NASA Technical Memorandum 104566, Vol. 15

SeaWiFS Technical Report Series

Stanford B. Hooker and Elaine R. Firestone, Editors

Volume 15, The Simulated SeaWiFS Data Set,

Version 2

Watson W. Gregg, Frederick S. Patt, and Robert H. Woodward

January 1994
NASA Technical Memorandum 104566, Vol. 15

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 15, The Simulated SeaWiFS Data Set,

Version 2

Watson W. Gregg

NASA Goddard Space Flight Center

Greenbelt, Maryland

Frederick S. Patt and Robert H. Woodward

General Sciences Corporation

Laurel, Maryland

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

1994
The Simulated SeaWiFS Data Set, Version 2

Preface

In the prelaunch era of any space mission, simulated data sets are required in order to prove concepts of data

formatting; mission health and safety; and mission operations including scheduling, transmission, and capture.

Additionally, with a science mission like SeaWiFS, simulated data sets are necessary to test the ground data

processing procedures and hopefully, test prelaunch science algorithms. Including the latter functions demands

that the simulated data retain a high degree of fidelity to the data expected to be obtained. Producing such

a data set for the simulation of scientific observations (including major geophysical variability based on global

geophysical fields, sensor physics, and radiative transfer) is time consuming and requires the application of

state-of-the-art scientific understanding of the entire remote sensing problem—from sensor physics to the final

research algorithms.

Version 2 of the SeaWiFS data sets represents a major advance in the generation of a complete simulation. It

has already proven extremely useful in testing various components of the SeaWiFS ground processing systems.

Hopefully, it will prove valuable to other investigators and institutions who wish to process SeaWiFS data.

It will, however, be of limited use for the complete testing of level-2 and level-3 products with at-launch algorithms. By necessity, it makes use of the preliminary sensor radiometric responses and gain relationships. It is

now clear that these will change significantly due to sensor modifications, which are required to minimize stray

light effects. Final values of these parameters will be available only after several months from the submission

date of this report. Whether there will be a Version 3 of the simulated data sets, including the at-launch sensor

responses, has not yet been decided; it will depend upon resources, and how soon before launch the newer version

could be ready. Being overtaken by events, in this case sensor modifications, is a risk borne by any simulation

system.

Greenbelt, Maryland — W. E. Esaias

September 1993 Project Scientist

ii
W.W. Gregg, F.S. Patt, and R.H. Woodward

Abstract

This document describes the second version of the simulated SeaWiFS data set. Arealistic simulated data

set is essential for mission readiness preparations and can potentially assist in all phases of ground support for

a future mission. The second version improves on the first version primarily through additional realism and

complexity. This version incorporates a representation of virtually every aspect of the flight mission. Thus, it

provides a high fidelity data set for testing several aspects of the ground system, including data acquisition, data

processing, data transfers, calibration and validation, quality control, and mission operations. The data set is

constructed for a seven-day period, 25–31 March 1994. Specific features of the data set include Global Area

Coverage (GAC), recorded Local Area Coverage (LAC), and real-time High Resolution Picture Transmission

(HRPT) data for the seven-day period. Arealistic orbit, which is propagated using a Brouwer-Lyddane model

with drag, is used to simulate orbit positions. The simulated data corresponds to the command schedule based

on the orbit for this seven-day period. It includes total (at-satellite) radiances not only for ocean, but for

land, clouds, and ice. The simulation also utilizes a high-resolution land-sea mask. It includes the April 1993

SeaWiFS spectral responses and sensor saturation responses. The simulation is formatted according to July

1993 onboard data structures, which include corresponding telemetry (instrument and spacecraft) data. The

methods are described and some examples of the output are given. The instrument response functions made

available in April 1993 have been used to produce the Version 2 simulated data. These response functions will

change as part of the sensor improvements initiated in July–August 1993.

1. INTRODUCTION

The availability of simulated data is essential for the

preparation of a remote sensing mission. The usefulness of

the simulated data for mission preparation activities depends upon the thoroughness with which the data are prepared, the adherence to format and content specifications,

and the realism of the data. For example, data transfer speeds, storage capabilities, and computer memory requirements can usually be tested using dummy data sets

of the expected volume. Unpacking algorithms, computer

processing requirements, and intricacies of storing the data

require that at least the correct data structures and formats are created in the simulated set. More advanced

mission preparation activities, such as quality control, algorithm development, mission health and safety monitoring, and the initiation of an awareness of potential in-flight

problems and discoveries, require a realistic data set containing observations similar to the expected flight data,

with the correct volumes and structures. Such a simulated data set can potentially increase the success of the

mission by exposing problems in sensor design, spacecraft

operations, orbit anomalies, etc., well in advance of launch,

allowing repair (if detected in time) or compensation by developing algorithms or revising the sensor and spacecraft

operations scenario.

The development of a realistic simulated data set is

simplified if a predecessor mission exists. If the predecessor mission is an exact copy of the future mission, then

development of simulated data is simply a matter of using

the previous data. This is rarely the case, however, since

the predecessor mission often yields insights that lead to

an improved sensor design and capability, or perhaps a

different spacecraft or orbit configuration. In most cases,

additional effort and data are required for development of

the simulated data set.

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

mission, due for launch in 1994, is an example of a mission that has a highly successful predecessor sensor, the

NIMBUS-7 Coastal Zone Color Scanner (CZCS), but contains many improvements in sensor design that render direct use of the predecessor data insufficient for mission

preparation. The most important differences are the spectral band placement and the global, routine operations scenario for SeaWiFS, since CZCS was a limited duty sensor.

Additional differences include the sensor scan parameters

and the overall data content, especially the telemetry.

This method for constructing a simulated SeaWiFS

data set takes advantage of the fact that the eight years

of accumulated CZCS data led to many insights into the

processes of radiative transfer in the ocean, and the relationship of these processes to remote sensing principles. By

emphasizing this knowledge, a realistic simulated data set

for a similar, but not identical, sensor may be developed

without relying excessively on manipulation of previous,

and only approximately valid, data sets.

The primary use of this simulated data set is to support

SeaWiFS data system testing prior to launch. Thus, it

attempts to include all information and characteristics to

support processing and handling by all components of the

SeaWiFS Project. The functions to be tested include, but

are not limited to:

1) Transmission from the Wallops Flight Facility

(WFF) to the Goddard Space Flight Center’s

1
The Simulated SeaWiFS Data Set, Version 2

(GSFC) SeaWiFS Data Capture Facility (DCF);

2) Frame formatting of the data by the DCF and

transfer to the SeaWiFS Data Processing System (SDPS);

3) Ingestion by the SDPS and generation of level1a, level-2, and level-3 products, including navigation, atmospheric correction, and determination of geophysical parameters;

4) Quality control by the Calibration and Validation element, and navigation analysis by the Mission Operations element; and

5) The transfer of data products to the GSFC Distributed Active Archive Center (DAAC), where

data are ingested, cataloged, and distributed.

The Version 2 simulated data relies upon April 1993 sensor

responses. These response functions will change as part of

sensor improvements initiated in July–August 1993; therefore, its value for testing level-2 and atmospheric correction

is limited.

As is typical in the development of simulated data sets,

the process proceeds in steps, each step building on the previous one in complexity and realism. The data set version

presented in this paper is a direct descendant of Version 1

(Gregg et al. 1993). This version improves on Version 1 in

the following ways:

a) Constructed for a seven-day period, 25–31 March

1994;

b) Includes all data types, i.e., Global Area Coverage (GAC), recorded Local Area Coverage (LAC)

and real-time High Resolution Picture Transmission (HRPT) data for the seven-day period;

c) Data corresponds to a realistic command schedule for same seven-day period;

d) Includes total (at-satellite) radiances not only

for ocean, but for land, clouds, and ice, and includes a high-resolution land-sea mask based on

April 1993 (linear) response functions;

e) Includes preliminary SeaWiFS spectral responses and prelaunch sensor saturation responses

provided by Hughes/Santa Barbara Research

Corporation (SBRC), the instrument manufacturer;

f) Formatted according to revised and current (as

of this writing) onboard data structures specified by Orbital Sciences Corporation (OSC), the

spacecraft manufacturer;

g) Includes corresponding telemetry (instrument

and spacecraft) data; and

h) Corresponds to a realistic orbit generated using

a Brouwer-Lyddane model with drag.

Note that items d) and e) are outdated due to subsequent

sensor improvements.

The methods for constructing the data set are described

in the following, along with examples of data output.

2. BACKGROUND

The primary scientific goal of the SeaWiFS mission is

to provide global monitoring of ocean color. However, because the spacecraft contains limited onboard storage capacity (119 Mbytes), onboard subsampling of the data is

required to obtain global coverage. Thus, SeaWiFS will

produce two different resolutions of data: LAC and GAC.

LAC data is full sensor resolution (1 km), while GAC data

is simply LAC data subsampled every fourth pixel along

scan and along-track. GAC data also contains only data

within a 45◦ swath width, in contrast to the 58.3◦ swath

for LAC data. Since both of these data are stored on

board the spacecraft data recorder, they are referred to

as stored data. Characteristics of the SeaWiFS sensor and

the SeaStar spacecraft are shown in Tables 1a and 1b.

Table 1a. SeaWiFS spectral bands and center

wavelengths, shown with those of CZCS for comparison. Wavelengths (λ) are in nm.

SeaWiFS CZCS

Band No. λ Band No. λ

1 412 1 443

2 443 2 520

3 490 3 550

4 510 4 670

5 555 5 750†

6 670 6 13.5μm‡

7 765

8 865

† Intended for surface vegetation analyses only (Williams et

al. 1985).

‡ Data suspect after 1979 (Williams et al. 1985).

In addition to stored LAC and GAC data, SeaWiFS

will broadcast real-time LAC data whenever the sensor is

turned on. HRPT stations may capture these data whenever the spacecraft is visible. However, due to the agreement between the National Aeronautics and Space Administration (NASA) and OSC, these real-time LAC data

will be encrypted: decryption methods will require either

a commercial license from OSC, in which case the data

may be decrypted in real time, or a research license from

GSFC in which case a two-week delay in decryption will

be enforced.

3. METHODS

An overview of the methods will contribute to clarity

and understanding. First, orbit positions are generated

for a seven-day period in March 1994, initiated by simulated SeaStar orbital elements. Then a command schedule,

which specifies the data collection periods and sensor state,

2
W.W. Gregg, F.S. Patt, and R.H. Woodward

Table 1b. Orbit and sensor characteristics for the SeaWiFS and the CZCS, shown for comparison.

Characteristic CZCS SeaWiFS

Altitude (km) 955 705

Period (minutes) 104.0 98.9

Inclination 99.28◦ 98.25◦

Equator Crossing Time (local) Noon Noon

Node Type Ascending Descending

Scan Width 39.34◦ 58.3◦ (LAC); 45◦ (GAC)

Instantaneous Field of View (IFOV) 0.05◦ 0.09◦

Ground IFOV at Nadir (km) 0.825 1.12

Pixels Along Scan 1,968 1,285 (LAC); 248 (GAC)

Scan Period (seconds) 0.134 0.167 (LAC); 0.667 (GAC)

Scan Plane Tilt ±20◦ ±20◦

Scan Ground Coverage (km) 1,566 2,802 (LAC); 1,502 (GAC)

Maximum Spacecraft Zenith Angle 46.8◦ 70.8◦ (LAC); 51.7◦ (GAC)

Digitization (bits) 8 10

Table 2. Simulated NORAD two-line elements for the SeaStar orbit used for orbit propagation in the simulated

data set. The important components are: day of year (seventh word, first row), drag term (10th word, first

row), inclination (third word, second row), right ascension ascending node (fourth word, second row), eccentricity

(fifth word, second row—assume preceding decimal point), argument of perigee (sixth word, second row), mean

anomaly (seventh word, second row), mean motion (eighth word, second row), and orbit number (first four

digits in ninth word, second row).

Line 1: 00000U9332A9480.00000000.0000038000000-018855-303084

Line 2: 0000098.2330178.300000100000.00000.000014.5540000029414

is created from these orbit positions based upon a realistic data acquisition requirements scenario, including both

routine observations and calibration activities. Then, for

each data collection period, the orbit positions to navigate

the pointing vectors to Earth locations, according to GAC

and LAC sensor specifications and the tilt configuration, is

used. The geolocated pixels are associated with a number

of atmospheric, land, and oceanic data files to obtain their

radiative characteristics. The pixels are determined to be

either cloud and ice, land, or ocean, each of which has a

different logical pathway for computing at-satellite radiance. Sensor configuration information is appended, such

as tilt, gain, etc., along with orbit position and velocity.

Telemetry fields are then inserted, using realistic values

wherever possible, and dummy fields where not. Finally,

the computed radiances are converted to digital counts and

adjusted for the sensor saturation responses using the preliminary linear radiometric response function.

The data are stored in two formats: one corresponding to the onboard structure (10-bit science data), and the

other corresponding to the ground system frame formatter output (10-bit words in 16 bits, but all other data as

in the onboard structure). The frame formatter output is

considered to be level-0, since it is the first product seen

by the GSFC SDPS and research HRPT stations. The onboard structure is maintained only in the spacecraft flight

recorder and at acquisition by the primary ground station,

WFF.

3.1 Orbit Propagation

Orbit positions and velocities are computed using a

modified Brouwer-Lyddane model, with atmospheric drag

included. The model is the Simplified General Perturbations Model (SGP4), distributed by the US Space Command. Simulated North American Air Defense Command

two-line elements were created for the SeaStar orbit (Table 2) in the so-called NORAD Two-Line Element format,

assuming the originally planned launch date of August

1993. The orbit positions and velocities are required for the

geolocation step of the simulation, and are also included

in the telemetry to simulate Global Positioning System

(GPS) data, which are included in the SeaWiFS data.

3.2 Navigation

For Version 2, perfect spacecraft attitude control is assumed, and thus roll, pitch, and yaw are set to zero. The

tilt configuration involves tilting aft of the velocity vector

(toward the North Pole), and changing to fore (toward the

South Pole) near the solar declination latitude to minimize

sun glint contamination. Geolocation is achieved using an

exact algorithm employing vector algebra, developed for

SeaWiFS navigation (Patt and Gregg 1993).

3.3 Command Schedules

The sensor command schedules used for the simulation correspond to the orbit position data generated for

3
The Simulated SeaWiFS Data Set, Version 2

the period 25–31 March 1994, and incorporate a routine

operations scenario, including GAC observations and calibration activities. The events included in the command

schedule are:

1) GAC and LAC record times, including calibration times;

2) real-time HRPT data broadcast times;

3) recorded data downlink times;

4) tilt change times; and

5) sensor configuration for each event.

The process of scheduling begins with knowledge of

down-link orbits at WFF. The mission requires two downlinks per day at WFF for full Earth coverage—one near

local noon and one near local midnight. The local midnight pass always occurs first in each Greenwich Mean

Time (GMT) day as a consequence of the orbit. During

flight operations, these will be selected by WFF personnel, who must perform conflict resolution to maximize the

acquisition requirements for many spacecraft. For simulation, the orbits are determined by selecting downlink orbits

that provide a variety of expected conditions, i.e., as few as

six orbits of data collection between downlinks to a maximum of more than nine orbits of data collection (Table 3).

The orbit numbers in the table are based on the August

1993 launch date and the late March simulation dates. The

selection of downlink orbits to produce variety in data collection schedules simulates a realistic scenario for SeaStar,

which is only one of many spacecraft using WFF as the

primary data acquisition station.

Given downlink orbits, the GAC recorder is then scheduled. A40 minutes-per-orbit maximum duty cycle is adhered to, as determined by SeaStar power constraints. This

duty cycle corresponds to a maximum solar zenith angle

of 72.7◦, which is the actual limit used in the scheduling

software for GAC data collection. A series of commands

is required to configure the instrument and flight recorder

for start up and shutdown, and is included in the schedule. Asample portion of a command schedule is shown in

Table 4.

Next, individual channel gains and Time Delay and Integration (TDI) settings are selected to maximize the scientific usefulness of the data being collected. For Earthviewing observations, gains are set to unity and TDIs are

set to zero, meaning that all four detectors per band are

being used to increase the signal-to-noise ratio (SNR). During lunar, solar, intergain, and detector calibration events,

gain and TDI settings follow specific instructions (Woodward et al. 1993), which are discussed below. The available

gain settings for Version 2 are shown in Table 5.

The tilt strategy employed in the command schedules

for the simulation data set involves a single tilt change on

the descending node. The location of the tilt change is set

to minimize sun glint contamination. In flight, the recommendation of Gregg and Patt (1993), which is called

the “staggered tilt” strategy, will be followed. This strategy shifts the tilt change location a few degrees north of

the maximum sun glint point (near the solar declination

latitude) for two days, then shifts the position a few degrees south for the next two days. Gregg and Patt (1993)

showed that this strategy improves the ocean coverage over

a four-day period while simultaneously reducing sun glint

contamination.

Table 3. Downlink orbit numbers at Wallops used

in the command schedule construction.

Orbit Number Day of Year

3002 84

3010 84

3017 85

3024 85

3031 86

3038 86

3046 87

3053 87

3060 88

3067 88

3074 89

3083 89

3090 90

3096 90

The SeaWiFS instrument tilt can be commanded to

zero (nadir), 20◦ forward and 20◦ aft. For the SeaWiFS

convention, an aft 20◦ tilt (opposite the velocity vector) is

defined as +20◦, and a forward tilt is defined as −20◦. Note

that the tilt changes are not instantaneous, but require

approximately 13 seconds to complete, with tilt change

rates that vary continuously during this period (Fig. 1).

The sensor tilt position during a tilt change is computed

using a mathematical fit to the SBRC data:

T = a tanh(bt) (1)

where T is the tilt position in degrees, t is the time in

seconds and

a = −20

tanh(2), (2)

b = 1

3

. (3)

The LAC data capacity is determined by the total capacity of the flight recorder and the GAC storage requirements. Calibration and other LAC recording periods must

be constrained by the available LAC space. Calibration

requirements for the simulation run are derived from a

simulated LAC target file. During the mission, this file

will be supplied to the Mission Operations team by the

Calibration and Validation team. There are five types of

calibration activities in the SeaWiFS mission. These are,

in order of priority: lunar calibration, solar calibration,

4
W.W. Gregg, F.S. Patt, and R.H. Woodward

Fig. 1. Comparison of SBRC measured sensor tilt change response (squares) and mathematical fit used

in the simulated data (line).

Fig. 2. Lunar calibration maneuver (courtesy of Orbital Sciences Corp.).

5
The Simulated SeaWiFS Data Set, Version 2

Table 4. Sample portion of the schedule for day of year 84.

Command Setting Year Day Time Orbit Latitude Sun

L-band Transmitter Turn On 1 1994 84 604 2999 72.32◦ 72.7◦

Reset Tilt Aft Position 20 1994 84 634 2999 72.32◦ 72.7◦

Set Earth Mode On 1 1994 84 639 2999 72.32◦ 72.7◦

Electronics Turn On Power 1 1994 84 654 2999 72.32◦ 72.7◦

Change Gain Band 1, 2,...,8 1 1994 84 659 2999 72.32◦ 72.7◦

Change TDI Band 1, 2,...,8 0 1994 84 660 2999 72.32◦ 72.7◦

LAC Transmitting Turn On 1 1994 84 663 2999 72.32◦ 72.7◦

GAC Recorder Turn On 1 1994 84 663 2999 72.32◦ 72.7◦

LAC Recorder Turn On 1 1994 84 864 2999 61.27◦ 62.1◦

LAC Recorder Turn Off 0 1994 84 894 2999 59.22◦ 62.1◦

LAC Recorder Turn On 1 1994 84 1680 2999 12.57◦ 13.5◦

Change Tilt To Forward −20 1994 84 1855 2999 1.55◦ 0.4◦

LAC Recorder Turn Off 0 1994 84 1860 2999 0.30◦ 1.7◦

GAC Recorder Turn Off 0 1994 84 3063 2999 −69.47◦ 72.7◦

LAC Transmitting Turn Off 0 1994 84 3063 2999 −69.47◦ 72.7◦

L-band Transmitter Turn Off 0 1994 84 3065 2999 −69.47◦ 72.7◦

Electronics Turn Off Power 0 1994 84 3066 2999 −69.47◦ 72.7◦

Fig. 3. Solar calibration maneuver (courtesy Orbital Sciences Corporation).

6
W.W. Gregg, F.S. Patt, and R.H. Woodward

intergain check, detector check, and in situ LAC target

observations. For this simulation, the file contains instructions to include one solar calibration per day, which includes an intergain check, and one detector check per day.

Afull moon occurs during the simulation period, on 27

March 1994, so a lunar calibration event is also scheduled.

The file also includes several ship, buoy, and region targets with an accompanying prioritization (Table 6). These

requirements are implemented in data collection via the

command schedule.

Lunar calibration is achieved by pitching the spacecraft

360◦ on the dark side of the orbit to view a moon near full

phase (Fig. 2). The SeaWiFS Project has chosen a 7◦ lunar

phase angle for lunar calibration (Woodward et al. 1993)

to ensure calibration consistency and availability (smaller

phase angles do not always occur in a given month). The

specific time of the moon view is predicted based on the

spacecraft position at the start of the pitch maneuver and

the selected pitch rate. The pitch rate has been selected to

collect about 20 LAC lines including moon data. The LAC

recorder is turned on for two minutes total, centered on the

predicted viewing time, to allow for uncertainties in the

spacecraft pitch rate. Specific gain settings are utilized to

prevent saturation and to ensure maximum dynamic range

(Table 5).

Table 5. Gain settings for SeaWiFS.

Band Gain 1 Gain 2 Gain 3 Gain 4

412 1 23 1.73 1.3

443 1 2 1.73 1.3

490 1 2 1.7 1.25

510 11 2 1.7 1.252

555 12 2 1.61 0.77

670 1 2 0.71 0.462

765 1 2 0.611 0.322

865 1 2 0.551 0.262

1. Used for lunar calibration.

2. Used for solar calibration.

3. Used for both lunar and solar calibration.

Solar calibration involves tilting the sensor 20◦ aft of

the velocity vector when the spacecraft is at the southern terminator to view reflection off a solar diffuser plate

mounted on the sensor (Fig. 3). The instrument is commanded into a unique solar mode configuration, which

causes the sensor to sample a different part of the scan

circle to allow a view of the diffuser plate, although, the

LAC scan line still consists of 1,285 science pixels. Again,

specific gain settings are used to maximize the scientific

usefulness of the solar irradiance scattered off the diffuser

plate (Table 5). The solar mode also includes an internal calibration signal. During each scan, after viewing the

diffuser plate, the sensor electronics receives a constantmagnitude electronic pulse, called the calibration pulse,

which enables a highly consistent intergain check to be

performed. This check is performed immediately after the

full solar calibration, using a specific sequence of channel

gains (Table 7).

Detector checks also use the solar diffuser plate, and

are performed on the orbit following the solar calibration

activity. Again, a specific TDI and gain sequence is used

(Table 8).

Finally, the remaining LAC recorder space is used to

schedule in situ calibration targets. Adistinction is made

between two types of in situ targets for the SeaWiFS mission: ship and buoy targets, and region targets. Ship and

buoy targets are discrete locations which have the higher

priority of the two in situ types. For ship and buoy targets,

the LAC recorder is turned on 15 seconds before viewing

the target, and left on for 15 seconds after the target. This

30 second viewing duration provides 100 km of observations about the target. For regions, the recorder is turned

on only if the sub-satellite point is within the region. This

ensures that at least half the scan is in the region of interest. In this simulated data set, not all the available LAC

space is used, due to the prototype status of the scheduling algorithms and code, which are under development and

testing. For the mission, all available LAC space will be

used.

3.4 Determining At-Satellite Radiances

At-satellite radiances are derived from five backscattering sources: clouds, land, ice, non-cloud atmosphere,

and the ocean. In each case, the method for computing

radiances involves the assumed known reflectance properties of the contributing source; solar geometry, which

is dependent on the year, time of day, and position; and

scan geometry, which is dependent on the simulated orbit

position and known scanning characteristics of the sensor. Intensive radiative transfer calculations translate this

knowledge into quantitative radiances taking into account

the specific optical responses of the SeaWiFS sensor available as of April 1993. The calculations have not yet been

made for a bilinear instrument response.

The calculation of at-satellite radiances thus begins

with a determination of the state of the atmosphere, land,

and oceans at the time of observation. This is obtained

through the use of several global data sets. The same

seven-day period in March 1990 for each data set was chosen to ensure coherence among the state variables. The

data sets include information on cloud cover, ice cover,

land vegetation, ocean chlorophyll concentration, wind

speeds, surface pressure, and ozone concentration (Table 9).

Each of these variables affects SeaWiFS observations:

1) Cloud cover determines the ability of the sensor to view the Earth and also determines the

amount of saturation;

2) Ice cover and land vegetation affect the optical

properties of land;

3) Ocean chlorophyll concentration contributes to

the determination of the spectral properties of

water-leaving radiance;

7
The Simulated SeaWiFS Data Set, Version 2

Table 6. LAC target file used for the simulated SeaWiFS data set. In situ targets have longitude and latitude

associated with them, plus a priority indicator. Calibration activities are associated with a number indicating

the number of such activities per month.

Calibration Targets

1994 82

In situ

10

Clark’s Buoy -156.3400 18.6700 4

Bermuda Buoy -71.9000 32.1200 6

JGOFS 63.2500 19.4000 3

NOAA S. Atlantic Bight -77.5200 32.0300 4

NOAA Gulf of Cal. -107.2600 22.1100 5

S. Africa 10.2300 -32.8700 6

Galapagos -92.6200 -3.2500 8

Gulf of Mexico -86.8600 24.7900 3

Oregon St. -131.1400 45.7700 1

Navy Bering Sea -175.5800 63.4200 10

Regions

5

Sargasso Sea -70.0000 -45.0000 20.0000 30.0000 2

Gulf of Mexico -110.0000 -80.0000 17.0000 31.0000 1

SE Pacific -150.0000 -90.0000 -60.0000 -30.0000 3

Galapagos -105.0000 -75.0000 -15.0000 0.0000 5

Micronesia 135.0000 180.0000 0.0000 15.0000 4

Solar Calibration

30

Lunar Calibration

1

Intergain Calibration

30

TDI Check

30

4) Wind speeds determine the aerosol type over the

oceans and the sun glint radiance magnitudes;

5) Surface pressure affects the Rayleigh scattering

of the atmosphere and the oxygen concentration

which absorbs irradiance and radiance in some

SeaWiFS bands; and

6) Ozone concentrations affect the spectral transmittance of irradiance and radiance through the

atmosphere.

The effect of water vapor on SeaWiFS bands is small,

and so is set to a global mean of 1.5 cm. As stated above,

the simulation procedure includes orbit propagation and

navigation to determine the position of each pixel. The

pixel’s position is associated with the known position of

each variable in the data sets, enabling knowledge of the

current state. Examples of cloud and ice cover used are

shown in Figs. 4 and 5.

Given knowledge of the state of the atmosphere and

surface, and the pixel under examination in a full orbit

propagation, the radiative properties are determined next.

For cloud and ice cover, concentrations greater than 50%

means that obscuration of the surface is assumed and the

at-satellite radiance is computed as:

Lt(λ) = ρc,iEd(λ, θ0)

π , (4)

where Lt is the total radiance received by the satellite (atsatellite radiance), ρ is the reflectance of clouds (subscript

c) and ice (subscript i), and Ed is the incident irradiance on

the Earth’s surface as a function of the Earth-sun distance

and atmospheric transmittance. The atmospheric transmittance properties are determined by the solar zenith

angle, θ0, which is known at each pixel from orbit position, pointing knowledge, and geolocation. Division by π

enforces a Lambertian scattering assumption. For both

clouds and ice, ρ is set to 1, i.e., clouds and ice are completely reflecting.

The incident irradiance is computed using the method

of Gregg and Carder (1990), where extraterrestrial irradiance and other atmospheric optical properties are weighted

to conform to the latest SeaWiFS spectral responses (Table 10). If a pixel is found to be greater than 50% ice or

8
W.W. Gregg, F.S. Patt, and R.H. Woodward

9
The Simulated SeaWiFS Data Set, Version 2

10
W.W. Gregg, F.S. Patt, and R.H. Woodward

cloud, (4) is utilized and no further calculations are performed, under the assumption that the high reflectance

properties of ice and clouds overwhelm other atmospheric,

non-ice land, and oceanic contributions. If a pixel is found

to be non-cloudy and non-ice, then it must be determined

whether the pixel is land or ocean. This determination is

made using a high resolution land-sea mask, which is derived from the World Vector Shoreline (WVS) Database,

available from the National Geophysical Data Center

(NGDC). The resolution of the land or sea mask is 128

pixels per degree of latitude or longitude, corresponding to

0.9 km at the equator, or slightly better than the LAC resolution. If the pixel under observation is found to be land,

then the land radiance determination method is employed.

Otherwise, the ocean radiance determination method is

used.

Table 7. Command sequence for intergain check.

Gain 1, Gain 2, Gain 1, Gain 3, Gain 1, Gain 4,

Gain 1

This gain sequence is repeated for each of 5 TDI

configurations:

1. Use of all four detectors

2. Use of Detector 1 only

3. Use of Detector 2 only

4. Use of Detector 3 only

5. Use of Detector 4 only

The overall pattern is repeated once, along with

a finalrepeat using allfour detectors, requiring

a totalof 77 seconds to complete.

Table 8. Command sequence for a TDI check.

This sequence is performed using solar calibration

gains on all bands, since the check occurs in solar

mode using the solar diffuser plate. Unique TDI

configuration codes are defined by OSC, and these

are used in the simulated data set.

TDI Configuration Code Meaning

0 All 4 detectors

164 Detector 1 only

0

26 Detector 2 only

0

74 Detector 3 only

0

161 Detector 4 only

0

The pattern is repeated 9 times, requiring

81 seconds

The land radiance determination method begins with

the Advanced Very High Resolution Radiometer (AVHRR)

reflectance data set. First, it is assumed that the reflectance of AVHRR band 1 (centered at 640 nm) equals

the reflectance at SeaWiFS band 6 (670 nm). The Normalized Difference Vegetation Index (NDVI) is then computed.

If the NDVI is greater than 0.2, the pixel is vegetated, and

it is assumed that the reflectance at AVHRR band 2 (centered at 850 nm) equals the reflectances at SeaWiFS bands

7 and 8 (765 and 865 nm, respectively).

Table 9. External data sets used in the creation

of simulated SeaWiFS data and their sources.

External Data Set Source

Chlorophyll Global CZCS composite

(CZCS Global Reprocessing)

Land Vegetation 10-day AVHRR composite

from April1988 (AVHRR

Pathfinder)

Wind Speed and FNOC data from

Surface Pressure 25–31 March 1990 (NCDS)

Clouds ISCCP from 25–31 March 1990

(NCDS)

Ice ISCCP climatological mean

(NCDS)

Ozone TOMS from 25–31 March 1990

Table 10. Spectrally weighted (FWHM) mean extraterrestrial irradiance F0(λ) (mW cm−2 μm−1),

Rayleigh optical thickness (τr), ozone absorption

coefficient (aoz), water vapor absorption coefficient

(awv), and oxygen absorption coefficient (ao). All

units are in cm−1, except τr, which is dimensionless.

λ F0 τr aoz awv ao

410 171.07 0.3139 0.0000 0.0000 0.0000

443 189.91 0.2341 0.0030 0.0000 0.0000

490 194.33 0.1561 0.0213 0.0000 0.0000

510 188.24 0.1324 0.0382 0.0000 0.0000

555 185.93 0.0942 0.0897 0.0008 0.0000

670 152.14 0.0439 0.0470 0.0043 0.0053

765 123.55 0.0257 0.0083 0.0007 3.3780

865 100.00 0.0155 0.0000 0.0057 0.0000

Reflectances are then computed at SeaWiFS bands 1–

5 as an inverse function of chlorophyll absorption coefficients weighted by the SeaWiFS spectral response, where

the magnitude conforms to the reflectance at band 6. Values for chlorophyll absorption are taken from Gregg et al.

(1993). If the NDVI is less than 0.2, the pixel is nonvegetated, and the slope is computed from AVHRR band

2 minus AVHRR band 1. A linear reflectance response,

through SeaWiFS bands 1–5, is assumed following this

slope. This method provides reasonable agreement with

observations for two arbitrarily selected vegetated and nonvegetated points (Fig. 6). The reflectances are converted

to at-satellite radiances as in (4), with the reflectance determined above substituted for ρc,i. Note that this method

does not explicitly account for the atmosphere, although

some is implicit in the AVHRR reflectances which do not

correct for the atmosphere, nor for scan angle.

The ocean radiance method is described in great detail

in Gregg et al. (1993) and will not be elaborated upon in

11
The Simulated SeaWiFS Data Set, Version 2

Fig. 6. a) Land reflectance data from Tucker and Miller (1978). b) Simulated land reflectances from

AVHRR data for a vegetated location near the Nicaraguan and Costa Rican border, and for a nonvegetated location in the Mexican plateau (redrawn with permission from J. Tucker).

12
W.W. Gregg, F.S. Patt, and R.H. Woodward

this document. There are, however, three significant differences in the method used here. First, wind speeds are

taken from Fleet Numerical Oceanographic Center (FNOC)

data for 25–31 March 1990, rather than using the climatological mean as in Gregg et al. (1993). Second, pressure

effects are explicitly accounted for in the computation of

multiple Rayleigh scattering through

I

(λ) = Io(λ) 1 − e−τ

r(λ)M(θ)

1 − e−τro(λ)M(θ) , (5)

where I0(λ) is the Rayleigh scattering intensity at standard

pressure (Gordon et al. 1988), τro is the Rayleigh optical

thickness weighted by the SeaWiFS spectral response, and

M is the slant path length through the atmosphere (see

Gregg et al. 1993). The term τ 

r is the pressure-corrected

optical thickness

τ 

r = τro

P

P0

, (6)

where P and P0 are the local surface pressure and the standard pressure, respectively. Finally, the factor 4π is eliminated in the denominator of (28) in Gregg et al. (1993),

since it is already accounted for in (30) of that reference.

This error produced incorrectly low aerosol radiances in

Version 1.

3.5 Conversion to Digital Counts

SeaWiFS simulated total radiance data were converted

into digital counts by

DC(λ, G) = 20 + Lt(λ) − LNER(λ, G)

s(λ, G) , (7)

where DC is the digital count value, LNER(λ, G) is the

Noise Equivalent Radiance (NER) as a function of wavelength and gain factor G, and s is the slope for the range

0–1,023. This is applicable for 10-bit digitization, given by

s(λ, G) = Lsat(λ, G) − LNER(λ, G)

1003 , (8)

where Lsat(λ, G) is the saturation radiance for the sensor

as a function of wavelength and gain setting. LNER(λ, G)

and Lsat(λ, G) for Gain 1 are shown in Table 11. The

addition of 20 counts in (7) represents the dark restore

value used in the simulation. In flight, a dark restore value

will be contained in the data stream and will be applicable

for each scan line. This dark restore value also accounts for

the division by 1,003 in (7), rather than division by 1,023.

Application of (7) and (8) does not truncate the data

to 10-bit quantization. In the first run of the simulation

data set, this is desirable, since it provides knowledge of

the extent of saturation (number of counts above 1,023),

which is required for determination of the sensor saturation

responses. After the saturation responses are accounted

for, the final simulation data set values are truncated to a

maximum count value of 1,023.

Table 11. LNER and saturation radiances (Lsat)

for SeaWiFS (units are mW cm−2 μm−1 sr−1). Lsat

will change in the launch configuration due to instrument modifications.

Band λ [nm] LNER Lsat

1 412 0.0094 13.63

2 443 0.0085 13.25

3 490 0.0055 10.50

4 510 0.0050 9.08

5 555 0.0041 7.44

6 670 0.0037 4.20

7 765 0.0022 3.00

8 865 0.0015 2.13

3.6 Sensor Saturation Response

The preliminary April 1993 test data from the SeaWiFS

sensor exhibited significant saturation response. This response has two main features:

1) An optical effect due to stray light in the sensor

that produces elevated digital counts preceding

a saturated pixel, and

2) An electronic effect, e.g., bright target recovery

(BTR), that produces elevated counts following

a saturated pixel.

Furthermore, these effects are asymmetric with band

number; even numbered bands exhibit greater stray light

effects, while odd numbered bands exhibit greater bright

target recovery effects. These effects were added to the

simulated data to enhance realism. Using data from a sensor characterization examination in April 1993, methods

were developed to simulate the stray light and BTR responses. Both are a function of the level of saturation,

i.e., the real digital count value for a sensor not limited

to 10-bit words. In the calculation discussed earlier, count

values were saved as computed, i.e., not truncated to 10-bit

accuracy as is the case for the actual flight.

The sensor characterization data provided the saturation responses at two levels of saturation, or overdrive, for

each pixel in the scan line. Alinear function was fit individually for each pixel away from the saturated pixel.

This linear function fit provided an excellent reproduction

of the tabulated saturation responses (Figs. 7 and 8).

3.7 Telemetry

The SeaStar data stream contains a large number of instrument and spacecraft telemetry fields in addition to the

SeaWiFS science observations contained in the scan lines.

These fields represent a combination of direct measurements from spacecraft hardware components, e.g., temperatures, voltages, and currents; status of commandable

components, e.g., on or off, and A/B side switches, as well

as tilt and gain settings; and computed values from onboard processors, e.g., spacecraft time, orbit position, and

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The Simulated SeaWiFS Data Set, Version 2

14
W.W. Gregg, F.S. Patt, and R.H. Woodward

15
The Simulated SeaWiFS Data Set, Version 2

attitude. Fields that represent physical quantities (both

measured and computed), also known as analog telemetry,

are usually digitized for inclusion in the data stream, while

status information, also known as discrete, is typically represented by single bit fields packed into status bits.

Several telemetry fields are required as input to the

simulation process. They are:

a) scan line time,

b) orbit position and velocity,

c) spacecraft attitude,

d) instrument tilt angle (commanded and actual),

e) gain and TDI settings, and

f) instrument mode.

Anumber of additional fields are also included to support data processing and otherwise improve the realism

of the data stream. Specific examples include instrument

analog and digital telemetry, spacecraft attitude sensor

data, and GPS telemetry. In addition, the spacecraft telemetry includes a large number of analog and status fields,

from the attitude control system data, GPS subsystem,

electrical power subsystem, propulsion subsystem, transmitters, and flight computers. In most cases, the information presently available for simulating these values is

limited. The methods for each type of data are as follows.

The simulated science data discussed earlier are saved

scan line-by-scan line. The scan line time and instrument

mode are inserted for each LAC scan line and for every fifth

GAC scan line, since GAC lines are stored five per minor

frame (discussed in the next section). The gain and TDI

are included with every scan line. Time, sensor tilt, and

mode are required for the instrument telemetry packet,

included for two of every three scan lines for both GAC

and LAC. Time, orbit position and velocity, and spacecraft

attitude are required for the ancillary data packet, included

for one of every three scan lines. The remaining instrument

telemetry fields are set to static values based on a sample

of actual values provided by SBRC.

The spacecraft telemetry packet is included for 1 of every 3 scan lines for LAC data and 1 of 15 lines for GAC

data, in accordance with the OSC specified onboard data

structure. The scan line time, orbit, and attitude data

for the appropriate scan line are included in the spacecraft telemetry. In addition, simulated attitude sensor data

is generated for the spacecraft packet to support realistic

navigation processing by the SDPS. The sensor data consist of sun angles and presence flags for each of three digital

sun sensors, and Earth width and phase angles for each of

two Earth scanners. The angles are computed using the

simulated orbit and attitude data, according to the sensor

manufacturer’s specifications and information from OSC

regarding the sensor mounting and orientation, as well as

general reference information (Wertz 1978). The remaining spacecraft fields are set to arbitrary static values.

3.8 Data Formatting

The data is formatted according to the specifications

provided by OSC for the SeaStar minor frame and the individual data packets. The LAC format is described in the

SeaStar Spacecraft L-band Downlink to Receiving Stations

Interface Control Document (ICD), currently being prepared by OSC. This document includes the overall minor

frame format and details of the spacecraft identification

(ID) and time tag, scan line data (including the gain and

TDI), instrument telemetry, and ancillary data packets.

However, the structure of the data fields is shown here

for completeness (Fig. 9). The GAC minor frame format

specifications were obtained from OSC, but are not yet

available in a formal document. The formats of the GAC

data ID, time tag, spacecraft telemetry packet, instrument

telemetry packet and ancillary data packet are identical

to the LAC data, although, the instrument and ancillary

packets are stored in different locations in the GAC minor frame (Fig. 10). The GAC scan lines are formatted

and stored according to the data reduction specifications

provided by OSC.

The overall format of the LAC minor frame is given in

Fig. 9, which shows the location of the major elements. As

stored on the spacecraft, the data include a combination

of 10-bit and 8-bit fields. All data, except the spacecraft

telemetry, are stored as 10-bit words; the spacecraft fields

are 8-bit aligned. The figure also shows a frame synch

at the beginning of each minor frame and an auxiliary

synch at the end; the simulation of these fields was not

attempted, but will be added by the DCF to support endto-end testing.

The Version 2 format is based upon this minor frame

definition and on the initial frame formatting of the data.

Clearly the 10-bit aligned data cannot be readily interpreted by standard computing systems. The DCF has

provided a programmable frame formatter (PFF) which

reformats the data into a more useful format. Specifically,

each 10-bit word is right-justified in a 16-bit word, while

the 8-bit words are maintained in their original format.

The frame synchs are stripped and discarded. This processing increases the frame length from 13,860 bytes to

21,504 bytes, but greatly facilitates subsequent processing.

The data in the format generated by the PFF is referred

to as level-0, since it is the first format seen by the SDPS

or any remote HRPT station.

The simulation reverses the processing performed by

the DCF. First the simulated science and telemetry data

are combined to generate a PFF (level-0) output file, with

all data aligned in 16- or 8-bit fields. This format is not

only much easier to generate initially, but also facilitates

reading of the data by other software for quality control

(QC); it can be ingested and processed directly by the

SDPS for internal testing of its systems and all downstream

functions (QC and data archiving).

The level-0 files are then processed to compress the

16-bit words to 10 bits to simulate the spacecraft format.

16
W.W. Gregg, F.S. Patt, and R.H. Woodward

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The Simulated SeaWiFS Data Set, Version 2

18
W.W. Gregg, F.S. Patt, and R.H. Woodward

Table 12. SeaStar spacecraft telemetry engineering conversion of analog telemetry.

Analog Telemetry Points Units Start Byte Slope Intercept

Byte Length

Orbit X position (ECEF) m 143 4 0.00391155 −8400000.0

Orbit Y position (ECEF) m 147 4 0.00391155 −8400000.0

Orbit Z position (ECEF) m 151 4 0.00391155 −8400000.0

Orbit X velocity (ECEF) m s−1 155 4 3.49246E-6 −7500.0

Orbit Y velocity (ECEF) m s−1 159 4 3.49246E-6 −7500.0

Orbit Z velocity (ECEF) m s−1 163 4 3.49246E-6 −7500.0

Attitude yaw angle degrees 121 2 0.00549316 −180.0

Attitude roll angle degrees 123 2 0.00549316 −180.0

Attitude pitch angle degrees 125 2 0.00549316 −180.0

Sun sensor 1 angle 1 degrees 61 2 0.001953125 −64.0

Sun sensor 1 angle 2 degrees 63 2 0.001953125 −64.0

Sun sensor 2 angle 1 degrees 67 2 0.001953125 −64.0

Sun sensor 2 angle 2 degrees 69 2 0.001953125 −64.0

Sun sensor 3 angle 1 degrees 73 2 0.001953125 −64.0

Sun sensor 3 angle 2 degrees 75 2 0.001953125 −64.0

Earth scanner 1 phase degrees 79 2 0.005493164 0.0

Earth scanner 1 width degrees 81 2 0.005493164 0.0

Earth scanner 2 phase degrees 85 2 0.005493164 0.0

Earth scanner 2 width degrees 87 2 0.005493164 0.0

ECEF = Earth-Centered Earth-Fixed

Place holders are inserted for the frame synch words to be

filled by the DCF. These files are then used by the DCF

and the GSFC Code 500 Simulation Operations Center

(SOC) to generate simulated data tapes which can be used

to test the WFF data receipt, transmission to GSFC, and

PFF processing. Adescription of the DCF and SOC simulation support is beyond the scope of this paper. All

of the scan lines and telemetry corresponding to each data

collection period are collected and formatted as a unit.

The methods involved in formatting the individual fields

and packets for the minor frames are different for each type

of data and are as follows. The spacecraft ID is computed

for each minor frame from the frame number and the data

type. As shown in Fig. 9, there are three minor frames

per major frame; the frame number is started at 1 at the

beginning of each data collection period and cycled for all

frames in the period. The time tag is converted to two

integer fields corresponding to the truncated Julian day

(days since 13 January 1993, at midnight GMT, Julian

day 2,449,000.5) and the milliseconds of the day; the significant bits of these two fields are combined into a 40-bit

time tag, which is divided into four 10-bit words.

The spacecraft telemetry fields are digitized and stored

according to the best available specifications from OSC

(Table 12). Note that these specifications have not been

updated since September 1992 and are very likely to change

prior to launch. Spacecraft fields are included only for the

first minor frame of each major frame, corresponding to

spacecraft (S/C) state of health (SOH) telemetry, (field 1

in Fig. 9). OSC has designated fields 2 and 3 as dynamic

and are therefore, not useful for data processing. All fields

are digitized using a linear conversion (with a specified

slope and offset) and stored in either 16 or 32 bits. The remaining spacecraft packet bytes are set to arbitrary values

(determined as the byte offset modulo 256).

The instrument telemetry specifications are shown in

Table 13. Note that, although the instrument data are

included in the 10-bit portion of the minor frame, in fact

only the 8 least significant bits (LSB) of each word are

used. The instrument analog telemetry fields also use linear digitization specifications. The measured tilt angle is

the only actively simulated analog value. The tilt alignment status and the sensor mode (Earth or solar) are used

to set the appropriate discrete status bits; the mirror side

bit is alternated for the LAC scan lines. The time tag is

set to the milliseconds since the last exact second. The

remaining fields are set to fixed, but realistic, values as

stated above.

The ancillary data specifications are shown in Table 14.

The ancillary data fields use signed integers rather than

linear conversions for digitization; the units are meters and

meters per second for the orbit data, and microradians for

the attitude angles. The time tag is set to the millisecondsof-day.

The gain and TDI for each band are combined into a

single 10-bit field, with the 8 fields corresponding to the 8

bands immediately preceding each scan line in the minor

frame, as shown in Fig. 9. (Note that the gain values in

the data are 0 through 3, corresponding to gains 1 through

4 in Table 5.) Each scan line is also preceded in the frame

19
The Simulated SeaWiFS Data Set, Version 2

Table 13. SeaStar instrument telemetry specification.

Word Bit Time Stamp of Sync Pulse Word SeaWiFS Analog

Number Number in Scan Line Number Telemetry

1 Milliseconds Since Last GPS Pulse 8 Band 1 and 2 FPA Temperature2

2 Milliseconds Since Last GPS Pulse 9 Band 3 and 4 FPA Temperature

3 Milliseconds Since Last GPS Pulse 10 Band 5 and 6 FPA Temperature

4 Milliseconds Since Last GPS Pulse 11 Band 7 and 8 FPA Temperature

Word No. Bit No. SeaWiFS Discrete Telemetry 12 Telescope Motor Temperature

5 1 Pad 13 Tilt Base Temperature

5 2 Pad 14 Tilt Platform Temperature

5 3 Servo A or B Select 15 Half Angle Motor Temperature

5 4 AMC On1 16 Power Supply A Input Current

5 5 Servo A Locked 17 Power Supply B Input Current

5 6 Servo B Locked 18 +15 V Analog Power Voltage

5 7 Timing A or B Select 19 −15 V Analog Power Voltage

5 8 Tilt A On 20 +5 V Logic Power Voltage

5 9 Tilt B On 21 Power Supply Temperature

5 10 Tilt Telemetry On 22 B1 and B2 Post-amplifier Temperature

6 1 Pad 23 Servo Driver Temperature

6 2 Pad 24 +30 V Servo Power Voltage

6 3 Stow On 25 +21 V Servo Power Voltage

6 4 Stow Aligned 26 −21 V Servo Power Voltage

6 5 Heaters Enable 27 +5 V Servo Power Voltage

6 6 Solar Door Status 28 AMC Phase Error

6 7 Analog Power On 29 Tilt Platform Position

6 8 Tilt Platform Limit 30 Tilt Base Position

6 9 Tilt Base Limit 31 +28V Heater Power

6 10 Tilt Nadir (0◦) Aligned 32 Telescope A Motor Current

7 1 Pad 33 Telescope B Motor Current

7 2 Pad 34 Half-Angle Mirror A Motor Current

7 3 Tilt Aft (+20◦) Aligned 35 Half-Angle Mirror B Motor Current

7 4 Tilt Forward (−20◦) Aligned 36 Servo A Phase Error

7 5 Data Mode Select 37 Servo B Phase Error

7 6 Half Angle Mirror Side 38 AMC A Motor Current

7 7 Image Data Sync 39 AMC B Motor Current

7 8 AMC at Speed Word No. Padding to Fill 44 Word Field

7 9 AMC at Speed 40 Spare

7 10 Spare 41 Spare

42 Spare

43 Spare

44 Spare

AMC = Angular Momentum Compensation

FPA = Focal Point Assembly

by start synch and dark restore pixels, and followed by a

stop synch pixel. Thus, the total number of stored pixels

per scan line is three more than the actual number of data

pixels (1,288 for LAC and 251 for GAC). The start and

stop synchs are set to alternating values of 0 and 1,023 (10

binary ones) based on information provided by OSC, while

the dark restore value is arbitrarily set to 20 for all bands.

The scan line radiances are initially computed using

the full 16-bit dynamic range, to allow realistic computation of the sensor saturation response. The final step prior

to inclusion in the minor frame is to truncate all values

to 1,023 (maximum 10-bit value). The completed minor

frame is then written to the level-0 simulated data file.

4. EXAMPLES OFDATA

This section includes examples of GAC, stored LAC,

and real-time HRPT data.

20
W.W. Gregg, F.S. Patt, and R.H. Woodward

4.1 GAC Data

Simulated Version 2 data for SeaWiFS band 1 for the

second (daytime) downlink on 25 March 1994, mapped to

Earth coordinates, shows how the descending node orbit

acquires GAC data (Fig. 11). This image shows eight full

descending nodes of data, plus a partial node over Wallops

prior to a daytime downlink (the Wallops visibility mask

is illustrated). Approximately half of an overpass at Wallops results in downlinked data for that opportunity since

the spacecraft contains two onboard data recorders—one

transmits while the other acquires. The remaining half of

the data taken during the overpass will be received at the

next (night) downlink.

In Fig. 11, the grey scale shows lower (darker) to higher

(lighter) count values representing total, at-satellite radiances. White indicates saturation; in this case, due almost

entirely to clouds and ice. (See also Plate 1, where a blueto-green-to-red scale is used, and the brightest red indicates saturation.) Some saturated pixels, however, may be

noted in the Saharan Desert. Note that even clouds and

ice do not saturate at higher latitudes due to reduced incident irradiance. The pinching of the swath width near

the equator shows the effects of the tilt change. The tilt

change requires the sensor to pass through nadir, where

the swath width is reduced relative to tilted scans. The

black speckles in this region indicate lost coverage due to

excessively large effective ground speed, a function of the

orbital speed and the tilt change speed (see Fig. 1). It

is not clear how well data collected during a tilt change

will be navigated due to attitude perturbations resulting

from the tilt motor. In this simulated data set, no such

perturbations were allowed to occur and pointing information is as well known as anywhere in the orbit. Other than

navigation difficulties and a large occurrence of sun glint,

data collected during a tilt change is expected to be of high

scientific quality.

Whereas band 1 saturates only over clouds, ice, and

parts of the Saharan Desert, band 8 saturates over nearly

all land features (Fig. 12; Plate 1). This is because vegetated areas have large reflectance in the near-infrared regions of the solar spectrum (Fig. 6).

Arelatively cloud-free portion of a GAC orbit was selected to show how GAC data will actually look, as received, in the data stream. Asection for band 1 shows

Haiti and the Dominican Republic—near the center of the

image—as dark, with Puerto Rico slightly to the east

(Fig. 13; Plate 2). Greater variability is seen over the land

than over the oceans. This is because ocean at-satellite radiances are dominated by the atmosphere (approximately

90% of the total), and in particular, Rayleigh scattering.

Some minor brightening may be seen near the scan edges

due to increased Rayleigh scattering as a function of the

greater atmospheric path length here.

An image of band 8 shows land as saturated once again

(Fig. 14; Plate 2). The blocky, rectangular features now

Table 14. SeaStar ancillary telemetry specification.

Word No. Time Reference

1 Milliseconds since Midnight UTC

(MSB first)

2 Milliseconds since Midnight UTC

3 Milliseconds since Midnight UTC

4 Milliseconds since Midnight UTC

(LSB last)

Word No. Orbit Position Data1

5 X (MSB first)2

6 X

7 X

8 X (LSB last)

9 Y (MSB first)

10 Y

11 Y

12 Y (LSB last)

13 Z (MSB first)

14 Z

15 Z

16 Z (LSB last)

Word No. Orbit Velocity Data3

17 X ̇ (MSB first)

18 X ̇ (LSB last)

19 Y ̇ (MSB first)

20 Y ̇ (LSB last)

21 Z ̇ (MSB first)

22 Z ̇ (LSB last)

Word No. Attitude Angular Position Data4

23 Φ (MSB first)

24 Φ (LSB last)

25 θ (MSB first)

26 θ (LSB last)

27 Ψ (MSB first)

28 Ψ (LSB last)

Word No. Attitude Angular Rates Data5

29 Φ ̇ (MSB first)

30 Φ ̇ (LSB last)

31  ̇

θ (MSB first)

32  ̇

θ (LSB last)

33 Ψ ̇ (MSB first)

34 Ψ ̇ (LSB last)

35–44 Spare

1. ECEF Cartesian, units are in meters.

2. MSB is the acronym for most significant bits.

3. ECEF Cartesian, units are in m s−1.

4. Spacecraft centered coordinate system of roll and pitch

(Φ and θ, respectively), and yaw (Ψ); all of the units are

in μrad.

5. Spacecraft centered coordinate system of roll and pitch

(Φ and θ, respectively), and yaw (Ψ); all of the units are

in μrad s−1.

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The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

23
The Simulated SeaWiFS Data Set, Version 2

Fig. 13. Aportion of Version 2 simulated SeaWiFS GAC data, band 1, in satellite coordinates (i.e.,

scan is x axis, orbit propagation direction is y axis). The Dominican Republic and Haiti is the dark

object near the center of the image, with Puerto Rico just to the east. The grey scale indicates low

at-satellite radiance (dark) to high radiance (bright). All of the bright white objects in this image are

clouds.

24
W.W. Gregg, F.S. Patt, and R.H. Woodward

Fig. 14. As in Fig. 13 but for band 8. Land features are saturated in band 8.

25
The Simulated SeaWiFS Data Set, Version 2

26
W.W. Gregg, F.S. Patt, and R.H. Woodward

visible, are the result of the coarse resolution wind speed

and pressure fields used to compute aerosol and sun glint,

and Rayleigh scattering contributions, respectively. Some

evidence of minor sun glint contamination may be seen in

the southern portion of the image, near the center, before

obscuration by clouds. Because of the small saturation

radiance in band 8 (see Table 10), this band is particularly

subject to sun glint contamination, even though greater

values occur at other bands.

4.2 Stored LAC Data

Stored LAC data collection in the simulated data set

follows the command schedule described earlier. The in

situ target data acquisition schedule for 25 March 1994,

is shown in Fig. 15. Simulated LAC data for the second

(daytime) downlink on 25 March conform to three of the

in situ target sites (Fig. 16). Many of the other target

sites are included in the first (nighttime) downlink on 26

March 1994 (Fig. 17), although they appear in the schedule

for March 25 because actual data collection occurs at this

time. The remaining targets in the 25 March schedule are

downlinked at the next Wallops overpass. This scenario

illustrates the difficulties in creating schedule data that

occur on GMT boundaries and data collection which is

tied to local noon and midnight Wallops overpasses.

Actual images of the first three LAC segments in band

1 show the high spatial resolution of LAC data (Fig. 18;

Plate 3). The first segment occurs over Saudi Arabia, and

the second over South Africa, and the third over Cuba

(Fig. 19), in a similar view of the GAC image shown earlier (Fig. 13), but exhibiting the larger swath width of

LAC data. Note that the saturation at the scan edges

on all three segments is due to the very large atmospheric

path length (nearly 72◦ spacecraft zenith angle tilted) in

this Version 2 data. Asolar calibration with an intergain

check is also included in the LAC data on each day of the

simulated data set. Adepiction of solar calibration and

intergain check LAC data is shown in Fig. 20. Recall that

the procedure involved acquiring data in solar mode off

the solar diffuser at specified gains first, followed by intergain checks using the so-called calibration pulse. The

truncated object on the left represents the solar calibration

data, while the perpendicular stripe represents the results

of the calibration pulse, which is solid in color until completion of the solar calibration. Then the intergain check

begins, represented by alternating bands of six scans at

selected gains.

The TDI check is similar to the solar calibration activity, but is shorter in duration (Fig. 21). Although solar

diffuser data appear brighter in the center, they are not in

this simulation. The increased brightness is due to different grey scaling given the absence of the intergain check.

Data from different detector combinations are assumed to

be identical in this simulated set.

Afull moon occurs during the period of the simulated

data set. The required 7◦ phase angle for data acquisition

actually occurs in the GMT morning of 27 March 1994.

Simulation of the lunar calibration uses data collected from

an actual scan of the full moon from the SeaWiFS sensor

in December 1992. These data produced the image shown

in Fig. 22. For the simulated data set, the actual moon

data were packaged into a realistic scan of two minutes in

duration, showing the actual size of the moon within the

downlinked SeaWiFS scan data (Fig. 23).

4.3 Real-Time HRPT Data

Simulated data acquired at the GSFC HRPT station

are also provided in this data set. Mapped to Earth coordinates, a single overpass of SeaStar at the GSFC station

appears as in Fig. 24, where the GSFC visibility mask is

denoted. This overpass is band 1, and is the first pass

of 25 March 1994. Thus, the pass may be related to the

corresponding GAC image (Fig. 11). Note that the data

collection does not obey the GSFC station mask boundaries. This is a result of the fact that the sensor is tilted

aft of the velocity vector at this location, and the fact that

the sensor scans 58◦ west-to-east of the satellite position.

Anon-mapped view of Version 2 simulated real-time

HRPT data is provided for band 1 in Fig. 25 (also Plate

4). The Florida peninsula is visible at the western edge of

the scan, with Cuba, Haiti, and the Dominican Republic,

and Puerto Rico successively west-to-east along the southern portion of the image. One may note significant saturation along the extreme western edge of the scans. This

image corresponds directly with the GAC image shown

earlier (Fig. 13), as well as with the third recorded LAC

segment shown in Fig. 19. This sequence of images shows

the relationships among GAC data, stored LAC data, and

real-time HRPT data.

Version 2 HRPT data for band 8 shows once again that

land saturates at this wavelength (Fig. 26; Plate 5). What

is particularly notable is the high resolution of land features, resulting from the use of the high resolution WVS

land mask.

4.4 Version 2 Sensor Saturation Response

The April 1993 sensor saturation response is fairly subtle and consequently is not readily apparent in the images

discussed up to now. Aclose-up view is provided here of

a portion of an HRPT image to illustrate the saturation

response effects. The image portion chosen is a segment on

the east coast of Puerto Rico, where a number of saturating

islands and coastlines occur. Band 8 was chosen because

it saturates over these land features (bands 1–5 most likely

will not saturate here). The evidence is again somewhat

subtle, but saturation effects appear as a kind of blurring

preceding (stray light effects) and following (bright target

recovery effects) small land objects (Fig. 27; Plate 6).

27
The Simulated SeaWiFS Data Set, Version 2

28
W.W. Gregg, F.S. Patt, and R.H. Woodward

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The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

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The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

33
The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

35
The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

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The Simulated SeaWiFS Data Set, Version 2

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W.W. Gregg, F.S. Patt, and R.H. Woodward

39
The Simulated SeaWiFS Data Set, Version 2

5. DATA AVAILABILITY

The data set containing 16-bit science data (frame formatter output or level-0 data) is available on Internet from

the GSFC DAAC. The address is: eosdata.gsfc.nasa.gov.

Log in as anonymous with password guest, then change

directories to pub/seawifs. All files begin with S followed

by the year, so all files belonging to this simulated data set

(Version 2) will begin with S1994. GAC files end with the

suffix L0 GAC, recorded LAC files with L0 LAC and HRPT

files with L0 HRPT. Assistance may be obtained by dialing

301–286–3209. Please note that for the mission, authorization must be obtained before acquiring the data.

The data files containing 10-bit science data (onboard

structure) were intended to be used internally for endto-end system testing. The data are available from the

authors on 4 mm tape for Silicon Graphics IRIX or Sun

SunOS systems.

Acknowledgments

The authors are indebted to a large number of people for their

assistance and advice which was required due to the complexity of this undertaking. They are in alphabetical order: Robert

Barnes (Man Tech Environmental), Frank Corprew (HughesSTX), Gene Feldman (GSFC), Mary James (GSFC), Ken Lambert (University of Maryland), Robert Mack (Hughes-STX),

and George Riggs (Research and Data Systems, Corp.). We

would also like to thank Wayne Esaias for critical comments on

the manuscript, and for encouraging us to submit it despite the

sensor modifications agreed upon after the completion of this

effort. smallbreak

Glossary

AMC Angular Momentum Compensation

AVHRR Advanced Very High Resolution Radiometer

BTR Bright Target Recovery

CZCS CoastalZone Color Scanner

DAAC Distributed Active Archive Center

DCF Data Capture Facility

ECEF Earth-Centered Earth-Fixed

FNOC Fleet Numerical Oceanography Center

FPA FocalPoint Assembly

GAC Global Area Coverage

GMT Greenwich Mean Time

GPS Global Positioning System

GSFC Goddard Space Flight Center

HRPT High Resolution Picture Transmission

ICD Interface ControlDocument

ISCCP International Satellite Cloud Climatology Project

LAC LocalArea Coverage

LSB Least Significant Bits

MSB Most Significant Bits

NASA NationalAeronautics and Space Administration

NASCOM NASA Communications

NCDS NASA Climate Data System

NDVI Normalized Difference Vegetation Index

NER Noise Equivalent Radiance

NGDC NationalGeophysicalData Center

NIMBUS Not an acronym, a series of NASA experimental

weather satellites containing a wide variety of atmosphere, ice, and ocean sensors.

NORAD North American Air Defense (Command)

OSC OrbitalSciences Corporation

PFF Programmable Frame Formatter

QC Quality Control

SBRC (Hughes) Santa Barbara Research Center

S/C Spacecraft

SDPS SeaWiFS Data Processing System

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SOC Simulation Operations Center

SOH State of Health

TDI Time-Delay and Integration

TOMS TotalOzone Mapping Spectrometer

WFF Wallops Flight Facility

WVS World Vector Shoreline

Symbols

a A constant equalto −20/tanh(2).

ao Oxygen absorption coefficient.

aoz Ozone absorption coefficient.

awv Coefficient for water vapor absorption.

b A constant equalto 1/3.

DC Digitalcount value.

Ed Incident downwelling irradiance.

F0(λ) Mean extraterrestrialspectralirradiance.

G Gain factor.

LNERλ) Noise equivalent radiance.

Lsat(λ) Saturation radiance for the sensor.

Lt(λ) At-satellite radiance.

M Atmospheric slant path length.

P Localsurface pressure.

P0 Standard pressure.

s(λ) Slope for the range 0–1,023.

t Time in seconds.

T Tilt position.

V Volts.

X ECEF X component of orbit position.

X ̇ ECEF X component of orbit velocity.

Y ECEF Y component of orbit position.

Y ̇ ECEF Y component of orbit velocity.

Z ECEF Z component of orbit position.

Z ̇ ECEF Z component of orbit velocity.

λ Wavelength of light.

Ψ Yaw.

Ψ Yaw rate.  ̇

Φ Roll.

Φ Roll rate.  ̇

ρc,i Reflectance of clouds and ice.

θ Pitch.

 ̇

θ Pitch rate.

θ0 Solar zenith angle.

τr Rayleigh optical thickness.

τ 

r Pressure corrected Rayleigh optical thickness.

τro Rayleigh optical thickness weighted by the SeaWiFS

spectralresponse.

40
W.W. Gregg, F.S. Patt, and R.H. Woodward

References

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Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 17 pp.

, and F.S. Patt, 1993: Assessment of tilt capability for

spaceborne global ocean color sensors. IEEE Trans. Geosci.

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Coastal Zone Color Scanner (CZCS) level-1 data product

users’ guide. NASA Tech. Memo. 86203, NASA Goddard

Space Flight Center, Greenbelt, Maryland, 49 pp.

Woodward, R.H., R.A. Barnes, C.R. McClain, W.E. Esaias,

W.L. Barnes, and A.T. Mecherikunnel, 1993: Modeling of

the SeaWiFS solar and lunar observations. NASA Tech.

Memo. 104566, Vol. 10, S.B. Hooker and E.R. Firestone,

Eds., 26 pp.

The SeaWiFS Technical Report Series

Vol. 1

Hooker, S.B., W.E. Esaias, G.C. Feldman, W.W. Gregg, and

C.R. McClain, 1992: An Overview of SeaWiFS and Ocean

Color. NASA Tech. Memo. 104566, Vol. 1, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 24 pp., plus color plates.

Vol. 2

Gregg, W.W., 1992: Analysis of Orbit Selection for SeaWiFS:

Ascending vs. Descending Node. NASA Tech. Memo.

104566, Vol. 2, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16 pp.

Vol. 3

McClain, C.R., W.E. Esaias, W. Barnes, B. Guenther, D. Endres, S. Hooker, G. Mitchell, and R. Barnes, 1992: Calibration and Validation Plan for SeaWiFS. NASA Tech.

Memo. 104566, Vol. 3, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 41 pp.

Vol. 4

McClain, C.R., E. Yeh, and G. Fu, 1992: An Analysis of GAC

Sampling Algorithms: A Case Study. NASA Tech. Memo.

104566, Vol. 4, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 22 pp., plus color plates.

Vol. 5

Mueller, J.L., and R.W. Austin, 1992: Ocean Optics Protocols. NASA Tech. Memo. 104566, Vol. 5, S.B. Hooker and

E.R. Firestone, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 43 pp.

Vol. 6

Firestone, E.R., and S.B. Hooker, 1992: SeaWiFS Technical

Report Series Summary Index: Volumes 1–5. NASA Tech.

Memo. 104566, Vol. 6, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 9 pp.

Vol. 7

Darzi, M., 1992: Cloud Screening for Polar Orbiting Visible

and IR Satellite Sensors. NASA Tech. Memo. 104566, Vol.

7, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 7 pp.

Vol. 8

Hooker, S.B., W.E. Esaias, and L.A. Rexrode, 1993: Proceedings of the First SeaWiFS Science Team Meeting. NASA

Tech. Memo. 104566, Vol. 8, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 61 pp.

Vol. 9

Gregg, W.W., F.C. Chen, A.L. Mezaache, J.D. Chen, J.A.

Whiting, 1993: The Simulated SeaWiFS Data Set, Version 1. NASA Tech. Memo. 104566, Vol. 9, S.B. Hooker

and E.R. Firestone, Eds., NASA Goddard Space Flight

Center, Greenbelt, Maryland, 17 pp.

Vol. 10

Woodward, R.H., R.A. Barnes, C.R. McClain, W.E. Esaias,

W.L. Barnes, and A.T. Mecherikunnel, 1993: Modeling of

the SeaWiFS Solar and Lunar Observations. NASA Tech.

Memo. 104566, Vol. 10, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 26 pp.

Vol. 11

Patt, F.S., C.M. Hoisington, W.W. Gregg, and P.L. Coronado,

1993: Analysis of Selected Orbit Propagation Models for

the SeaWiFS Mission. NASA Tech. Memo. 104566, Vol.

11, S.B. Hooker, E.R. Firestone, and A.W. Indest, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 16 pp.

Vol. 12

Firestone, E.R., and S.B. Hooker, 1993: SeaWiFS TechnicalReport Series Summary Index: Volumes 1–11. NASA Tech.

Memo. 104566, Vol. 12, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 28 pp.

41
The Simulated SeaWiFS Data Set, Version 2

Vol. 13

McClain, C.R., K.R. Arrigo, J. Comiso, R. Fraser, M. Darzi,

J.K. Firestone, B. Schieber, E-n. Yeh, and C.W. Sullivan, 1993: Case Studies for SeaWiFS Calibration and Validation, Part 1. NASA Tech. Memo. 104566, Vol. 13,

S.B. Hooker and E.R. Firestone, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 52 pp., plus

color plates.

Vol. 14

Mueller, J.L., 1993: The First SeaWiFS Intercalibration RoundRobin Experiment, SIRREX-1, July 1992. NASA Tech.

Memo. 104566, Vol. 14, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 60 pp.

Vol. 15

Gregg, W.W., F.S. Patt, R.H. Woodward, 1993: The Simulated SeaWiFS Data Set, Version 2. NASA Tech. Memo.

104566, Vol. 15, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 42 pp., plus color plates.

42
W.W. Gregg, F.S. Patt, and R.H. Woodward

COLOR PLATES

The following color plates are presented as submitted by the authors.
The Simulated SeaWiFS Data Set, Version 2

Plate 1. Top: Simulated SeaWiFS GAC data, 25 March 1994, band 1, mapped to Earth coordinates.

Bottom: band 8.
W.W. Gregg, F.S. Patt, and R.H. Woodward

Plate 2. Left: Aportion of simulated SeaWiFS GAC data, band 1, in satellite coordinates (i.e., scan is

x axis, orbit propagation direction is y axis). The Dominican Republic and Haiti is the dark blue object

near the center of the image, with Puerto Rico to the east. The color scale indicates low at-satellite

radiance (dark blue) to high radiance (bright red). All of the bright red objects in this image are clouds.

Left: band 8. Land features are saturated in band 8.
The Simulated SeaWiFS Data Set, Version 2
W.W. Gregg, F.S. Patt, and R.H. Woodward
The Simulated SeaWiFS Data Set, Version 2
W.W. Gregg, F.S. Patt, and R.H. Woodward
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 and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of

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 January 1994 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

 SeaWiFS Technical Report Series

 Volume 15–The Simulated SeaWiFS Data Set, Version 2

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

6. AUTHOR(S)

Watson W. Gregg, Frederick S. Patt, and Robert H. Woodward

Laboratory for Hydrospheric Processes

Goddard Space Flight Center 94B00041

Greenbelt, Maryland 20771 Code 970.2

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING

 AGENCY REPORT NUMBER

National Aeronautics and Space Administration

Washington, D.C. 20546–0001 TM–104566, Vol. 15

11. SUPPLEMENTARY NOTES

12a. DISTRIBUTION/AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE

Frederick S. Patt, Robert H. Woodward, and Elaine R. Firestone: General Sciences Corporation, Laurel, Maryland.

13. ABSTRACT (Maximum 200 words)

This document describes the second version of the simulated SeaWiFS data set. A realistic simulated data set is essential

for mission readiness preparations and can potentially assist in all phases of ground support for a future mission. The

second version improves on the first version primarily through additional realism and complexity. This version incorporates a representation of virtually every aspect of the flight mission. Thus, it provides a high-fidelity data set for testing

several aspects of the ground system, including data acquisition, data processing, data transfers, calibration and validation, quality control, and mission operations. The data set is constructed for a seven-day period, 25–31 March 1994.

Specific features of the data set include Global Area Coverage (GAC), recorded Local Area Coverage (LAC), and realtime High Resolution Picture Transmission (HRPT) data for the seven-day period. A realistic orbit, which is propagated

using a Brouwer-Lyddane model with drag, is used to simulate orbit positions. The simulated data corresponds to the

command schedule based on the orbit for this seven-day period. It includes total (at-satellite) radiances not only for

ocean, but for land, clouds, and ice. The simulation also utilizes a high-resolution land-sea mask. It includes the April

1993 SeaWiFS spectral responses and sensor saturation responses. The simulation is formatted according to July 1993

onboard data structures, which include corresponding telemetry (instrument and spacecraft) data. The methods are

described and some examples of the output are given. The instrument response functions made available in April 1993

have been used to produce the Version 2 simulated data. These response functions will change as part of the sensor

improvements initiated in July–August 1993.

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

SeaWiFS, Oceanography, GAC Data, LAC Data, Orbit Propagation, Navigation, 51

Command Schedules, At-Satellite Radiances, Sensor Saturation Response,

Data Formatting, HRPT Data