axis calibration is sufficient and the device will correctly measure irradiance arriving at the plane

of the collector, regardless of the directional distribution

at which the light arrives.

The preferred irradiance collector design has an improved cosine response over that of a simple flat plate diffuse collector (Boyd 1955 and Tyler and Smith 1979). This

improvement is mostly for near-grazing angles (θ approaching 90◦ to the normal) and is particularly important when

measurements of the upwelling underwater irradiance are

made, i.e., with the collector facing downward. In that

case, most of the light is from the sides, in the region of

these near-grazing angles.

Since Ed(z, λ) measurements are to be made underwater, the testing to determine the fidelity of the instrument

to the cosine function must be made with the instrument

submerged. A description of the suitable experimental procedure follows Petzold and Austin (1988).

The instrument is suspended in a tank of water while

supported by a fixture designed to allowrotation about

an axis through the surface and center of the collector. A

tungsten-halogen lamp with a small filament is enclosed in

a housing with a small exit aperture and placed approximately 1 m from a large window in the tank. The collector is placed approximately 25 cm behind this window; an

equivalent lamp distance of 1.25 m or more is required. A

circular baffle should be placed immediately in front of the

window to reduce stray light. The water should be highly

filtered to the extent that the effects of scattered light are

indiscernible.

The equivalent air path lamp distance should be approximately 1.25 m or greater. At this distance, the falloff at the outer edge of a 6 cm diameter diffuse collector

would be 0.9994, or −0.06%, when the diffuser is at θ = 0◦

with the normal. The net effect over the entire area of

the diffuser would be 0.9997 or −0.03%. When θ = 90◦,

with the diffuser edge-on to the lamp, the distance to the

lamp varies for different points on the surface. The net

error over the entire surface for this condition is 0.99997

or −0.003%. All other angles fall between these limiting

cases.

The signals from the instrument are recorded for θ = 0◦

and at 5◦ intervals to θ = ±75◦ and 2.5◦ intervals over

75◦ <θ< 90◦. The readings at θ = 0◦ are recorded at

the beginning, the middle, and the end of each run and

examined as a measure of lamp and instrument stability

over the time involved. At least two runs should be made

about different axes through the surface of the diffuser.

All readings are normalized to 1.000 at θ = 0◦ and then

compared with the value of the cosine of each angle. If

V (θ) is the normalized measured value, relative local error

at angle θ is given as (V (θ)/cos θ) − 1.

Assuming the average response to the four measurements made at each θ (four separate azimuth angles φ)

adequately represent the overall mean cosine response of

the collector, then the error, , in measuring irradiance

over the interval θn <θ<θN for a uniform radiance distribution is approximately

 =



N

i=n

V (θi) sin θi ∆θ



N

i=n

cos θi sin θi ∆θ

− 1, (1)

using a simple trapezoidal quadrature. Similarly, for a

radiance distribution of the form 1 + 4 sin θ, to simulate

upwelled irradiance

 =



N

i=0

V (θi) (1 + 4 sin θi) sin θi ∆θ



N

i=0

cos θi (1 + 4 sin θi) sin θi ∆θ

− 1, (2)

where θ0 = 0, θN = π

2 and ∆θ = π2N .

The asymmetry of the cosine response, δ, is equivalent

to an effective tilt of an ideal cosine collector with respect

to the instrument’s mechanical axis, which can be quantified as

δ =



θ2

θ1

cos(θ + θt) sin θ dθ



θ2

θ1

cos(θ − θt) sin θ dθ

, (3)

where θt is the tilt angle.

The measured asymmetry is computed as the ratio of

sums of measurements at opposite φ (θ ≥ 0) and −π (θ <

0) in the same plane, that is,

δ =

θN=π/2

i=0

V (θi, 0) sin θi ∆θ

θN =

−π/2

i=0

V (θi) sin θi ∆θ

− 1, (4)

for ∆θ = ± π

2N .

Variations in asymmetry from channel to channel may

be due to the placement of the individual detectors behind

the diffuser. Any offset of the average asymmetry with the

23
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

mechanical axis could be due to any one of a variety of

causes:

1) the alignment on the rotating test fixture not

being correct,

2) tilt of the diffuser,

3) the detector array not being centered,

4) nonuniformity of the reflectance of the internal

surfaces of the instrument between the diffuser

and the sensor array, or

5) nonuniformity of the diffuser.

4.1.6 Immersion Factors

When a plastic, opal-glass, or Teflon diffuser is immersed in water, its light transmissivity is less than it was

in air. Since an instrument’s irradiance responsivity is calibrated in air, a correction for this change in collector transmissivity must be applied to obtain irradiance responsivity

coefficients for underwater measurements.

The change in a collector’s immersed transmissivity is

the net effect of two separate processes: a change in the

reflection of light at the upper surface of the collector, and

internal scattering and reflections from the collector’s lower

surface. A small part of the light flux falling on the collector is reflected at the air-plastic, or water-plastic, interface, and the majority of the flux passes into the collector

body. The relative size of this reflectance, called Fresnel

reflectance, depends on the relative difference in refractive

indices between the diffuser material and the surrounding

medium.

The refractive index of the collector material is always

larger than that of either water or air, and because the

refractive index of water is larger than that of air, Fresnel

reflectance is smaller at a diffuser-water interface than at

a diffuser-air interface. Thus, the initial transmission of

light through the upper surface of an irradiance collector

is larger in water than in air. The immersed upper surface is, on the other hand, also less effective at reflecting

the upward flux of light backscattered within the diffuser

body and light reflected at the lower diffuser-air interface

in the instrument’s interior, processes that are not affected

by immersion. Therefore, a larger fraction of the internally

scattered and upwardly reflected light passes back into the

water column than would be lost into air. Because the increased upward loss of internally reflected flux exceeds the

gain in downward flux through the diffuser-water interface,

the net effect of these competing processes is a decrease in

the collector’s immersed transmissivity.

To measure this effect, a suggested and acceptable procedure is as follows: The instrument is placed in a tank of

water with the irradiance collector level and facing upward.

A tungsten-halogen lamp with a small filament, powered

by a stable power supply, is placed at some distance above

the water surface. The depth of the water is lowered in

steps and readings are recorded for all wavelengths from

each carefully measured depth. A final reading is taken

with the water level below the collector, i.e., with the collector in the air. The amount of energy arriving at the

collector varies with the water depth and is a function of

several factors:

a) the attenuation at the air-water interface, which

varies with wavelength;

b) the attenuation over the water pathlength, which

is a function of depth and wavelength; and

c) the change in solid angle of the light leaving the

source and arriving at the collector, caused by

the light rays changing direction at the air-water

interface, which varies with wavelength and water depth.

Using Fresnel reflectance equations, the transmittance

through the surface is

Ts(λ) = 4nw(λ)



1 + nw(λ)

2 , (5)

where nw(λ) is the index of refraction of the water at wavelength λ.

The transmittance through the water path, Tw(λ), will

be

Tw(λ) = e−K(λ) z, (6)

where K(λ) is an attenuation coefficient of the water and

z is the path length in corresponding units.

The change in solid angle with water depth z is given

by the factor

G(z, λ) = 1 − z

d

	

1 − 1

nw(λ)


−2

, (7)

where d is the distance of the lamp source from the collector surface.

The immersion correction factor Fi(λ) for irradiance is

then calculated for each depth z as

Fi(λ) = Ea(λ)

Ew(z, λ)

Ts(λ) Tw(z, λ) G(z, λ), (8)

where Ea(λ) and Ew(z, λ) are the irradiance in air and the

irradiance underwater at depth z, respectively.

There are two unknowns in (5)–(8): the attenuation coefficient of the water K(λ) and the immersion factor Fi(λ).

A minimum of three measurements must be made to solve

for Fi(λ): one in air to get Ea(λ), and two at different

water depths for Ew(z, λ). The recommended method is

to take readings of Ew(z, λ) at many depths. Then, using

the exact form of (8), a least-squares regression is solved

for the Fi(λ) and K(λ) terms giving the best fit. The complete derivation of (5)–(8) is given in Petzold and Austin

(1988).

24
Mueller and Austin

The absolute calibration for the spectral radiance channels is found by viewing a surface of known radiance in air

in the laboratory. When the instrument is submerged in

water, a change in responsivity occurs and a correction

must be applied. This change in responsivity is caused by

the change in the indices of refraction of the different media in which the instrument is immersed—in this case air

and water. Two optical changes occur, both of which are

caused by the change in refractive index. The two effects

to be corrected are:

1) the change in transmission through the interface between the air and the window during calibration, and the same effect through the waterwindow interface during data measurement, and

2) the change in the solid angle included in the underwater FOV relative to that in air.

Since the refractive index of seawater, nw(λ), is a function

of wavelength λ, the correction factor Fi(λ) will also be a

function of wavelength.

If the refractive index of air is assumed to be 1.000 at

all wavelengths, and if ng(λ) is the index of refraction for

the (glass) window and nw(λ) is the index of refraction for

water, then, as shown in Austin (1976), the correction for

the change in transmission through the window, Tg(λ), is

Tg(λ) =



nw(λ) + ng(λ)

2

nw(λ)



1 + ng(λ)

2 , (9)

and the correction for the change in the FOV, Fv, is

Fv(λ) = 

nw(λ)

2

. (10)

The index of refraction of a PlexiglasTM window, ng(λ),

may be computed using an empirical fit to the Hartmann

formula, that is,

ng(λ)=1.47384 + 7.5

λ − 174.71, (11)

where λ is the wavelength in nanometers (Austin 1976).

The index of refraction for seawater nw(λ) may be similarly

computed using an empirical fit of the data from Austin

and Halikas (1976),

nw(λ)=1.325147 + 6.6096

λ − 137.1924. (12)

The immersion factor Fi(λ) is then obtained as

Fi(λ) = Tg(λ) Fv(λ)

= nw(λ)



nw(λ) + ng(λ)

2



1 + ng(λ)

2 . (13)

4.1.7 Linearity and Electronic Uncertainty

The linearity of the radiometric channels must be determined over their expected range of use. The abovesurface (deck cell) and underwater irradiance sensors intended for the measurement of downwelling irradiance have

full-scale (saturation) values that are not readily obtained

with the usual incandescent blackbody sources, such as

1,000 W 3,200 K tungsten-halogen projection lamps. The

linearity at the high end of the calibrated range may be

determined by using 900–2,000 W high pressure xenon arc

lamps, which provide a small, stable source of high intensity (approximately 6,000 K) radiation. With such lamps,

irradiance levels approximating full sunlight can be attained. Using such sources for the high end, and the more

easily managed tungsten-halogen lamps over the range below20–30% of full scale, the linearity of the response characteristic of the radiometric channels can be assessed. The

flux should be changed in 5 db (0.5 log), or less, steps using

a proven and accepted procedure for controlling irradiance

such as inverse square law, or calibrated apertures. These

suggested procedures for testing linearity at the higher levels are not well established in practice, and research is

needed to determine the precision which can be attained.

If departures from linearity are found, they must be incorporated into the calibration function for the instrument

and be properly applied to the rawlevel-1 data to obtain

calibrated level-2 irradiance and radiance data. Level-1

and level-2 data are defined in Section 6.1.

It is recommended that all instruments utilizing inputs

from ancillary sensors, e.g., transmissometers, be characterized for the linearity and uncertainty of the voltage measurement covering the full output range of the ancillary

sensor. For instruments with range dependent gain changing, either manual or automatic, the scale offset and linearity for each range should, at a minimum, be tested annually. Uncertainties exceeding 0.1% of any reading within

the normal working range must be investigated and corrected.

Other characteristics of electronic sensor systems may

adversely affect measurement uncertainty. During the design and engineering prototype development of a radiometer, the design and implementation must be analyzed to

characterize, and correct as needed, possible effects of hysteresis, overload, recovery times, cross talk between either

optical transducers or electronic channels, and sensitivity

to orientation in the Earth’s magnetic field, which is particularly likely with photomultiplier tubes.

4.1.8 Temperature Characterization

Two major types of temperature-induced variation may

be seen in an optical radiometric instrument: 1) offset or

dark changes, and 2) scale responsivity changes. Each

underwater instrument must be individually characterized

over the range of −2–40◦ C. In the case of deck cells, the

25
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

temperature range for testing should be extended to −10–

45◦ C. Sensors exhibiting temperature coefficients greater

than 0.01% per ◦C over this temperature range, should be

fully characterized over their respective ranges to establish the means and precision with which post-acquisition

processing can be used to correct for temperature dependency. Although knowledge of the zero, or dark current,

drift is essential for working at the lowest radiances or irradiances, it should be emphasized that more significant

near-surface errors may be induced by temperature variations in responsivity. These possible responsivity changes

must be individually determined across the spectrum.

In the above discussion, the temperatures cited are environmental temperatures, but it should be emphasized

that any correction must use the temperature of the affected element, which is normally in the interior of the

instrument. This is best accomplished by routinely using

temperature sensors placed at critical locations within the

instrument. For highest precision, dynamic temperature

testing involving temporal transients, as well as possible

temperature gradients within an instrument, may be appropriate.

4.1.9 Pressure Effects

Pressure can cause radiometric measurement errors by

deforming irradiance collectors. Pressure coefficients associated with polytetrafluoroethylene (PTFE) based irradiance diffusers are known to exist, but they are not uniform

and there may be hysteresis effects. It is recommended

that each type of irradiance detector be examined for variations in responsivity with pressure. If a significant effect

is observed, then pressure-dependent responsivity coefficients should be determined separately for each instrument

and collector. The pressure characterization should also

test for, and quantify, hysteresis and temporal transients

in responsivity under a time varying pressure load. The

characterization of pressure effects has not previously been

common practice, and the requisite procedures are therefore poorly defined; newprotocols must be developed.

4.1.10 Pressure Transducer Calibration

The radiometer’s pressure transducer, which is used to

measure instrument depth during profiles, should be tested

and calibrated before and after each major cruise.

4.2 RADIOMETRIC STANDARDS

This section describes sources and methods by which

the NIST scale of spectral irradiance is transferred to calibrate irradiance and radiance sensors. The principal working standards used for spectral irradiance responsivity calibration are FEL lamp working standards (Section 4.2.1).

The spectral irradiance scales of the FEL lamps are in

turn transferred to spectral radiance scales using plaques

of known bidirectional reflectance, or integrating spheres,

or both (Section 4.2.2). An ongoing series of SeaWiFS Intercalibration Round-Robin Experiments (SIRREXs) has

been initiated by the SPO to assure internal consistency

between the laboratories which calibrate radiometers for

SeaWiFS validation (Mueller 1993 and Mueller et al. 1994).

4.2.1 Lamp Irradiance Standards

The options available for radiometric calibration standards are limited to standard sources or standard detectors. Lamp standards of spectral radiance and irradiance

are provided by NIST and various commercial standardizing laboratories and manufacturers who furnish NIST

traceable secondary standards. The uncertainty cited for

these standards by NIST is, at best, 1% in the visible and

3% is a more realistic estimate of absolute uncertainty attainable using lamp standards alone. Over the calibration

range from 250–2,500 nm, the uncertainty is approximately

6% at the endpoints.

The lamp standard of spectral irradiance is traditionally used for radiometric calibration, mainly because of its

ease of use compared to the spectral radiance lamp. NIST

publishes guidelines for the setup, alignment, and use of

these standards. The vendors that manufacture and calibrate these lamps also issue guidelines for their use.

4.2.2 Radiance

Spectral radiance may be obtained by using an irradiance standard lamp and a Lambertian reflecting plaque.

The standard lamp is positioned on axis and normal to

the center of the plaque at the calibrated distance. The

instrument or detector package to be calibrated is nominally positioned to viewthe plaque at 45◦ measured from

the axis. The radiance, then, is given by

L(λ) = 1

π ρ(λ)E(λ), (14)

where ρ(λ) is the bidirectional reflectance of the plaque for

0◦ incidence and 45◦ viewing, E(λ) is the known spectral

irradiance from the lamp during calibration and the total

FOV of the instrument being calibrated is filled by the

illuminated plaque.

The known radiance of the plaque provides an uncertainty comparable with that of the irradiance standard

lamp, i.e., less than or equal to 3%, for calibrating a radiance detector with a very narrow FOV (≈1◦). Large

plaques, e.g., 40 cm2, have been successfully used to calibrate radiance sensors having up to 25◦ full-angle FOVs.

Intercomparisons of calibrations on underwater radiance

sensors (possessing in-air full-angle FOVs ranging from 20–

24◦), made using this technique at different laboratories,

have generally agreed within approximately 5%.

A better approach to calibrating multispectral radiance

sensors is to viewan integrating sphere that is uniformly illuminated by stable, appropriately baffled lamps, and that

26
Mueller and Austin

also has an exit port large enough to completely fill the sensor’s FOV. The sphere and exit port must be large enough

to place the radiance sensor far enough away to prevent significant secondary illumination of the sphere walls due to

retro-reflection off the sensor’s entrance optics; if the sensor

is too close, the retro-reflected light will both increase and

distort the uniformity of the radiance distribution within

the sphere. Traditionally, the calibration of an integrating

sphere radiance source has been accomplished by appropriately transferring the known output from a standard lamp

irradiance source.

Sphere Calibration Methods

1. The approach used at NASA/GSFC is to view

the irradiance output of the lamp, initially, and

then the sphere, with a spectroradiometer equipped with integrating input optics (McLean and

Guenther 1989 and Walker et al. 1991). The

spectral irradiance responsivity of the radiometer is calibrated using the lamp data, and the

(assumed) Lambertian radiance of the sphere is

determined by dividing the measured spectral

irradiance output of the sphere by π.

2. An alternative method is to calibrate a stable,

narrowFOV radiometer by viewing the standard lamp output reflected from a plaque, as described above. The output from the sphere’s exit

port is then viewed within this radiometer. The

radiometer should also be used, at this point, to

map the angular distribution of radiance in the

sphere as viewed through the exit port. This important verification of a uniform radiance distribution is not possible when Method 1 is used to

calibrate sphere radiance. A promising variant

of Method 2 is to calibrate the sphere using a

self-calibrating radiometer (Palmer 1988).

4.2.3 Radiance Standardization

Detectors of the type embodied in the United Detector Technology QED-200 (where QED stands for Quantum

Efficient Device) radiometer are 99.99% quantum efficient.

Palmer (1988) shows how such a detector may be combined with precision apertures and well-characterized filters to measure self-calibrated spectral radiance with an

absolute uncertainty less than 1%. A calibration approach

based on such radiometer standards is essential to achieve

1% internal consistency in the radiometric uncertainty of

measurements made for SeaWiFS radiometric validation.

It is worth emphasizing here that the essential objective is to achieve internal consistency in the SeaWiFS optical database through uniform application of calibration

techniques based on a common radiometric standard with

precision approaching 1%, or less if possible. An important, but not essential, goal is to establish NIST traceable

absolute uncertainty of less than 1% with this standard.

A self-calibrating radiometer may be used directly to

calibrate and map the radiance distribution of integrating

sphere sources (Method 2 in Section 4.2.2 above). The selfcalibrating radiometer standard of radiance may be transferred to a stable lamp source of irradiance through the reversal of the reflectance plaque technique, described above,

for calibrating radiance sensors with a standard lamp irradiance source.

These ideas have not yet been incorporated into a practical and widely accepted set of procedures for the calibration of oceanographic or airborne radiometers using selfcalibrating radiometric standards. A significant level of

laboratory work must be done to establish the repeatability

of results attainable through these techniques under a variety of conditions, and to codify that experience into calibration protocols. The spectral responsivity of the QED200 type detector is known, for example, to vary systematically with temperature (Kohler et al. 1990), and the spectral transmission functions of the filters in a self-calibrating

radiometer must be re-characterized at a frequency that

will guarantee the uncertainty of the calculated radiance.

This frequency must be established through experience,

but a reasonable first approximation is that filter transmission functions should be remeasured every fewmonths.

One goal of the SeaWiFS mission is to base radiometric

validation on shipboard, moored, and airborne radiometry

with 1% uncertainty. If that goal is to be substantially

achieved, then the work described above to establish new

calibration standards and protocols must be pursued vigorously over the next two years.

4.2.4 Traceability and Comparisons

The variety of instruments available for validation measurements makes it imperative that some common calibration traceability exists. Recognizing that it would be

impractical to characterize and calibrate all oceanographic

and airborne radiometers at GSFC, several remote calibration facilities should be established, and working standards

and protocols used at these facilities should all be traced

directly to those at the GSFC calibration facility. This

organizational structure is shown schematically in Fig. 2.

Methods of standards intercomparison may include use of

NIST calibrated filter radiometers to track and document

the operation of each facility (radiometer wavelengths for

this intercomparison will be determined). Round-robin

blind calibration comparisons of a standard instrument

would also be implemented to benchmark the internal consistency of calibrations performed at the various facilities

involved.

4.2.5 Portable Standards

Between radiometric calibration activities, stable lamp

sources in rugged, fixed geometric configurations should be

27
Secondary

Standards

Radiometric

Standard

Protocols

Primary

Standards

Radiometric

Standard

Protocols

Marine Optical

Calibration Facilities

NASA Goddard

Space Flight Center

National Institute of

Standards and Technology

Irradiance

and

Radiance

Sources

and

Detectors

Radiometric

System

Calibration

Portable

Radiometric

Source

In Situ Optical Instruments

Secondary

Standards

Radiometric

Standard

Protocols

Intercalibration

Standards

Space Instruments

Portable

Radiometric

Source

Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Fig. 2. Organizational structure for optical instrumentation characterization and calibration.

used to track instrument performance. Irradiance channels can be monitored with irradiance sources at fixed distances from the collectors, while radiance sources can be

monitored by filling the FOV with diffuser plates placed

in front of the irradiance sources, or by using integrating

cavity sources. In each case, careful attention must be

given to fixing specific geometries of source and detector

in each use. The stability of the lamp output and the

repeatability of measurement must be sufficient to detect

2% variations in an instrument’s performance. An instrument should be connected to the portable standard and its

response recorded daily, keeping a record of instrument responsivity throughout an experiment. Furthermore, these

sources would provide an essential warning of problems if

they appear.

The portable field reference source must be available

when the complete radiometric calibrations are performed

so that a baseline may be established and maintained for

each sensor channel (Section 4.1.1). These sources are

not a substitute for complete calibrations. The temporal

record they provide will, however, be invaluable in cases

where the pre- and post-cruise calibrations disagree or if

the instrument is disturbed, e.g., opened between calibrations or if the data quality are otherwise suspect. These

portable standards are an important part of the recommended instrument package.

Although several manufacturers offer somewhat portable irradiance and radiance sources, there has been very

little previous work to validate and use portable radiometric standards to test oceanographic radiometers in the field.

Therefore, detailed hardware specifications and procedural

protocols must be developed through a series of laboratory

and field tests using candidate equipment and standards.

4.3 ABOVE-WATER RADIOMETRY

In general, the protocols specified in Section 4.1 for

in-water oceanographic radiance sensors are applicable for

28
Mueller and Austin

characterizing and calibrating shipboard and airborne radiometers used to measure water-leaving radiance. Obvious exceptions are that immersion and underwater FOV

characterizations are not appropriate for above-water sensors.

Polarization sensitivity is more critical in above-water

radiometry than underwater radiometry. If a radiometer

measures polarization components of radiance, then its

responsivity and rejection of cross-polarization radiance

must be characterized for each component channel. For

above-water scalar radiance instruments, as with the SeaWiFS radiometer, sensitivity to linear polarization must

be less than 2%, and the actual degree of polarization sensitivity must be characterized for each channel.

A generalized protocol for characterizing the polarization sensitivity of a radiometer is given here. The instrument should viewa source of linearly polarized radiance, and its apparent radiance response L1(λ) should

be recorded. The instrument should then be rotated 90◦

about its FOV axis, still viewing the linearly polarized radiance source, and the apparent radiance response L2(λ)

should be recorded. The polarization sensitivity of the instrument will be calculated as

P(λ) =









2



L1(λ) − L2(λ)



L1(λ) + L2(λ)









. (15)

As required for the SeaWiFS radiometer, airborne and

shipboard radiometers must satisfy P(λ) < 0.02.

A very simple, semi-quantitative test of a radiometer’s polarization sensitivity can be performed outdoors

on a cloud- and haze-free day. The instrument should

be pointed at the sky in the zenith-sun plane at an angle of approximately 90◦ from the sun, and its response

L1(λ) recorded. Since singly-scattered Rayleigh radiance

is 100% polarized at a scattering angle of 90◦, if aerosol

scattering is small, the sky radiance viewed at this angle

will be strongly polarized. If the instrument is then rotated

90◦ about its FOV axis to measure L2(λ), an approximate

estimate of P(λ) may be computed, as above.

Specification of detailed protocols for laboratory characterization of a radiometer’s polarization sensitivity will

require more attention than is available here. In particular,

protocols should be developed which describe in detail:

1) laboratory setups for producing a stable, uniform, extended source of linearly polarized radiance; and

2) laboratory procedures for measuring the actual

degree of polarization of the polarized radiance

source and for determining the uncertainty of

the polarization sensitivity estimate achieved using a particular experimental setup.

Temperature dependence of an airborne radiometer’s

polarization sensitivity should initially be characterized at

5◦and 30◦ C. If significant differences in P(λ) exist at these

extremes of instrument operating temperatures, then polarization sensitivity measurements should be made at several additional temperatures in that range.

4.4 CALIBRATION OF IOP METERS

Calibration of beam transmissometers has traditionally

been carried out by means of in-air measurements, with a

subsequent adjustment for changes in the Fresnel reflections by the windows upon submergence into water. The

660 nm transmissometers produced by Sea Tech, Inc. are

independently calibrated at the factory after which calibration is maintained via frequent air calibrations (Sections 5.4.1 and 6.7). This approach is adequate for this

generation of 660 nm transmissometers.

The newer generation of combined spectral absorption

and beam transmission meters require a more accurate calibration procedure. This class of instruments must be calibrated with optically pure water, which has been freshly

prepared using multiple-pass reverse osmosis filtration and

analyzed with special optical techniques to verify optical

purity. Ordinary laboratory grade pure water, prepared

using distillation, deionization, or ordinary reverse osmosis filtration, will not ordinarily be optically pure enough

to serve as a calibration standard. In general, it will not

be practical to perform this calibration procedure either

at sea or in the average oceanographic laboratory. Annual recalibration, either by the manufacturer, or another

qualified laboratory, together with air calibrations every

three days during deployments, are recommended (Section 5.2.4). The air calibration procedure for this class

of instruments is also more elaborate than for the red

(660 nm) transmissiometers (Section 5.2.4).

Procedures for calibrating a scattering meter depend on

the detailed design of the instrument. For example, backscattering meters are calibrated with Spectralon plaques

of known reflectance. Detailed protocols for calibrating

scattering meters remain to be developed in a future revision to this document.

4.5 SUN PHOTOMETERS

Sun photometer calibrations should be performed at

least annually, when used consistently, through a Langley

calibration procedure. In this procedure, the solar signal transmitted through the atmosphere is measured over

different air masses, i.e., at different solar zenith angles,

throughout the course of the day. The validity of using

these measurements as calibration of a sun photometer

hinges strongly on the assumption that aerosols are uniformly distributed and do not vary throughout the day.

These Langley calibrations, therefore, should be performed

in areas of atmospheric stability with low aerosol loading.

Suitable locations include the astronomical observatories

at Mauna Loa, Hawaii, and Kitt Peak, Arizona. In between these calibrations, radiance calibrations with standard lamps may be used as a stability check (Shaw1976).

29
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Temperature stability should be characterized for each

instrument. Linearity and spectral calibrations should be

performed with the same frequency as the absolute calibration; these characterizations must be performed in the

laboratory.

4.6 SKY RADIANCE CAMERAS

Absolute and spectral calibrations should be performed

on the radiance distribution camera before and after each

cruise. A full characterization of the instrument should

be performed initially, including camera lens roll-off characteristics for each camera (Voss and Zibordi 1989). If

attenuation devices are used to prevent solar saturation,

these should be calibrated frequently to track drift. Linearity calibrations should also be performed with the same

frequency as the absolute and spectral calibration. Procedures for characterizing this class of instruments are essentially the same as for other radiance detector systems.

Each individual detector element in the detector array is

essentially regarded as an independent radiometer.

4.7 PIGMENT CALIBRATIONS

HPLC equipment used to measure phytoplankton pigment concentrations is to be calibrated using standards

distributed under the auspices of the SeaWiFS Program.†

Concentrations of the pigment standards should be determined using a monochromator-based spectrophotometer and the extinction coefficients summarized in Bidigare

(1991). The use of a diode array spectrophotometer can

† The HPLC pigment standards are available from Robert R.

Bidigare, Department of Oceanography, University of Hawaii,

Honolulu, HI 96822.

result in the underestimation of chlorophyll a concentration because of errors associated with fluorescence contamination (Latasa et al. 1994). Bench fluorometers used

to measure concentrations of extracted chlorophyll a and

phaeopigments should be calibrated using authenticated

standard chlorophyll a adopted for HPLC. In situ fluorometers should be calibrated against extracted chlorophyll a

from concurrent bottle samples.

4.8 CTD CALIBRATIONS

The conductivity probe, temperature probe, and pressure transducer of the CTD should be recalibrated before and after each major cruise by a properly equipped

physical oceanographic laboratory, including those maintained by many CTD manufacturers. In addition, the conductivity probe should be independently calibrated during the course of each cruise by obtaining salinity water

samples (Section 5.2.3) simultaneous with CTD readings.

These salinity samples are to be analyzed, either at sea

or ashore, with a laboratory salinometer calibrated with

International Association for the Physical Sciences of the

Ocean (IAPSO) Standard Seawater.

If simultaneous deployment of the CTD with optical

instruments having independent pressure transducers is

practical, the two depths measured by the different instruments should be compared over the range of the cast. If

depth measurements disagree significantly, these comparisons may be used to correct whichever transducer is found

to be in error through analysis of pre- and post-cruise pressure transducer calibrations.

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Mueller and Austin

Chapter 5

Measurement Protocols

Introduction

This chapter describes the methods and procedures by which measurements are to be made during oceanographic

deployments for SeaWiFS algorithm development and validation. Section 5.1 gives protocols for obtaining radiance and irradiance measurements from ships and aircraft. Section 5.2 gives protocols for measuring IOP,

chlorophyll a fluorescence, and CTD profiles. Section 5.3 gives protocols for sun photometry and sky radiance

distribution measurements. Section 5.4 covers protocols for obtaining and processing water samples for phytoplankton pigment concentration measurements and spectrophotometric determination of absorption by particles

and dissolved matter. Sections 5.5–5.7 describe ancillary observations to be recorded at each station, radiometric

measurements from moorings, and radiometry on drifting buoys. Finally, Section 5.8 gives protocols addressing

sampling strategy, station location, and coordination of ship and aircraft measurements in Case-1 and Case-2

water masses.

5.1 IRRADIANCE AND RADIANCE

Determinations of in-water spectral Ed, Eu, and Lu,

both near the surface and as vertical profiles, are required

for calibration and validation of the water-leaving radiance as retrieved from the SeaWiFS satellite sensor. Nearsurface measurements should profile through at least the

top three optical depths to reliably extrapolate to z = 0;

it is essential to obtain a profile through at least the top

optical depth. To better characterize the water column

for remote sensing applications, e.g., primary productivity estimation, deeper vertical profiles should be made to

200 m, or seven optical depths whenever possible. Sea bed

reflection influences on Lu and Eu should be avoided for

SeaWiFS validation and algorithm development by collecting data only from water deeper than six optical depths

for Ed(490); remote sensing applications for optically shallowsituations where bottom reflectance is present are not

within the scope of these protocols.

There are two primary sources of error in the determination of these optical parameters: the perturbation of

the in-water radiant energy field by the ship (Gordon 1985,

Smith and Baker 1986, Voss et al. 1986, and Helliwell et al.

1990), and atmospherically induced variability in radiant

energy incident on the sea surface during in-water measurements (Smith and Baker 1984). The influence of ship

shadowon the vertical profiles of Ed, Eu, and Lu is dependent upon the following variables: solar zenith angle, the

spectral attenuation properties of the water column, cloud

cover, ship size (length, beam, draft, and freeboard) and

color, and the geometry of instrument deployment. Atmospheric variability is primarily dependent upon sun elevation and variations in cloud cover. The near surface inwater data also show variability caused by wave focusing,

which can be minimized at a fixed depth by averaging over

several wave periods, but which can pose severe problems

in vertical profiles during which the instrument descends at

speeds of 0.5–1 m s−1. Raman scattering and fluorescence

result in second-order errors near 490 nm (CDOM fluorescence), and at longer wavelengths, contributions from phycoerythrin and chlorophyll a fluorescence and water Raman

scattering are significant.

5.1.1 Ship Shadow Avoidance

The complete avoidance of ship shadow, or reflectance,

perturbations is a mandatory requirement for all radiometric measurements to be incorporated into the SeaWiFS

validation and algorithm database. The influence of ship

shadowis best characterized in terms of attenuation length

1/Kd(λ) (Gordon 1985). Because LW is required with an

uncertainty of 5% or better, the protocol requires that vertical profiles be measured outside the effects of ship perturbation to the radiant energy field. To accomplish this,

the instrument must be deployed from the stern, with the

sun’s relative bearing aft of the beam.

Estimates of the minimum distance away from the ship,

under conditions of clear sunny skies, are given below. The

distances are expressed in attenuation lengths to minimize

error. For Ed(λ) measurements, the general equation for

distance away, ξ, in meters is given as

ξ = sin(48.4◦)

Kd(λ) . (16)

The distance from the ship is required to be 3/Ku(λ) m for

Eu(λ) and 1.5/KL(λ) m for Lu(λ) measurements. These

31
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

distances should be increased if the instrument is deployed

off the beam of a large vessel.

A variety of methods have been used to deploy optical instruments beyond the influence of the ship. During

CZCS algorithm development, floating plastic frames were

equipped with small winches and instruments to obtain

near surface optical profiles at some distance away from

the ship. An umbilical cable provided power and data

transfer. These platforms, while being somewhat difficult

to deploy, worked well at avoiding ship shadow. Alternatively, extended booms can be used to deploy the instrument away from the ship and have the advantages of allowing relatively rapid deployment and simultaneous rosette

bottle sampling. As a point of caution, however, very long

booms may accentuate unwanted vertical motions due to

ship pitch and roll.

Waters et al. (1990) used an optical free-fall instrument

(OFFI) that allows optical data to be obtained outside

the influence of ship perturbation. In addition, the OFFI

approach allows optical data to be obtained independently

from violent ship motion, which may be transmitted to the

instrument via the hydrowire, especially on a long boom.

Yet another method for the deployment of optical sensors

is via an ROV. Some groups, e.g., Smith (pers. comm.),

have deployed a spectrometer on an ROV and obtained

data completely free of ship influences.

The above criteria for ship shadowavoidance are admittedly very conservative. Unfortunately, the above cited

models and observations provide only approximate guidance on minimum distances at which ship reflectance and

shadoweffects become insignificant under all circumstances. Therefore, the SPSWG has adopted relatively extreme

distance criteria, recognizing that in many specific combinations of lighting conditions, ships and optical properties,

ship shadow, and reflection effects may become unimportant much closer to the ship.

The essential requirement is that each investigator establish that any measurements of Ed, Eu, and Lu, submitted for SeaWiFS validation and algorithm development,

are free from ship-induced errors. The simplest way to do

this is to adhere to the above distance criterion, which is

not difficult when using either a tethered free-fall system

or instruments mounted on an ROV. In other cases, it is incumbent on the investigator to otherwise demonstrate the

absence of ship effects, e.g., through analysis of a series of

profiles at increasing distance.

At wavelengths where attenuation lengths are the same

order of magnitude as, or less than, the size of the instrument package, e.g., in the ultraviolet-B (UVB) or red and

near infrared spectral regions, care must be taken to consider possible perturbation of the radiant energy field by

the instrument package itself. Methods of accounting for

self-shadowing by the instrument are not well established

and newmeasurement approaches must be developed (Section 5.1.6).

5.1.2 Depth Resolution in Profiles

The instrument sampling rate and the speed at which

the instrument is lowered or raised through the water column should yield at least two, and preferably six to eight,

samples per meter.

5.1.3 Instrument Dark Readings

The dark current of optical sensors is frequently temperature dependent. As a consequence, accurate radiometric measurements require that careful attention be given to

dark current variability. It is recommended that each optical measurement be accompanied by a measurement of the

instrument dark current. When there is a large temperature difference between the instrument on the deck and

the water temperature, the instrument should be allowed

to equilibrate with ambient water temperature at the beginning of each cast.

Deep casts, e.g., 500 m, may permit the determination

of the dark current in each optical channel at the bottom of

each cast. Many instruments, however, are not designed to

be safely lowered to 500 m, and this approach is usually not

feasible. Furthermore, there is some intrinsic uncertainty

over possible contamination by bioluminescence when dark

readings are obtained in this way. If the instrument is

equipped with a shutter, dark currents can be measured at

any depth in the cast. If the dark current is not determined

during the cast, it should be determined as soon as possible

after the instrument is returned to the deck.

Temperature effects on sensor responsivity can be significant and should not be ignored. Therefore, sensors

should be equipped with thermistors on detector mounting

surfaces to monitor temperatures for data correction. Otherwise, deck storage should be under thermally protected

conditions prior to deployment and on-deck determination

of dark voltages.

5.1.4 Surface Incident Irradiance

Atmospheric variability, especially under cloud cover,

leads directly to variability of the in-water light field and

must be corrected to obtain accurate estimations of optical

properties from irradiance or radiance profiles. First order

corrections for this variability can be made using above

water (on deck) measurements of downwelling spectral irradiance, Es(λ) = Ed(0+, λ). Smith and Baker (1984) and

Baker and Smith (1990) theoretically computed the irradiance just belowthe air-water interface, Ed(0−, λ), from

deck measurements to correct in-water profile data.

The deck sensor must be properly gimballed to avoid

large errors in Es(λ) due to ship motion in a seaway. Improper gimballing can actually accentuate sensor motion

under some circumstances, however, and this aspect of

a shipboard radiometer system must be engineered with

some care.

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Mueller and Austin

Recently, Waters et al. (1990) have demonstrated a

method to more directly determine Ed(0−, λ) by deploying an optical surface floating instrument (OSFI) to obtain

continuous optical data just belowthe air-water interface.

These Ed(0−, λ) are used as a normalization factor to correct for variations in irradiance during a vertical profile,

or over the period of a day for a sequence of profiles. Research and development is needed to determine whether

this should be the preferred approach for SeaWiFS validation measurements.

5.1.5 Instrument Attitude

An instrument’s attitude with respect to the vertical is

a critical factor in measurements of Ed(z, λ) and Eu(z, λ),

and is only slightly less critical for Lu(z, λ). Roll and pitch

sensors must, therefore, be installed in the underwater radiometers used for the SeaWiFS program. The data from

these attitude sensors are to be recorded concurrently with

the data from the radiometric channels and are to be used

as a data quality indicator. It is not deemed necessary to

determine or control attitude determination errors resulting from surface wave-induced accelerations at very shallowdepths.

5.1.6 Instrument Self-Shading

Gordon and Ding (1992) recently modeled the errors

introduced by an instrument’s own shadow in direct measurements of Lu(λ) and Eu(λ). For this source of error to

be less than 5%, without modeled corrections, the instrument radius r must satisfy r ≤ 


40a(λ)

−1 for Eu(λ) and

r ≤ 
100a(λ)

−1 for Lu(λ). They calculate for λ = 865 nm

in pure water, as an example, that the instrument radius

must be approximately 0.3 cm to measure Eu(865) with a

maximum of 5% error; the instrument radius must be significantly smaller for direct measurement error in Lu(865)

to be 5% or less.

Gordon and Ding (1992) also propose a simple model

for correcting Lu(λ) and Eu(λ) for the self-shadowing effect. They write

Lu(λ) = Lu(λ)

1 − ε(λ) (17)

and

ε(λ)=1 − e−k

a(λ)r, (18)

where  is the true value,  is the measured value, k =

y/ tan θ0w, θ0w is the refracted solar zenith angle and y is

an empirical factor for which they give values determined

by fitting their model results (y ≈ 2). A similar correction,

with a different table of values for y applies to Eu(λ).

When the above geometric corrections are applied, Gordon and Ding (1992) estimate that errors less than or equal

to 5% in Lu(λ) could be determined from measurements

with instruments having maximum diameters of 24 cm for

λ ≤ 650 nm, and with instruments of maximum diameter 10 cm for 650 < λ ≤ 700 nm at solar zenith angles

(θ0) greater than or equal to 20◦, and maximum chlorophyll concentrations of 10 mg m−3. To measure Lu(λ) correctable to less than 5% error at θ0 = 10◦ (with chlorophyll

concentrations less than or equal to 10 mg m−3), maximum

instrument diameters are 12 cm for λ ≤ 650 nm and 5 cm

for 650 < λ ≤ 700 nm. Even with these corrections, however, instrument diameters of 1 cm or less must be used to

assure self-shading Lu(λ) errors are 5% or less at 780 and

875 nm.

The Gordon and Ding (1992) model predictions have

recently been compared to experimental measurements of

Lu(λ) just beneath the sea surface, using a fiber-optic radiometric probe (Zibordi and Ferrari 1994). The experiment was performed in a lake, with solar zenith angles

ranging between 25◦ and 50◦, on several days with cloudfree skies. Spectrophotometric methods (similar to those

in Sections 5.4.2 and 6.8.2) were used to measure absorption by particles and Gelbstoff. At wavelengths of 500,

600, and 640 nm, a series of discs was employed to vary

instrument self-shading geometry in several steps over the

range 0.001 < a(λ)r ≤ 0.1. The Gordon and Ding (1992)

model predicted self-shading radiance and irradiance effects that may be applied as corrections, and which agreed

with measured values within 5% and 3% respectively. The

model corrections were all biased high relative to the measured values. Zibordi and Ferrari (1994) chose to compare

their measurements to the Gordon and Ding (1992) point

sensor model, and use of their finite-sensor model results

may have improved the comparisons.

This initial confirmation of the Gordon and Ding (1992)

instrument self-shading model is confined to clear-sky conditions, solar zenith angles greater than 25◦, near-surface

Lu(0−, λ) and Eu(0−, λ), and a(λ)r less than or equal to

0.1. Additional theoretical and experimental research will

be necessary to generalize this correction for cloudy sky

conditions and for variations with depth in Lu(z, λ) and

Eu(z, λ) profiles. The above restrictions notwithstanding,

the excellent agreement shown so far covers a very important range of conditions for SeaWiFS algorithm development and validation. Therefore, a provisional protocol for applying self-shading corrections to Lu(0−, λ) and

Eu(0−, λ) is given in Section 6.1.7.

5.1.7 Airborne Ocean Color Radiometry

Ocean color may be measured from aircraft using either imaging radiometers (usually flown at high altitude),

or single FOV spectral radiometers (usually flown at low

altitude to measure profiles of ocean color beneath an aircraft’s trackline). For SeaWiFS validation, either of these

types of data can be an extremely valuable addition to

shipboard measurements.

Aircraft measurements observe the horizontal variability in ocean color radiance spectra on spatial scales which

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

are much smaller than SeaWiFS pixels; therefore, these

data are more comparable to shipboard measurements. At

a qualitative level, this information can indicate howwell

shipboard radiometric and bio-optical measurements can

be compared to SeaWiFS data at greater than 1 km pixel

resolution. For more quantitative work, if an airborne radiometer’s characteristics conform to specifications of Section 3.3, and if accurate corrections are applied for atmospheric and surface reflection effects, the high resolution airborne data may be spatially integrated to quantitatively extrapolate shipboard bio-optical measurements

to SeaWiFS pixel scales. (Note that the original data must

be corrected for sun and sky glitter, as well as atmospheric

transmission and path radiance, before spatial integration

to SeaWiFS resolution.) Finally, in cases when airborne

normalized water-leaving radiances estimated from aircraft

measurements are independently validated as being in conformity with SeaWiFS uncertainty goals, they may be used

for direct radiometric validation of SeaWiFS radiometric

performance.

Methods for atmospheric correction and estimation of

normalized water-leaving radiances from high altitude airborne ocean color imagery are nearly identical to, and as

challenging as, those methods which must be applied to

SeaWiFS data itself (Carder et al. 1992 and Hamilton et

al. 1992). These problems and their solutions lie beyond

the scope of the ocean optical protocols per se, at least in

this revision. The elements of ocean color radiometry from

lowflying aircraft are more closely associated with shipboard ocean optical measurements and will be addressed

here.

Under clear skies, or partial cloud cover, the radiometer

should be pointed approximately 15–20◦ from nadir in the

azimuth direction opposite from the sun, to avoid specular

sun glint from wave facets. If seas are rough and the solar

zenith angle is small, an even larger nadir angle may be

necessary. Under completely uniform overcast conditions,

the instrument should point to the nadir. If an imaging

radiometer is fixed in the nadir plane, sampling should be

scheduled to provide a solar zenith angle between 35◦ and

45◦, and all flight lines should be flown toward or away

from the sun.

For quantitative lowaltitude ocean color radiometry,

solar downwelling spectral irradiance must be measured

using a sensor mounted on top of the aircraft. Incident solar irradiance spectra are modified significantly by transmission through the atmosphere above the aircraft, and direct spectral irradiance measurements are absolutely essential for computing normalized water-leaving radiances from

flight level radiances. The measured flight-level downwelled irradiances should be used to model atmospheric

transmission and path radiance corrections, which must

be applied at altitudes of 100 m and higher. Reflected

skylight must also be removed from the measured radiances. Finally, for use in algorithms related to SeaWiFS,

the water-leaving radiances must be normalized by the ratio F0(λ)/Es(λ), where F0(λ) is the mean extraterrestrial

solar flux, and Es(λ) is the measured incident spectral irradiance propagated to the sea surface. This normalization

is also critical for ratios of water-leaving radiance, because

the spectral quality of incident irradiance is modified significantly, in a generally unpredictable way, by atmospheric

transmittance.

Under either clear skies or a completely uniform cloud

cover, i.e., overcast skies, the downwelling irradiance measurements may be used directly to model corrections for

lowaltitude atmospheric transmission and path radiance,

and for reflected sky radiance. On the other hand, ocean

color radiance data measured under variable cloud conditions are very difficult to correct and interpret. Under

these conditions, the area on the sea surface viewed by the

radiometer is often illuminated differently than is the incident irradiance sensor at the aircraft, and sky radiance

incident on the surface also varies unpredictably.

The requirement to directly measure incident spectral

irradiance may sometimes be relaxed when the experimental objective is simply to characterize spatial variability of

bio-optical properties qualitatively. Under cloud-free conditions, moreover, it may often be possible to model surface

incident irradiance accurately enough for semi-quantitative

analyses of chlorophyll concentrations from lowaltitude

airborne spectral upwelled radiance measurements alone.

For atmospheric correction and analyses of aircraft radiance data, the following ancillary parameters must be

recorded: date and time [Greenwich Mean Time (GMT)],

azimuth and nadir angle of the radiometer, heading of the

aircraft (and all other aircraft attitude angles, if available),

the flight altitude, and air pressure at that altitude. The

height of the inversion should also be recorded, as most

of the aerosols will normally be concentrated under this

height. Furthermore, a precise navigation recording is required for identification of the aircraft track within the

satellite image and for comparisons to shipboard measurements. In addition to the radiometer, a video camera is

very helpful to check for the effects of cloud shadows, foam,

and ocean fronts—effects which are difficult to identify in

the horizontal radiance profile alone.

5.1.8 Shipboard Radiance Measurements

Water-leaving radiances can, of course, be measured

from the deck of a ship using methods directly analogous to

those of low-altitude airborne radiometry (Section 5.1.7).

Given a very close proximity to the sea surface, no corrections are needed for atmospheric transmission and path radiance. Shipboard water-leaving spectral radiances must,

however, be corrected for light reflected at the sea surface,

and must also be normalized using direct measurements of

Es(λ). Performance characteristics for radiometers used to

measure Es(λ) and Lu(λ) are specified in Sections 3.2–3.3.

34
Mueller and Austin

The best position for measuring the water-leaving radiance is usually near the bowof the ship. At this position, the ship will have the least influence with respect

to shading or reflection. It is also easy to point in a direction away from the sun to reduce specular reflection of

sunlight. While underway, ocean color radiance measurements should always be made from the bow, because this is

the only position where the water is normally undisturbed

by the ship’s wake and without foam.

To measure LW (λ), the radiometer should point to the

sea surface with an angle of about 20◦ from nadir and away

from the sun’s azimuth by at least 90◦. (A viewing angle

that is 180◦ away from the sun’s azimuth may be contaminated by the glory phenomenon.) This is the point with

the minimum in specularly reflected sun and sky radiance.

Under overcast conditions, the instrument should point

closer to nadir, but not so close that ship shadowor hull

reflections affect the water-leaving radiance. (Indeed, some

larger ships have a long bulbous bownose, which must be

avoided.) Under a high sun elevation (such as in tropical

regions) and a rough sea, it may be very difficult, or even

impossible, to avoid large amounts of specularly reflected

sunlight, since large nadir angles cause severe problems due

to variations in reflected skylight. In addition, foam and

floating material must be avoided during measurements.

Because of temporal variability due to waves, it is important to record a number of spectra within a period of

a fewseconds, e.g., 30 spectra within 15 s. Before calculating final mean and standard deviation spectra, outliers

should be removed by computing initial estimates of these

statistics and rejecting radiance spectra containing values

falling more than 1.5 standard deviations from the estimated mean.

Incident spectral irradiance Es(λ) should be measured

at a location free from shadows of, and reflections by,

the ship’s superstructure. As in low-altitude aircraft radiometry, Es(λ) must be used both to normalize measured water-leaving radiance and to calculate spectral reflectance. Some investigators (Carder and Steward 1985

and Doerffer pers. comm.) advocate calculating spectral

reflectance using relative Es(λ) estimated by viewing a reference diffuse reflectance plate. Spectralon plates are used

most often, but Kodak gray cards and plates painted with

NextelTM coating have good Lambertian reflectance characteristics (Doerffer pers. comm.).

The contribution by specularly reflected sky light to

a water-leaving radiance measurement can be calculated

from measurements of the sky radiance, made either by

looking at a horizontal first surface mirror (a mirror with

no layers other than the reflective surface) at the same

nadir and azimuth angles, or by pointing the radiometer

into the sky with a zenith angle equal to the nadir angle

and with the same azimuth angle. The specular reflectance

of the water surface can be calculated using the Fresnel

equation (reflectance is approximately 0.02 within 20◦ of

nadir).

The sequence of water-leaving radiance, diffuser plate,

and sky radiance [Lsky(λ)] measurements can usually only

be completed under clear sky or uniform overcast conditions. When coupled with concurrent direct measurements

of Es(λ), however, LW (λ) and Lsky(λ) can probably be

measured under variable cloud conditions, provided a sequence of several [LW (λ), Es(λ)] and [Lsky(λ), Es(λ)], sets

of spectra can be measured in rapid succession without

significant variations.

5.2 ANCILLARY PROFILES

Beam transmittance, CTD profiles, and chlorophyll a

fluorescence should be measured at the same stations as the

irradiance and radiance measurements. Preferably, these

auxiliary profiles should be measured simultaneously with,

or otherwise immediately before or after, the radiometer

profiles. If possible, these profiles should be made in conjunction with bottle samples. For the verification of the

satellite sensor, these data will be used as a guide to the

uniformity of the first optical depth and to determine water

bottle sampling depths.

The IOP, fluorescence, and CTD profiles will also be

used as a guide for, and constraints on, the smoothing

of K(z, λ) from the radiometric profiles. The location of

maxima and other features in the structure of these profiles

identify inflection points for segmenting the optical profiles

into finite depth elements (layers) for the analytical methods described by Mueller (1991) or Petzold (1988). Both of

these techniques use multiple segments for the statistical

fit of analytic functions to the measured profiles. These

data will also be used to develop and validate pigment and

primary productivity algorithms.

5.2.1 Beam Transmittance

The windows on the beam transmissometer must be

cleaned with lens cleaner or a mild detergent solution and a

soft cloth or tissue, rinsed with distilled water, then rinsed

with isopropyl alcohol and wiped dry. An approximate air

calibration reading should be made before every cast to

verify that the windows are clean. A transmissometer dark

voltage should also be measured at this time. These ondeck air calibrations are not, however, very reliable measures of temporal drift or degradation in the instrument’s

source or detector. In the humid, or even wet, environment on the deck of a ship, the windows are often quickly

obscured by condensation, and the glass also tends to absorb enough water to affect transmission slightly (Zaneveld

pers. comm.). A very careful air calibration should be performed before and after each cruise under dry laboratory

conditions. During an extended cruise, it is also recommended to remove the instrument to a dry location in a

shipboard laboratory, and after allowing several hours for

the windows to dehydrate, a careful air calibration should

be performed. Only the laboratory air calibrations should

35
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

be used in the final processing of beam transmissometer

data.

Both the laboratory condition air calibration and dark

voltages, and the factory calibration voltages, assume the

data acquisition system measures instrument response as

true volts. It is imperative, therefore, to calibrate the

end-to-end analog-to-digital (A/D) data acquisition system and characterize its response to known input voltages.

Corrections are in the form of a linear function:

V = g(T)V + f(T), (19)

where T is temperature, must usually be applied to external voltage inputs recorded with the A/D circuits of

CTDs or profiling radiometer systems. The range dependent A/D bias coefficients should be determined at approximately 5◦ C intervals, over the range from 0–25◦ C,

to characterize the temperature sensitivity of the data acquisition system.

For the development of bio-optical algorithms describing the inherent and apparent optical properties of the water, and for algorithms estimating primary productivity,

more stringent requirements are recommended for transmissometer calibration and characteristics. Spectral measurements of beam transmittance should be made with absolute uncertainties of 0.1% transmittance per meter, or

0.001 m−1 beam attenuation coefficient c(λ).

Different and more stringent calibration protocols are

specified in Section 5.2.4 for the newcombined spectral

absorption and beam attenuation meters. Laboratory calibrations of these instruments are based on measurements

using optically pure water, produced using extraordinarily

careful reverse osmosis procedures. It is ordinarily impractical to produce and verify optically pure water either at

sea or in the average oceanographic laboratory. As with

the older red-wavelength beam transmissometers, air calibrations are prescribed as a basis for correcting instrumental drift between calibrations at a qualified laboratory.

The increased sensitivity required for the newinstruments

makes it essential to carry out more frequent air calibrations at sea. As discussed above, accurate air calibrations

must be carried out in a dry laboratory environment with

controlled relative humidity—conditions which may be difficult to implement on some ships.

5.2.2 Chlorophyll a Fluorescence

An in situ fluorometer should be employed to measure a continuous profile of chlorophyll a fluorescence. The

fluorometer should be mounted on the same underwater

package as the transmissometer, CTD, and water sampler,

if one is employed. If possible, the radiometer should also

be on this package.

The A/D channel used to acquire and record signal

voltages from the in situ fluorometer must be calibrated,

and its temperature-dependent response to known voltage

inputs characterized. During processing, a correction of

the form given in (19) must usually be applied to values

recorded with the A/D circuits of CTDs and profiling radiometer systems. As in beam transmittance, the range

dependent A/D bias coefficients should be determined at

approximately 5◦ C intervals over the range from 0–25◦ C

to characterize the temperature sensitivity of the data acquisition system.

Zero fluorescence offsets should be measured on deck

before and after each cast; the optical windows should be

shaded to avoid contamination of the zero offset value by

ambient light. Before each cast, the fluorometer windows

should be cleaned following the manufacturer’s instructions.

For chlorophyll a determinations, the fluorescence measurements should be compared to HPLC and extracted pigment measurements from discrete water samples, to permit

comparison with JGOFS standard measurements and historical databases. The in situ fluorescence measurements

will be used to provide continuous vertical profiles of interpolated pigment concentration using the bottle samples

as tie points.

5.2.3 CTD Profiles

Vertical profiles of CTD should be measured to at least

the depth of the deepest bio-optical profile. If the station

schedule will permit it, sections of CTD casts extending

to 500 m, or deeper, will be useful for computing relative

quasi-geostrophic currents and shear, which may affect the

advection and mixing of bio-optical properties during a

cruise. A real-time analysis and display of the CTD profile, together with displays of c(660) and in situ fluorescence profiles, should be available as a guide in choosing

the depths at which water sampling bottles will be closed.

If possible, a fewdeep (1,500 m depth or greater) CTD

and bottle sample profiles should be made during each

cruise to obtain data for calibrating the CTD’s conductivity probe. During these CTD calibration casts, water samples should be taken at depths where the vertical gradient

of salinity is very small. This practice will minimize errors

in the conductivity calibration resulting from the spatial

separation of the water bottle and CTD profile. The bottled salinity samples may be stored for post-cruise analyses

ashore at a laboratory equipped with an accurate salinometer and IAPSO Standard Seawater, if suitable equipment

and standard water are not available aboard the ship.

5.2.4 Spectral Absorption Profiles

Currently, there are two methods for measuring spectral absorption coefficients which use commercially available equipment. The first is conventional benchtop spectrophotometer measurements of spectral absorption by particles extracted from water samples and concentrated on

filters, followed by measurements of the spectral absorption

36
Mueller and Austin

by the dissolved component in the filtrate (Section 5.4.2).

More recently, in situ profile measurements of spectral absorption have been made using instruments which capture

most scattered light using a reflecting tube. A combination

of these two methods allows one to measure profiles of total absorption and absorption by the dissolved component

with the reflecting tube instrument, and to independently

partition the absorption spectrum at discrete depths into

its components due to particulate and dissolved substances

using filters and spectrophotometry.

In situ spectral absorption coefficient profiles can also

be measured with spectral radiometers conforming to the

performance specifications listed in Section 3 above, if the

radiometric package is extended to measure Ed(λ) and

Eu(λ), as well as scalar irradiances E0d(λ) and E0u(λ).

This combination may be approached either using hemispherical collectors to measure upwelling and downwelling hemispherical irradiances, or by using cosine collectors on one radiometer in tandem with spherical collectors on another radiometer. Given these irradiance components, spectral absorption is then computed using Gershun’s equation as

a(λ) = K(λ) E(λ)

E0(λ)

, (20)

where E(λ) = Ed(λ)−Eu(λ) is vector irradiance, and K(λ)

is the vertical attenuation coefficient for vector irradiance.

In a recent experiment, comparisons between absorption profiles measured using Gershun’s equation with E(λ)

and E0(λ) (scalar irradiance) data, and absorption profiles

measured with a reflecting tube instrument, agreed within

8% (Pegau et al. 1994). This level of agreement is well

within the calibration uncertainties of the particular prototype instruments used for that experiment, which were

approximately 10% uncertainties in both the scalar irradiance radiometer and in the reflecting tube instrument.

Less than 5% uncertainty in absorption is expected in future experiments. In very clear oligotrophic water, however, uncertainty in water absorption values may make it

impossible to realize this level of relative agreement. Unfortunately, an adequate commercially available scalar, or

hemispherical, irradiance radiometer does not exist today,

and development and characterization of suitable spherical or hemispherical collectors is a prerequisite to application of this method. The present version of the protocols

will, therefore, emphasize the combination of filter spectrophotometry (Section 5.4.2) and in situ reflecting tube

total absorption measurements. The present section covers field calibration and sampling procedures for using the

reflective tube absorption and beam transmission meter.

Recommended methods of data analysis to derive vertical

profiles of a(z, λ) and c(z, λ) are presented in Section 6.8.1.

It is always best to determine optical properties in situ,

if possible. Sampling variability, changes of light intensities, filtration procedures, and sample degradation over

time all affect the particulate matter and distort its true

optical properties as they existed in the ocean, and as

they determine the remote sensing reflectance viewed by

SeaWiFS. The reflecting tube method has been used to

measure spectral absorption in the laboratory for many

decades (James and Birge 1938). In recent years, this

method has been adapted for use in the ocean (Zaneveld

1992). Suitable instruments are nowcommercially available and are coming into general use within the oceanographic community.

The reflecting tube does not perfectly gather all scattered light and transmit it to the detector, and as a result,

there is a scattering error on the order of 13% of the scattering coefficient. This error can be largely corrected if

the beam attenuation coefficient is measured simultaneously. In that case, the scattering coefficient is obtained as

b(λ) = c(λ)−a(λ). By assuming that the measured absorption is due to water and scattering error at a wavelength in

the infrared, and by subsequent correction at other wavelengths using a provisional b(λ), it is possible to correct the

spectral absorption to within a few percent of the scattering coefficient. Only in waters with very high scattering

and very lowabsorption would this error pose a serious

absorption error. This correction method is described in

more detail in Section 5.4.5 below.

The in situ reflecting tube is normally used to measure profiles of total spectral absorption, but it has been

recently demonstrated that if the unit’s intake is fitted

with a large area 0.2 μm filter, the spectral absorption

of the dissolved component can be measured (Zaneveld

pers. comm.). A pair of reflecting tube absorption meters

can thus be used to determine the separate constituents of

absorption due to particulate and dissolved substances—

a distinction of fundamental importance in relating absorption to remote sensing reflectance. More traditionally,

the filtration and spectrophotometry techniques developed

over the last decade also lend themselves well to this task.

Using the methods described in Section 5.4.2, the spectral absorption coefficient is partitioned into components

associated with Gelbstoff, pigments, and non-pigmented

particles (the latter sometimes referred to misleadingly as

detritus).

There are two primary weaknesses of the filtration spectroscopic method:

1. Uncertainties associated with correcting the filter absorption values for scatter within the filter are not well characterized. The correction

factor for this phenomenon, called the β factor,

does not currently have a unanimous consensus

value.

2. The instrumental uncertainty in absorption due

to the dissolved component, which attenuates

weakly over the 10 cm path of a typical spectrophotometer, is also not well characterized.

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Note that some longer path spectrophotometers are in use

experimentally, and may reduce this source of uncertainty

following a suitable validation procedure. In any event,

when the filter spectroscopy absorption values are combined with total absorption values measured with the reflecting tube, the absolute values may be largely corrected

to remove these uncertainties, if two reflecting tube meters

are not available. Conversely, these comparisons serve to

validate and control the quality of the a(λ) profiles measured in situ.

5.2.5 Backscattering Profiles

While the spectral absorption can nowbe measured

with sufficient accuracy for the purpose of SeaWiFS, backscattering is not routinely measured, yet it has a large

influence on the reflectance. The nowgenerally accepted

dependence of the remote sensing reflectance on the ratio

of the backscattering coefficient and the absorption coefficient has never led to a systematic investigation of the

dependence of bb(λ) on the various particulate parameters.

Gordon (1989a) showed that the irradiance reflectance depends on the shape of the scattering function in the backward direction. Zaneveld (1994) derived the functional dependence of the remote sensing reflectance on backscattering.

There is little historic data on the variation of the shape

of the volume scattering function, β(θ, λ), in the backward

direction. Petzold (1972) described β(λ) measured with

the GASM. This reference is the one most widely used to

describe shapes of β(θ, λ). Since that time, only Balch et

al. (1994) have published newdata regarding the shape of

β(θ, λ). Several single wavelength integrated backscattering bb(θ, λ) meters have been constructed (Maffione et al.

1991 and Smart 1992), all of which measure a weighted integral of the scattering function. Maffione’s meter has the

centroid angle near 150◦, whereas Smart’s meter has the

centroid angle near 170◦. The 150◦ centroid angle is more

appropriate for SeaWiFS. This observation also points out

a problem in the reporting of results from scattering meters, in that results are commonly reported as simple bb(λ).

In the future, more detail should be provided to allowintercomparisons between results reported by different investigators.

All scattering sensors measure a parameter that is a

weighted integral of the volume scattering function. The

weighting function W(θ) depends on the geometry of the

device. Knowledge of the weighting function is critical in

comparing scattering meters. For each scattering meter,

documentation should be available describing this weighting function and howit was derived. The weighting function can generally best be derived by moving a Spectralon

target through the scattering volume space.

The scattering meter measurement may be defined as

βb(θ, ∆θ, λ, ∆λ)=2π

π

0

β(θ, λ)W(θ) sin θ dθ, (21)

where θ is the centroid angle computed as

θ =



π

0

θW(θ) sin θ dθ



π

0

W(θ) sin θ dθ

, (22)

and ∆θ is the FWHM bandwidth of the weighting function

multiplied by sin(θ), λ is the central wavelength of the color

filter, and ∆λ is the FWHM bandpass of the filter. While

the parameters do not give a complete description of the

weighting function, they allow an informed comparison of

scattering meter results. Investigators making backscattering measurements are encouraged to report backscattering

meter results in the format βb(θ, ∆θ, λ, ∆λ).

Backscattering measurement should be made in close

proximity to absorption meters, if both are used, to avoid

space-time aliasing.

5.3 ATMOSPHERIC RADIOMETRY

This section is concerned with two types of atmospheric radiometric measurements that are distinct from

those described earlier in Section 5.1. The first of these

is the photometric measurement of the direct solar beam

to determine the optical thickness of the atmosphere (Section 5.3.1). The second is a measurement of the sky radiance distribution using a radiance distribution camera

(Section 5.3.2).

5.3.1 Sun Photometry

Measurements of the direct solar beam, using the sun

photometer, should be performed during the optical stations. If sky radiance distribution measurements are performed, it is important that these measurements are performed concurrently. While the preferred method of determining the optical thickness of the atmosphere is by measuring the solar transmission as a function of solar zenith

angle, the atmospheric conditions are rarely stable enough

at sea for this method to work. Thus, a stable, well calibrated photometer can be used with measurements at a

single zenith angle to obtain the solar transmission, and

thus, the aerosol optical depth.

Atmospheric measurements should be performed only

when clouds, including high cirrus, do not obstruct the

solar disc. Careful documentation of sky conditions is important, as are accurate recordings of the time of day and

the geographic location of the station. The latter data

are important in determining the true solar zenith angle

and, hence, the air mass in the solar path. It should also

be obvious that care should be taken to avoid ship perturbations (e.g., stack gas) from interfering with the measurements. Ancillary measurements, such as barometric

pressure, are important in separating Rayleigh scattering

from the aerosol scattering.

38
Mueller and Austin

5.3.2 Sky Radiance Distribution

Complete sky radiance distributions should be measured with a radiance distribution camera during the SeaWiFS radiometric initialization and validation optical stations. For this purpose, it is critically important that these

measurements be obtained whenever totally clear sky conditions persist. Coincident with these measurements, sun

photometer measurements should be obtained. When locating the camera system for these measurements, it is

important that the FOV be as unobstructed as possible.

While it would be optimum to have a completely unobstructed FOV, this is often not practical. During measurements, therefore, at least one hemisphere (defined by the

sun-zenith plane) should be unobstructed; through symmetry, this should yield a complete radiance distribution.

Ship perturbations, e.g., stack gas, must be avoided

completely. It is important to document where the instrument is located and what possible perturbations might exist, even though these effects may be obvious in the data.

It would also be highly desirable to add sky radiance

measurements to every SeaWiFS algorithm development

and validation cruise. Gordon (1989b) rigorously demonstrated the importance of determining μd, the mean cosine for downwelling radiance (Morel and Smith 1982), for

the bio-optical interpretation of Kd(z, λ). Gordon (1989b)

also showed, for cloud-free skies, how to obtain a reasonable estimate of μd(0+) from spectral irradiance deck cell

measurements with, and without, the sun blocked from the

viewof the irradiance collector. This procedure should be

done routinely whenever it is practical to do so. Unfortunately, the collective scientific experience is that cloud-free

skies rarely occur at ocean optical stations.

If a calibrated spectral radiance distribution camera

is available, then Lsky(λ, θ, φ) should be measured several

times during each spectral radiometer cast and used to

compute μd(0+, λ). Radiance distribution cameras are expensive to build, however, and one is not likely to be available aboard every SeaWiFS validation vessel. A recommended alternative approach is to acquire:

1) all-sky photographs taken either with a conventional camera or, preferably, a digitally recorded

camera system (some research must be done to

develop procedures for attenuating, or blocking,

the sun’s image and for using filters);

2) measurements, with a narrow FOV spectral radiometer of Lsky(λ, θi, φi) at several discrete angles θi and φi; and

3) Es(λ) measurements of Esun(λ) + Esky(λ) with

the sun’s image blocked by shadowing the deck

cell irradiance collector (Gordon 1989b).

During the prelaunch experiments, μd(0+, λ) values estimated from measurements of these types should be compared with μd(0+, λ) values determined from direct measurements of sky radiance using a spectral radiance distribution camera system.

5.4 WATER SAMPLES

Duplicate samples should be taken at each of 12 depths,

including at least three depths within the first attenuation

length, 1/K(490); however, in coastal areas with short

attenuation lengths, this may not be possible. Samples

should also be taken in the in vivo fluorescence and beam

attenuation maxima. The remaining samples should be

spaced throughout the water column using beam attenuation, in situ fluorescence, and CTD profiles as a guide.

5.4.1 Pigment Analysis

Water samples should be taken at the site of, and simultaneously with, the surface in-water upwelled radiance and

reflectance measurements, and at depth increments sufficient to resolve variability within the top optical depth.

The K(z, λ) profiles over this layer will be used to compute optically weighted, near-surface pigment concentration for bio-optical algorithm development (Gordon and

Clark 1980).

When possible, samples should be acquired at several

depths distributed throughout the upper 200 m of the water column [or in turbid water, up to seven optical depths,

ln(E(0)/E(z)



= 7], to provide a basis for relating chlorophyll a fluorescence signals to pigment mass concentration.

For lowuncertainty determinations of chlorophylls a,

b, and c, as well as carotenoid pigments, HPLC techniques are recommended. It should be noted, however,

that the reverse-phase C18 HPLC method recommended

by the Scientific Committee on Oceanographic Research

(SCOR) (Wright et al. 1991) is not capable of separating monovinyl chlorophyll a from divinyl chlorophyll a nor

monovinyl chlorophyll b from divinyl chlorophyll b. This

method, therefore, only provides estimates of total chlorophyll a and total chlorophyll b concentrations, respectively.

Divinyl chlorophyll a, the major photosynthetic pigment found in prochlorophytes, accounts for 10–60% of

the total chlorophyll a in subtropical and tropical oceanic

waters (Goericke and Repeta 1993, Letelier et al. 1993,

Bidigare et al. 1994, and Bidigare and Ondrusek 1994).

Divinyl chlorophyll a is spectrally different from normal

(monovinyl) chlorophyll a, and its presence results in a significant overestimation of total chlorophyll a concentration

as determined by the conventional HPLC methods (Goericke and Repeta 1993, Letelier et al. 1993, and Latasa et

al. 1994). To avoid these errors, it is recommended that

monovinyl and divinyl chlorophyll a be spectrally resolved

or chromatographically separated in order to obtain an unbiased determination of total chlorophyll a (that is, total

chlorophyll a equals divinyl chlorophyll a plus monovinyl

chlorophyll a) for the purpose of ground-truthing SeaWiFS

imagery. These co-eluting chlorophyll species can be resolved spectrally following C18 HPLC chromatography

(Wright et al. 1991) and quantified using dichromatic equations at 436 and 450 nm (Goericke and Repeta 1993 and

39
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Latasa et al. 1994). Alternatively, these two chlorophyll

species can be separated chromatographically and individually quantified using the C8 HPLC technique described

by Goericke and Repeta (1993). (C18 and C8 designate

column packing materials used in HPLC.)

These protocols, to be employed in the SeaWiFS validation program for HPLC pigment analyses, are prescribed in

the JGOFS Core Measurement Protocols (JGOFS 1991).

These protocols include:

a) use of Whatman GF/F glass fiber filters, approximately 0.7 μm pore size,

b) extraction in 90% acetone, and

c) calibration with authenticated standards.

It is recommended that seawater samples not be prefiltered to remove large zooplankton and particles as this

might result in the exclusion of pigment-containing colonial and chain-forming phytoplankton, e.g., diatoms and

Trichodesmium sp. Large zooplankton can be removed

following filtration using forceps.

When it is appropriate to measure phycoerythrin concentration, it is important to discriminate between Trichodesmium and Synechococcus phycoerythrins, as they

have different spectral absorption characteristics. The concentration of Trichodesmium phycoerythrin may be determined using the glycerol uncoupling method described by

Wyman (1992). Separating Trichodesmium from Synechococcus may require pre-filtering.

In addition to HPLC analyses, it is recommended that

the standard fluorometric methodology used for measuring chlorophylls and phaeopigments (Yentsch and Menzel

1963, Holm-Hansen et al. 1965, and Strickland and Parson 1972) also be applied to the same extracted pigment

samples used for HPLC analysis (Section 6.6.1). This additional analysis will enable a direct link to the historical

bio-optical algorithms and database development during

the CZCS validation experiments.

5.4.2 Spectrophotometric Absorption

This section describes laboratory protocols for separating the total spectral absorption coefficient, a(z, λ), into

its components due to absorption by pure water, in vivo

phytoplankton pigments [aφ(λ)], dissolved material [ag(λ),

Gelbstoff], and other particulate material [at(λ), tripton]

by spectrophotometric measurements of filtered discrete

water samples. Associated data analysis protocols are presented in Section 6.8.2.

All equipment utilized in water sample processing for

Gelbstoff samples should minimize contamination by organic or colored material and should protect samples from

photodegradation. Glass provides the best material for filtration units and sample storage containers. Glass filtration units should have stainless steel filter supports and not

ground glass frits, since these tend to clog over time and

change particle retention efficiencies of the units. Ambercolored borosilicate glass bottles are preferred for samples

and filtrate collection because they protect the dissolved

samples from ambient light. Caps lined with PTFE are

preferred to minimize contamination. Prior to each experiment, all filtration and storage bottles should be thoroughly cleaned with detergent and rinsed several times

with distilled water (DIW).

For measurement of absorption by dissolved organic

matter (DOM), samples should be filtered through 0.2 μm

membrane filters, e.g., NucleporeTM polyester 0.2 μm filters. Membrane filters minimize the contamination of the

filtrate by filter fibers. It is recommended that separate

water samples be filtered for DOM, particulate matter, and

pigment analyses. Combining several analyses in one filtration can introduce errors, because each analysis has a

specific filtering protocol.

The procedure for preparing a sample for DOM measurements is as follows:

1. Before filtering a sample for the measurement,

filter at least 100 ml of DIW through the filter to

remove wetting agents or other organic material.

2. Swirl and rinse the filter trap.

3. Filter 30–50 ml of the available volume, and capture in a trap.

4. Rinse the filter and flask a second time with a

second aliquot of sample, or, if sample is scarce,

refilter the first-pass filtrate.

5. Swirl and rinse the trap after the second filtration, and discard the filtrate.

6. Filter the remaining volume, capture in the trap,

and refilter the sample.

7. Rinse a clean, amber glass, storage bottle three

times with filtrate, then fill, cap and store upright.

If it is necessary to delay the measurement of the Gelbstoff sample for more than a fewhours, freeze each filtrate

sample in an amber bottle, and store upright and in the

dark.

An alternate simple and rapid filtration method for

measuring absorption spectra of dissolved organic matter

in water samples has been proposed by Yentsch and Phinney (pers. comm.). A high-volume 0.22 μm SterivexTM filter cartridge† is used to perform a one-step filtration with

the sample introduced directly into the cuvette from the

filter cartridge. The sample is pushed through the cartridge using a 50 cc sterile plastic syringe attached by a

Luer lock connection. Sample handling is minimized and

preparation time, including rinses, is only a fewminutes

per sample. The cartridges cost approximately $2.00 each,

which makes them expensive to use for only one sample.

Yentsch and Phinney found, however, that rinsing between

samples with distilled water permits the use of one cartridge per station with no measurable contamination effects. They verified non-contamination by measuring the

† A membrane filter made by Millipore Corporation.

40
Mueller and Austin

absorption spectrum of a final distilled water rinse after

all samples for a station were filtered, and then comparing the absorption spectrum of this sample to the baseline

spectrum measured prior to the sample analysis.

A potential disadvantage of the Yentsch and Phinney

method results from the need to detach and reattach the

cartridge to the syringe between sample and rinses. Back

pressure applied while removing the syringe plunger with

the cartridge attached can rupture the membrane. This

problem can be avoided by using a peristaltic pump to introduce the sample and rinse water directly from separate

bottles.

The samples should be allowed to equilabrate to room

temperature before spectrophotometer measurements are

made, and they should be protected from ambient light.

If the Yentsch and Phinney suggestion to inject the sample directly into a cuvette is followed, this implies use of

several cuvettes per station and some type of dark storage

arrangement. Otherwise, the samples should be injected

into amber bottles which have been prerinsed in the sample filtrate. It may be possible to wait approximately 20

minutes before filtering, to allowthe samples to warm to

room temperature, provided an investigator demonstrates

that this delay does not allowmodification of the sample

filtrate.

To summarize, the following method can be employed

on samples collected and stored using any currently established technique:

1. Prerinse a Sterivex cartridge using 100 ml of

Nanopure or similarly polished DIW.

2. For spectrophotometric baseline determination,

rinse the reference and sample cuvettes 2 or 3

times with filtered DIW and fill the cuvette,

measure the absorption spectrum, and store it

as the baseline.

3. For each successive sample, evacuate the cartridge, and rinse it with 50 ml DIW. Then, evacuate the cartridge and rinse it with a 50 ml sample. Refill the syringe with a sample, rinse the

sample cuvette, and inject the sample from the

syringe through the filter cartridge into the cuvette. Measure the absorption spectrum in a

spectrophotometer (see below).

4. After all samples have been analyzed, rinse the

cartridge with 50 ml DIW, refill the syringe with

DIW, rinse the sample cuvette and fill it with

filtered DIW, and measure the absorption spectrum. Compare this absorption spectrum to the

baseline.

To measure the absorption of the dissolved fraction,

minimize the distance between the detector and the cuvettes in the spectrophotometer, and use 10 cm quartz cuvettes to maximize the absorption signal. Warm the filtrate samples to room temperature while protecting them

from direct light. Filter reverse osmosis or Milli Q purified

water (ROW) through a rinsed GF/F filter for reference

as a blank, discarding the first 100 ml. Begin the analyses

when the sample and reference material are both at room

temperature. Perform a newbaseline measurement range

using a ROW blank each time the instrument has been

powered up or the configuration changes.

Using a dual beam spectrophotometer, scan the instrument’s baseline optical density spectrum ODb(λ) from approximately 300–700 nm, beginning at the lowest ultraviolet (UV) wavelength the instrument will measure without

cuvettes in the light path. Place the reference blank ROW,

filtered as described above, in both sample and reference

cuvettes and scan the reference optical density spectrum

ODr(λ). Rinse the sample cuvette with approximately

5 ml of the sample three times. Rinse and fill the sample

cuvette with the DOM sample filtrate and scan ODg(λ).

Replace reference water blanks every few samples to prevent bubble formation in the reference cuvette. Between

samples, block the reference light and open the sample

compartment door to minimize temperature changes in the

ROW reference.

The GF/F filter (which is binder-free and combustible,

with a nominal pore size of 0.7 μm) is the best choice for

particle absorption sampling. This filter has a large scattering coefficient at visible wavelengths, which increases

the optical path length of the photons and improves the accuracy of particulate absorption measurements. This type

of filter is also recommended by (JGOFS 1991) for carbon,

hydrogen, and nitrogen (CHN); pigment; and primary productivity analyses. The optical transparency of the GF/F

filter decreases significantly below380 nm.

Some authors have reported that particulate material

less than 0.7 μm in size will not be retained by the GF/F

filter, and that this fraction may contain up to 10–15%

of the phytoplankton biomass as measured by chlorophyll

concentration. Chavez et al. (1995), however, found no

statistical difference between GF/F and 0.2 μm filters for

chlorophyll and productivity measurements.

The goals for filtration of particulate samples are to

minimize contamination and particle degradation, maximize retention, and concentrate an adequate amount of

particles on the filters to permit accurate spectrophotometric measurements. Vacuum pressures below5 inches of

mercury, i.e., 117 mm Hg, are recommended to reduce the

chances of particle breakage. It is currently recommended

to set the filtration volume for each sample to approximate an optical density value of 0.25 at 400 nm (Roesler

and Perry 1992). Small area (13 mm2) filtration units may

be used to reduce water sample volumes.

Optical density spectra of the filters should be measured as soon as possible, because pigment decomposition

may occur (Stramski 1990). If necessary to store filters,

place the unfolded filters into polypropylene tissue capsule

containers and store in liquid nitrogen. Freezing in conventional freezers causes ice crystals to form on the particles

and leads to cell breakage and pigment degradation.

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

A newinstrument baseline scan should be measured

each time the spectrophotometer is powered up or anytime its configuration has been changed. To measure the

particulate absorption spectrum, first prepare a blank filter by soaking it in 50 ml DIW for 20 minutes (remembering to select it from the same box as the sample filters).

An alternative approach is to use prefiltered seawater (prefiltered using a 0.2 μm Millipore GS filter) to wet the GF/F

filter blank (Cleveland pers. comm.), for the reason that

the sample filters are also wetted with seawater. If using

a single beam spectrophotometer, scan the instrumental

baseline ODb(λ) without the filter. Then insert the wetted filter blank to obtain the reference spectrum ODr(λ).

With a dual beam spectrophotometer, two wetted reference filter blanks must be used to measure the reference

spectrum, and one is left in the reference beam during sample measurements. Some investigators recommend aligning

the filter fibers in a fixed orientation each time a filter is

inserted.

If the samples were frozen, remove the sample filter

from the liquid nitrogen. Place a fewdrops of DIW or

filtered seawater on a glass (or Plexiglas) slide and then

place the sample filter, bottom side down, on the water.

This moistens the filter and hastens thawing. Place the

filter in the sample compartment with the filtered material facing the source. Scan the ODp(λ). Place the sample

filter back in the filter cup. Gently pour 30–50 ml of hot

spectrophotometric- or HPLC-grade methanol over the filter, taking care not to lift any particulates off the filter

(Kishino et al. 1985). Let the filter sit 10–15 minutes under the methanol, filter through, and repeat the process.

Rinse with 10–20 ml of 0.2 μm DIW. Seawater is not used

here, because methanol may cause precipitates to form

on the filter. Position the filter in the spectrophotometer and scan ODt(λ). This spectrum is associated with

raw, non-pigmented particulates, often referred to as detritus or tripton. The absorption spectrum should decrease

exponentially with wavelength. If there is a residual chlorophyll a absorption peak at 676 nm, repeat the extraction

process until the peak disappears.

Recommended methods for analysis to convert the measured optical density spectra to absorption spectra are discussed in Section 6.8.2.

5.4.3 Total Suspended Matter

All suspended particulate material (SPM) dry weight

(mg l−1) will be determined gravimetrically as outlined in

Strickland and Parsons (1972) and as specified in JGOFS

(1991). In general, samples are filtered through 0.4 μm

preweighed polycarbonate filters. The filters are washed

with three 2.5–5.0 ml aliquots of DIW and immediately

dried, either in an oven at 75◦ C, or in a dessicator. The

filters are then reweighed in a laboratory back on shore

using an electrobalance with at least seven digits of precision.

5.5 ANCILLARY OBSERVATIONS

Ancillary observations are often of key importance in

flagging and interpreting apparently aberrant data. The

minimal set of ancillary supporting observations must include:

1) date and time (both GMT and local);

2) geographic location, using the Global Positioning System (GPS) if possible, before and after

each cast and at times of satellite and aircraft

overpasses;

3) solar azimuth and zenith angles, as calculated

from position, date, and time;

4) position of the optical cast in relation to the ship

orientation and position of the ship relative to

the sun (a sketch in the field notes is recommended);

5) sea state (photographed if possible) with approximate swell height, direction, and notes on

presence and density of whitecaps;

6) quantitative measurements of surface wire angles during deployments of the instrument package;

7) time of cast (begin and end), as well as time and

depth of water samples collected;

8) percent cloud cover and cloud type, and solar

occlusion conditions; and

9) wind direction and velocity.

Desirable additional ancillary measurements include:

a) an all-sky photograph plus a photographed time

history of sea surface is advised for radiometric

stations; and

b) Secchi depth.

5.6 PROTOTYPE OPTICAL BUOY

A prototype optical measurement system designed for

long-term buoy deployment with a satellite data telemetry

capability is presently under development and is focused

on satisfying the SeaWiFS optical data requirements. The

concept is constrained by the requirement that the instrument be capable of maintaining measurement integrity

while being unattended for long periods of time. This

constraint has lead to a design that minimizes the number of moving parts to one, and has resulted in the spectrographic application of concave holographic diffraction

gratings. These holographic gratings provide an approximate flat focal field to the degree that planar silicon photodiode arrays may be used as detectors. Inherent within

this technology are the features of simplicity, compactness,

durability, and stability.

The optical system utilizes two spectrographs, in tandem with a dichroic mirror specifically designed to avoid

measurements in the water absorption region, in order to

42
Mueller and Austin

measure radiometric properties with high spectral resolution and stray light rejection. The dichroic mirror is designed to transmit the red (630–900 nm) and reflect the

blue portions (380–600 nm) of the spectrum, making the

transition from reflectance to transmittance between 600

and 640 nm. The potential for stray light is greatly reduced by splitting the visible spectrum at the beginning

of the water absorption region, since most of the short

wavelength energy is diverted from the entrance slit of the

long wavelength spectrograph. The splitting also allows

the spectrographs, i.e., gratings and sampling periods, to

be optimized for the two distinctive spectral domains. A

further reduction of stray light for the long wave spectrograph will be achieved by utilizing a minus blue filter.

The optical system will be deployed on a slack-line

moored wave rider buoy that has a 10–20 m optical bench

attached. Apparent optical properties will be measured

by a series of remote collectors that are coupled to the

instrument with fiber optics. Data will be compressed,

stored, and forwarded through a NOAA Geostationary Operational Environmental Satellite (GOES) and an ARGOS

telemetry link.

This type of optical mooring represents a newand challenging technology. Detailed protocols for deploying and

maintaining this type of mooring, and for evaluating its

data quality, must be developed in light of the experience

to be gained over the next 2–3 years.

The current practice is to apply marine antifouling compounds (such as OMP-8) to prevent the growth of marine

organisms on the windows of moored radiometer systems.

This approach is less satisfactory for IOP instruments, because for collimated light, transmission characteristics of

the optical windows can be adversely affected by the layer

of the anti-fouling material.

5.7 DRIFTINGOPTICAL BUOYS

Drifting optical instruments are a recent development

and there is almost no history of their quantitative application to problems in ocean color algorithm development

and remote sensing radiometric validation. It is probable

that significant experience in the uses and limitations of

such instruments will be gained in SeaWiFS related experiments during the prelaunch period. The critical questions

about these instruments, which should be answered during

prelaunch work, include:

1. Howaccurately can LW (λ) be estimated from

Lu(z, λ) at a single near surface depth, using

only an estimate of KL(λ) obtained from ocean

color ratios? Is 5% uncertainty feasible?

2. Howaccurately can a normalized water-leaving

radiance ratio LWN (λ1)/LWN (λ2) be estimated

with these instruments using only a single channel Ed(λ) measurement for normalization, which

is contemplated for instruments currently being

developed (Section 2.6)? Are the normalized

water-leaving radiance ratios from clear sky and

overcast conditions comparable enough that the

drifter data can provide a basis for interpolating

SeaWiFS data through cloudy periods?

When answers to these fundamental questions are in hand,

it will be possible to draft and implement more detailed

protocols for the use of optical drifters in SeaWiFS radiometric validation and algorithm development.

Many potential applications of optical drifters in oceanographic research using SeaWiFS data are more obvious,

but from a radiometric standpoint are less stringently demanding. Protocols for those applications are, however,

beyond the scope of this report.

5.8 SAMPLINGAND VALIDATION

The following discussion of bio-optical sampling protocols is organized into three subtopics: sampling for the

initial and ongoing validation of the SeaWiFS radiometric system performance (Section 5.8.1), algorithm development and validation in Case-1 waters (Section 5.8.2), and

algorithm development and validation in Case-2 waters

(Section 5.8.3). The distinction between the first subtopic

and the second two is clear-cut, but what precisely is meant

by Case-1 and Case-2 water masses?

In its literature and reports, the ocean color research

community has formally adopted definitions originally due

to Morel and Prieur (1977), who stated:

“Case-1 is that of a concentration of phytoplankton

[which is] high compared to that of other particles.

The pigments (chlorophyll, [and] carotenoids) play

a major role in actual absorption. In contrast, the

inorganic particles are dominant in Case-2, and pigment absorption is of comparatively minor importance. In both cases, [the] dissolved yellowsubstance is present in variable amounts and also contributes to total absorption.”

In practice, however, only those water masses where

the CZCS-type blue-green ratio algorithms for phytoplankton pigment concentration (chlorophyll a + phaeopigment

a) work reasonably well have been treated as Case-1. All

other water masses have often been loosely lumped into the

Case-2 definition, albeit with considerable confusion over

howto categorize coccolithophorid blooms, and similar

phenomona normally classified as Case-1 waters, in which

strong concentrations of Gelbstoff vary independently from

chlorophyll a concentration.

In the present discussion of sampling protocols, Case-1

will be considered to refer to what might be called ordinary

open ocean Case-1 waters, wherein scattering and absorption are dominated by phytoplankton, pigments, and Gelbstoff concentrations, and where global blue-green color ratio algorithms for chlorophyll a concentration and K(490)

work well. Most areas in the deep ocean belong to this

case. Water masses which do not satisfy this criteria will

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

be grouped under the heading Case-2. Within Case-2, by

this definition, water masses with a wide diversity of biooptical characteristics will be found. Prominent subcategories include:

1) coccolithophorid blooms, wherein the detached

coccoliths dominate light scattering and remote

sensing reflectance independently from pigment

concentration;

2) coastal areas, wherein DOM of terrestrial origin contributes a strong absorption component

which does not co-vary with pigment concentration;

3) phytoplankton blooms with unusual accessory

pigment concentrations, e.g., red tides, which require the use of special regional or local ocean

color algorithms; and

4) classical extreme Morel and Prieur (1977) Case2 waters where optical properties are dominated

by inorganic particles, with many possible variations in chemical and geometric characteristics.

It is important to recognize that some aspects of the

water mass distinctions given above are dependent on the

spectral regions in which measurements are to be made.

Strong absorption at UV, red, and near-IR wavelengths

requires the use of radiometric techniques similar to those

required for Case-2 waters.

In addition to determining the bio-optical category and

characteristics of a particular water mass, the validation

sampling strategy must be concerned with spatial and temporal variability. Spatial and temporal variability in biooptical properties will profoundly affect the validity of comparisons between SeaWiFS and in-water optical measurements. A single SeaWiFS instantaneous FOV measurement will integrate LW (λ) over approximately a square

kilometer, or a larger area at viewing angles away from

nadir. Furthermore, the location uncertainty for a single

pixel may be several kilometers, except in near-shore areas

where image navigation can be improved by using landnavigated anchor points.

Bio-optical profiles measured at a single station are representative of a spatial scale that is only a small fraction of

a kilometer. Data from a grid of several station locations

may be required to estimate the spatial averages of optical properties represented by a SeaWiFS pixel, or a block

of pixels. Because the ship measurements over the grid

are not instantaneous, temporal variability in bio-optical

properties can add additional uncertainty to the comparisons. Aircraft radiometric observations can, conceptually,

be used both to locate comparison sites away from areas of

strong spatial variability and to document changes in the

pattern of spatial variability over the period required for a

ship to occupy all stations in a comparison grid.

Vertical stratification of water temperature, salinity,

and density often affect the vertical structure of variability

in bio-optical properties. This variability, in turn, affects

the remote sensing reflectance. Vertical stratification of

the water column becomes especially important in many

Case-2 waters, where the top attenuation depth may be as

shallowas 1–2 m and the entire euphotic zone may be confined to less than 10 m depth. It is important, therefore,

to minimize ship-induced disruption of vertical stratification in the water column. Whenever possible, the ship

should be maneuvered as little as possible while on station with its propellers and bow thruster, and the practice of backing down hard to stop quickly when on station

should be strongly discouraged. If wind and sea conditions

permit, the preferred method of approaching a station is

to take enough speed off the ship to coast to a stop over

approximately the last 0.5 km of approach to the station.

The approach should be planned to allowthe ship to be

turned, preferably using only the rudder, to place the sun

abaft the beam or off the stern, depending on where the

radiometers will be deployed. It must be realized, however, that depending on wind and sea conditions, and a

particular ship’s hull and superstructure configuration, it

may not be possible to maintain an acceptable orientation,

with respect to the sun, while the ship is adrift. In these

situations, some use of the engines to maintain an acceptable ship’s heading may be unavoidable.

The chief scientist should also consult with the ship’s

captain and chief engineer to avoid, or at least minimize,

overboard discharges while the ship is on station. Material

from a ship’s bilge or sewage treatment system can significantly change near-surface chemical and optical properties

if discharged near the immediate site of a bio-optical profile

or water sample.

In some coastal areas, where a relatively transparent

water mass overlies a highly reflective bottom, LW (λ) includes light reflected from the sea floor. These cases require

special treatment of bottom reflectance effects whether the

local water mass regime is Case-1, Case-2, or a combination of both. Methods of measurement, experiment design,

and sampling strategies to study bottom reflectance effects

are beyond the scope of this revision to the ocean optics

protocols. There is a significant current research effort focused in this area (Carder et al. 1992, Hamilton et al. 1992,

and Lee et al. 1994), and it is expected that experience will

evolve the basis for newprotocols in this topic area to be

included in the next revision of this document.

The bottom reflection of areas with a water depth exceeding 30 m normally does not contribute to the water

leaving radiance, LW (λ). Areas with a depth shallower

than 30 m will be flagged in the SeaWiFS level-2 data

product. Pixels covering very turbid waters may, however,

even be usable even in shallower areas. As a general rule,

the water depth should be deeper than 2.5 attenuation

lengths, 1/K(490), at all SeaWiFS algorithm development

and validation stations. The prime exception to this rule

is in developing local SeaWiFS algorithms where bottom

reflectance contributions must be taken into account (Lee

et al. 1994).

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Mueller and Austin

Variables to be measured at each validation station are

summarized in Table 1, and methods for making each measurement are discussed in the previous subsections of Section 5. Methods of data analysis and reporting are discussed in Section 6.

5.8.1 Initialization and Validation

Data intended for direct comparisons between observed

Lu(λ) and SeaWiFS LW (λ) estimates should usually be acquired in areas where bio-optical variability is known to be

very small. This will ordinarily dictate that such data be

acquired from optically clear and persistently oligotrophic

Case-1 water masses. Potentially suitable sites include the

northeastern Pacific central gyre off Baja, California (to

the southwest), and the central Sargasso Sea. When planning validation cruise locations and timing, seasonal and

regional cloud cover statistics should also be considered in

order to maximize the likelihood of simultaneous SeaWiFS

and shipboard observations. A semi-oligotrophic site in

the northeast Pacific, near Hawaii, is the prime candidate

for placing a moored radiometer for continuous time-series

radiometric comparisons with SeaWiFS LW (λ) estimates.

A series of radiometric comparison stations should be

made over a wide range of latitude in both the Northern

and Southern Hemispheres, to look for evidence of cyclic

thermal sensitivity affecting SeaWiFS. The spacecraft and

instrument will be heated by sunlight throughout the descending (daylight) data acquisition segment of each orbit

and will be cooled by thermal radiation while in the Earth’s

shadowthroughout the remainder of the orbit. This cycling is likely to induce transient thermal gradients in the

instrument, as well as a time varying cycle in the temperatures of its detectors and other components; these thermal

variations could affect the spectral bandpass or responsivity of one or more SeaWiFS channels. Unfortunately, a

set of stations covering the full range of latitudes cannot

all be sited in regions where mesoscale variability in ocean

optical properties can be neglected. As when acquiring

data for developing and validating Case-1 bio-optical algorithms (Section 5.8.2), a significant effort must be exerted

to quantify spatial variability in normalized water-leaving

radiance. When possible, airborne radiometer data, in

combination with careful characterization of atmospheric

aerosol and cloud conditions, should be employed to augment shipboard radiometry at the stations selected for this

aspect of the validation. If aircraft support is not available,

semi-synoptic shipboard transects covering a 20×20 km2

grid should be used to characterize spatial bio-optical variability near a sampling station.

The minimum set of variables to be measured for radiometric validation are those from the Product Verification

column of Table 1. Measurements used to calculate normalized water-leaving radiance for direct comparison to

SeaWiFS radiances must be made under cloud-free conditions and within five minutes of the satellite overpass.

5.8.2 Case-1 Water Protocols

In open-ocean oligotrophic water, it is usually practical to assume that a station is in a Case-1 water mass,

although some caution must be taken to detect coccolithophorid blooms and suspended coccoliths. In more turbid coastal transition regimes, however, the classification

of the local water mass as Case-1 or Case-2 may be less obvious. In this environment, moreover, Case-1 and Case-2

water masses may both be present in the domain sampled

by a ship. One example of this situation would be Case1 water within an eddy-like intrusion from offshore into

coastal areas normally occupied by Case-2 water masses.

Another would be Case-2 waters in a major river plume

intruding into an ambient Case-1 water mass regime.

In general, a water mass may be categorized as Case-1

if:

1) Gelbstoff absorption at 380 nm, ag(380), is less

than 0.1 m−1 (Sections 5.2.4, 5.4.2, 6.8.1, and

6.8.2);

2) total SPM concentration is less than 0.5 mg l−1

(dry weight) (Section 5.4.4);

3) measured LW (λ) values, used in the SeaWiFS

Case-1 algorithm, predict measured fluorometric

chlorophyll a concentration within 35%; and

4) measured LW (λ), used in the SeaWiFS algorithm, predicts measured remote sensing K(490)

within 20%.

The determination of criteria 1 and 2 above (Doerffer

pers. comm.) will ordinarily require retrospective analysis. On the other hand, radiometric profiles and pigment

samples can ordinarily be analyzed on board to allowdetermination of criteria 3 and 4 shortly after the samples

are acquired.

SeaWiFS Case-1 algorithm development and validation

requires measurements from Case-1 water masses spanning a wide range of optical properties and phytoplankton pigment concentrations. In optically transparent lowchlorophyll oligotrophic water masses, spatial variability is

usually small and a station location and sampling strategy

like that discussed in Section 5.8.1 is appropriate.

In high-chlorophyll mesotrophic Case-1 water masses

with increased turbidity, mesoscale and smaller scale variability is often significant. In very productive Case-1 water

masses, station placement and many other aspects of sampling schemes are similar to those appropriate for Case-2

water masses (Section 5.8.3). At algorithm development

stations, where measurements need neither be coincident

with, nor matched to, SeaWiFS observations, it will be necessary to characterize spatial and temporal variability only

over the relatively short scales distinguishing the separate

in-water radiometric, optical, and pigment measurements.

Airborne ocean color, or lidar characterizations, of spatial

variability in the vicinity of these stations will not usually

45
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

be essential, although such additional information may be

very helpful.

At stations where data are acquired for algorithm validation, and where a match to concurrent SeaWiFS measurements is required, it will be necessary to determine

the patterns of spatial variability over a domain extending

approximately 20×20 km2 centered at the station, and to

place the ship in a 2×2 km2 domain over which K(490)

and chlorophyll concentrations vary less than 35% about

the mean. Within a fewhours before and after a SeaWiFS overpass, in-water measurements should be made at

several random locations to characterize variability within

the 2×2 km2 validation comparison site. In some cases,

it may be possible to determine spatial variability adequately from ship station data and along-track measurements alone. In regions of strong mesoscale variability,

however, concurrent aircraft ocean color or lidar measurements should be used both as a guide for selecting the

ship’s location, and as a basis for spatially extrapolating the in-water measurements to match the much coarser

resolution of the SeaWiFS measurements (Section 5.1.7).

These topics are developed in more detail, with respect to

Case-2 waters, in Section 5.8.3.

5.8.3 Case-2 Water Protocols

Although coastal and continental shelf areas comprise

only 10% of the total ocean area, they provide roughly

half of the oceanic newproduction and most of the sequesterable DOC (Walsh et al. 1981). These areas are

typically higher in phytoplankton pigment concentration,

and may include colored terrigenous constituents such as

DOM and suspended sediments. In these Case-2 waters,

the global color ratio algorithms break down because two

or more substances with different optical properties are

present which do not co-vary with chlorophyll a concentration (Section 5.8 above). These might be waters with

exceptional plankton blooms (such as red tides), areas discolored by dust transported by the wind from deserts into

the sea, or coastal areas influenced by river discharge of

mineral and organic suspended materials, and DOM, i.e.,

Gelbstoff, such as humic acids.

It is not always easy to decide to which case a water mass belongs. As a starting point, the water belongs

to Case-2 if any of the four Case-1 criteria, set forth in

Section 5.8.2, are not satisfied. For Case-2 waters defined

by any one of these criteria, it remains a further problem

to determine the specific bio-optical characteristics which

distinguish it from Case-1. Case-2 sampling must usually

include a more complete subset of the variables in Table 1,

in addition to ag(λ) (Sections 5.2.4 and 5.4.2), SPM concentration (Section 5.4.3), chlorophyll a concentration, and

radiometry. For example, it may be necessary to determine

complete pigment composition and other optically important characteristics of exceptional phytoplankton blooms

for such planktonic groups as coccolithophorids, diatoms,

cyanobacteria, or microflagellates.

To achieve valid comparisons between the ship and satellite data, sharp horizontal gradients and sub-pixel patchiness must be avoided, and image navigation must have land

anchor points near the study site. Suitable landmarks are

usually available in near-shore coastal waters. The other

conditions are difficult to meet in Case-2 water masses,

where mesoscale and sub-mesoscale variability is typically

very strong. Sub-pixel variations of no more than ± 35% of

the mean pixel chlorophyll will be tolerated, but variability must be measured and taken into account statistically

in the analysis (see below).

From the above generalities, it is clear that significant problems are encountered in near-shore coastal waters characterized by small scale patches and dynamic variability due to tidal currents. A particular problem occurs

in the shallowareas which are influenced by strong tidal

currents—areas that are normally well mixed during part

of the tidal cycle. In the slack water tidal phase, however, a vertical gradient of the suspended matter concentration may form, which may cause problems in relating

water-leaving radiance to the concentration of suspended

matter. During calm periods with strong insolation, even

water that is normally well mixed can become stratified.

In these cases, the formation of very dense phytoplankton

blooms, such as red tides, can be observed. Such blooms

will occur in coastal seas when nutrient concentrations are

elevated by the influx of river water. In these circumstances, it is especially critical to avoid disturbing the vertical

stratification of the water column with the ship’s propellers

(Section 5.8 above).

5.8.4 Case-2 Sampling Strategy

One approach to sampling in this environment has been

suggested by R. Doerffer (pers. comm.). In order to get a

good statistical base, water samples are first taken in a random order within the area under research. The concentrations derived from the SeaWiFS data are then compared

with the ground truth data by statistical parameters, such

as the mean, median, standard deviation, and the shapes

of histograms (frequency distribution). For this type of

statistical comparison, only sections of SeaWiFS images

which match the area covered by the ship should be analyzed. Water samples and satellite data should also be temporally concurrent within the same tidal phase in order to

avoid biases due to temporal variability. In these regimes,

analyses to validate algorithms cannot be based on SeaWiFS data directly, but must instead be based on waterleaving radiance spectra measured in situ (Sections 5.1.1–

5.1.6) or from a ship (Section 5.1.8). This approach has

the advantage that water samples and radiance spectra are

taken nearly simultaneously.

Using either flow-through pumping systems or systems

towed outside the ship’s wake, fluorometry can be used

to assess chlorophyll patchiness if frequent, i.e., every 10-

15 minutes, chlorophyll fluorescence-yield calibration measurements are performed. Towed absorption, scattering,

46
Mueller and Austin

reflectance, and beam transmission meters can also be used

to characterize spatial variability. Within a fewhours of

the overpass, the ship should occupy several stations at

random locations within a 2×2 km2 area central to the

area selected for comparison with SeaWiFS data. Sampling stations placed across a tidal front during a SeaWiFS

overpass may help to identify two different water masses

even when the front has moved. Comparisons between in

situ and SeaWiFS data in patchy coastal areas may be

enhanced by using horizontal radiance profiles measured

from an aircraft flying at lowaltitude (Section 5.1.7). Subsets of such airborne profiles allowdirect comparisons with

shipboard data. A corresponding profile may then be extracted from the SeaWiFS data for a direct comparison to

the aircraft track line profiles. In Case-2 situations, such

direct radiometric comparisons are valuable for validating

and tuning local algorithms, but are not appropriate for

SeaWiFS system validation per se.

To validate the SeaWiFS atmospheric correction, waterleaving radiances measured in situ from the ship should

be compared with those derived from the SeaWiFS data.

Sample matching problems aside, Case-2 waters are often characterized by strongly varying patchiness in optical

properties, pigment concentrations, and remote sensing reflectance at spatial scales smaller than a SeaWiFS pixel.

Because of the nonlinear relationship between bb(λ)/a(λ)

and remote sensing reflectance, the pigment concentration

derived from spatially averaged SeaWiFS LWN (λ) values

will systematically underestimate the true spatial average

concentration by as much as a factor of 2 when sub-pixel

variability is significant. It is, therefore, essential to describe sub-pixel scale variability in Case-2 waters both

statistically and in terms of organized structure. Such a

description may be accomplished through rapid sampling

at closely spaced ship stations in combination with airborne ocean color measurements—for this purpose, track

line data from lowaltitudes and high-resolution imagery

from high altitudes are both acceptable.

Absorption coefficients are large enough in all Case2 waters to require instrument self-shadow corrections to

Lu(0−, λ), even though the correction model (Gordon and

Ding 1992) has been experimentally verified only for the

case where a(λ)r is less than 0.1 (Sections 5.1.6 and 6.1.7).

In extreme Case-2 waters, large values of spectral absorption may confine the first optical attenuation depth to the

top 1–2 m, where it is difficult to measure remote sensing reflectance in situ. Such short absorption scale lengths

lead to instrument self-shading effects in Lu(λ) which are

correctable only for instruments with diameters no larger

than approximately 1 cm (Gordon and Ding 1992). Radiometers with such a small shadow cross section are conceptually feasible, and a fewprototype instruments exist which may be suitable, but they are not commercially

available, and self-shadowsensitivities have not yet been

experimentally verified for these extreme conditions. In

these extreme cases, direct in situ measurements of a(λ)

and c(λ) (Sections 5.2.4 and 6.8.1) and βb(θ, ∆θ, λ, ∆λ)

(Section 5.2.5), together with above-water measurements

of LW (λ) or RL(λ), may provide the only practical means

of validating semi-analytic Case-2 algorithms. This topic

is an important area for near-term research and development.

5.9 VICARIOUS CALIBRATIONS

An important obligation of any flight project is the

production of a high quality, calibrated, Earth located

(level-1) data set. Consequently, the production of a calibrated set of SeaWiFS radiances that have been verified

through direct, or vicarious, calibration techniques was

recommended by the original workshop participants.

One potentially useful technique follows the approach

currently in use to verify the responsivity of the AVHRR

Television and Infrared Observation Satellite (TIROS) satellite instruments. Twice a year, an aircraft instrument,

which has been recently calibrated directly to laboratorybased NIST traceable standards, should be used to obtain

simultaneous views of a particular ocean scene. The aircraft scene must be obtained from a high altitude aircraft,

such as the NASA Earth Resources-2 (ER-2), and flown at

an altitude above most of the terrestrial atmosphere. The

existing data sets of the AVHRR-NASA Aircraft/Satellite

Instrument Calibration (NASIC) Project demonstrate a

capability to limit the uncorrected trend in the AVHRR

data sets to under 2% over two years. This concept may

allowan independent verification of the atmospheric radiative transfer models used to compute ocean biological

quantities, when the aircraft data are used in conjunction with the surface truth campaign measurements of

those same ocean biological quantities. The SeaWiFS absolute uncertainty requirements, however, are more stringent than those associated with the AVHRR, and a correspondingly more accurate airborne radiometer system

(Sections 3.3 and 4.3) must be used (Section 2.3).

47
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Chapter 6

Analytical Methods

Introduction

This chapter describes methods for processing, analyzing, and reporting SeaWiFS validation data sets acquired

following the protocols of Chapter 5. Where a consensus from the community exists for a preferred method, it

has been adopted and protocols are given accordingly, e.g., for phytoplankton pigments (Section 6.5). In other

instances, different methods are in current use, and as yet, there is insufficient evidence to give protocols specifying a preferred approach, e.g., the different methods of K-analysis described in Section 6.1.4. Intercomparisons

are in progress to evaluate this particular topic.

6.1 IN-WATER RADIOMETRY

Spectral surface irradiance, Es(λ); upwelling irradiance,

Eu(z, λ); downwelling irradiance, Ed(z, λ); and upwelling

radiance, Lu(z, λ), measurements should all be recorded

and archived at four levels.

a) level-0: rawinstrument digital output;

b) level-1: instrument output in volts, or frequency

(if appropriate), and depth;

c) level-2: calibrated irradiance and radiance, ancillary measurements in appropriate geophysical

or biological units, and depth, with all variables

corrected for dark or zero offsets;

d) level-3: Smoothed profiles of K(z, λ) and associated Ed(z, λ) or Lu(z, λ) with irradiance or

radiance normalized by measured surface irradiance; and

e) level-4: level-3 data normalized to clear-sky, a

zenith sun at the mean Earth-sun distance, and

spectrally adjusted to match the actual reference

wavelengths and FWHM bandwidths.

The formats of these data sets will vary somewhat between individual instruments. It is anticipated that the

SPO will promulgate suitable standard format specifications, or guidelines, to facilitate database management and

interchanges of level-1, level-2, level-3, and level-4 data.

These data files should each contain a header record identifying as a minimum:

1) date and time, i.e., GMT, of the station;

2) geographic location (latitude and longitude in

decimal degrees to the nearest 0.001);

3) cloud cover and sky conditions;

4) identification of each variable, including units

and wavelengths, for radiometric channels;

5) source of dark (zero-offset) data;

6) calibration date and file identification;

7) instrument identification;

8) method for determining K (level-3);

9) normalization algorithm (level-4);

10) Secchi depth;

11) depths of associated water samples, if any; and

12) depth offsets (to nearest cm) between the pressure transducer and all sensor probes, including

Lu window, Ed and Eu collectors, and all ancillary probes on a package.

In addition to profile files, each data set should contain:

i) calibration files used to compute level-2 data;

ii) level-0 and level-1 dark files, and an average

dark voltage file used for computing the corresponding level-2 files (in some cases a dark value

may be extracted from the deep portion of a profile);

iii) files with data from comparisons with a portable

irradiance and radiance reference standard made

in the field and used to track the instrument’s

stability during a deployment; and

iv) anecdotal and environmental information about

each profile, either in the header, or in an accompanying American Standard Code for Information Interchange (ASCII) text file.

In general, the data should be retained at full resolution as recorded, but with noise-contaminated records

removed through level-2. If the data are binned prior

to K-determination, as is sometimes done in the derivative method (Section 6.1.4), the binned representations

should be recorded as a level-2a file, in addition to the full

resolution level-2 file. Depth offsets between the sensor

port (where depth is determined) and the sensor apertures

[Ed(λ) and Eu(λ) collectors and Lu(λ) window] must be

48
Mueller and Austin

recorded as header information in level-2 data files, and

applied to the data prior to K-analysis (see Section 6.1.4

below).

6.1.1 Instrument Calibration Analysis

Instrument data from pre- and post-deployment calibrations should be compared with:

1) each other;

2) the long-term history of an instrument’s calibrations; and

3) the record of comparisons with a portable field

irradiance and radiance standard, to be made

frequently during a cruise.

Based on this analysis of the instrument’s history, a calibration file will be generated and applied to transform the

data from level-1 to level-2. This analysis, and the rationale for adopting a particular set of calibration coefficients,

both for responsivity and wavelength, should be fully described in the documentation accompanying the data set,

preferably in an ASCII file to be retained on line with each

data set.

6.1.2 Raman Corrections

Marshall and Smith (1990), and the references cited

therein, showtranspectral Raman scattering contributes

significantly to measured irradiance between 500–700 nm.

At a particular wavelength, the Raman contribution is

excited by ambient irradiance at a wavenumber shift of

3,400 cm−1. For example, Raman scattering at a wavelength of 500 nm (20,000 cm−1), is excited by light at wavelength 427 nm (23,400 cm−1), and at 700 nm (14,286 cm−1)

by light at 565 nm (17,686 cm−1). Marshall and Smith

(1990) give a transverse Raman scattering cross section (at

90◦) of 8.2 × 10−30 cm−2 molecule−1 sr−1, a value within

the range of other published observations. By integration,

they derive a total Raman scattering coefficient of:

br(488) = 2.6 × 10−4 m−1. (23)

The wavelength dependence of the Raman scattering cross

section is theoretically about the same as that for Rayleigh

scattering

br(λ) ≡ br(488) 	 λ

488
−4

, (24)

although this has not yet been experimentally confirmed.

A method for applying Raman corrections to measured

profiles of irradiance and radiance is suggested and applied

to homogeneous clear-water profiles by Marshall and Smith

(1990). Additional work is needed to develop a robust

Raman scattering correction model for general application

in more turbid and vertically stratified water masses. The

relative magnitude, and thus importance, of the Raman

signal at each wavelength in the upper three attenuation

lengths should also be investigated more thoroughly than

has been done to date.

6.1.3 Normalization by Surface Irradiance

The dominant errors in measured K(z, λ) profiles result from changes in cloud cover. Cloud cover variability causes strong variations in incident surface irradiance,

Es(λ, t), measured at time t, during the time required to

complete a radiometric cast. In present usage, Es(λ, t)

refers to incident spectral irradiance measured with a deck

cell aboard a ship. Smith and Baker (1984 and 1986) discuss a method for propagating Es(λ) through the sea surface to estimate Ed(0−, λ), and they also present a model

for adjusting Ed(0−, λ) to compensate for solar zenith angle.

An alternative, and conceptually better, scheme for estimating Ed(0−, λ) is to measure Ed(zr, λ) using a radiometer which has been floated away from the ship and held at

a shallowdepth, zr, during a cast (Waters et al. 1990). In

either case, the record of Es(λ, t) or Ed(zr, t) is recorded

together with profiles of Ed(z, λ, t), Eu(z, λ), and Lu(z, λ).

Assuming that transmission of Es(λ, t) through the surface

does not vary with time, then a simple and effective normalization of the profiles is obtained as

E

d(z, λ) = Ed(z, λ)Es(0−, λ)

Es(λ, t) , (25)

where Es(λ, t) is the deck cell irradiance measured at the

time t when the radiometer was at depth z and Es(0−, λ) is

the measurement when the radiometer was at the surface.

Some previous investigators have used Es(λ, t) at a single reference wavelength, e.g., 550 nm, to normalize profiles, and have thus ignored the usually small spectral variations in incident irradiance. For SeaWiFS validation and

algorithm development, however, the recommended protocol is to use multispectral Es(λ, t), or possibly near-surface

Ed(zr, λ, t), to determine Ed(z, λ, t) at each wavelength.

Because of spatial separation between the surface and

underwater radiometers, cloud shadow variations are not

measured, either identically or in phase, by the two instruments. The Es(λ, t) or Ed(zr, λ, t) profiles should, therefore, be smoothed to remove high frequency fluctuations

while retaining variations with periods of 15 seconds or

greater. The smoothed Es(0−, λ)/Es(λ, t) profiles should

then be applied as a normalizing function to the irradiance

and radiance profiles.

6.1.4 K-Analysis

Normalized and Raman corrected profiles of Ed(z, λ),

Eu(z, λ), and Lu(z, λ) (with z corrected for pressure transducer depth offset relative to each sensor) should be fit to

the equations

Ed(z, λ) = Ed(0−, λ) e

−

z

0

Kd(z,λ)dz

, (26)

Eu(z, λ) = Eu(0−, λ) e

−

z

0

Ku(z,λ)dz

, (27)

49
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

and

Lu(z, λ) = Lu(0−, λ) e

−

z

0

KL(z,λ)dz

, (28)

respectively. The vertical profiles of attenuation coefficients Kd(z, λ), Ku(z, λ), and KL(z, λ), together with the

respective values of Ed(0−, λ), Eu(0−, λ), and Lu(0−, λ)

at the surface, provide the needed specifications for the

smoothed irradiance and radiance profiles.

If the natural logarithm of (26), (27), and (28) is taken,

equations of the following form are obtained:

−

z

0

K(z)dz = lnE(z)

 − ln

E(0−)



, (29)

so that

K(z) = −d ln

E(z)



dz











z

. (30)

The traditional method of K-analysis, e.g., Smith and

Baker (1984 and 1986), is to estimate K(z) as the local

slope of measured ln
E(z)



in an interval of a fewmeters

centered at depth zm, i.e., at depths near depth zm,

ln
E(z)

 ∼= ln


E(zm)

 − (z − zm)K(zm). (31)

The unknowns ln
E(zm)

 and K(zm) are determined as

the intercept and (negative) slope of a least-squares regression fit to measured ln


E(z)

 data within the depth

interval zm − ∆z ≤ z<zm + ∆z. The half-interval ∆z

is somewhat arbitrary. Smith and Baker (1984 and 1986)

suggest a ∆z of approximately 4 m, but for noisy profiles,

a ∆z as large as 10 m may be needed to smooth over incident irradiance fluctuations left as residuals by the deck

cell normalization.

When this method is used, the shallowest possible values in the smoothed E(z) and K(z) profiles are at depth

∆z m, and the deepest values are ∆z m above the deepest

measurements in the profile. If obvious ship shadoweffects

are present in the data, the shallowest valid smoothed data

point will be at depth zs + ∆z, where zs is the depth to

which the data are regarded as contaminated and are excluded from the analysis.

It is often convenient, although not necessary, to preaverage radiometric data into, e.g., 1 m, bins prior to performing the least-squares analysis. If this is done, the data

should be pre-filtered to remove any noise spikes and then

averaged before it is log-transformed.

A corollary to having a large database is the need to

facilitate its manipulation and analysis in order to make

its application to various tasks feasible. In the proposed

SeaWiFS effort, for example, radiometric measurements

from many oceanographic stations will be examined. Each

station will require one or more vertical profiles, from the

surface to depths of up to 200 m, of downwelling irradiance,

upwelling radiance, and upwelling irradiance, measured in

at least 5–8 spectral bands. By using a multispectral radiometer (such as the MER class of instruments) during a

profile, the data in all channels will be sampled contemporaneously and recorded digitally 2–10 times per meter.

These are level-1 data and are stored in files for subsequent

processing and analysis.

The level-2 through level-4 data give increasingly refined information in each successive processing level, which

requires various amounts of intervention from the analyst.

After appropriate editing to remove artifacts, such as the

effects of ship shadow, vertical profiles of K are computed

from the logarithmic decrement with depth of the radiometric profiles. Direct derivative method calculations of

K profiles using computer techniques (see above) require

the use of a depth interval so large, frequently 20 m, that

information about the slope, and hence, about K near the

top and bottom of the profile, is lost. Averaging over such

a large interval causes the slopes in sharply defined layers,

e.g., regions of high gradients, to be poorly represented.

Attempts to reduce these effects by using a significantly

smaller depth interval result in unacceptably noisy K profiles.

An improved approach, suggested by Petzold (1988), is

to fit a series of analytic functions to the radiometric data

using non-linear least-squares regression fitting techniques.

The profiles are broken up into as many layers as required,

and functions are fit to each layer, with the constraint that

the functions and the derivatives of the functions be everywhere continuous and finite. It is found that the logarithm

of the radiometric data versus depth can be fit by a series

of hyperbolic tangents superimposed on straight lines using this technique. The data for a profile consisting of two

layers can be matched by using the analytic expression

together with the values of five parameters derived from

the regression fitting procedure. In analyses of 2,100 profiles, the most complicated profiles encountered required

20 parameters—most required 5 or 10.

With the analytic form of the curve fitting the data,

it is a simple matter to differentiate the function to determine the slope of the radiometric profile and obtain noisefree profiles of K. Using this technique, Petzold is able to

store a very large database in a very compact form, storing only the parameters and the program for reconstructing the data. Additional analyses can be easily performed

using the analytic representation of the data in lieu of the

original large discrete data files.

The basic functional form of the expression used to fit

the data is

Y = P1 + P2B + P3

A − 1

A

A + 1

A

, (32)

where B = P4 − X, A = eB/P5 , P1 through P5 are coefficients to be determined in the analysis, X is the depth in

meters, Y is the base 10 logarithm of the radiometric measurement, i.e., the downwelling irradiance (Ed), upwelling

50
Mueller and Austin

irradiance (Eu) or upwelling radiance (Lu). The form of

(32) is a hyperbolic tangent superimposed upon a straight

line. It has a point of inflection at X = P4,Y = P1 and approaches the asymptote Y = P1 +P2B ±P3 as X becomes

larger or smaller than P4.

The first derivative is

dY

dX = −P2 − P3P5

	 2

A + 1

A


2

. (33)

When X = P4, B = 0, and Y = P1, then

dY

dX = −P2 − P3P5

. (34)

It is also possible to define K as the slope of the plot of

the natural logarithm of the measured radiometric variable

against depth, or

K = 2.3026

dY

dX . (35)

At the point of inflection (X = P4 and Y = P1),

K = 2.3026 	P2 +

P3

P5




. (36)

In the limit K → 2.3026 P2, and K will not exceed some

finite value.

The method described above was applied to radiometric profile data from six cruises covering a wide variety of

ocean regimes and latitudes from 24.0–77.4◦ N. Approximately 2,100 profiles were fitted, and typically, the standard deviation of the ratio between the function derived

from the regression method and the original radiance and

irradiance data was 6% or less. For a large fraction of the

fitted profiles, the standard deviations were between 1–3%.

An alternative method of determining K-profiles was

recently developed by Mueller (1991). Radiometric profiles

are represented in terms of optical depth, τ , which from

(26), (27), and (28) is

τ (z, λ) = z

0

K(z, λ)dz

= ln

E(0−, λ)

E(z, λ)



.

(37)

The K-profile is represented analytically by Hermitian cubic polynomials, γij (ξ), over finite depth elements. The

argument ξ is a local coordinate such that ξ = 0 at the

center of a finite depth element, ξ = −1 at the shallowend

point (node) of the element and ξ = 1 at the deep node.

[Hermitian cubic polynomials are defined in any text on

finite element modeling, e.g., Pinder and Gray (1977).]

At depth z, K(z, λ) is expressed as

K(z, λ) = K0(λ)γ01(ξ) + ∂zK0(λ)γ11(ξ)

+ K1(λ)γ02(ξ) + ∂zK1(λ)γ12(ξ), (38)

where K0 and K1 are values of K, and ∂zK0 and ∂zK1

are its vertical derivatives at the two nodes of the depth

element containing z. With this representation of K(z, λ),

it is possible to write (37) for each measured depth zm as

the weighted sum

τ (zm, λ) = 

N

n=0

hm,nKn + hm,n+N ∂zKn (39)

for the n = 0, 1, ... ,N nodes dividing the water column

into N depth elements. The coefficients hij are obtained as

analytic integrals over the Hermitian polynominals γij for

the finite elements above and including depth z; hij = 0

for elements belowthe one containing z. Since such an

equation may be written for every measured optical depth,

the profile may be represented in matrix form as

3τ = H 3

K, (40)

where 3τ is the vector of measured optical depths, H is the

matrix of coefficients hij , and 3

K is the vector of Kn and

∂zKn at the N nodes. The least-squares solution for the

unknown vector 3

K is obtained as

3

K =



HT H

−1

HT 3τ, (41)

which with (38) yields the complete profile K(z).

The surface boundary condition assumed by Mueller

(1991) is that K(z) is constant between the sea surface

(node 0) and the first subsurface node (node 1). If obvious

or suspected ship shadoweffects are present in the upper

profile, the depth of node 1 is set immediately belowthe

affected area and the data in that top element are excluded

from the fit; the solution to (41) at nodes 0 and 1 is, in this

case, determined entirely by the data from depths below

node 1.

The solution at the deepest node is not constrained

and depends only on the observations in the depth element immediately above it. The one-sided solution to (41)

is often unstable at this node. If two nodes are placed close

together at the bottom of the cast, then the unstable solution is confined to only the bottom node, which may be

discarded after (41) is solved.

In order to solve (41), the surface values of Ed(0−, λ),

Eu(0−, λ), and Lu(0−, λ) must be independently determined or specified. At present, this is done iteratively

by requiring the solution to closely approximate the mean

value of measurements in the top 1–2 m of the profile. Data

from this near-surface layer are usually not significantly affected by ship shadow, but they may be severely affected

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Ocean Optics Protocols for SeaWiFS Validation, Revision 1

by irradiance fluctuations associated with light focusing by

surface waves. Additional research is needed to develop a

more objective method of determining these surface values.

In the present implementation (Mueller 1991), placement of nodes is largely subjective, even when guided by

structure in accompanying c(660) and chlorophyll fluorescence profiles. Qualitatively, the integral solutions mimic

the structure in the c(660) and fluorescence profiles more

faithfully than do the derivative solutions; they also do

a better job of filtering irregularities that are apparently

associated with large fluctuations in deck cell irradiance.

Quantitative evaluation of sensitivity to exact node placement is in progress. Development of objective criteria for

node placement will require further research.

6.1.5 Finite Bandwidth Correction

Siegel et al. (1986) and Marshall and Smith (1990) discuss the effects of finite spectral FWHM bandwidth, and

the normalized response function, on determination of the

attenuation coefficient, K(λ), for a vertically homogeneous

water column. Given a channel’s nominal wavelength, λ

,

and normalized response function, h(λ), the apparent attenuation coefficient measured in a homogeneous water column is approximately

Ks(z, λ

) =



∞

0

K(λ)h(λ)e−K(λ)zdλ



∞

0

h(λ)e−K(λ)zdλ

. (42)

Marshall and Smith (1990) applied a correction for this

effect to clear-water profiles of Ed(z, 589). In general, correction of Ks(z, λ

) for finite bandwidth effects associated

with K for pure water is straightforward. Additional research will be needed to model, from the spectral irradiance data itself, additional bandwidth effects associated

with attenuation by phytoplankton and other particles,

and to correct Ks(z, λ) accordingly.

6.1.6 Extrapolation to the Sea Surface

Because of surface waves, it is rarely possible to measure Ed, Eu, or Lu at depths that closely approximate

z ∼= 0−. The shallowest reliable readings typically occur at depths ranging from 0.5–2 m. The data from this

zone usually exhibit strong fluctuations associated with

surface waves, and thus require some form of smoothing

or averaging. It is almost always necessary to apply some

means of extrapolating the data upward to the sea surface.

Whatever method is used should reconcile extrapolated

Ed(0−, λ) with deck measurements of Es(λ).

If K(z) profiles are determined using the derivative

method, the shallowest smoothed estimates will occur at

depth z0 = ∆z, if there are no ship shadoweffects. The

usual procedure is to extrapolate values to z = 0− as

Ed(0−, λ) = Ed(z0, λ)eKd(z0,λ)z0 , (43)

Eu(0−, λ) = Eu(z0, λ)eKu(z0,λ)z0 , (44)

and

Lu(0−, λ) = Lu(z0, λ)eKL(z0,λ)z0 . (45)

If ship shadowis present, z0 may be 20 m or more, and the

extrapolation becomes somewhat tenuous.

If K(z) profiles are determined by means of the integral method, then Ed(0−, λ), Eu(0−, λ), and Lu(0−, λ) are

automatically determined as part of the fitting procedure.

The surface values thus obtained are not necessarily superior to those obtained by extrapolating the derivative

method solutions, but they do have the advantage of representing an internally consistent fit to the entire profile

beneath the surface boundary layer.

By either method, extrapolation of measured Ed(z, λ),

Eu(z, λ), and Lu(z, λ) to z = 0− becomes very difficult at

λ ≥ 670 nm. At these wavelengths, the rapid decrease in

daylight over an extremely shallowfirst attenuation length

may compete with an increase in flux with depth due to

chlorophyll fluorescence. Additional research is needed

to address measurement and estimation of Ed(0−, λ) and

Lu(0−, λ) at these wavelengths, especially in chlorophyllrich Case-2 waters.

6.1.7 Instrument Self-Shading Corrections

A provisional protocol is given here for radiometer selfshading corrections to Lu(0−, λ) and Eu(0−, λ) measurements (see also Section 5.1.6). The protocol is based on the

model of Gordon and Ding (1992) and limited experimental confirmation by Zibordi and Ferrari (1994). Although

additional research is necessary to extend and verify these

correction algorithms, the results published to date show

clearly that even a provisional correction will significantly

improve Lu(0−, λ) and Eu(0−, λ) estimated from underwater measurements.

It is first necessary to estimate the spectral absorption

coefficient a(λ), preferably using measurements following

the protocols of Sections 5.2.4, 5.4.2, 6.8.1, and 6.8.2. It is

also possible to estimate a(λ) using other approximations

suggested by Gordon and Ding (1992), based either on

measurements of phytoplankton pigment concentrations or

of irradiance attenuation coefficients.

It will also be necessary to measure, or estimate, the

direct solar, Esun(λ), and skylight, Esky(λ), components of

incident spectral irradiance, Es(λ), where Es(λ) = Esun(λ)

+Esky(λ). Zibordi and Ferrari (1994) describe one method

of estimating the ratio Esky(λ)/Esun(λ), and Gordon and

Ding (1992) suggest other alternatives.

Following Zibordi and Ferrari (1994), the coefficients,

κ

, given in Table 2 of Gordon and Ding (1992), are fit

to linear regression models as functions of the solar zenith

angle θ0 in the range 30◦ ≤ θ0 ≤ 70◦. The results given

for Lu(0−, λ), with sun only, for a point sensor may be

computed as

κ

sun,0 tan θ0w = 2.07 + 5.6 × 10−3θ0, (46)

52
Mueller and Austin

and for a finite sensor occupying the full diameter of the

instrument,

κ

sun,l tan θ0w = 1.59 + 6.3 × 10−3θ0, (47)

where θ0 and θ0w are the solar zenith angles in air and

water, respectively, measured in degrees. In practice, the

diameter of the radiance sensor aperture is usually a small

fraction of the instrument diameter. In the results reported

by Zibordi and Ferrari (1994), the point sensor model always overestimated , and use of the finite sensor model

(47) will always yield a lower estimate of . Pending new

insights from future theoretical and experimental work, it

is suggested to estimate

κ

sun tan θ0w = (1−f)κsun,0 tan θ0 + fκsun,l tan θ0, (48)

where f is the ratio of sensor-to-instrument diameters. The

coefficient, κ

sky, for the self-shading effect on Lu(0−, λ)

caused by incident diffuse skylight is similarly estimated

as

κ

sky = 4.61 − 0.87f, (49)

where the coefficients are derived from values given in

Table 3 of Gordon and Ding (1992). Self-shading errors

sun(λ) and sky(λ) for Esun(λ) and Esky(λ) components,

respectively, are then computed as

sun(λ)=1 − eκ

suna(λ)r, (50)

and

sky(λ)=1 − eκ

skya(λ)r, (51)

where r is the instrument radius in meters, and the absorption coefficient a(λ) is in units of m−1.

The self-shading error in Lu(0−, λ) is then calculated

as

(λ) = sun(λ) + sky(λ)h

1 + h , (52)

where

h = Esky(λ)

Esun(λ)

. (53)

Finally, the corrected radiance Lu(0−, λ) is estimated

as

Lu(0−, λ) = L

u(0−, λ)

1 − (λ)

, (54)

where L

u(0−, λ) is determined by analysis of the measured

upwelled radiance profiles (Section 6.1.6).

Similarly, for Eu(0−, λ), the values given in Tables 2

and 3 of Gordon and Ding (1992) determine that for a

point irradiance sensor,

κ

sun,0 = 3.41 − 1.55 × 10−2θ0. (55)

For an irradiance collector with a diameter equal to that

of the instrument,

κ

sun,l = 2.76 − 1.21 × 10−2θ0, (56)

so that

κ

sun = (1 − f)κsun,0 + fκsun,l, (57)

where f is the ratio of the diameter of the irradiance collector to that of the instrument.

For the sky component, κ

sky is defined as

κ

sky = 2.70 − 0.48f. (58)

Values of κ

sun and κ

sky from (57) and (58) are then substituted in equations (50) and (51) to obtain sun(λ) and

sky(λ), which are then used in (52) to solve for (λ). Finally, corrected upwelled spectral irradiance Eu(0−, λ) is

estimated as

Eu(0−, λ) = E

u(0−, λ)

1 − (λ)

, (59)

where E

u(0−, λ) is determined from the upwelled spectral

irradiance profile (Section 6.1.6).

It is recommended that this correction algorithm be

applied to all Lu(0−, λ) and Eu(0−, λ) measurements used

for SeaWiFS validation and algorithm development. Recognizing the provisional nature of the correction, however, the uncorrected measured values must also be reported. Moreover, the method and data used to estimate

a(λ), Esun(λ), and Esky(λ) must be documented and reported with all data sets corrected using this protocol.

6.1.8 Spectral Adjustments

Newmethods must be developed to reconcile in-water

measurements Lu(0−, λ0 + ∆λ1) integrated over a sensor

response function h1(λ) with SeaWiFS measurements of

Lt(λ0+∆λ2) integrated over a wider sensor response function h2(λ). The challenge is to account for differing radiometric sensitivities to fine-scale Fraunhofer structure

in extraterrestrial solar spectral flux, F0(λ), as modified

by atmospheric spectral transmittance, t(λ), and oceanic

spectral reflectance, RL(λ). By assuming F0(λ) is exactly

known, and that over the wavelength range defined by

h2(λ) and h1(λ), both t(λ) and RL(λ) vary slowly with

wavelength, it should be possible to adjust the LW (λ0 +

∆λ1) derived directly from the in-water instrument, to estimate the water-leaving radiance LW (λ0+∆λ2). This will

be transmitted through the atmosphere and contribute to

Lt(λ0 + ∆λ2) measured by SeaWiFS. At the very least,

this type of correction should be practical for a given atmosphere. Prelaunch radiative transfer model sensitivity

studies and experimental verifications should be done to

determine the magnitudes and uncertainties of such corrections for the various SeaWiFS bands.

6.1.9 Normalized Water-Leaving Radiance

To standardize the in-water SeaWiFS algorithms, it is

necessary to normalize measured LW (λ) to those values

53
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

that would be measured were the sun at the zenith, at the

mean Earth-sun distance, and with the effects of the atmosphere removed. Following Gordon (1988), normalized

water-leaving radiance as measured by the satellite sensor

may be defined as

LWN (λ) = LW

t(λ, θ0)



1 − ρ(θ0)



cos θ0

r

R ̄

2

, (60)

where θ0 is the solar zenith angle, ρ(θ0) is the air-water

Fresnel reflectance for incident angle θ0, t(λ, θ0) is the atmospheric transmittance and R ̄ is the mean Earth-sun distance. The Earth-sun distance on the day of the measurement, r, is given by

r = R ̄

1+0.0167 cos D−3

365  , (61)

where D is the sequential day of the year.

The (r/R ̄)2 adjustment was not employed by Gordon

and Clark (1981) or Gordon (1988) because it cancels in

ratio algorithms, and the measurements they used were all

taken within the span of a few months, so this source of

variation was very small in their data. The range of variation in (r/R ̄)2 is approximately 6% over a full annual cycle.

This adjustment should be made, nevertheless, for it becomes important in algorithms predicting absolute values

of LW (λ), as in the clear-water radiance model of Gordon

and Clark (1981), and in algorithms for either estimating

or detecting anomalously high water reflectances in, for

example, a coccolithophore bloom.

To obtain LW (λ) it is necessary to propagate Lu(λ)

upward through the sea surface as

LW (0+, λ) = Lu(0−, λ)

1 − ρ(λ, θ)

n2

w(λ) , (62)

where ρ(λ, θ and nw(λ) are the Fresnel reflectance and refractive index of sea water, respectively. Normalized water

leaving radiance is then computed as

LWN (λ) = LW (λ)

F0(λ)

Es(λ)

, (63)

where F0(λ) denotes the mean extraterrestrial solar irradiance (Neckel and Labs 1984).

6.2 ABOVE-WATER RADIANCE

When upwelled radiance above the water surface is

measured from a ship (Section 5.1.8), the measured radiance, L(λ, θ, φ), must be corrected for the reflected sky

radiance, Lsky(λ, θ, φ). If Lsky(λ, θ, φ + π) is measured by

directly viewing the sky, water-leaving radiance should be

calculated as

LW (λ) = L(λ, θ, φ) + ρ(λ, θ)Lsky(λ, θ, φ + π), (64)

where ρ(λ, θ) is Fresnel reflectance of the water surface.

If L

sky(λ, θ, φ + π) is measured by viewing a horizontally

oriented mirror of reflectance ρm(θ), then (64) must be

modified to

LW (λ) = L(λ, θ, φ) + ρ(λ, θ)

ρm(λ, θ)

L

sky(λ, θ, φ + π). (65)

The remote sensing reflectance, RL(0+, λ), may be calculated from LW (λ) as

RL(0+, λ) = LW (λ)

Es(λ) , (66)

where Es(λ) is incident spectral irradiance, preferably measured concurrently with a calibrated irradiance meter, or

estimated with greater uncertainty by viewing a horizontally oriented gray reflectance plaque (Section 5.1.8). Normalized water-leaving radiance is similarly calculated using

(63).

An alternative approach may be used to calculate reflectance from an uncalibrated radiometer as

R

L(0+, λ) = Sw(λ) − ρ(λ, θ)Ssky(λ)

πSG(λ)ρg(λ, θ) , (67)

where Sw(λ), Ssky(λ), and SG(λ) are the radiometer signals measured viewing the water, sky, and a reflectance

plaque of approximately 10% reflectance (e.g., Spectralon),

respectively; ρ(θ) is the Fresnel reflectance of the surface;

and ρg(λ) is the reflectance of the reference plaque. To

remove residual surface reflectance due to wave facets, it

is assumed that the residual signal at 750 nm is entirely

due to surface reflection, so that the corrected reflectance

is calculated as

RL(λ) = R

L(λ) − RL(0+, 750). (68)

When using this technique, it is critical to measure all

radiances well clear of the ship’s superstructure and to hold

the reference plaque horizontally.

It is more difficult to make verifiable corrections to

L(λ, θ, φ) when measured from low flying aircraft (Section 5.1.7). In this case, atmospheric transmittance and

path radiance are not entirely negligible, and water-leaving

radiance must be calculated as

LW (λ, θ, φ) = t

−1


L(λ, θ, φ) − L∗(λ, θ, φ)



− ρ(λ, θ)Lsky(λ, θ, φ + π), (69)

where t(λ, θ) is the atmospheric transmittance from the

surface to the aircraft altitude, L∗(λ, θ, φ) is the atmospheric path radiance at flight altitude, and Lsky(λ, θ, φ+π)

is the sky radiance incident at the surface. At altitudes

up to 300 m, t(λ, θ) is close to 1, and may usually be estimated with relatively low uncertainty. Unfortunately,

there is no straightforward way to measure Lsky(λ, θ, φ +

54
Mueller and Austin

π) or L∗(λ, θ, φ) from an aircraft. These variables must,

therefore, normally be estimated using an atmospheric radiative transfer model. Verification of model estimates

of Lsky(λ, θ, φ + π) and L∗(λ, θ, φ) is difficult under ideal

cloud-free sky conditions, and is wholly impractical under

variable cloud cover.

Incident irradiance Ed(z, λ) measured at flight altitude

must also be propagated to the surface to compute RL(λ)

and LWN (λ) from airborne measurements, i.e.,

RL(λ) = LW (λ)

Ed(z, λ)td(z, λ)

, (70)

and

LWN (λ) = LWN (λ) F0(λ)

Ed(z, λ)td(z, λ)

, (71)

where td(z, λ) is the downward spectral irradiance transmittance from flight altitude z to the surface.

The authors defer any recommendation for specific protocols for applying atmospheric radiative transfer models

to estimate LW (λ), RL(λ), and LWN (λ) with (69)–(71), respectively. It is incumbent on each investigator to report

in detail the methods used to analyze (through measurements, models, or both) the necessary correction terms,

and to include a detailed error analysis of the results which

are obtained. Aircraft radiometric data sets that do not

include this information should not be used for SeaWiFS

algorithm development or validation.

6.3 MOORED RADIOMETRY

Methods are not highly developed for analyzing data

from moored radiometers to calculate LWN (λ). The principles of this analysis are well understood, but the community has had little experience with moored measurements

of Lu(z, λ), determination of KL(z, λ), and extrapolation

to Lu(0−, λ). The moored optical system being developed

by D. Clark of the NOAA National Environmental Satellite Data Information Service (NESDIS) for SeaWiFS and

MODIS is the first system to be specifically engineered to

address this problem.

Smith et al. (1991) successfully acquired a nine-month

time series of spectral Ed(z, λ, t) and Lu(z, λ, t) at three

depths (32, 52, and 72 m). They placed an additional

above-water radiometer on a surface float, but this unit

failed and provided no data. Smith et al. (1991) analyzed

the Kd(441) time series using a broad-band irradiance measurement to estimate Ed(0−, 441) for the 0–32 m depth interval, and using measured Ed(z, 441) over the 32–52 and

52–72 m depth intervals. They did not, however, estimate

KL(λ) for Lu(λ). They also developed and evaluated algorithms for estimating phytoplankton pigment concentrations from spectral reflectance and from naturally stimulated (by incident daylight) chlorophyll fluorescence at

Lu(683). Smith et al. (1991) demonstrated that continuous time series of Kd(λ, t) and pigment concentration may

be measured using this type of moored system.

Smith et al. (1991) and Dickey et al. (1991) together

illustrate methods that can be used to specify protocols

for oceanographic analyses of bio-optical time series measured using moored optical systems. Such protocols would

be very valuable for planning and executing oceanographic

studies using data from moored systems together with SeaWiFS time series data; they are not, however, directly relevant to SeaWiFS validation. It is anticipated that optical

protocols for US and International JGOFS will be published by working groups convened by these programs.

6.4 AEROSOL OPTICAL DEPTH

If multiple measurements of the solar beam are obtained during stable atmospheric conditions, then the Langley method can be used to obtain the atmospheric transmittance. This method consists of plotting the natural

logarithm of the voltage from the sun photometer versus

the inverse of the cosine of the solar zenith angle. The

slope of this straight line is the total optical depth of one

atmosphere. If only a single measurement is obtained, the

instrument calibration is applied to determine radiance,

which can be combined with the extraterrestrial solar irradiance to calculate the atmospheric optical depth.

To obtain the aerosol optical depth, total optical depth

must be used with computed optical depths due to molecular scattering (Rayleigh optical depth), and absorption

by ozone and other important gases (NO2 for some spectral bands). By subtracting the optical depths of these

well-mixed gases from the total measurements, the aerosol

optical depth can be determined.

6.5 SKY RADIANCE

Sky radiance distributions, Lsky, measured with a calibrated radiance distribution camera, perhaps augmented

by sun photometry or narrowFOV Lsky discrete measurements in the zenith-sun plane, will be used to estimate

the aerosol phase function (Voss and Zibordi 1989). Development of detailed protocols and methods of analysis,

including newinverse modeling techniques, for estimating

aerosol optical depths and phase functions will require new

research. The spectral mean cosine μd(0+, λ) for downwelling radiance at the sea surface will be calculated directly

from radiance distribution camera data, when available.

Under cloud-free conditions, μd(0+, λ) can also be estimated by measuring Esky(λ) + Esun(λ) with an irradiance

deck cell. The algorithm for these computations is given

by Gordon (1989b).

When a spectral radiance distribution camera system

is not available and skies are not cloud free, it may be

possible to estimate μd(0+, λ) from some combination of

deck cell unshaded Esky(λ) + Esun(λ) and shaded Esky(λ)

measurements, all-sky photographs, and measurements of

Lsky(λ, θi, φi) made at discrete angles with a hand-held

radiometer. Additional research will be required to develop and test viable protocols for μd(0+, λ) estimation

from these types of measurements.

55
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

6.6 PHYTOPLANKTON PIGMENTS

This section specifies methods of analysis for determining pigment concentrations by HPLC and fluorometry (following acetone extraction) from filtered water samples obtained at discrete depths, and for using in situ profiles of

chlorophyll a fluorescence to interpolate pigment concentration over depth.

6.6.1 HPLC Pigment Concentration

The JGOFS protocols and standards for HPLC pigment concentration analysis (JGOFS 1991) will be the primary method of determining pigment concentrations for all

SeaWiFS algorithm development and validation activities.

6.6.2 Fluorometric Determination

Protocols for fluorometric determination of the concentrations of chlorophyll and phaeopigments were developed

initially by Yentsch and Menzel (1963) and Holm-Hansen

et al. (1965), and are described in detail by Strickland and

Parsons (1972). Although these measurements have been

shown to contain errors as compared to HPLC determinations, e.g., Trees et al. (1985), the CZCS phytoplankton

pigment concentration algorithms were based on them entirely. The SeaWiFS protocols for this analysis will be

those given in Strickland and Parsons (1972) as updated

by Smith et al. (1981).

6.6.3 In Situ Chlorophyll a Fluorescence

In situ fluorometers produce nearly continuous profiles

of artificially stimulated chlorophyll a fluorescence. Level-1

fluorometer data (in volts) should be converted to level-2

simply by subtracting an offset, determined by shading the

instrument on deck. For qualitative guidance in K-profile

analysis, level-2 (or even level-1) fluorometer profiles are

adequate.

To produce vertical profiles of pigment concentration,

HPLC-derived pigment concentrations from water samples

taken at discrete depths should be interpolated, with the

aid of in situ fluorescence profiles, for SeaWiFS bio-optical

algorithm development. These fluorescence interpolated

profiles should then be used with Kd(z, λ) profiles to compute optically weighted pigment concentration over the top

attenuation length (Gordon and Clark 1980).

6.7 BEAM ATTENUATION

Rawbeam transmissometer voltage profiles, V(z), are

first corrected for any range-dependent bias of the A/D

data acquisition system (Section 5.2.1). The corrected

voltages, V(z), are then further adjusted for instrument

drift (occurring subsequent to the factory calibration) with

the equation

V (z) = V(z) − VdarkV 

air

Vair

, (72)

where Vdark is the instrument’s current dark response with

the light path blocked, and V 

air and Vair are, respectively,

the current air calibration voltage (Section 5.2.1) and the

air calibration voltage recorded when the instrument was

calibrated at the factory. V (z) is then converted to transmittance, T(z, λ), over the transmissometer’s path length,

r, following the manufacturer’s instructions for the particular instrument.

The beam attenuation coefficient c(z, λ) is then computed as

c(z, λ) = −1

r

lnT(z, λ)



, (73)

which has units of m−1. The apparent values of c(z, λ)

should be further corrected, again following the manufacturer’s instructions, for the finite acceptance angle of the

instrument’s receiver; this is usually a small, but significant, correction. Finally, the beam attenuation coefficient

due to particles is computed as

cp(z, λ) = c(z, λ) − cw(λ), (74)

where cw(λ) is the beam attenuation coefficient, i.e., the

sum of absorption, aw(λ), and scattering, bw(λ), for pure

water. Smith and Baker (1981) tabulate aw(λ) and bw(λ)

over the spectral range of interest here.

6.8 SPECTRAL ABSORPTION

Protocols are given above in Section 5.2.4 for measuring

absorption profiles in situ using reflective tube meters, and

in Section 5.4.2 for laboratory spectrophotometric analyses

of water samples captured at discrete depths.

Data from a reflective tube absorption and beam attenuation meter may be analyzed to obtain vertical profiles of

a(z, λ), ag(z, λ), and c(z, λ), and by difference b(z, λ) =

c(z, λ) − a(z, λ) and ap(z, λ) = a(z, λ) − ag(λ, t), using the

protocols of Section 6.8.1. Optical density spectra for filtrate and filtered water samples (Section 5.4.2) may be analyzed to obtain independent measures of ag(z, λ), ap(z, λ),

and at(λ, t), and by difference af (z, λ) = ap(z, λ)−at(z, λ),

using the protocols of Section 6.8.2. Methods for merging

and comparing the two independent types of absorption

measurements, and for interpreting the results in terms of

remote sensing reflectance, are the subject of currently active research by several investigators. The next revision

to this document may be expected to contain extensive

modifications and extensions of these protocols.

6.8.1 Reflective Tube Measurements

At the time of this writing, there is only one commercially available reflective tube absorption and beam attenuation meter, the AC-9, manufactured by Western Environmental Technology, Inc., of Philomath, Oregon. The

following data analysis protocol is, therefore, based on the

characteristics of that instrument (Zaneveld and Moore

pers. comm.).

56
Mueller and Austin

The AC-9 output in each a(λ) or c(λ) channel consists

of the digital responses of a reference detector and a water transmission detector, Cr(λ) and Ct(λ). During the

instrument’s factory calibration using optically pure water

(Sections 4.4 and 5.2.4), the responses C

(λ) and C

r(λ)

are recorded and entered on the instrument’s calibration

sheet, along with the instrument temperature T at which

the calibration was performed. Calibration factors for each

channel are then determined as

A(λa) = C

r(λa)

C

t(λa)

e−aw(λa)x, (75)

for absorption at wavelength λa, and

A(λc) = C

r(λc)

C

t(λc)

e−cw(λc)x, (76)

for beam attenuation at wavelength λc, where x is the

optical pathlength in meters, and aw(λa) and cw(λc) are

the absorption and beam attenuation coefficients of optically pure reference water, respectively (Smith and Baker

1981). The instrument’s factory calibration also includes

determination of a temperature coefficient Bt(λn) for each

channel.

In the subsequent discussion in this section, the subscript i designates initial values of the absorption beam attenuation coefficients derived directly from measurements.

The subscript e denotes the corrected values of the same

coefficients due to (extra) substances other than water.

When data are recorded in the field, apparent absorption coefficients ai(λa) due to substances other than pure

water are calculated as

ai(λa, T) = − ln

Ct(λa, T)

Cr(λa, T)

T A(λa)



+ (T − T)Bt(λa)

+ 
aair(λa) − a

air(λ0)



,

(77)

where T and T denote the instrument temperature, and

a

air(λ0) and aair(λ0) are air calibration values at the times

of the instrument factory calibration and field data recording, respectively (Section 5.2.4). A similar equation is

applied to obtain apparent beam attenuation coefficients

ci(λc) for substances other than water at each wavelength.

Apparent absorption coefficients ai(λ, T) must be corrected for the fraction of scattering that is undetected by

the reflective tube and detector assembly (Section 5.2.4).

An initial estimate of particle scattering at each wavelength bi(λ) is obtained as

bi(λ) = ci(λ) − ai(λ, T), (78)

recalling that attenuation by pure water already has been

removed from ci(λ) and ai(λ, T) using the instrument’s

calibration coefficients. It is assumed that:

1) the uncertainty in ci(λ) due to forward scattered

light, which is viewed by the detector (Section 6.7),

is a wavelength-independent fraction kc of total particle scattering bp(λ);

2) the fraction k of bp(λ) included in ai(λ) is also independent of wavelength; and

3) at a near-IR wavelength λr, absorption is entirely

due to pure water, and the apparent absorption

ai(λr, T) is completely due to undetected scattering kbp(λr) and temperature dependent variations

in water absorption (Pegau and Zaneveld 1993) relative to absorption at T (the calibration temperature).

From assumptions 1) and 2), it follows that

bp(λ1)

bp(λ2) = bi(λ1)bi(λ2)

. (79)

From assumption 3), it follows that

k = ai(λr, T) + S(λr)(T − T

)

bi(λr) , (80)

where S(λr) represents the coefficient of water temperature variation in aw(λ, T). At λr = 712 nm, for example,

S(712 = 0.0035 m−1 ◦C−1, and S(λ) is negligible at λ <

700 nm (Pegau and Zaneveld 1993). It is then useful to

combine (79) and (80) to determine the absorption coefficient ae(λ) due to substances other than water (Zaneveld

pers. comm.) as

ae(λ) = ai(λ, T)

−




ai(λr, T) − S(λr)(T − T

)



bi(λ)

bi(λr) . (81)

When equations (75) through (81) are applied to unfiltered

total absorption measurements, it follows that

ae(λ) = ap(λ) + ag(λ), (82)

where ap(λ) and ag(λ) are respectively the particulate and

Gelbstoff (dissolved substances) components of absorption.

If a 0.2 μm intake filter canister is used to exclude the particulate fraction from the water, then ae(λ) is due to ag(λ)

alone. If profiles are made with two AC-9 meters (one filtered and one unfiltered), the total absorption coefficient

may, therefore, be partitioned as

a(λ) = aw(λ) + ap(λ) + ag(λ). (83)

To further partition ap(λ) into aφ(λ) (phytoplankton pigments) and at(λ) (tripton) absorption coefficient components, it is necessary to obtain discrete water samples at

several depths distributed over the profiles, and to apply

57
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

the filtration and spectrophotometry laboratory analyses

described in Sections 5.4.2 and 6.8.2.

The fraction of total particle scattering, kcbp(λ), included in the beam transmission measurement may be estimated from the detector acceptance angle and path length

geometry of a particular instrument. Using this coefficient,

the corrected non-water beam attenuation coefficient ce(λ)

may be calculated as

ce(λ) = ci(λ) + kc




ce(λ) − ae(λ)



, (84)

or

ce(λ) = ci(λ) − kcae(λ)

1 − kc

. (85)

Therefore, the corrected particle scattering coefficient

may be estimated as

bp(λ) = ce(λ) − ae(λ). (86)

6.8.2 Analysis of Absorption Spectra

Spectral absorption coefficients ag(λ) (Gelbstoff), ap

(total particulates), and at (tripton) in units of m−1 are

calculated from optical density spectra measured using the

protocols of Section 5.4.2. For Gelbstoff,

ag(λ) = 2.303

l




ODg(λ) − ODr(λ)



, (87)

where l is the cuvette pathlength (0.1 m), and the other

terms are introduced in Section 5.4.2.

An equation similar to (87) is used to calculate absorption coefficients ap(λ) and at(λ), but in these cases,

a correction must be applied to account for the effective

increase in pathlength due to scattering in the GF/F filters (Mitchell and Kiefer 1984). The nominal absorption

pathlength ls of the filtered material in suspension is given

by

ls = V

A, (88)

where V is the volume of water filtered and A is the clearance area of the filter. Scattering of light within the GF/F

filter lengthens the absorption pathlength. This factor is

termed the β factor by Mitchell and Kiefer (1988) after

Butler (1962), which is not to be confused with the volume

scattering coefficient β(θ) used elsewhere throughout this

document. The absorption coefficient of filtered particles

must, therefore, be corrected for pathlength amplification

and the equivalent absorption in suspension is computed

as

ap(λ) = 2.303A

βV




ODp(λ) − ODr(λ)



. (89)

To correct for residual offsets in the filter spectrophotometric measurement, it is assumed that at 850 nm the true

optical densities are zero. The apparent measured values

of ODp(850) and ODr(850) are, therefore, subtracted from

ODp(λ) and ODr(λ) prior to applying (89). Previously,

some investigators have used apparent optical densities at

750 nm for this correction, but recent work has shown this

wavelength to be inappropriate in some oceanic waters.

The prevalent current practice is to estimate β empirically through a function that may be expressed in the form

β−1 = C1 + C2




ODp(λ) − ODr(λ)



, (90)

where C1 and C2 are coefficients of a polynomial regression

fit. For example, Mitchell (1990) gives C1 = 0.392 and

C2 = 0.665, while Cleveland and Weidemann (1993) give

C1 = 0.378 and C2 = 0.523.

Spectrophotometers that disperse white light into its

spectrum using a monochromator prior to illuminating the

sample are termed pre-sample monochromators, while instruments that pass the light through a monochromator

after it has passed through the sample are termed postsample monochromators. The value of the pathlength

amplification factor has been found to be independent of

post-sample optical geometry for a variety of standard

laboratory instruments with pre-sample monochromators

(Mitchell 1990, Stramski pers. comm., and Cleveland pers.

comm.). Clark (pers. comm.) and Cleveland (pers. comm.)

have found, however, that diode array spectrophotometers

with a post-sample grating require the use of an integrating

sphere attachment which may affect the β factor. Lee et al.

(1994) use a diode array system, which collects and focuses

the post-sample light and gives rawODp values similar

to standard instruments with pre-sample monochromators

(Cleveland pers. comm. and Carder pers. comm.).

Substituting (90) in (89) directly yields the spectral

absorption coefficient for particles in suspension as

ap(λ) = 2.303A

V



C1




ODp(λ) − ODr(λ)



+ C2




ODp(λ) − ODr(λ)

2



,

(91)

and for tripton

ap(λ) = 2.303A

V



C1




ODt(λ) − ODr(λ)



+ C2




ODt(λ) − ODr(λ)

2



.

(92)

Finally, the spectral absorption coefficient for in vivo phytoplankton pigments is computed as

aφ(λ) = ap(λ) − at(λ). (93)

The best overall performance of this algorithm will be

achieved when filtered sample density yields ODp(675) between 0.05 and 0.1. The volume of water filtered for particle absorption measurements should therefore be adjusted

accordingly (Section 5.4.2).

58
Mueller and Austin

For purposes of data reporting and archiving, the absorption coefficients ag(λ), ap(λ), and at(λ) will be reported

in m−1 as computed using equations (87), (91), and (92),

respectively. Uncorrected optical density spectra for the

blank filters and distilled water blank must be recorded

and provided with absorption coefficients to allow reversal

of the correction algorithms. The values of ODp(850) and

ODr(850), which have been subtracted to remove residual instrument offset, must also be reported with each absorption spectrum. The pathlength amplification factor,

together with a description of the method and date of its

determination, must also be reported with all particle absorption coefficients based on filter spectrophotometry.

Roesler and Perry (pers. comm.) have proposed a theoretically derived expression for β, with a formulation different from (90). At this writing, however, this approach has

not gained widespread acceptance in the community. Further reviewof this protocol is warranted for possible future

revision. Sosik and Mitchell (1994) have proposed a spectrofluorescence excitation method to make direct estimates

of absorption by the photosynthetically active pigments




aps(λ)



. They found aps(λ) ≤ aφ(λ), where the difference

is attributable to photo-protective pigments in the phytoplankton. Carder and some of his associates (pers. comm.)

recommend the determination of aM

φ (666) in the methanol

extract using a spectrophotometric method at 666 nm with

850 nm zero. This method sets an upper limit to aφ(675)

for the unpackaged state, and allows an alternate estimate

of chlorophyll a.

6.9 CTD PROFILE ANALYSES

Each CTD profile should be prefiltered to remove any

depth reversal segments resulting from violent ship or hydrowire motions. This will remove many instances of salinity spiking, an artifact which occurs when water temperature changes at a rate faster than the conductivity probe

can follow. The CTD data should then be processed to

profiles of potential temperature (◦C), salinity (Practical

Salinity Units [PSU] based on the Practical Salinity Scale

of 1978, PSS78), and density (kg m−3) using the algorithms which have been endorsed by the United Nations

Educational, Scientific, and Cultural Organization (UNESCO)/SCOR/International Council of Exploration of the

Seas (ICES)/IAPSO Joint Panel on Oceanographic Tables

and Standards, and also by SCOR Working Group 51 (Fofonoff and Millard 1983).

At this stage, each set of CTD profiles should be carefully examined to detect any significant static instability

artifacts resulting from salinity spiking. After any such

major artifacts are removed by editing, the data should be

further smoothed by averaging temperature and conductivity data into 2 m depth bins, and the final profiles of

salinity, density, and other derived parameters should be

recomputed using the smoothed CTD profile.

For any hydrographic station, descriptive hydrographic

analyses should include T-S profile characterizations of water masses. Features in the density profile which appear

to be related to physical mixing and stability should be

compared with features in the corresponding bio-optical

profiles. CTD profiles from horizontal transects (i.e., twodimensional grids) should be used in the computation of

two-dimensional sections, or three-dimensional gridded arrays, for such variables as geostrophic currents, temperature, salinity, and the density anomaly σt. These analysis products, together with corresponding two- or threedimensional representations of bio-optical variability, can

be used to estimate the relative importance of advection

and isopycnal mixing in redistributing or modifying upper

ocean optical properties during a cruise.

59
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

Acknowledgments

These protocols originated from discussions and draft material

contributed by the workshop participants in April 1991. The

authors thank all of them for their help. The participants’

names and affiliations (as of the time the workshop was held in

April 1991) are given in Table 7.

Table 7. Workshop Participants.

Name Affiliation

Workshop Co-chairs

Roswell Austin SDSU/CHORS

James Mueller SDSU/CHORS

Workshop Participants

Robert Arnone NOARL/Stennis Space Center

Rocky Booth BSI

Kendall Carder Univ. of South Florida

Dennis Clark NOAA/NESDIS

Donald Collins Jet Propulsion Laboratory

Wayne Esaias NASA/GSFC

Howard Gordon Univ. of Miami

Bruce Guenther NASA/GSFC

Ronald Holyer NOARL/Stennis Space Center

Robert Kirk NASA/GSFC

Charles McClain NASA/GSFC

James McLean NASA/GSFC

B. Gregory Mitchell NASA Headquarters

Donald Montgomery Ofc. Oceanogr. of the Navy

Raymond Smith Univ. of Calif. Santa Barbara

Charles Trees SDSU/CHORS

Kenneth Voss Univ. of Miami

Alan Weidemann NOARL/Stennis Space Center

Ronald Zaneveld Oregon State University

Administrative Support

Meta Frost Westover Consultants

Over the past two years, many of the above scientists, and others from the SeaWiFS Science Team and oceanographic community at large, have participated in the ongoing evolution of

these ocean optics protocols, culminating in the present revision. Several people deserve special recognition and thanks

for their time and effort. Robert Bidigare (Univ. of Hawaii)

drafted the improved protocols for pigment analyses. Ronald

Zaneveld contributed draft versions of new protocols for calibrating and using instruments for in situ spectral absorption

and beam attenuation profiles, and for backscattering measurements. Expanded protocols for spectrophotometric determination of absorption by particles and dissolved matter were

contributed through the combined efforts of Charles Trees, B.

Gregory Mitchell, Joan Cleveland (SDSU/CHORS), Charles

Yentsch (Bigelow Marine Laboratory), Colin Roesler (Univ. of

Connecticut), Kendall Carder, and David Phinney (Bigelow

Marine Laboratory). New protocols for Case-2 waters and

above-water radiometry are based on material contributed by

Kendall Carder, Roland Doerffer (GKSS Forschungszenstrum,

Germany), Curtiss Davis (Naval Research Laboratory), and

Robert Arnone. Thanks are due to all of these people, and

other colleagues who continue to participate in the critical review, discussion, and improvement of this body of protocols.

Glossary

A/D Analog-to-Digital

ALSCAT ALPHA and Scattering Meter (Note: the symbol

α corresponds to c(λ), the beam attenuation coefficient, in present usage.)

AOL Airborne Oceanographic Lidar

ARGOS Not an acronym: the name given to the data collection and location system on NOAA Operational

Satellites

ASCII American Standard Code for Information Interchange

AVHRR Advanced Very High Resolution Radiometer

AVIRIS Advanced Visible and Infrared Imaging Spectrometer

BSI Biospherical Instruments, Inc.

CDOM Colored Dissolved Organic Material

CHN Carbon, Hydrogen, and Nitrogen

CTD Conductivity, Temperature, and Depth

CW Continuous Wave

CZCS Coastal Zone Color Scanner

DIW Distilled Water

DOC Dissolved Organic Carbon

DOM Dissolved Organic Matter

ER-2 Earth Resources-2, a research aircraft

FEL Not an acronym; a type of standard lamp for irradiance and radiance calibration

FOV Field-of-View

FWHM Full-Width at Half-Maximum

GAC Global Area Coverage

GASM General Angle Scattering Meter

GF/F Not an acronym; a specific type of glass fiber filter

manufactured by Whatman

GMT Greenwich Mean Time

GOES Geostationary Operational Environmental Satellite

GPS Global Positioning System

GSFC Goddard Space Flight Center

HPLC High Performance Liquid Chromatography

IAPSO International Association for the Physical Sciences

of the Ocean

ICES International Council on Exploration of the Seas

IFOV Instantaneous field-of-view

IOP Inherent Optical Properties

IR Infrared

JGOFS Joint Global Ocean Flux Study

MARS Multispectral Airborne Radiometer System

MER Marine Environmental Radiometer

MERIS Marine Environment Research Imaging Spectroradiometer (French)

MODIS Moderate Resolution Imaging Spectrometer

NAS National Academy of Science

NASA National Aeronautics and Space Administration

NASIC NASA Aircraft/Satellite Instrument Calibration

NESDIS National Environmental Satellite Data Information

Service

NIST National Institute of Standards and Technology

NOAA National Oceanic and Atmospheric Administration

NOARL Naval Oceanographic and Atmospheric Research

Laboratory

60
Mueller and Austin

OCTS Ocean Color and Temperature Sensor (Japanese)

OFFI Optical Free-Fall Instrument

OMP-8 Not an acronym; a type of marine anti-biofouling

compound

OSFI Optical Surface Floating Instrument

PAR Photosynthetically Available Radiation

POC Particulate Organic Carbon

POLDER Polarization and Directionality of the Earth Reflectance (French)

PON Particulate Organic Nitrogen

PSU Practical Salinity Units

PTFE Polytetrafluoroethylene, commonly known by the

trade name Teflon

QED Quantum Efficient Device

ROSIS Remote Ocean Sensing Imaging Spectrometer, also

known as the Reflecting Optics System Imaging

Spectrometer (German)

ROV Remotely Operated Vehicle

ROW Reverse Osmosis Water

SCOR Scientific Committee on Oceanographic Research

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SIRREX SeaWiFS Intercalibration Round-Robin Experiment

SNR Signal-to-Noise Ratio

SPM Suspended Particulate Material

SPO SeaWiFS Project Office

SPSWG SeaWiFS Prelaunch Science Working Group

SST Sea Surface Temperature

T-S Temperature-Salinity

TIROS Television Infrared Observation Satellite

TSM Total Suspended Material

UNESCO United Nations Educational, Scientific, and Cultural Organizations

UV Ultraviolet

UVB Ultraviolet-B

WMO World Meteorological Organization

Symbols

A Fitting coefficient for P4 − X, or clearance area of

a filter, depending on usage.

A(λa) AC-9 instrument calibration factor for absorption.

A(λc) AC-9 instrument calibration factor for beam attenuation.

a(λ) Total absorption coefficient.

a(z, λ) Spectral absorption coefficient.

ae(λ) Absorption coefficient due to substances other than

water.

af (z, λ) ap(λ) − at(z, λ).

ag(λ) Gelbstoff spectral absorption coefficient.

ai(λa, T) Initial estimate of the apparent absorption coefficient; used for determining the apparent absorption

coefficient for substances other than water.

aM

φ (λ) Phytoplankton pigment spectral absorption coefficient determined in methanol extract.

ap(λ) Particulate spectral absorption coefficient.

aps(λ) Photosynthetically active pigment spectral absorption coefficient.

at(λ) Tripton spectral absorption coefficient.

aw(λ) Absorption coefficient for pure water.

aφ(λ) Phytoplankton pigment spectral absorption coefficient.

B Fitting coefficient for eB/P5 .

b(z, λ) Total scattering coefficient.

b(z, λ0, θ) Volume scattering coefficient.

bb(z, λ) Spectral backscattering coefficient.

bi(λ) Initial estimate of the particle scattering coefficient;

used for determining the apparent particle scattering coefficient for substances other than water.

bp(λ) Total particle scattering.

br(λ) Total Raman scattering coefficient.

bw(λ) Scattering coefficient for pure water.

c(z, λ) Spectral beam attenuation coefficient.

c(z, 660) Red beam attenuation (at 660 nm).

ce(λ) Corrected non-water beam attenuation coefficient.

ci(λ) Initial estimate of the beam attenuation coefficient;

used for determining the apparent beam attenuation coefficient for substances other than water.

cp(λ) Beam attenuation coefficient due to particles.

cw(λ) Beam attenuation coefficient for pure water equal

to aw(λ) + bw(λ).

C1 Polynomial regression factor.

C2 Additional polynomial regression factor.

C

(λ) AC-9 factory calibration coefficient.

C

r(λ) Additional AC-9 factory calibration coefficient.

Cr(λ) Digital response of reference detector.

Ct(λ) Digital response of water transmission detector.

D Sequential day of the year.

d Distance of lamp source from collector surface.

E(λ) Irradiance.

Eˆ(z,m Smoothed estimate of irradiance obtained by leastsquares regression fit in the center of a depth interval.

Ea(λ) Irradiance in air.

Ecal Calibration source irradiance.

Ed(0−, λ) Incident spectral irradiance.

E

d(z, λ) Normalized downwelled spectral irradiance

Ed(z, λ) Downwelled spectral irradiance

Es(λ) Surface irradiance.

Esky(λ) Spectral sky irradiance.

Esun(λ) Spectral sun irradiance.

Eu(z, λ) Upwelled spectral irradiance.

Ew(z, λ) Irradiance in water.

F0(λ) Mean extraterrestrial solar flux.

Fi(λ) Immersion correction factor.

Fv(λ) Field-of-view coefficient.

f Ratio of sensor-to-instrument diameters.

f(T) Offset voltage correction from the linear function

characterizing temperature response.

G(z, λ) Solid angle dependence with water depth.

g(T) Coefficient of a linear function characterizing temperature response.

H Matrix of coefficients hij .

hij Analytic integral coefficients over the Hermitian polynomials γij .

h(λ) Normalized response function.



K Vector of Kn.

K(λ) Generic irradiance attenuation coefficient.

K(z, λ) Diffuse attenuation coefficient.

Kd(z, λ) Vertical attenuation coefficient for downwelled irradiance.

61
Ocean Optics Protocols for SeaWiFS Validation, Revision 1

KL(z, λ) Attenuation coefficient upwelled radiance.

Kn K at node depth zn determined, with its vertical

derivative by least-squares fit to radiometric profiles. (See equations 37–41 and surrounding text.)

Ks(z, λ

) Apparent attenuation coefficient measured in a homogenous water column.

Ku(z, λ) Vertical attenuation coefficient for upwelled irradiance.

k Fractional factor of total particle scattering.

ky/ tan θ0w.

kc Wavelength independent fraction.

l Cuvette pathlength.

ls Nominal absorption pathlength.

L(z, θ, φ) Submerged upwelled radiance distribution.

L∗(λ, θ, φ) Atmospheric path radiance at flight altitude.

Lcal Calibration source radiance.

Lsky(λ, θ, φ) Spectral sky radiance distribution.

Lt Radiance at top of atmosphere.

Lu(z, λ) Upwelled spectral radiance.

Lˆu(λ) True upwelled spectral radiance.

L ̃u(λ) Measured upwelled spectral radiance.

LW (λ) Water-leaving radiance.

LWN (λ) Normalized water-leaving radiance.

L1(λ) Apparent radiance response to a linearly polarized

source.

L2(λ) Orthogonal apparent radiance response to a linearly

polarized source.

n Starting index in measurement for angular measurements, or node index for the integral K analysis.

ng(λ) Index of refraction of Plexiglas.

nw(λ) Index of refraction of water.

N Ending index in measurement sequence for angular

measurements.

ODb(λ) Baseline optical density spectrum.

ODg(λ) Optical density of soluble material (Gelbstoff).

ODp(λ) Optical density spectra of filtered particles.

ODr(λ) Optical density reference for filter or distilled water.

ODt(λ) Optical density of non-pigmented particulates (tripton).

P(λ) Polarization sensitivity.

Pi Fitting coefficient for i = 1 to 5.

Q(λ) Lu(0−, λ) to Eu(0−, λ) relation factor (equal to π

for a Lambertian surface).

R Mean Earth-sun distance.

R

L Reflectance from an uncalibrated radiometer.

RL(z, λ) Spectral reflectance.

r Radius, or Earth-sun distance depending on usage.

S(λr) A coefficient of water temperature variation in

aw(λ, T).

SG(λ) Radiometer signal (uncalibrated) measured viewing

a reflectance plaque.

Ssky Radiometer signal (uncalibrated) measured viewing

the sky.

SW (λ) Radiometer signal (uncalibrated) measured viewing

the water.

TInstrument temperature during calibration.

Tg(λ) Transmittance through a glass window.

Ts(λ) Transmittance through the surface.

Tw(λ) Transmittance through a water path.

td(z, λ) Downward spectral irradiance transmittance from

flight altitude z to the surface.

V Volume of water filtered.

Vˆ True voltage.

V ̃ Measured voltage.

V (z) Transmissometer voltage.

V 

air Current transmissometer air calibration voltage.

V (θ) Normalized measured value for a cosine collector.

V (θi) Mean normalized measured value of instrument response.

Vair Factory transmissometer air calibration voltage.

Vdark Transmissometer dark response.

Wθ Weighting function.

X Depth in meters.

y Empirical factor.

Y Base 10 logarithm of the radiometric measurement

Ed, Eu, or Lu.

z Vertical coordinate.

zCorrected depth for pressure transducer depth offset

relative to a sensor.

zm Centered depth.

zr Shallow depth.

zs Exclusion depth due to data contamination.

β Filter absorption correction factor for scattering

within the filter.

β(z, θ, λ) Spectral volume scattering function.

βb The measured integral of the volume scattering function in the backward direction. The symbol in the

text—βb(θ, ∆θ, λ, ∆λ)—is for the measurement in

the backward direction over the angle θ at a given

wavelength λ.

γij (ξ) Hermitian cubic polynomial.

∆z Half-interval depth increment.

∆θ Angular increment.

δ Cosine response asymmetry.

2 Cosine collector response error.

2sun Self-shading error for Esun.

2sky Self-shading error for Esky.

ε(λ) 1 − e−ka(λ)r.

θ Centroid angle of the scattering measurement.

θa In-air measurement angle.

θi Any nominal angle.

θN Angular terminus.

θn Angular origin.

θt Tilt angle.

θw In-water measurement angle.

θ0w Refracted solar zenith angle.

θ1 Lower integration limit.

θ2 Upper integration limit.

κSelf-shading coefficients.

λChannel of nominal wavelength.

λ0 Center wavelength.

λn Any nominal wavelength.

λr Near-IR wavelength.

μd(z, λ) Spectral mean cosine for downwelling radiance at

depth z.

ξ(λ) Minimum ship-shadow avoidance distance.

62
Mueller and Austin

ρ(λ) Bidirectional reflectance.

ρg(λ) Gray card or plaque reflectance.

σt Density anomaly.

τ Vector of measured optical depths.

τ (z, λ) Spectral optical depth.

τs(λ) Spectral solar atmospheric transmission.

φ Azimuth angle.

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The SeaWiFS Technical Report Series

Vol. 1

Hooker, S.B., W.E. Esaias, G.C. Feldman, W.W. Gregg, and

C.R. McClain, 1992: An Overview of SeaWiFS and Ocean

Color. NASA Tech. Memo. 104566, Vol. 1, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 24 pp., plus color plates.

Vol. 2

Gregg, W.W., 1992: Analysis of Orbit Selection for SeaWiFS:

Ascending vs. Descending Node. NASA Tech. Memo.

104566, Vol. 2, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16pp.

Vol. 3

McClain, C.R., W.E. Esaias, W. Barnes, B. Guenther, D. Endres, S. Hooker, G. Mitchell, and R. Barnes, 1992: Calibration and Validation Plan for SeaWiFS. NASA Tech.

Memo. 104566, Vol. 3, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 41 pp.

Vol. 4

McClain, C.R., E. Yeh, and G. Fu, 1992: An Analysis of GAC

Sampling Algorithms: A Case Study. NASA Tech. Memo.

104566, Vol. 4, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 22 pp., plus color plates.

Vol. 5

Mueller, J.L., and R.W. Austin, 1992: Ocean Optics Protocols

for SeaWiFS Validation. NASA Tech. Memo. 104566, Vol.

5, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 43 pp.

Vol. 6

Firestone, E.R., and S.B. Hooker, 1992: SeaWiFS Technical

Report Series Summary Index: Volumes 1–5. NASA Tech.

Memo. 104566, Vol. 6, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 9 pp.

Vol. 7

Darzi, M., 1992: Cloud Screening for Polar Orbiting Visible

and IR Satellite Sensors. NASA Tech. Memo. 104566, Vol.

7, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 7 pp.

Vol. 8

Hooker, S.B., W.E. Esaias, and L.A. Rexrode, 1993: Proceedings of the First SeaWiFS Science Team Meeting. NASA

Tech. Memo. 104566, Vol. 8, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 61 pp.

Vol. 9

Gregg, W.W., F.C. Chen, A.L. Mezaache, J.D. Chen, J.A.

Whiting, 1993: The Simulated SeaWiFS Data Set, Version 1. NASA Tech. Memo. 104566, Vol. 9, S.B. Hooker,

E.R. Firestone, and A.W. Indest, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 17 pp.

Vol. 10

Woodward, R.H., R.A. Barnes, C.R. McClain, W.E. Esaias,

W.L. Barnes, and A.T. Mecherikunnel, 1993: Modeling

of the SeaWiFS Solar and Lunar Observations. NASA

Tech. Memo. 104566, Vol. 10, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 26pp.

66
Mueller and Austin

Vol. 11

Patt, F.S., C.M. Hoisington, W.W. Gregg, and P.L. Coronado,

1993: Analysis of Selected Orbit Propagation Models for

the SeaWiFS Mission. NASA Tech. Memo. 104566, Vol.

11, S.B. Hooker, E.R. Firestone, and A.W. Indest, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16pp.

Vol. 12

Firestone, E.R., and S.B. Hooker, 1993: SeaWiFS Technical Report Series Summary Index: Volumes 1–11. NASA Tech.

Memo. 104566, Vol. 12, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 28 pp.

Vol. 13

McClain, C.R., K.R. Arrigo, J. Comiso, R. Fraser, M. Darzi,

J.K. Firestone, B. Schieber, E-n. Yeh, and C.W. Sullivan, 1994: Case Studies for SeaWiFS Calibration and Validation, Part 1. NASA Tech. Memo. 104566, Vol. 13,

S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 52 pp., plus

color plates.

Vol. 14

Mueller, J.L., 1993: The First SeaWiFS Intercalibration RoundRobin Experiment, SIRREX-1, July 1992. NASA Tech.

Memo. 104566, Vol. 14, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 60 pp.

Vol. 15

Gregg, W.W., F.S. Patt, and R.H. Woodward, 1994: The Simulated SeaWiFS Data Set, Version 2. NASA Tech. Memo.

104566, Vol. 15, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 42 pp., plus color plates.

Vol. 16

Mueller, J.L., B.C. Johnson, C.L. Cromer, J.W. Cooper, J.T.

McLean, S.B. Hooker, and T.L. Westphal, 1994: The Second SeaWiFS Intercalibration Round-Robin Experiment,

SIRREX-2, June 1993. NASA Tech. Memo. 104566, Vol.

16, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 121 pp.

Vol. 17

Abbott, M.R., O.B. Brown, H.R. Gordon, K.L. Carder, R.E.

Evans, F.E. Muller-Karger, and W.E. Esaias, 1994: Ocean

Color in the 21st Century: A Strategy for a 20 -Year Time

Series. NASA Tech. Memo. 104566, Vol. 17, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 20 pp.

Vol. 18

Firestone, E.R., and S.B. Hooker, 1994: SeaWiFS Technical Report Series Summary Index: Volumes 1–17. NASA Tech.

Memo. 104566, Vol. 18, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 47 pp.

Vol. 19

McClain, C.R., R.S. Fraser, J.T. McLean, M. Darzi, J.K. Firestone, F.S. Patt, B.D. Schieber, R.H. Woodward, E-n. Yeh,

S. Mattoo, S.F. Biggar, P.N. Slater, K.J. Thome, A.W.

Holmes, R.A. Barnes, and K.J. Voss, 1994: Case Studies

for SeaWiFS Calibration and Validation, Part 2. NASA

Tech. Memo. 104566, Vol. 19, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 73 pp.

Vol. 20

Hooker, S.B., C.R. McClain, J.K. Firestone, T.L. Westphal,

E-n. Yeh, and Y. Ge, 1994: The SeaWiFS Bio-Optical

Archive and Storage System (SeaBASS), Part 1. NASA

Tech. Memo. 104566, Vol. 20, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 40 pp.

Vol. 21

Acker, J.G., 1994: The Heritage of SeaWiFS: A Retrospective on the CZCS NIMBUS Experiment Team (NET) Program. NASA Tech. Memo. 104566, Vol. 21, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 43 pp.

Vol. 22

Barnes, R.A., W.L. Barnes, W.E. Esaias, and C.R. McClain,

1994: Prelaunch Acceptance Report for the SeaWiFS Radiometer. NASA Tech. Memo. 104566, Vol. 22, S.B. Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 32 pp.

Vol. 23

Barnes, R.A., A.W. Holmes, W.L. Barnes, W.E. Esaias, C.R.

McClain, and T. Svitek, 1994: SeaWiFS Prelaunch Radiometric Calibration and Spectral Characterization. NASA

Tech. Memo. 104566, Vol. 23, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 55 pp.

Vol. 24

Firestone, E.R., and S.B. Hooker, 1995: SeaWiFS Technical Report Series Summary Index: Volumes 1–23. NASA Tech.

Memo. 104566, Vol. 24, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, (in production).

Vol. 25

Mueller, J.L., and R.W. Austin, 1995: Ocean Optics Protocols

for SeaWiFS Validation, Revision 1. NASA Tech. Memo.

104566, Vol. 25, S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 67 pp.

67
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 James L. Mueller and Roswell W. Austin

Laboratory for Hydrospheric Processes

Goddard Space Flight Center 95B00043

Greenbelt, Maryland 20771

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 James L. Mueller and Roswell W. Austin: San Diego State University, San Diego, California; Elaine R. Firestone: General

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13. ABSTRACT (Maximum 200 words)

This report presents protocols for measuring optical properties, and other environmental variables, to validate the radiometric

performance of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and to develop and validate bio-optical algorithms

for use with SeaWiFS data. The protocols are intended to establish foundations for a measurement strategy to verify the

challenging SeaWiFS uncertainty goals of 5% in water-leaving radiances and 35% in chlorophylla concentration. The

protocols first specify the variables which must be measured, and briefly review the rationale for measuring each variable.

Subsequent chapters cover detailed protocols for instrument performance specifications, characterizing and calibrating

instruments, methods of making measurements in the field, and methods of data analysis. These protocols were developed at

a workshop sponsored by the SeaWiFS Project Ofice (SPO) and held at the Naval Postgraduate School in Monterey, California (9--12 April 1991). This report began as the proceedings of the workshop, as interpreted and expanded by the authors and

reviewed by workshop participants and other members of the bio-optical research community. The protocols are an evolving

prescription to allow the research community to approach the unprecedented measurement uncertainties implied by the

SeaWiFS goals; research and development are needed to improve the state-of-the-art in specific areas. These protocols

should be periodically revised to reflect technical advances during the SeaWiFS Project cycle. The present edition (Revision

1) incorporates new protocols in several areas, including expanded protocol descriptions for Case-2 waters and other improvements, as contributed by several members of the SeaWiFS Science Team.

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 SeaWiFS Technical Report Series

Volume 25–Ocean Optics Protocols for SeaWiFS Validation, Revision 1 Code 970.2

 Series Editors: Stanford B. Hooker and Elaine R. Firestone

 Technical Editor: James G. Acker