NASA Technical Memorandum 104566, Vol. 5

SeaWiFS Technical Report Series

Stanford B. Hooker and

Elaine R. Firestone, Editors

Volume 5, Ocean Optics Protocols

for SeaWiFS Validation

James L. Mueller and Roswell W. Austin

July 1992
NASA Technical Memorandum 104566, Vol. 5

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

Volume 5, Ocean Optics Protocols

for SeaWiFS Validation

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

1992
Ocean Optics Protocols for SeaWiFS Validation

Preface

The Nimbus-7 Coastal Zone Color Scanner (CZCS) introduced remotely sensed ocean color 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 mid-1986. At present, therefore, research in these areas

is limited to retrospective, albeit productive, investigations of the CZCS historical database. In late 1993, the

launch of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the next generation ocean color sensor, will

bring to the ocean community a welcomed and improved renewal of ocean color time series observations.

The CZCS experiment was unquestionably a scientific success, but it also taught the participants that the

satisfactory performance of a satellite remote sensing system cannot be taken for granted. Initially, 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% accuracy in water-leaving radiance and 35% accuracy in chlorophyll a concentration are to be met, or

even closely approached. To that end, the National Atmospheric and Space Administration’s (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.

This document reports the protocols agreed to by the participants, as expanded by the authors, in consultation

with the participants and others in the ocean bio-optics community.

The Ocean Optical Protocols for SeaWiFS Validation 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 accurate

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

adhere closely to the protocols.

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. However, protocols in several areas

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 extremely challenging SeaWiFS

accuracy goals, and that the community feels that we can closely approach these standards with a significant but

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

are summarized below.

1. Model sensitivity studies and experimental verifications 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 (sections 4.2.2 and 4.2.3).

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

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Mueller and Austin

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 and 5.1.6). The maximum diameter of a radiometer for which self-shading error can be corrected

to within less than 5% varies with the absorption coefficient and, therefore, as a function of wavelength

and water mass, and of solar zenith angle. For oligotrophic to moderately turbid coastal water

masses, wavelengths less 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.

Furthermore, candidate correction models must be verified experimentally.

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

exclusive use of profiling radiometer configurations which are not in wide use 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 (ROV), 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

we were able to do here because of time constraints (sections 3.3 and 4.3).

7. The accuracies 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 accuracies 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 SeaWiFS validation. Therefore,

a significant effort to carefully characterize the effect, and to work with instrument manufacturers to

approach or achieve the specified accuracies, 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 develop detailed procedures for

their use in the field.

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. New moored and drifting optical systems are currently being developed and tested, in

preparation for applications to SeaWiFS validation. As results from these efforts become available,

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

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

the workshop participants, and of many others who participated in the review process. The final document has,

by necessity however, been interpreted and written by us and we accept full responsibility for any remaining

mistakes and misrepresentations. As can be readily deduced from the above list of critically needed improvements, this document represents only a first attempt to establish protocols for ocean optical measurements. It

will be appropriate to develop and issue a revised set of protocols, reflecting our collective experience in prelaunch algorithm development activity, approximately 18 months from now, just prior to the scheduled SeaWiFS

launch.

San Diego, California — J. L. M. and R. W. A.

March 1992

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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 accuracy 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 review rationale. 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 Office (SPO) and

held at the Naval Postgraduate School in Monterey, California (9–12 April, 1991). This report is the proceedings

of that 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 a first prescription to approach unprecedented

measurement accuracies implied by the SeaWiFS goals, and research and development are needed to improve

the state-of-the-art in specific areas. The protocols should be periodically revised to reflect technical advances

during the SeaWiFS Project cycle.

1. INTRODUCTION

The National Aeronautics and Space Administration’s

(NASA) SeaWiFS Prelaunch Science Working Group (SPSWG) has recommended baseline satellite ocean color products consisting of normalized water-leaving radiance (LWN )

at five wavelengths, aerosol radiance at three wavelengths,

chlorophyll a concentration, chlorophyll-like pigment (chlorophyll a plus phaeopigments a) concentration, the diffuse

attenuation coefficient at 490 nm, K(490), and calibrated

radiances observed at the satellite. The primary SPSWG

goals for product accuracy are derived water-leaving radiances to within 5% and chlorophyll a concentration to

within 35% in Case 1 waters, both globally and throughout a five-year mission. These goals have been accepted

by NASA, who has the responsibility to lead a product

assurance, calibration, and validation program which will

determine how well the commercially procured ocean color

data fulfills the contractually stated NASA requirements.

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

needed to develop bio-optical algorithms and validate the

SeaWiFS calibration. The observations and data will accrue over several years from a variety of sources, using different instruments and techniques. To be useful, the data

must be internally consistent, of known and documented

accuracy, and in a form readily accessible form.

Aworkshop was conducted to draft protocols, standards, and sampling strategies for optical measurements to

be used for SeaWiFS algorithm development and system

validation. Also addressed were procedures for obtaining

biogeochemical observations to validate chlorophyll a concentrations derived from SeaWiFS data. The findings and

recommendations of that workshop are presented here. Although immediate concerns have focused this document

on preparations for the SeaWiFS mission, the capabilities

of the Japanese Ocean Color Temperature Sensor (OCTS),

Moderate Resolution Imaging Spectrometer (MODIS),

Medium Resolution Imaging Spectrometer (MERIS), the

German Reflecting Optics System Imaging Spectrometer

(ROSIS), and other potential ocean color sensors are also

recognized, with the intent of developing databases that

are relevant to longer term future needs.

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

optical measurements that will define:

1. The required and useful optical parameters for

validation of SeaWiFS normalized water-leaving

radiances and atmospheric correction algorithms,

and for monitoring the satellite sensor’s calibration and stability.

2. The measurement requirements and standards,

including definitions of quantities, wavelengths,

sensitivity, accuracy and stability, field-of-view

(FOV) and band specifications.

3. The instrument characterization, intercalibration,

and related protocols, including:

a) laboratory calibration and characterization

measurements, accuracies and procedures to be

applied to instruments used in SeaWiFS validation and algorithm development activities;

b) pre- and post-deployment measurements and

procedures for moored instruments; and

c) procedures for instrument calibration and characterization, and requirements for record keeping and traceability, including intercalibrations

of radiometric and optical standards between

participating laboratories.

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Ocean Optics Protocols for SeaWiFS Validation

4. The at-sea optical sampling strategy and protocols, including such considerations as:

a) the rationale and justifications for moored,

underway, drifting, shipboard, and airborne measurements;

b) depth resolution in optical profiles, total sampling depths, and ship shadow avoidance; and

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

5. The analysis approaches to be used, including

the procedures and methodologies recommended

for generating variables from the in situ observations, e.g., LWN (z) from Lu(z), K(z), remote

sensing reflectance, etc., and error analysis.

6. The protocols for obtaining ancillary measurements, data archiving, database population, and

access to data.

7. The atmospheric measurements and the degree

to which standard methodologies are available.

Development and validation of bio-optical algorithms

for SeaWiFS will be addressed by a separate working group,

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, including:

1. Discrete chlorophyll a and pigment concentrations will be measured using the U.S. 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

JGOFS Core Measurement Protocols, Chapter

9, “Pigments and Chlorophyll.”

2. The roles of underway, moored, and discrete chlorophyll a fluorescence, and its calibration for satellite data product validation.

3. Other biogeochemical measurements, e.g., coccoliths, suspended sediment, colored dissolved

organic material (CDOM), needed for the baseline products and the extent to which standards

and protocols have been defined for them.

This report is complementary to anticipated reports of U.S.

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

1.1 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 the 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’s (NOAA) Advanced Very High Resolution

Radiometer (AVHRR) (Brown and Evans 1985, 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, pigment concentrations less than 0.25 mg m−3,

(Gordon and Clark 1981), Evans (unpub.) was able to develop a vicarious calibration that was used in the global

processing of the entire CZCS data set (Esaias et al. 1986,

Feldman et al. 1989). However, the approach requires assumptions that may limit the scientific utility of ocean

color imagery. Specifically, the normalized clear waterleaving 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 operation

on the calibration could not be performed.

Unlike the 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 prelaunch and 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

water-leaving radiances and other related quantities, from

ships, drifting buoys, and fixed moorings, to develop time

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Mueller and Austin

series and geographically diverse samples of oceanic and

atmospheric data sets. Each approach has advantages and

disadvantages, but when combined, 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.

1.2 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, K490, 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, K490, 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 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 colored dissolved organic material 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 low confidence 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. Therefore, the radiometric,

optical, and chemical field observations used in deriving

the bio-optical algorithms and for the satellite vicarious

calibration must conform to stringent requirements with

respect to instrument calibration and characterization, and

to observation protocols 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.

1.3 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. Aminimal subset of

these observations will be sponsored by the SPO, but many

projects sponsored by NASA’s Research and Application

Program and other agencies are expected to make major

contributions to the global five-year effort. This requires

close coordination of these programs and a clear definition of the observations, accuracies, and data collection

protocols that are required for each type of activity. The

purpose of this document is to clarify these requirements.

1.4 Vicarious Calibration

For ocean observations, it is easy to show (Gordon

1987 and 1988) that satellite sensor calibration requirements based on the quality of the existing CZCS pigment

algorithms exceed currently available capabilities. In addition, 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 fine

tuned until the best agreement was obtained between the

retrieved and true pigments.

The CZCS vicarious calibration was not radiometric.

Rather, 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, the wind speed, and the ozone optical thickness.

3
Ocean Optics Protocols for SeaWiFS Validation

These data for vicarious calibration and validation are to

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 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. This exercise is 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.

2. DATA REQUIREMENTS

The prime objective of in-water optical measurements

for SeaWiFS is to derive accurate normalized water-leaving

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.

The required and useful variables to be measured for

SeaWiFS validation are listed in Table 1 for radiometric

initialization and ongoing validation, and for bio-optical

algorithm development and validation.

2.1 Initialization and Calibration

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

radiance Lu(z, λ) are the fundamental measurables 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 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 remote

sensing reflectance RL(z, λ), which is used to normalize

Lu(z, λ) when developing and validating bio-optical 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 to normalized water-leaving radiance LWN (λ) that

will be measured under the restricted illumination and

viewing conditions which are 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 few optical depths and reconciled with 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 normalized waterleaving radiance, LWN (λ), for a clear-sky zenith sun at

mean Earth-sun distance. Unfortunately, it is not practical to measure Lu(0−, λ) precisely at an infinitesimal depth

below the surface. Therefore, the profile of Lu(z, λ) must

be measured over the upper few optical 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 wavelengths, the first optical depth is confined to the upper few

tens 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, 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; however, for the latter application it need only be estimated by occulting the

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

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Mueller and Austin

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, KE(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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Ocean Optics Protocols for SeaWiFS Validation

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 inherent optical properties and biogeochemical substances, e.g., chlorophyll a and colored dissolved organic material, 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 SLu because there exist

both empirical and theoretical relationships between inherent optical properties, phytoplankton pigments, total

suspended matter, and irradiance reflectance. Lu(0−, λ)

and Eu(0−, λ) are related by the factor Q(λ), which is not

well determined at present. 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.

Inherent optical properties, including spectral volume

absorption, spectral beam attenuation, spectral backscattering, and integral moments of the volume scattering function will be useful, but not required, aids to relating normalized water-leaving radiances to chlorophyll a and other

bio-optical variables. Eventually, a sufficiently complete

description of inherent optical properties may provide a

set of physically based bio-optical algorithms and models

of water-leaving radiance. In particular, measurements of

inherent optical properties may be valuable in modeling

upwelled radiance spectra at near-infrared wavelengths,

where the remote sensing optical depth is confined to the

upper few tens of centimeters, a region where direct measurements of Lu(0−, λ) are especially difficult.

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, only

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 Properties

Pigment concentrations will be determined, using the

HPLC method and standards adopted by the JGOFS program, to develop and validate chlorophyll a algorithms and

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 for SeaWiFS, the classical technique is

still required to allow the CZCS and SeaWiFS data sets

and algorithms to be compared.

Phycobilipigments, common in some cyanobacteria and

prymnesiophytes, are treated separately from the HPLC

fat soluble pigments. 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. Phycobilipigment species at times, account for

a major fraction of the primary productivity, especially at

high latitudes and 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, but they

are desirable, since several aircraft sensors do, e.g., the Airborne Visible /Infrared Imaging Spectrometer (AVIRIS),

Airborne Oceanographic Lidar (AOL), the Multispectral

6
Mueller and Austin

Airborne Radiometer System (MARS), and future satellite sensors, e.g., the Moderate Resolution Imaging Spectrometer (MODIS) and the Medium Resolution Imaging

Spectrometer (MERIS).

Total suspended material (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 accuracies 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 particulate organic carbon (POC)

and particulate organic nitrogen (PON), are required for

process studies to help characterize the adaptive state of

phytoplankton and to inventory critical biogeochemical elements.

Dissolved organic carbon (DOC) has been shown to be

a major pool of carbon in the oceans due, in part, to improvements in measuring techniques. 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 water-leaving radiances, and it must be taken into

consideration for pigment concentration algorithms. DOC

measurements are needed to develop robust relationships

between CDOM and DOC, 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, the number density of small

plates of calcium carbonate, which are produced in copious

amounts by marine phytoplankton called coccolithophores,

is very important to light scattering. Scattering 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 calcium carbonate concentration, to aid in 1) the correction of chlorophyll a concentration algorithms, 2) coccolith algorithm development, and

3) atmospheric correction development and validation.

Particle absorption coefficient, 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 absorption coefficient, that is, 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 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, derived for particle scattering to

fluorescence ratios using laser sources on single cell flow

systems, is also very useful for evaluating the population

structure of the plankton.

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. However, this information 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, 14C, is not strictly required for

validation of 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. However, it will 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 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 Airborne Spectral Radiometry

Radiance measurements from aircraft can augment inwater measurements of Lu(z, λ), made to compare directly

with SeaWiFS measurements for validation of its radiometric performance and algorithms. Radiance measurements from aircraft can, if they are accurately made, contribute an additional useful constraint in defining internally consistent sun-ocean-atmosphere-sensor models that

will comprise the essence of SeaWiFS radiometric valida7
Ocean Optics Protocols for SeaWiFS Validation

tion. For this application, aircraft radiometers must meet

the SeaWiFS specifications for radiometric accuracy, SNR,

spectral resolution at a spatial resolution that will permit direct comparisons with in-water measurements, and

through spatial averaging with SeaWiFS measurements.

Conversely, aircraft 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 Case 2

waters, where variability in ocean optical properties can be

large over mesoscale and smaller distances. Synoptic maps

of ocean color distributions can obviously 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 CDOM, chlorophyll 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.

AT-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 low optical 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), and the SeaWiFS

sensor 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 arises 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 deeper

structure. In many circumstances, subsurface changes may

go undetected without contemporaneous water column profile data from either shipboard or moored sensors. 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) have shown

that episodic wind events, which give rise to coastal upwelling and subsequent phytoplankton production along

the California coast, cause cloudiness that 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 which 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 how valuable in-water optical

measurements would have been to that program.

8
Mueller and Austin

2.6 Drifting Optical 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. There will probably

never be more than a few permanent optical moorings, due

to their high cost, and very few ship measurements can be

obtained on any given day, again due to cost 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, e.g., to study regions with chronically high levels of

aerosols due to dust storms, and to study 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 at Halifax (M.

Lewis) and the NASA/GSFC aim at 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. Therefore, these water-leaving radiance estimates will 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 biofouling 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 accuracy) 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 accuracy 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 accuracy of the instruments will be less than 5%. This is a

possibly pessimistic estimate 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%, they cannot be

used to verify SeaWiFS radiometry within 5%, no matter

how many drifter comparisons are made. Accuracies must

be less than 5% if this technology is to be used. Accuracies

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

and derived products, and for interpolating SeaWiFS data

through periods of extensive cloud cover.

3. SPECIFICATIONS

The measurements of optical properties and other variables described in this report are those necessary for validating data obtained with the SeaWiFS sensor, 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 allow use of instruments that are affordable and either

currently exist, or can be developed without major improvements in today’s state-of-the-art. In a few cases, new

or improved instruments must be developed to realize the

specified performance characteristics.

The data accuracy 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 accuracies thought by the

SPSWG to be sufficient and necessary for this task. The

validation analysis would be significantly degraded should

calibration errors or differences of even a few percent, or

wavelength errors or differences of a few nanometers, occur

in (between) the instruments used to acquire the SeaWiFS

bio-optical database.

9
Ocean Optics Protocols for SeaWiFS Validation

3.1 In-Water Radiometers

3.1.1 Spectral Characteristics

In-water radiometers shall be capable of making measurements at the wavelengths shown in Table 2 as a minimum. 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 (C. 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

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 4121 412

2 433–453 443, 4352 443

3 480–500 490 490

4 500–520 510 510

5 545–565 5503, 5603 5504

6 660–680 665, 683 6654

7 745–785 5 780

8 845–885 5 8756

1. A preferred option is to substitute two separate 10 nm

FWHM bands centered at 406 and 416 nm, for a single 412 nm

channel. The two channels would allow more accurate modeling of LW N (412) matching SeaWiFS characteristics.

2. An optional extra band is used to improve modeling of

LW N radiances to match the SeaWiFS 443 nm channel.

3. The 545–565 nm range is broken into two channels to

detect possible phycoerythrin fluorescence.

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

5. Due to the specialized nature of infrared in-water measurements, specialized sensors will be needed.

6. Optional for Es.

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 vary rapidly

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.

However, when the filter is installed in a radiometer with a

10◦ (half-angle) FOV, 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.

In a single instrument, all channels at a given nominal

wavelength should match within 1 nm, if possible. Therefore, it is desirable to obtain all of the filters used by an

investigator for measurements at any nominal wavelength

λm from a single manufacturing lot when possible. If this is

done, Es(λm), Ed(λm), Eu(λm), Lu(λm), and any atmospheric radiometric quantities measured with that investigator’s systems, would all have greater likelihood of being

measured over the same range of wavelengths, for each

nominal wavelength λm. 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.

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

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.)

10
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 200 200 200 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 80 80 40 Saturation Irradiance (Case 2/coccoliths)

Upwelled 25 15 1 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 16 16 8 Saturation Radiance (Case 2/coccoliths)

Upwelled 5 3 0.2 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.

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 200 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.

3. Aminimum Ed(0) implies a minimum detectable

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

(3/K).

4. Digital resolution must be ≤ 0.5% of reading

to maintain a 100:1 SNR. To permit 1% accuracy in absolute calibration, if that goal can be

met, the instrument must digitally resolve 0.1%

of the irradiance (radiance) produced by laboratory standards; 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,” respectively. An SNR

of 100:1 requires Ed(z) at three optical depths

be resolved to 0.005 μW cm−2 nm−1 per count

or 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 Sub-Working

Group’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 low for 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)

11
Ocean Optics Protocols for SeaWiFS Validation

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

and 40 μW cm−2 nm−1 for λ ≥ 660 nm.

6. The minimum required irradiances at 3 optical

depths (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% accuracy 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 nm) to

minimum expected Lu(665 nm). This situation will require specially designed radiometers in any event (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. Aradiometer 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.

3.1.3 Linearity and Stability

Errors attributable to linearity or stability should be

less than 0.5% of readings over the 104 ranges specified in

Table 4. This is a challenging goal, but one which must be

met if the equally challenging goal of achieving 1% accuracy 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 to within 10 msec at each depth.

The time response of the instrument to a full-scale (saturation to dark) step change in irradiance should be <1 s

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 SNR performance,

provided adequate depth resolution is maintained.

3.1.5 Angular Response Characteristics

The response of a cosine collector to a collimated 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 ∼10◦ (half-angle). The resulting solid angle FOV (∼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 accuracy of

0.5 m and a precision 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 accuracy of ±1◦ in a static mode; it is not intended

that this accuracy 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

Due to the fact that the SeaWiFS red and near infrared channels–bands 6–8 at wavelengths of 665, 780, and

12
Mueller and Austin

865 nm, respectively–have such short attenuation lengths

in water, special attention must be paid to these measurements. Problems due to instrument self-shading (Gordon

and Ding 1991) and very rapid attenuation of Lu(z, λ)

must be considered at these wavelengths. Large instruments, such as the standard Biospherical Instruments, Inc.,

MER packages, 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.

While 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).

3.2 Spectral Surface Irradiance

The 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 view the 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. However, improperly designed

gimbal systems 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 floatation 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 below the surface.

Unfortunately, the community has only very limited experience with this approach for measuring Es(λ) (Waters et

al. 1990) and the 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 (see Table 2). Saturation irradiances are the same as for Ed(λ) (Table 4). The dynamic

operating range for these sensors needs to 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 ≤ 10 ms. 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 specifications 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. Abroad-band, or photosynthetically available

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

purpose.

3.3 Airborne Radiometer Specifications

The performance characteristics to be specified for an

airborne radiometer will vary, depending on how a 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 waterleaving radiance derived from airborne measurements must

have the same accuracy specified for those derived from inwater measurements of Lu(z, λ) (Table 4). Aless accurate

radiometer may be used to semi-quantitatively characterize spatial variability near ship stations.

In general, the spectral characteristics of airborne 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, that

13
Ocean Optics Protocols for SeaWiFS Validation

being, 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 of the SeaWiFS, inwater radiometer, or airborne radiometer measurements of

radiance at each channel’s nominal center wavelength.

Ahigh altitude imaging radiometer must have a radiometric accuracy 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. However,

direct radiometric comparisons between aircraft and SeaWiFS radiances 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 the aircraft

and ship radiometry may require that SNR and accuracies

realized in combined analyses of the two data sets must

represent a smaller spatial resolution than the SeaWiFS

nominal 1 km FOV.

Aradiometer’s sensitivity to the polarization of aperture radiance is critical for ocean color sensing. An airborne ocean color radiometer 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., as in the polarization channels of the

French Polarization Detecting Environmental Radiometer

(POLDER) instrument.

Each application of a particular airborne radiometer

system, which is proposed for SeaWiFS validation, must be

evaluated on its own merits. The instrument’s responsivity, accuracy, 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 signal-to-noise 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. On the other hand, finer resolution aircraft imagery, or 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 radiometry can obviously contribute extremely valuable data for validating SeaWiFS

radiometric performance and algorithms. However, there

is a wide possible range of airborne radiometer characteristics that can be applied to this program, and detailed

specifications 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

can be specified here.

3.4 IOP Instruments

The inherent optical properties (IOP) are the beam attenuation coefficient c(z, λ) (units of m−1), the absorption

coefficient a(z, λ) (units of m−1), and the volume scattering function, b(θ, z, λ0) (units of m−1 sr−1). The integral

of the volume scattering function over 4πsr is the total

scattering coefficient, b(z, λ) (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 have,

at a minimum, 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 accuracy 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, 520,

510 and 670 nm

Bandwidth: 10 nm

Accuracy: 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 accuracy. 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 accuracy of

its determination will be approximately 10%.

The shape of the volume scattering function can, at

14
Mueller and Austin

present, be determined in situ only crudely with devices

like the Alpha and Scattering Meter (ALSCAT) and the

General Angle Scattering Meter (GASM), which were built

more than a decade ago at the Scripps Institute of Oceanography Visibility Laboratory (VISLAB). 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) at the time of deployment

of SeaWiFS, the determination of the shape of the volume

scattering coefficient could possibly be determined with

acceptable accuracy by measuring a few moments of the

scattering function. Anew instrument 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 be in agreement with 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, 520, and 565 nm should be added to the WMO

set.

3.6 Sky Radiance Distribution

Spectral sky radiance distribution measurements 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 accuracy 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 for the JGOFS Core Measurement Protocols, Chapter 9, “Pigment and Chlorophyll.”

In situ chlorophyll fluorometers should have a resolution

of at least 0.001 mg chlorophyll a per m3.

3.8 Hydrographic Profiles

Acalibrated 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. Minimum instrument characteristics for

the measurement of hydrographic profiles.

Parameter Range Accuracy Resolution

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

4. SENSOR CHARACTERIZATION

4.1 Radiometric Characterization

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. Thus, in addition to the

obvious radiometric calibration, it is 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 an instrument to provide suitable data for SPO use,

the investigator must be certain 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, typically

remain constant so it is sufficient to determine them once,

unless instrument modifications are performed. 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.

15
Ocean Optics Protocols for SeaWiFS Validation

Fig. 1. Elements of radiometer characterization and calibration.

Either the sources or the sensors must have known spectral radiometric characteristics 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,

highly regulated power supplies for the operation of the

lamps, and precision electronic measurement capabilities

for setting and monitoring the 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 few centrally 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

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 which will be

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

sensor channel being calibrated; 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 calibrations require a source of uniform known

radiance that will fill the angular field of view of the radiance sensor. Either of two methods may be used:

Method 1: Aworking 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

view the 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

16
Mueller and Austin

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.

Method 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 accuracy.

These methods are discussed more fully in section 4.2.2.

The requirements given above for noting and controlling temperatures and for use of the portable irradiance

and radiance reference standard (section 4.2.5), apply here

as well.

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

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 will usually be 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., HeNe, 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 significantly higher

combined transmission of the three filters 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 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 present.

While leakage of blue light into red channels is the most

significant oceanographic optical problem, the leakage of

red and infrared (IR) light into blue channels can cause

significant errors when the instrument is calibrated using

a red-rich source. Aconvenient 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.

Anon-zero 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.

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Ocean Optics Protocols for SeaWiFS Validation

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.

Astable 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

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

are demonstrated to be uniform throughout the run.

Absolute responsivity calibration is done in air with

light arriving normal to the plane of the collector. To

properly measure all irradiance arriving at the plane of

the collector, the response should follow a cosine function

such that E(θ) = E(0) cos θ, where E(θ) is the indicated

irradiance in response to flux arriving at angle θ with the

normal to the plane of the collector, and E(0) is the irradiance the same flux would produce if it were normal to

the surface. If this requirement is met, then the on-axis

calibration is sufficient and the device will correctly measure the irradiance arriving at the collector regardless of

the direction, or directions, from 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, Tyler and Smith 1979). This

improvement is mostly for near-grazing angles (θ ∼ 90◦ to

the normal) and is particularly important when upwelling

underwater irradiance measurements are made, i.e., with

the collector facing downward. In that case, most of the

light is from the sides, in the region of 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. Adescription 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 allow rotation 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 is required.

Acircular 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 limits.

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 .

18
Mueller and Austin

The asymmetry of the cosine response, δ, is equivalent

to a 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

mechanical axis could be due to:

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 the diffuse plastic material used in most irradiance collectors is submerged in water, the transmission

through the material becomes less than the transmission in

air. As light enters the diffuser a small part is reflected at

the air-plastic or water-plastic interface. The relative size

of this reflectance, called Fresnel reflectance, depends upon

the index of refraction of the medium on either side of the

interface. The change is such that the relative amount of

light which enters through the interface is larger in water

than in air. After entering the plastic diffusing material

some of the light will, due to scattering, arrive back at the

interface where some gets reflected back into the material

and some will exit into the air or water. More of this light

is able to leave the plastic and reenter the external medium

in water than in air. Thus this mechanism decreases the

transmission when the diffusing material is submerged relative to the transmission in air. The net result is a loss

of transmission when the diffusing material is submerged.

Since the instrument is calibrated in air, an error due to

this change in transmission will result when measurements

are made with the instrument submerged, unless a correction is made for this immersion effect.

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.

Atungsten-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. Afinal 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:

a) the attenuation at the air-water interface, which

varies with wavelength,

b) the attenuation over the water path, which varies

with 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), is

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(λ, z) = 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 Eqs. (5) through (8): the

attenuation coefficient of the water K(λ) and the immersion factor Fi(λ). Aminimum 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

19
Ocean Optics Protocols for SeaWiFS Validation

regression is solved for the Fi(λ) and K(λ) terms giving

the best fit. The complete derivation of Eqs. (5) through

(8) is given in Petzold and Austin (1988).

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 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 air-window

interface during calibration and 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 nw(λ) is a function of wavelength 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

window,then, as shown in Austin (1976), the correction for

the change in transmission through the window 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 for a plexiglass window, ng(λ),

may be computed using an emperical fit to the Hartmann

formula, i.e.,

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 emperical fit of the data from Austin

and Halikas (1976),

nw(λ)=1.325147 + 6.6096

λ − 137.1924. (12)

The immersion factor F(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 Accuracy

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, (∼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 below 20–30%

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 raw level-1 data to obtain

calibrated level-2 irradiance and radiance data. Level-1

and level-2 data are defined in section 6.1.

Ancillary sensors, such as, transmissometers, should be

characterized for the linearity and accuracy of the measurement covering the full output range of the sensor. Instruments with manual or automatic range dependent gain

changing should be tested annually (at a minimum) for

scale offset and linearity in each range. Errors exceeding

0.1% of reading over the normal range must be corrected.

Other characteristics of electronic sensor systems may

adversely affect measurement accuracy. 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

temperature range for testing should be extended to -10–

45◦ C. If sensors exhibit temperature coefficients greater

than 0.01% per degree-Centigrade over this temperature

range, they 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, more significant near-surface errors

20
Mueller and Austin

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 Teflon-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 pressuredependent 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; new

protocols 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

4.2.1 LampIrradiance 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 accuracy 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 view the plaque at 45◦ measured from

the axis. The radiance, then, is given by

L(λ) = ρ(λ)E(λ)

π , (14)

where ρ(λ) is the bidirectional reflectance of the plaque for

0◦ incidence and 45◦ viewing, E(λ) is lamp irradiance, and

the total FOV of the instrument being calibrated is filled

by the illuminated plaque.

The known radiance of the plaque provides an accuracy

comparable with that of the irradiance standard lamp, i.e.,

≤ 3%, for calibrating a radiance detector with a very narrow FOV (∼1◦. Large plaques, e.g., 40 cm×40 cm, have

been successfully used to calibrate radiance sensors having

up to 25◦ full-angle FOVs. Intercomparisons of calibrations, made using this technique at different laboratories,

of MER-series radiance sensors (full-angle FOVs ranging

from 20–24◦ in air) have generally agreed within ∼5%.

Abetter approach to calibrating multispectral radiance sensors is to view an integrating sphere that is uniformly illuminated by stable, appropriately baffled lamps,

and which 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.

Method 1: The approach used at NASA/GSFC is

to view the irradiance output of the lamp, initially,

and then the sphere, with a spectrometer equipped

with integrating input optics (McLean and Guenther 1989; Walker, Cromer, and McLean 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.

Method 2: An alternative method is to calibrate

a stable narrow FOV radiometer by viewing the

standard lamp output reflected from a plaque, as

21
Ocean Optics Protocols for SeaWiFS Validation

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. Apromising 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 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 accuracy less than 1%. Acalibration approach

based on such radiometer standards is essential to achieve

1% internal consistency in the radiometric accuracy 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 accuracy of less than 1% with this standard.

Aself-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 calibrating

oceanographic or airborne radiometers using self-calibrating

radiometric standards. Asignificant 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 QED-200

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 accuracy of the calculated radiance. This

frequency must be established through experience, but a

reasonable first guess is that filter transmission functions

should be remeasured every few months.

One SeaWiFS goal is to base radiometric validation on

shipboard, moored, and airborne radiometry with 1% accuracy. 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 aircraft 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 TBD). 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.

4.2.5 Portable Standards

In between radiometric calibrations, stable lamp sources

in rugged, fixed geometric configurations should be 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. However, the temporal record they provide will be invaluable in cases where

the pre- and post-cruise calibrations disagree or if the instrument is disturbed, e.g., opened between calibrations,

or 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

22
Mueller and Austin

Fig. 2. Organizational structure for optical instrumentation characterization and calibration.

protocols must be developed through a series of laboratory

and field tests using candidate equipment and standards.

4.3 Airborne Radiometers

In general, the protocols specified in section 4.1 for

oceanographic radiance sensors are applicable for characterizing and calibrating airborne radiometers. Obvious exceptions are that immersion and underwater FOV characterizations are not appropriate for aircraft sensors.

Polarization sensitivity is more critical in airborne 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 aircraft radiometers,

as with SeaWiFS, sensitivity to linear polarization must be

less than 2%, and the actual degree of polarization sensitivity must be characterized for each channel.

Ageneralized protocol for characterizing a radiometer’s polarization sensitivity is given here. The instrument

should view a 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

instrument’s polarization sensitivity will be calculated as

P(λ) =
















2



L1(λ) − L2(λ)



L1(λ) + L2(λ)
















. (15)

As required for the SeaWiFS sensor, airborne radiometers

must satisfy P(λ) < 0.02.

Avery 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

23
Ocean Optics Protocols for SeaWiFS Validation

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 accuracy 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 measurements in air with a

subsequent adjustment for changes in the Fresnel reflections of the windows upon submergence into water. The

660 nm transmissometers produced by Sea Tech are independently calibrated at the factory against particle-free

water of measured transmittance, after which calibration

is maintained via frequent air calibrations. This approach

is adequate until a pure water standard, using water generated by reverse osmosis, has been developed and proven

reliable for shipboard use. It is anticipated that the pure

water standard will be proven by the time of the SeaWiFS

deployment. The pure water standard will be particularly

useful for pump-through devices, such as the spectral absorption and attenuation devices now being developed, as

they can be connected to the pure water system after each

cast to provide frequent calibration, and make it possible

to closely track any deterioration of the instruments. Daily

air calibrations of systems without pumps are desired.

Calibration of the scattering devices must be handled

on a case-by-case basis and calibration standards need to

be developed along with the instruments.

4.5 Calibration of 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.

Therefore, these Langley calibrations 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 (Shaw 1976).

Temperature stability should be characterized for each

instrument. Linearity and spectral calibrations should be

performed with the same frequency as the absolute calibration; this work must be performed in the laboratory.

4.6 Radiance Distribution Cameras

Absolute and spectral calibrations should be performed

on the radiance distribution camera before and after each

cruise. Afull 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 U.S. JGOFS Program

(JGOFS 1991). Bench fluorometers used to measure concentrations of extracted chlorophyll a and phaeopigments

should be calibrated using authenticated standard chlorophyll a adopted for HPLC (JGOFS 1991). In situ chlorophyll 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 re-calibrated 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.

24
Mueller and Austin

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.

5. MEASUREMENT PROTOCOLS

5.1 Spectral Irradiance and Radiance

Determinations of Ed, Eu, and Lu, both near the surface and as profiles, are required for calibration and validation of the satellite sensed water-leaving radiances. Nearsurface measurements through at least the top three optical depths are needed to reliably extrapolate to z = 0;

a profile through at least the top optical depth is essential. To better characterize the water column for remote

sensing applications, e.g., primary productivity estimation,

deeper 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 shallow situations where

bottom reflectance is present are not within the scope of

these protocols.

Two primary sources of error in the determination of

these optical parameters are the perturbation of the inwater radiance field by the ship (Gordon 1985; Smith and

Baker 1986; Voss et al. 1986; Helliwell et al. 1990), and

atmospherically induced variability in radiance incident on

the sea surface during in-water measurements (Smith and

Baker 1984). The influence of ship shadow on profiles of

the Ed, Eu, and Lu is dependent upon: solar zenith angle,

the spectral attenuation properties of the water column,

cloud cover, ship color and size (length, beam, draft, and

freeboard), and instrument deployment geometry. Atmospheric variability depends primarily upon sun elevation

and cloud cover. The near surface in-water 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 profiles when

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), at longer wavelengths,

contributions from phycoerythrum and chlorophyll a fluorescence and water Raman scattering are significant.

5.1.1 ShipShadow 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

shadow is best characterized in terms of attenuation length

1/Kd(λ) (Gordon 1985). Because LW is required with an

accuracy of 5% or better, the protocol requires that vertical profiles collect data 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,

expressed in attenuation lengths to minimize error, under

conditions of clear sunny skies, are given below. 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

distances should be increased if the instrument is deployed

off the beam of a large vessel.

Avariety 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 to obtain near surface optical

profiles 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 which

has the advantage of allowing relatively rapid deployment

and simultaneous rosette bottle sampling. As a point of

caution, however, 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 a remotely operated vehicle (ROV). Smith et al. (R.

Smith, pers. comm.) have deployed a spectrometer on an

ROV and obtained data completely free of ship influences.

The above criteria for ship shadow avoidance are admittedly very conservative. Unfortunately, the above cited

models and observations provide only approximate guidance on minimum distances at which ship reflectance and

shadow effects 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 his measurements of Ed, Eu, and Lu submitted for SeaWiFS validation and algorithm development are

25
Ocean Optics Protocols for SeaWiFS Validation

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 upon 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 IR spectral regions, care must be taken to consider

possible perturbation of the radiance field by the instrument package. Methods of accounting for self-shadowing

by the instrument are not well established and new measurement 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 water should

yield at least 2 and preferably 6–8 samples per meter.

5.1.3 Instrument Dark Readings

The dark current of optical sensors is frequently temperature dependent. Consequently, accurate radiometric

measurements require careful attention be given to dark

current variability. It is recommended that each optical

measurement be accompanied by a dark current measurement. 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. However, many instruments 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 below the 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. However, improper gimballing can actually accentuate sensor

motion under some circumstances, and this aspect of a

shipboard radiometer system must be engineered with care.

Waters et al. (1990) demonstrated a method to more directly determine Ed(0−, λ) by deploying an Optical Surface

Floating Instrument (OSFI) to obtain continuous optical

data just below the 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 series of profiles. Research is needed to determine whether this should be the preferred approach for

SeaWiFS validation measurements.

5.1.5 Instrument Attitude

An instrument’s vertical attitude is a critical factor in

measurements of Ed(z, λ) and Eu(z, λ) and is only slightly

less so for Lu(z, λ). Therefore, roll and pitch sensors must

be installed in the underwater radiometers used for the

SeaWiFS project. The data from the attitude sensors are

to be recorded concurrently with the radiometric data 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 shallow depths.

5.1.6 Instrument Self-Shading

Gordon and Ding (1991) modeled the errors introduced

by an instrument’s own shadow in direct measurements of

Lu(λ) and Eu(λ). For this 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 ≤ 5% error; the

instrument radius must be significantly smaller for direct

measurement error in Lu(865) to be ≤ 5%.

Gordon and Ding (1991) also propose a simple model

for correcting Lu(λ) and Eu(λ) for self-shadowing. 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

26
Mueller and Austin

an empirical factor for which they give values determined

by fitting their model results (y ∼ 2). Asimilar correction,

with a different table of values for y applies to Eu(λ).

When the above geometric corrections are applied, Gordon and Ding (1991) estimate errors ≤ 5% in Lu(λ) could

be determined from measurements with instruments having diameters ≤ 24 cm for λ ≤ 650 nm, and with instruments of diameter ≤ 10 cm for 650 < λ ≤ 700 nm at

solar zenith angles θ0 ≥ 20◦ and chlorophyll concentrations ≤ 10 mg m−3. To measure Lu(λ) correctable to less

than 5% error at θ0 = 10◦ (chlorophyll concentrations

≤ 10 mg m−3), instrument diameters must be ≤ 12 cm for

λ ≤ 650 nm and ≤ 5 cm for 650 < λ ≤ 700 nm. Even with

these corrections, however, instrument diameters ≤ 1 cm

must be used to assure self-shading Lu(λ) errors ≤ 5% at

780 and 875 nm.

Experimental tests are needed to confirm the accuracy

in Lu(λ) and Eu(λ), which can be obtained using corrections of the form proposed by Gordon and Ding (1992).

These experiments should be carried to completion prior

to SeaWiFS launch. In the interim, until confirming experimental results are available for fine tuning, corrections

should be made using the coefficients and procedures recommended by Gordon and Ding (1991) on the basis of

their Monte Carlo simulations.

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) 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 analysis 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, and finally rinsed with isopropyl alcohol and wiped dry. An approximate air calibration reading should be made before

every cast to verify the windows are clean. Atransmissometer dark voltage should also be measured at this time.

These on-deck 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 (J.R.

Zaneveld, pers. comm.). Avery careful air calibration

shall 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

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 of the form

V = a(T) + b(T)V ,  (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 accuracies of 0.1% transmittance per meter, or

0.001 m−1 beam attenuation coefficient c(λ). These accuracies may be achieved using new calibration techniques,

which include a clean-water standard such as a continuous

flow of reverse osmosis water, but methods and protocols

suitable for use at sea are presently under study (J.R. Zaneveld, pers. comm.).

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,

27
Ocean Optics Protocols for SeaWiFS Validation

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, fluorescence measurements should be compared to HPLC and extracted pigment measurements from discrete water samples, for comparison with JGOFS standard measurements and historical databases. In situ fluorescence measurements will be

used to provide continuous vertical profiles of interpolated

pigment concentration using 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. Areal 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 few deep (≥ 1500 m) 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.

5.3 Atmospheric Measurements

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 contemporaneously. 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, rarely are the atmospheric conditions 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 no clouds, including high cirrus, obstruct the solar

disc. Careful documentation of sky conditions are important, as are accurate recordings of time of day and station

location. 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 (stack gas) from interfering

with the measurements. Ancillary measurements such as

barometric pressure are important in separating Rayleigh

scattering from the aerosol scattering.

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 the FOV be as unobstructed as possible. While

it would be optimum to have a completely unobstructed

FOV, this is often not practical. Therefore, during measurements, at least one hemisphere, defined by the sunzenith plane, should be unobstructed; through symmetry,

this should yield a complete radiance distribution.

Ship perturbations must be avoided. 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 (1989) rigorously demonstrated the importance of determining μd, the mean cosine

for downwelling radiance (Morel and Smith 1982), for the

bio-optical interpretation of Kd(λ, z). Gordon (1989) also

showed for cloud-free skies how a reasonable estimate of

μd(0+) can be obtained from spectral irradiance deck cell

measurements with and without the sun blocked from the

irradiance collector’s view. 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+, z). Radiance distribution cameras are ex28
Mueller and Austin

pensive to build, however, and one is not likely to be available aboard every SeaWiFS validation vessel. Arecommended 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 1989).

During the prelaunch experiments, μd(0+, λ) estimated

from measurements of these types should be compared

with μd(0+, λ) 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 high accuracy determinations of chlorophylls a, b,

and c, as well as carotenoid pigments, it is recommended

that HPLC techniques be used (Mantoura and Llewellyn

1985, Gieskes and Kraay 1986). The 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:

1) pre-filtering to remove large zooplankton and

particles,

2) use of Whatman glass fiber filters (GFF) (approximately 0.7 μm pore size),

3) extraction in 90% acetone, and

4) calibration with authenticated standards.

In addition to HPLC analyses, it is also recommended

that the standard fluorometric method (Yentsch and Menzel 1963, Holm-Hansen et al. 1965, and Strickland and Parson 1972) for measuring chlorophylls and phaeopigments

also be applied to the same extracted pigment samples

(section 6.5.2) used for HPLC analysis. This additional

analysis by the standard fluorometric method will enable

a direct link to the historical bio-optical algorithms and

database developed during the CZCS validation experiments.

5.4.2 CDOM and DOC

The measurement of the absorption coefficient due to

dissolved organic matter (DOM) should follow the general

procedures prescribed in Bricaud et al. (1981). In addition, it is important to remove particles down to 0.2 μm

using, e.g., 0.2 μm Nuclepore or aluminum oxide filters, to

minimize scattering contributions to the quasi-diffuse attenuation measurements made by typical spectrophotometers, especially for ultraviolet spectra; laboratory work is

needed in this area to verify that commercially available

0.2 μm filters do not leach organics into the sample.

Spectrophotometric measurements should be made immediately if possible. If they cannot be performed immediately after sample collection, intermediate storage of the

filtrate as frozen samples in dark, clean, glass bottles is permissible in current practice. However, the effects of storing

frozen samples before DOM and DOC analyses are not yet

documented in the literature, and laboratory tests should

be carried out before such data are used in SeaWiFS algorithm development. Nevertheless, the DOM and DOC

data from such samples will be valuable, even if they are

only qualitative. Spectrophotometry should be performed

with a double-beam instrument using a 10 cm or longer cuvette, with monochromatic light to minimize fluorescence

effects. Scans should be made on multiple replicates from

300–800 nm to minimize photobleaching.

For waters with low values of absorption coefficient due

to DOM, logarithmic extrapolation from UV wavelengths

into the visible may be required. The spectral slope needed

for these extrapolations is dependent on both the spectral region in question and the humic/fulvic acid fraction

(Carder et al. 1989). Concentrations of marine humus can

be eluted onto XAD-3 resin columns, or equivalent, using methanol concentrated by evaporation, diluted (10:1)

in deionized water buffered to pH 8.3, and measured spectrophotometrically, which is a procedure similar to that

of Carder et al. (1989), except for separation and drying into the humic and fulvic acid fractions. The retention factor for the columns can be examined by comparing

29
Ocean Optics Protocols for SeaWiFS Validation

the absorption coefficients in the 300–370 nm region. This

method of concentrating CDOM to measure absorption in

the visible can be accomplished using small resin volumes

(< 50 ml). Data should be log-transformed and smoothed

with a multiple-point (< 20 nm range) running average and

reported for at least the following wavelengths: 300, 320,

340, 370, 400, 450, 490, and 520 nm.

5.4.3 Absorption by Particles

The absorption spectrum of suspended particles should

be determined at sea using GFF and a dual-beam spectrophotometer. Aknown volume of water is filtered, and

the combined transmission spectrum of the wetted filter

and particulates is measured with the spectrophotometer. Empirically derived algorithms are then used to calculate the absorption spectrum of the particles in suspension

from the transmission spectrum of the filter plus particles

(Mitchell and Kiefer 1984).

An aliquot (1–2 liters) of seawater sample is filtered

through a Whatman GFF (24 or 25 cm diameter, effective

pore size 0.7 μm) at low vacuum. Pre-filtered seawater,

using a Millipore GS filter with 0.22 μm pore diameter,

is filtered again through a second GFF filter, and this

wetted filter is used as a blank. Thorough saturation of

both filters is necessary (Mitchell and Kiefer 1988). Filters are affixed, sample side up, to a quartz slide with a

drop of pre-filtered seawater. The sample-side of the filter should face the spectrophotometer’s light source, with

the glass facing the detector. Spectra should be measured

as soon as possible, because pigment decomposition may

occur (Stramski 1990). Optical density spectra, ODfilt(λ)

(which are dimensionless), are scanned from 760 to 390 nm

and to 350 nm if possible. Values of ODfilt(λ) greater than

0.4 should be avoided because algorithms correcting for

multiple scattering in the filter have been limited to this

range (Mitchell 1990). Optical density of the particles in

suspension, ODsusp(λ), is calculated from ODfilt(λ) using

an algorithm of the form suggested by Mitchell (1990)

ODsusp(λ) = C1ODfilt(λ) + C2



ODfilt(λ)

2

. (20)

Previously determined coefficients C1 [0.396 (J. Cleveland,

pers. comm.) and 0.392 (Mitchell 1990)] and C2 [0.496 (J.

Cleveland, pers. comm.) and 0.665 (Mitchell 1990)] are in

general agreement.

Particulate absorption coefficient spectra, ap(λ) (units

of m−1), are then calculated from optical density spectra

as

ap(λ) = 2.3

X



ODsusp(λ) − ODsusp(750)

, (21)

where X, is the volume of water filtered divided by the

clearance area of the filter (Mitchell 1990). Ongoing investigations are evaluating uncertainties involved in this

methology, including non-zero absorption at 750 nm, variability between filter lots, and differences between filter

types (G. Mitchell and J. Cleveland, pers. comm.).

5.4.4 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 specified in the JGOFS

protocols (JGOFS 1991). In general, samples are filtered

through 0.4 μm preweighed polycarbonate filters, washed

with three 2.5–5.0 ml aliquots of distilled water and immediately dried, either in an oven at 75◦ C, or in a dessicator.

The filters are then reweighed in a laboratory ashore, on

an electrobalance with seven-place precision.

5.5 Ancillary Observations

Ancillary observations are often important in flagging

and interpreting apparently aberrant data. The minimal

set of ancillary supporting observations must include:

1) date and time [Greenwich Mean Time (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 (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 white caps;

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) for radiometric stations, an all-sky photograph

and a photographed time history of sea surface

is advised; and

b) Secchi depth.

5.6 Moorings

5.6.1 Prototype Optical Buoy System

Aprototype 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

30
Mueller and Austin

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 with a

dichroic water mirror in order to 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. Afurther 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 fiberoptics. Data will be compressed, stored,

and forwarded through a NOAA/Geosynchronous Orbital

Environmental Satellite (GOES) and an ARGOS telemetry link.

This type of optical mooring represents a new and 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. Current practice is

to apply OMP-8, or similar compounds, to prevent 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 Drifting Optical 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. How accurately 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% accuracy feasible?

2. How accurately can LWN (λ1):LWN (λ2) ratios

be estimated with these instruments using only

a single channel Ed(λ) measurement for normalization? (Which is contemplated for both

instruments currently being developed, as described in section 2.6.) Are the LWN 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 Sampling and Bio-optical Validation

Spatial and temporal variability in bio-optical 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

larger off nadir viewing angles. Furthermore, the location

accuracy of a single pixel may be several kilometers, except in near-shore areas where image navigation can be improved by using land-navigated 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.

5.8.1 Initialization and Sampling

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

31
Ocean Optics Protocols for SeaWiFS Validation

to be very small. This will ordinarily dictate that such

data be acquired from optically clear, persistently oligotrophic 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, to maximize the likelihood of simultaneous SeaWiFS

and shipboard observations. An 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.

Another set of radiometric comparisons between surface or near surface, and SeaWiFS measurements, should

be made to detect any thermally induced perturbations in

responsivity of the SeaWiFS channels. 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

shadow throughout 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 spectral bandpass and responsivity

of one or more SeaWiFS channels.

Aseries 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. 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 bio-optical algorithms (section 5.8.2), a significant effort must be exerted to quantify spatial variability

in normalized water-leaving radiance. 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.

5.8.2 Validation Sampling

For SeaWiFS algorithm development and validation,

measurements must be made in Case 1 and 2 water masses

spanning wide ranges of optical properties and phytoplankton pigment concentration. In optically transparent, low

chlorophyll, oligotrophic water masses, spatial variability is

usually small and a station location and sampling strategy

much like that discussed above for SeaWiFS radiometric

validation is appropriate.

In turbid, high chlorophyll, eutrophic water masses,

mesoscale and smaller scale variability is often significant.

In very productive Case 1 water masses, station placement

and other aspects of sampling schemes are identical with

those for Case 2 water masses (below). 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 separating 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 be essential, although such additional information will be very helpful.

At stations where data are acquired for algorithm validation, and where a match to contemporaneous SeaWiFS

measurements is required, it will be necessary to determine

the patterns of spatial variability over a domain extending

approximately 20 km ×20 km centered at the station, and

to center the ship in a 2 km ×2 km domain over which

K490 and chlorophyll concentration vary < 35% about the

mean. 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 for providing a basis for spatially extrapolating the in-water measurements to match

the much coarser resolution of the SeaWiFS measurements.

Although coastal and continental shelf areas comprise

only 10% of the total ocean area, they provide roughly half

of the oceanic new production and most of the sequesterable DOC (Walsh et al. 1991). These areas are typically

higher in phytoplankton pigment concentration and may

include colored terrigenous constituents such as DOM and

suspended sediments (Morel Case 2 waters). Precise locations where offshore Case 1 waters merge into Case 2

waters can neither be determined a priori, or from spacederived data alone. To rectify this uncertainty and to obtain data to develop Case 2 algorithms for chlorophyll a

and DOC, new protocols for sampling such waters need to

be established.

To achieve valid comparisons between the ship and satellite, sharp horizontal gradients and sub-pixel patchiness

must be avoided, and image navigation must have land

anchor points near the study site. Measurements used to

calculate normalized water-leaving radiance must be made

under cloud-free conditions and within five minutes of the

satellite overpass. These 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. To improve the chances of achieving this criterion, attempts should be made well before the overpass to

place the ship away from fronts and sharp gradients.

Accurate aircraft ocean color radiometry can be especially valuable for SeaWiFS algorithm validation in Case

2 waters. High altitude, well navigated (< 250 m) aircraft radiance imagery contemporaneous with a satellite

overpass can be used to assess sub-pixel patchiness and

horizontal gradients in the vicinity of ship measurements.

Similarly, flights prior to the overpass can be used to place

32
Mueller and Austin

the ship in a low gradient environment. Imaging spectrometers such as the Airborne Ocean Color Imager (AOCI) or

AVIRIS can be used the previous day to direct the ship

to the general low gradient study area, while near realtime information from low altitude airborne radiometers

or laser fluorometers, e.g., Ocean Data Acquisition System

(ODAS), MARS, and AOL, measured a few hours before

an overpass can be used to improve ship placement.

Fluorometry via flow-through pumping systems or towed

systems outside the ship wake, can be used to assess chlorophyll patchiness if frequent, i.e., every 10–15 minutes

depending upon gradients, chlorophyll fluorescence-yield

calibration measurements are performed. Towed absorption, scattering, reflectance, and c meters can also be used

to characterize spatial variability when a high degree of covariance exists between these parameters and chlorophyll a

concentration in a study area.

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, it is the recommendation of this

workshop to produce a calibrated set of SeaWiFS radiances that have been verified through direct, or vicarious,

calibration techniques.

One potentially useful technique follows the approach

currently in use to verify the responsivity of the AVHRR’s

Television and Infrared Observation Satellite (TIROS) satellite instruments. Twice a year, an aircraft instrument,

which has been recently calibrated directly to the laboratory based 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 ER-2, and flown at an altitude above most of the terrestrial atmosphere. Existing AVHRR-NASIC (NASA Aircraft Satellite Instrument

Calibration) Project data sets demonstrate a capability to

limit the uncorrected trend in the AVHRR data sets to under 2% over two years. This concept may allow an 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 ocean biological quantities. However, the SeaWiFS absolute accuracy requirements 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 (also

section 2.3).

6. METHODS OF ANALYSIS

6.1 In-Water Radiometric Profiles

Measurements of spectral surface irradiance Es(λ), upwelling irradiance Eu(z, λ), downwelling irradiance Ed(z, λ),

and upwelling radiance Lu(z, λ) should be recorded and

archived at four levels:

Level-0 Raw instrument digital output.

Level-1 Instrument output in volts, or frequency if

appropriate, and depth.

Level-2 Calibrated irradiance and radiance, ancillary measurements in appropriate geophysical or biological units, and depth corrected

for dark/zero offsets.

Level-3 Smoothed profiles of KE(z, λ) and associated Ed(z, λ) or Lu(z, λ) with irradiance/radiance

normalized by measured surface irradiance.

Level-4 Level-3 data normalized to clear-sky, zenith

sun at 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. The SPO will promulgate

suitable standard format specifications, or guidelines, to

facilitate database management and interchanges of level1, 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 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 of K-determination (level-3);

9) normalization algorithm (level-4);

10) Secchi depth; and

11) depths of associated water samples, if any.

In addition to profile files, each data set should contain:

a) calibration files used to compute level-2 data;

b) level-0 and level-1 dark files, and an average dark

voltage file used to compute the corresponding

level-2 files (in some cases a dark value may be

extracted from the deep portion of a profile);

c) 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

d) anecdotal and environmental information about

each profile, either in the header, or in an accompanying ASCII text file.

The data should be retained at full resolution, but with

contaminated records removed, through level-2. If the data

33
Ocean Optics Protocols for SeaWiFS Validation

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.

6.1.1 Instrument Calibration Analysis

The 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 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 references therein, show

transpectral Raman scattering contributes significantly to

measured irradiance between 500 and 700 nm. At a given

wavelength, the Raman contribution is excited by ambient irradiance at a wavenumber shift of 3,400 cm−1, e.g.,

Raman scattering at 500 nm (20,000 cm−1), is excited by

light at 427 nm (23,400 cm), 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

br(488) = 2.6 × 10−4 m−1. (22)

The wavelength dependence of the Raman scattering cross

section is theoretically similar to Rayleigh scattering

br(λ) ≡

 λ

488−4

br(488), (23)

although, this has not yet been experimentally confirmed.

Amethod for applying Raman corrections to radiance

profiles is suggested and applied to homogeneous clearwater profiles by Marshall and Smith (1990). Arobust

Raman scattering correction model for general application

in more turbid and vertically stratified water masses is

needed. 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 causing strong variations

in incident surface irradiance, Es(λ, t), measured at time

t, during the time required to complete a radiometric cast.

In present use, Es(λ, t) refers to incident spectral irradiance measured with a deck cell aboard a ship. Smith and

Baker (1984, 1986) discuss a method for propagating Es(λ)

through the sea surface to estimate Ed(0−, λ); 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 floated away from the ship and held at a shallow depth,

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) , (24)

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. Therefore, the Es(λ, t) or Ed(zr, λ, t) profiles

should 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) should be fit to the equations

Ed(z, λ) = Ed(0−, λ) e

−

z

0

Kd(z,λ)dz

, (25)

Eu(z, λ) = Eu(0−, λ) e

−

z

0

Ku(z,λ)dz

, (26)

and

Lu(z, λ) = Lu(0−, λ) e

−

z

0

KL(z,λ)dz

, (27)

respectively. The vertical profiles of attenuation coefficients Kd(z, λ), Ku(z, λ), and KL(z, λ), in conjunction

34
Mueller and Austin

with the respective surface values Ed(0−, λ), Eu(0−, λ),

and Lu(0−, λ) provide complete specifications of smoothed

irradiance and radiance profiles.

If the natural logarithm of (25), (26), and (27) is taken,

equations of the following form are obtained

−


z

0

K(z)dz = lnE(z)



− lnE(0−)



, (28)

so that

K(z) = −d ln

E(z)



dz













z

. (29)

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 lnE(z)



in an interval of a few meters

centered at depth zm, i.e., at depths near depth zm,

lnE(z)

 ∼= ln

E(zm)



− K(zm)(z − zm). (30)

The unknowns lnE(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 1988)

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 shadow effects

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.

Acorollary to having a large database, is the need to

facilitate its manipulation and analysis in order to make

its application to various tasks feasible. For example, in

the proposed SeaWiFS effort, 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 in at

least 5–8 spectral bands. Using a multispectral radiometer during a profile, such as the MER class of instruments,

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 processed information in each successive level, thereby

requiring 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

Ks using computer techniques (see above) require the use

of a depth interval so large, frequently 20 meters, that information about the slope and, hence, about K near the

top and bottom of the profile is lost, and 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 results 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 the 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

, (31)

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

irradiance (Eu) or upwelling radiance (Lu). The form of

(31) 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.

35
Ocean Optics Protocols for SeaWiFS Validation

The first derivative is

dY

dX = −P2 − P3P5

 2

A + 1

A

2

. (32)

When X = P4, B = 0 and Y = P1

dY

dX = −P2 − P3P5

. (33)

K may be defined as the slope of the plot of the natural logarithm of the measured radiometric variable against

depth, or

K = 2.3026

dY

dX . (34)

At the point of inflection (X = P4 and Y = P1)

K = 2.3026 P2 +

P3

P5



. (35)

In the limit, K → 2.3026P2 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 has

been recently developed by Mueller (1991). Radiometric

profiles are represented in terms of optical depth τ , which

from (25), (26), and (27) is

τ (z, λ) = 
z

0

K(z, λ)dz = ln E(0−, λ)

E(z, λ)



. (36)

The K-profile is represented analytically by Hermitian cubic polynominals 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 shallow

end-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), (37)

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 (36) for each measured depth zm as

the weighted sum

τ (zm, λ) = 

N

n=0

(hm,nKn + hm,n+N ∂zKn (38)

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 below the one containing z. Since such an

equation may be written for every measured optical depth,

the profile may be represented in matrix form as

1τ = H

∼

1

K, (39)

where 1τ is the vector of measured optical depths, H

∼ is the

matrix of coefficients hij and 1

K is the vector of Kn and

∂zKn at the N nodes. The least-squares solution for the

unknown vector 1

K is obtained as

1

K =



H

∼

T H

∼

−1

H

∼

T 1τ, (40)

which with (37) 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 shadow effects are present in the upper

profile, the depth of node 1 is set immediately below the

affected area and the data in that top element are excluded

from the fit; the solution to (40) at nodes 0 and 1 are,

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 (40)

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 (40) is solved.

In order to solve (40), 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

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), the 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.

36
Mueller and Austin

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

. (41)

Marshall and Smith (1990) applied a correction for this effect to clear-water profiles of Ed(z, 589). In general, correction of K(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

K(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, and the data from this zone

usually exhibit strong fluctuations (associated with surface

waves) and 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 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 shadow effects. The

usual procedure is to extrapolate values to z = 0− as

Ed(0−, λ) = Ed(z0, λ)eKd(z0,λ)z0 , (42)

Eu(0−, λ) = Eu(z0, λ)eKu(z0,λ)z0 , (43)

and

Lu(0−, λ) = Lu(z0, λ)eKL(z0,λ)z0 . (44)

If ship shadow is present, z0 may be 20 m or more, and the

extrapolation becomes somewhat tenuous.

If the integral method is used to determine K(z) profiles, 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 shallow first 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 Spectral Adjustments

New methods must be developed to reconcile in-water

measurements Lu(λ0 + ∆λ1, 0−) 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 F(λ), as modified by atmospheric spectral transmittance t(λ) and oceanic spectral

reflectance RL(λ). By assuming F(λ) is exactly known,

and that over the wavelength range defined by h2(λ) and

h1(λ), 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 waterleaving 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 accuracies of such corrections for the various SeaWiFS bands.

6.1.8 Normalized Water-Leaving Radiance

To standardize the in-water SeaWiFS algorithms, it

is necessary to normalize measured LW (λ) to those 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 may be defined as

LW N (λ) = LW

t(λ, θ0) (1 − ρ(θ0)) cos θ0

 r

R ̄

2

, (45)

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  , (46)

where D is the sequential day of the year.

37
Ocean Optics Protocols for SeaWiFS Validation

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.

6.2 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 NOAA’s National Environmental Satellite

Data Information Service (NESDIS) for SeaWiFS/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 (33, 52, and 72 m); they placed an additional abovewater radiometer on a surface float, but this unit failed

and provided no data. Smith et al. (1991) analyzed the

Kd(441) time series over 0–32 m, using a broad-band irradiance measurement to estimate Ed(0−, 441) and 32–52 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 chlorophyll fluorescence at

Lu(683) stimulated naturally by incident daylight; they

demonstrate 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 U.S. and International JGOFS will be published by working groups convened by these programs.

6.3 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 single measurements are 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.

6.4 Sky Radiance Distributions

Sky radiance distributions Lsky measured with a calibrated radiance distribution camera, and perhaps augmented by sun photometry or narrow FOV Lsky discrete

measurements in the zenith-sun plane, will be used to estimate the aerosol phase function (Voss and Zibori 1989).

Development of detailed protocols and methods of analysis, including new inverse 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 (1989).

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.

6.5 Phytoplankton Pigments

6.5.1 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.

6.5.2 Fluorometric Determination

Protocols for fluorometric determination of the concentrations of chlorophyll and phaeopigments were developed

initially by Yentsch and Menzel (1963) and Holm-Hansen

38
Mueller and Austin

et al. (1965) and are described in detail by Strickland and

Parsons (1972). These measurements have been shown to

contain errors, as compared to HPLC determinations, e.g.,

Trees et al. (1985), the CZCS photoplankton 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, Baker,

and Dustan (1981).

6.5.3 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

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).

6.6 Beam Attenuation Coefficient

Raw beam 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

(since factory calibration) with the equation

V (z) = V(z) − VdarkV 

air

Vair

, (47)

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)

 (48)

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), (49)

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.

6.7 Hydrographic Analyses of CTD Files

Each CTD profile should be pre-filtered 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 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 endorsed by the UNESCO/SCOR/ICES/IAPSO Joint Panel

on Oceanographic Tables and Standards and 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.

At each station, depictive hydrographic analyses should

include T-S profile characterizations of water masses, and

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, or two-dimensional grids,

of stations should be used to compute two-dimensional sections, or three-dimensional gridded arrays, of geostrophic

currents, temperature, salinity, and σt. These analysis

products, together with corresponding 2-D or 3-D representation 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.

Acknowledgments

The editors thank all of the workshop participants for their

help in defining and preparing the protocols presented in this

document:

Workshop Co-chairs

Mr. Roswell Austin San Diego State University

Dr. James Mueller San Diego State University

Workshop Participants

Mr. Robert Arnone NOARL

Mr. Rocky Booth Biospherical Instruments, Inc.

Dr. Kenneth Carder University of Miami

Mr. Dennis Clark NOAA/NESDIS

Dr. Donald Collins Jet Propulsion Laboratory

Dr. Wayne Esaias NASA/GSFC

Dr. Howard Gordon University of Miami

Dr. Bruce Guenther NASA/GSFC

39
Ocean Optics Protocols for SeaWiFS Validation

Workshop Participants Cont’d

Mr. Ron Holyer NOARL

Mr. Robert Kirk NASA/GSFC

Dr. Charles McClain NASA/GSFC

Mr. James McLean NASA/GSFC

Dr. Gregory Mitchell NASA Headquarters

Mr. Don Montgomery Office Ocean. of the Navy

Dr. Raymond Smith Univ. of Calif. at Santa Barbara

Dr. Charles Trees San Diego State University

Dr. Kenneth Voss University of Miami

Dr. Alan Weidemann NOARL

Dr. Ronald Zaneveld Oregon State University

Administrative Logistic Support

Ms. Meta Frost Westover Consultants

Several participants proofread the document at various stages

of completion and their assistance is particularly appreciated

by the editors .

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).

AOCI Airborne Ocean Color Imager

AOL Airborne Oceanographic Lidar

ARGOS Name given to the data collection and location

system on the NOAA Operational Satellites (not

an acronym)

AVHRR Advanced Very High Resolution Radiometer

AVIRIS Advanced Visible and Infrared Imaging Spectrometer

CDOM Colored Dissolved Organic Material

CPU Central Processing Unit

CTD Conductivity, Temperature, and Depth

CW Continuous Wave

CZCS Coastal Zone Color Scanner

DOC Dissolved Organic Carbon

DOM Dissolved Organic Matter

FOV Field-of-View

FWHM Full-Width Half-Maximum

GAC Global Area Coverage

GASM General Angle Scattering Meter

GFF Glass Fiber Filter by Whatman

GMT Greenwich Mean Time

GOES Geosynchronous Orbital Environmental Satellite

GPS Global Positioning System

GSFC Goddard Space Flight Center

HeNe Helium-Neon

HPLC High Performance Liquid Chromatography

IAPSO International Association for the Physical Sciences of the Ocean

ICES International Council on Exploration of the Seas

I/O Input/Output

IOP Inherent Optical Properties

IR Infrared

JGOFS Joint Global Ocean Flux Study

MARS Multispectral Airborne Radiometer System

MERIS Marine Environment Research Imaging Spectrometer

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

OCTS Ocean Color and Temperature Sensor (Japanese)

ODAS Ocean Data Acquisition System

OFFI Optical Free-Fall Instrument

OSFI Optical Surface Floating Instrument

PAR Photosynthetically Available Radiation

POC Particulate Organic Carbon

POLDER Polarization Detecting Environmental Radiometer (French)

PON Particulate Organic Nitrogen

PSU Practical Salinity Units

QED Quantum Efficient Device

ROSIS Remote Ocean Sensing Imaging Spectrometer,

also known as the Reflecting Optics System Imaging Spectrometer

ROV Remotely Operated Vehicle

SCOR Scientific Committee on Oceanographic Research

SeaWiFS Sea-viewing Wide Field-of-view Sensor

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

UVB Ultraviolet-B

VISLAB Visibility Laboratory (Scripps Institute of Oceanography)

WMO World Meteorological Organization

WOCE World Ocean Circulation Experiment

Symbols

a(z, λ) Spectral absorption coefficient

ap Particulate absorption coefficient spectra

b(z, λ) Total scattering coefficient

b(θ, z, λ0) Volume scattering coefficient

bb(z, λ) Spectral backscattering coefficient

br(λ) Total Raman scattering coefficient

c(z, λ) Spectral beam attenuation coefficient

c(z, 660) Red beam attenuation (at 660 nm)

Cp Beam attenuation coefficient due to particles

Ea(λ) Irradiance in air

Ecal Calibration source irradiance

Ed(0+, λ) On-deck spectral irradiance

Ed(0−, λ) Incident spectral irradiance

Ed(z, λ) Downwelled spectral irradiance

Es(λ) Surface irradiance

Esky(λ) Spectral sky irradiance distribution

Esun(λ) Spectral sun irradiance distribution

Eu(z, λ) Upwelled spectral irradiance

Ew(z, λ) Irradiance in water

40
Mueller and Austin

Fi(λ) Immersion correction factor

Fv(λ) Field-of-view coefficient

G(z, λ) Solid angle dependence with water depth

K(z, λ) Diffuse attenuation coefficient

KE(λ) Attenuation coefficient downwelled irradiance

KL(z, λ) Attenuation coefficient upwelled radiance

L(z, θ, φ) Submerged upwelled radiance distribution

Lcal Calibration source radiance

Lsky(λ) Spectral sky radiance distribution

Lt Radiance at the top of atmosphere

Lu(z, λ) Upwelled spectral radiance

LW (λ) Water-leaving radiance

LW N (λ) Normalized water-leaving radiance

ng(λ) Index of refraction of Plexiglass

nw(λ) Index of refraction of water

ODfilt(λ) Optical density spectra of filtered particles

ODsusp(λ) Optical density spectra of suspended particles

P(λ) Polarization sensitivity

Q(λ) Lu(0−, λ) to Eu(0−, λ) relation factor (theoretically equal to π)

RL(z, λ) Spectral reflectance

Tg(λ) Transmittance correction through glass

Ts(λ) Transmittance through the surface

Tw(λ) Transmittance through a water path

β(z, λ, θ) Spectral volume scattering function

δ Cosine response asymmetry

 Cosine collector response error

λ0 Center wavelength

λn Any nominal wavelength

μd(0+, λ) Spectral mean cosine for downwelling radiance

at the sea surface

ξ(λ) Minimum ship-shadow avoidance distance

ρ(λ) Bidirectional reflectance

τ (z, λ) Spectral optical depth

τs(λ) Spectral solar atmospheric transmission

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Yentsch, C.S. and D.W. Menzel, 1963: A method for the determination of phytoplankton, chlorophyll, and phaeophytin

by fluorescence, Deep-Sea Res., 10, 221–231.

43
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 July 1992 Technical Memorandum

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 SeaWiFS Technical Report Series

 Volume 5–Ocean Optics Protocols for SeaWiFS Validation Code 970.2

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17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT

 Unclassified Unclassified Unclassified Unlimited

 Oceanography, Ocean Optics, Coastal Zone Color Scanner (CZCS), Sensor, 46

 Bio-optics, Protocols, Calibration/Validation

James L. Mueller and Roswell W. Austin: San Diego State University, San Diego, California;

Stanford B. Hooker: NASA-GSFC, Greenbelt, Maryland; Elaine R. Firestone: General Sciences Corporation, Laurel,

Maryland.

Report is available from the Center for AeroSpace Information (CASI),

7121 Standard Drive, Hanover, MD 21076–1320; (301)621-0390

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Subject Category 48

13. ABSTRACT (Maximum 200 words)

National Aeronautics and Space Administration

Washington, D.C. 20546–0001 TM–104566, Vol. 5

Laboratory for Hydrospheric Processes

Goddard Space Flight Center 92B00097

Greenbelt, Maryland 20771

6. AUTHOR(S)

 James L. Mueller and Roswell W. Austin

 Series Editors: Stanford B. Hooker and Elaine R. Firestone

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 accuracy 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 review rationale. 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 is the proceedings of

that 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 a first prescription to approach unprecedented measurement accuracies

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

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