NASA Technical Memorandum 104566, Vol. 38

SeaWiFS Technical Report Series

Stanford B. Hooker and Elaine R. Firestone, Editors

Volume 38, SeaWiFS Calibration and Validation

Quality Control Procedures

Charles R. McClain, Michael Darzi, Robert A. Barnes, Robert E. Eplee,

James K. Firestone, Frederick S. Patt, Wayne D. Robinson, Brian D. Schieber,

Robert E. Woodward, and Eueng-nan Yeh

August 1996
NASA Technical Memorandum 104566, Vol. 38

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 38, SeaWiFS Calibration and Validation

Quality Control Procedures

Charles R. McClain

NASA Goddard Space Flight Center, Greenbelt, Maryland

Michael Darzi, Robert A. Barnes, Robert E. Eplee, James K. Firestone, Frederick S. Patt,

Wayne D. Robinson, Brian D. Schieber, Robert E. Woodward, and Eueng-nan Yeh

General Sciences Corporation, Laurel, Maryland

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

1996
SeaWiFS Calibration and Validation Quality Control Procedures

Preface

The scope of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Calibration and Validation Program

encompasses a broad variety of topics, as shown by numerous volumes (of so-called case studies) in the SeaWiFS Technical Report Series which are in a chapter format. Each case studies volume contains several chapters

discussing topics germane to the Calibration and Validation Program. Although this document, Volume 38, is

not a case studies volume per se, it further demonstrates both the breadth and complexity of the issues that the

Program must address, and provides further justification for a comprehensive calibration and validation effort.

The chapters in this volume present discussions of:

a) Engineering data display and quality control;

b) SeaWiFS calibration verification;

c) Quality control of SeaWiFS ancillary data;

d) SeaWiFS data quality control software; and

e) SeaWiFS derived product validation software.

Greenbelt, Maryland —C.R.M.

September 1995 Project Scientist

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McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table of Contents

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

1. Engineering Data Display and Quality Control ....................................................... 4

1.1 Introduction ......................................................................................... 4

1.2 Data Processing ..................................................................................... 4

1.3 Analysis Software ....................................................................................6

2. SeaWiFS Calibration Verification ................................................................... 10

2.1 Introduction ........................................................................................10

2.2 At-Sensor Radiances ................................................................................11

2.3 On-Orbit Calibration ............................................................................... 11

2.4 Vicarious Calibration ............................................................................... 12

2.5 Calibration Evaluation ............................................................................. 14

2.6 Sensor Characterization ............................................................................ 14

2.7 Data Archiving Strategy ............................................................................17

3. The Quality Control of SeaWiFS Ancillary Data .................................................... 20

3.1 Introduction ........................................................................................20

3.2 Noninteractive QC ................................................................................. 20

3.3 Interactive QC ..................................................................................... 22

4. SeaWiFS Data Quality Control Software ............................................................24

4.1 Software Overview ..................................................................................24

4.2 Level-1a QC Program .............................................................................. 25

4.3 Level-2 QC Program ............................................................................... 26

4.4 Level-3 QC Program ............................................................................... 33

4.5 Automatic QC Programs ........................................................................... 37

4.6 QC Procedure Details .............................................................................. 37

5. SeaWiFS Derived Product Validation Software ......................................................42

5.1 Introduction ........................................................................................42

5.2 Match-up Methodology ............................................................................. 42

5.3 Match-up Evaluation ............................................................................... 48

5.4 Databases .......................................................................................... 59

5.5 Conclusions ........................................................................................ 59

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

Symbols ................................................................................................ 60

References ............................................................................................ 60

The SeaWiFS Technical Report Series ............................................................ 62

iii
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Abstract

This document provides five brief reports that address several quality control procedures under the auspices of

the Calibration and Validation Element (CVE) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

Project. Chapter 1 describes analyses of the 32 sensor engineering telemetry streams. Anomalies in any of the

values may impact sensor performance in direct or indirect ways. The analyses are primarily examinations of

parameter time series combined with statistical methods such as auto- and cross-correlation functions. Chapter 2

describes how the various onboard (solar and lunar) and vicarious (in situ) calibration data will be analyzed to

quantify sensor degradation, if present. The analyses also include methods for detecting the influence of charged

particles on sensor performance such as might be expected in the South Atlantic Anomaly (SAA). Chapter 3

discusses the quality control of the ancillary environmental data that are routinely received from other agencies

or projects which are used in the atmospheric correction algorithm (total ozone, surface wind velocity, and

surface pressure; surface relative humidity is also obtained, but is not used in the initial operational algorithm).

Chapter 4 explains the procedures for screening level-1, level-2, and level-3 products. These quality control

operations incorporate both automated and interactive procedures which check for file format errors (all levels),

navigation offsets (level-1), mask and flag performance (level-2), and product anomalies (all levels). Finally,

Chapter 5 discusses the match-up data set development for comparing SeaWiFS level-2 derived products with

in situ observations, as well as the subsequent outlier analyses that will be used for evaluating error sources.

PROLOGUE

The experience gained with the Coastal Zone Color

Scanner (CZCS) has had a definitive impact on the responsibilities of the Calibration and Validation Element

(CVE) within the Sea-viewing Wide Field-of-view Sensor

(SeaWiFS) Project (McClain et al. 1992). As a result,

the SeaWiFS Project has gone to great lengths to implement and document a multifaceted program that addresses

sensor calibration, bio-optical and atmospheric correction

algorithm development, and product quality control and

validation. The present structure of the program and the

team members are shown in Fig. 1. It includes the elements

responsible for:

1) Determining the SeaWiFS sensor performance;

2) Field programs to collect high quality bio-optical

data;

3) Bio-optical data processing and archiving; and

4) Software development in support of the operational

data processing.

Through a series of meetings, the Project has worked

closely with the SeaWiFS Science Team (SST) subgroups

to define and review the algorithms for sensor calibration,

atmospheric correction, and derived products. Also, the

Project has worked closely with the SeaWiFS Data Analysis System (SeaDAS) development group, funded separately by the National Aeronautics and Space Administration (NASA) Headquarters Marine Biogeochemistry Program, to provide a processing capability available to the

SeaWiFS user community. Many of the SeaWiFS Technical Report Series volumes are the result of work performed

under the CVE, especially in the first three areas listed

above.

Because many of the studies and development efforts

under the auspices of the CVE are not extensive enough

to require dedicated volumes of the SeaWiFS Technical

Report Series, the CVE has decided to publish volumes

composed of brief, but topically specific, chapters. Three

of these volumes have been termed Case Studies and include Volumes 13, 19, and 27. Volume 28 deals with the

mask and flag algorithms, the sensor calibration algorithm,

and a sensor stray light correction algorithm. This volume,

Volume 38, addresses aspects of the CVE primarily associated with: items 1 and 4 (above), the initial operational

procedures for tracking sensor performance, and derived

product quality after launch. A short synopsis of each

chapter in this volume is given below.

1. Engineering Data Display and

Quality Control

The SeaWiFS data stream includes 32 engineering data

fields, which in total provide an indication of the SeaWiFS

instrument’s state of health during the mission. This chapter describes the significance of these data, the methods for

their processing and archiving by the Project, and software

applications built for displaying and quality controlling

these data. The software provides for generating statistics on a scene, latitude zone, or solar zenith angle basis.

The statistics, or raw scene-level engineering data, can be

displayed.

2. SeaWiFS Calibration Verification

The SeaWiFS CVE has undertaken a program to monitor the radiometric response of the SeaWiFS instrument

1
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 1. This CVE organization chart is an updated version of the one presented at the August, 1995, review.

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McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

over the course of its five-year ocean color mission. This

program will employ a combination of on-orbit calibration,

in situ calibration, and sensor characterization techniques

to track sensor performance. The procedures and data sets

that comprise the calibration verification program will be

described in this chapter.

3. Quality Control of SeaWiFS

Ancillary Data

Processing SeaWiFS data requires the use of external, i.e., ancillary, data products to derive the set of SeaWiFS standard geophysical (level-2) parameters. Ancillary meteorological data products of total column ozone

and surface values of zonal and meridional wind speed,

atmospheric pressure, and possibly relative humidity or

total precipitable water, will be used in the level-2 processing. These ancillary data files are provided by the

National Meteorological Center (NMC) and the Television

Infrared Observing Satellite (TIROS) Operational Vertical Sounder (TOVS) project; equivalent products may be

obtained from other sources.

The CVE has developed procedures and software to

assure the quality of the input products processed using

the SeaWiFS Data Processing System (SDPS). Ancillary

data files are converted to a SeaWiFS defined specification

and stored in the Hierarchical Data Format (HDF). The

HDF data undergo quality control (QC) procedures using both noninteractive and interactive programs to assess

their validity. The data are then used for level-2 processing

and are distributed to the research community through the

Goddard Space Flight Center (GSFC) Distributed Active

Archive Center (DAAC). This chapter describes the approaches to QC of SeaWiFS ancillary files through software

used by the SeaWiFS Project.

4. SeaWiFS Data Quality Control Software

This chapter presents the procedures and software employed to monitor and control the quality of the geophysical data from the SeaWiFS instrument aboard the SeaStar

satellite. The quality control programs consist of a set of

automated programs which verify that the data conforms

to broad statistical guidelines, and interactive programs

that allow for more in-depth investigation of problems, as

well as a final level of approval for the data. The QC

programs are applied to the data in all three stages of processing: level-1a, level-2, and level-3. The procedures for

the efficient use of these programs are also discussed.

5. SeaWiFS Derived Product Validation Software

The SeaWiFS derived product validation software was

developed to compare SeaWiFS level-2 data with in situ

data in order to assist in evaluating the sensor performance

and the accuracy of the level-2 algorithms. The software

will be used as part of an effort that will proceed continuously after launch to verify that the data generated by

the SeaWiFS Project for archiving and distributing meet

the required accuracy. The software will also be used to

test algorithms alternative to those used operationally. An

overview of this derived product validation software and its

use is presented herein.

3
SeaWiFS Calibration and Validation Quality Control Procedures

Chapter 1

Engineering Data Display and Quality Control

James K. Firestone

Robert A. Barnes

Robert E. Eplee, Jr.

Robert H. Woodward

Frederick S. Patt

Michael Darzi

General Sciences Corporation, Laurel, Maryland

Charles R. McClain

Goddard Space Flight Center, Greenbelt, Maryland

Abstract

The SeaWiFS data stream includes 32 engineering data fields, which in total provide an indication of the

SeaWiFS instrument’s state of health during the mission. This chapter describes the significance of these data,

the methods for their processing and archiving by the Project, and software applications built for displaying

and quality controlling these data. The software provides for generating statistics on a scene, latitude zone, or

solar zenith angle basis. The statistics, or raw scene-level engineering data, can be displayed.

1.1 INTRODUCTION

SeaWiFS is an ocean color instrument—its primary

measurements are ocean-leaving radiances that have passed

through the top of the atmosphere. As with other Earth

observing satellite instruments, SeaWiFS will be used to

detect short- and long-term changes in the condition of

the planet. It is critically important, however, to distinguish geophysical changes in the Earth-exiting radiances

from apparent changes that will result from the aging of

the sensor on orbit. The SeaWiFS Project has initiated

a program of onboard and vicarious measurements to detect the magnitude of instrumentally-based changes in the

SeaWiFS radiances during the sensor’s on-orbit life.

The QC programs for SeaWiFS engineering data will

be used to gain an understanding of internal changes in the

sensor and to provide relationships between these internal

changes and changes in SeaWiFS radiances. To do this,

the CVE will compile the engineering data stream from the

instrument for each scene and provide a continuous and automatically updated set of statistics about these data. The

engineering data QC software will have the capability of

notifying SeaWiFS Mission Operations if engineering parameters exceed established limits. The principal design

of the software has been for interactive analysis of engineering data to detect 1) trends in the along track values

during an orbit as the spacecraft encounters varying thermal and radiation environments, and 2) long-term trends

in average values (e.g., orbit and zones of latitude and solar

zenith angles), as system components age.

1.2 DATA PROCESSING

The SeaWiFS engineering telemetry data are transmitted in a packet consisting of 44 10-bit words (55 bytes), and

are included in the data stream for two out of every three

scan lines. (Note that the 44-word packet is transmitted

with every scan line, but contains instrument telemetry for

lines 1 and 3 for each set of three; the packet is not used

currently for line 2.) The location and contents of the

engineering telemetry are fully described in the SeaStar

Spacecraft L-band and S-band Downlink Interface Control

Documents [Orbital Sciences Corporation (OSC) internal

documents]. In the local area coverage (LAC) and High

Resolution Picture Transmission (HRPT) data streams,

the packet appears in the minor frame immediately after the spacecraft telemetry and before the gain and time

delay and integration (TDI) words. In the global area coverage (GAC) data, the five packets corresponding to the

five scan lines appear in the minor frame following the scan

line data.

The 44 words of engineering data are allocated as follows:

Words 1–4 represent an instrument time tag.

Words 5–7 are used for instrument discrete telemetry; 22 of the bits are used to represent the instru4
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 1. Engineering telemetry parameters and scaling for SeaWiFS. The table includes absolute limits and Red Limits

for the operation of SeaWiFS.

Analog Telemetry Point Conversion Absolute Limits Red Limits

Slope Intercept Low High Low High

Band 1/2 FPA1 Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Band 3/4 FPATemperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Band 5/6 FPATemperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Band 7/8 FPATemperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Telescope Motor Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Tilt Base Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Tilt Platform Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Half-Angle Motor Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Power Supply-AInput Current2 0.02 0.26 0.26 5.36 1.0 3.0

Power Supply-B Input Current2 0.02 0.26 0.26 5.36 1.0 3.0

+15 V Analog Power Voltage3 0.075 0.0 0.0 19.125 15.0 15.5

−15 V Analog Power Voltage3 −0.075 0.0 −19.125 0.0 −15.5 −15.0

+5 V Logic Power Voltage3 0.025 0.0 0.0 6.375 4.9 5.6

Power Supply Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

B1/B2 Post-Amplifier Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

Servo Driver Temperature −0.2667 66.667 −1.334 66.667 5.0 45.0

+30 V Servo Power Voltage3 0.15 0.0 0.0 38.25 28.5 31.0

+21 V Servo Power Voltage3 0.1044 0.0 0.0 26.622 20.0 22.0

−21 V Servo Power Voltage3 −0.1044 0.0 −26.622 0.0 −22.0 −20.0

+5 V Servo Power Voltage3 0.025 0.0 0.0 6.375 4.9 5.6

Angular Momentum Speed3,4 8.52 −377.0 −377.0 1795.6 1215.0 1255.0

Tilt Platform Position3 1.44 0.0 0.0 367.2 0.0 360.0

Tilt Base Position3 1.44 0.0 0.0 367.2 0.0 360.0

+28 V Heater Power3 0.14 0.0 0.0 35.7 27.0 29.0

Telescope-AMotor Current3,5 0.0024 0.0 0.0 0.612 0.1 0.4

Telescope-B Motor Current3,5 0.0024 0.0 0.0 0.612 0.1 0.4

Half-Angle-A Motor Current3,5 0.0024 0.0 0.0 0.612 0.1 0.4

Half-Angle-B Motor Current3,5 0.0024 0.0 0.0 0.612 0.1 0.4

Servo-APhase Error3,5 0.01 −1.25 −1.25 1.25 −1.0 1.0

Servo-B Phase Error3,5 0.01 −1.25 −1.25 1.25 −1.0 1.0

Angular Momentum Compensation

A-Motor Current3,4,5 0.016 0.0 0.0 4.08 0.08 0.6

Angular Momentum Compensation

B-Motor Current3,4,5 0.016 0.0 0.0 4.08 0.08 0.6

1. Focal Plane Assembly

2. This parameter is dependent upon the choice of power supply. (It does not appear in the instrument discrete telemetry, so it is

assumed to be a spacecraft field.)

3. This parameter is dependent upon the analog power on.

4. This parameter is dependent upon the angular momentum compensation on.

5. This parameter is dependent upon the choice of servo-A or -B.

ment state (for example, Earth or solar mode, tilt

status, or half-angle mirror side) with 8 pads or

spare bits.

Words 8–39 contain the 32 analog telemetry fields,

one field per word.

The remaining five words are spares.

Each of the 32 analog telemetry words contains a physical

quantity which has been scaled to an 8-bit integer value

for transmission in the data stream; the data are padded

to 10 bits. The types of sensor measurements are shown in

Table 1 and include: temperatures, voltages, and currents

for various sensor components; sensor tilt angle measurements; angular rate of the momentum compensator; and

servo phase errors (McClain et al. 1995).

Each measurement type in Table 1 has a linear conversion (slope plus intercept) to physical units. The temperature conversions, which are nonlinear, are approximated

by the linear conversion with sufficient accuracy for limit

checking. Units are in degrees Celsius (temperature), volts

(voltage), amperes (current), or degrees of rotation (position and error). The 8-bit data results in an absolute

measurement range; in addition, most measurements have

a more restricted range for safe operation. The upper and

lower limits of the safe operating range are referred to as

red limits; scan lines with readings outside of these lim5
SeaWiFS Calibration and Validation Quality Control Procedures

its indicate a high probability of a sensor problem and are

flagged in the level-2 SeaWiFS products (McClain et al.

1995). It is also important to note that some telemetry

points have “A” and “B” settings, corresponding to opposite mirror sides; in this case, only one side will be active

at a time, and this will be indicated by a bit in the discrete

telemetry.

The SDPS level-0 to level-1a processing software unpacks and converts the instrument telemetry and stores

them in the level-1a data product. The analog telemetry

are converted and stored in a floating point array, and the

discrete telemetry are unpacked into a byte array (one status bit per byte). The full set of data is stored for each scan

line in the level-1a product. The data are also written to a

separate (nonarchive) instrument telemetry file for off-line

analysis. In addition, the software performs limit checking

on the analog telemetry using the limits in Table 1, and

stores a summary of the data quality as metadata in the

products.

The SDPS level-0 to level-1a processing software also

computes a set of quality metrics for the eight bands of

the level-1a data files. These metrics computed for each

band in the scene are as follows: the number of saturated

pixels, the number of unsaturated pixels, the number of

zero pixels, and the mean radiance in counts. The additional metrics computed are the number of scan lines in

the scene, the number of zero-filled (missing) scan lines in

the scene, and the number of missing minor frames in the

scene. These metrics are stored as metadata in the level-1a

products.

1.3 ANALYSIS SOFTWARE

To facilitate the continuous monitoring of instrument

health and safety during the SeaWiFS mission, two software applications have been written using the Interactive Data Language (IDL) from Research System, Inc.:

ORBSTAT.PRO and TELEMETRY.PRO.

The ORBSTAT.PRO program computes engineering data

statistics for an entire scene, or a specified range of latitude or solar zenith angle within the scene. The program

is run automatically, so the statistics are generated as soon

as the telemetry is available. During statistics generation,

the individual engineering values within the scene will be

compared with the red limits described in Section 1.2. Any

values falling outside of the red limits will be logged to a

file residing on the SeaWiFS CALVAL computing system,

and the Mission Operations element will be notified of the

deviations through electronic mail after the scene is processed. Mission Operations may then choose to notify OSC

if the problems persist, so that OSC is aware of potential

instrument anomalies.

The ORBSTAT.PRO program requires as input a value

representing the field to use for generating zonal statistics

(LAT for latitude or SZA for solar zenith angle) and the increment to be used in defining the statistics zones, e.g., 10◦

of latitude or zenith angle. If a negative number is entered

for the zone increment, the zone type is ignored and statistics are computed for the entire contents of each level-1a

SeaWiFS file, i.e., scene. If the statistics zone increment is

positive, the value is assumed to be an increment of either

latitude or solar zenith angle. Statistics (mean, standard

deviation, and number of observations) are then computed

and written to either new American Standard Code for Information Interchange (ASCII) statistics files or appended

to existing ones. The statistics files are given unique names

which include the zone type (entire scene, solar zenith angle, or latitude), data type [GAC, LAC, solar, lunar, TDI,

intergain calibration (IGC), or HRPT], and engineering

field name (e.g., focal plane temperature).

When statistics by latitude zone have been requested,

north and south extents are computed which entirely encompass the scene for the requested latitude increment.

The northern extent is defined to be the nearest 10◦ increment north of the northern terminus of the scene. The

zones for statistics generation are then defined by applying the increment southward from the northern extent, to

encompass the southern extent. The individual level-1a

HDF scenes are read, and the individual points along the

scene are scanned. Those that fall within particular latitude zones between the northern and southern extents are

included in the statistics for that zone.

Statistics can also be generated by increments of the

solar zenith angle. In a manner similar to that used for

latitude, zones of solar zenith angles are defined which encompass the entire scene in each file. Only values within

the scene having solar zenith angles within one of the computed angle ranges will be included in that range’s statistics.

The files containing statistics for either latitude or solar

zenith angle zones will be ordered chronologically by time.

For each time, there is a second level of ordering by zone

(latitude or zenith angle) in a decreasing sense. A given

statistics file contains values for a particular field in the

engineering data. The files containing statistics by scene

are also ordered chronologically by time, with one line containing the statistics for each time. For all of the files, the

values written to each line are: year, sequential day of the

year, time, orbit number for the current sequential day,

total number of orbits for the current sequential day, spatial or angle range, data mean, data standard deviation,

and the number of elements used in computing mean and

standard deviation. The spatial range includes northern

latitude and longitude extents followed by the southern

latitude and longitude extents, relative to the entire scene

or current latitude increment. (Note that these extents

are not necessarily on the latitude increment boundaries

but reflect the actual data locations along the orbit.) The

angle range, if present, lists the minimum followed by the

maximum solar zenith angle for the current increment.

The ORBSTAT.PRO program compiles the data quality

metrics for each level-1a input file into corresponding metrics tracking files. These tracking files contain one entry

6
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 2. This is the main display for the TELEMETRY.PRO program.

line for each level-1a file, arranged in chronological order.

Each line in the file contains the start time of the level-1a

file and the metrics for each band. In order to avoid duplicate entries in the tracking files, the data quality metrics

are updated only when ORBSTAT.PRO is run solely with the

latitude option.

The TELEMETRY.PRO program is based on an IDL graphical user interface (GUI) for displaying and analyzing the

statistics generated by ORBSTAT.PRO and the raw engineering data values or satellite tracks within SeaWiFS level-1a

HDF scenes. Figure 2 illustrates the main display screen

appearing after TELEMETRY.PRO is started. The screen allows the user to define the criteria for the data or satellite

tracks to be displayed:

a) Spatial and temporal limits,

b) Engineering data fields,

c) Telemetry type,

d) Plot scales,

e) The number of scenes to include in the plots, and

f) The characteristics of background maps including

projection and grid type.

The following notes summarize pertinent information regarding the criteria:

Spatial Limits: This can be specified either by choosing

the option SELECT TRACK SPATIAL LIMITS WITH MOUSE,

whereby the user marks out an area of interest with a

mouse, or by explicitly entering the limits in the text boxes

ENTER NORTH LATITUDE, ENTER SOUTH LATITUDE, etc.

Temporal Limits: The default start time for data selection

is 24 hours prior to the current time, and the default end

time is the current time. The start and end times are

displayed when the interface starts, in the ENTER START

TIME and ENTER FINISH TIME text boxes. The user can

choose to change one or both of these values by manually

entering new ones.

Engineering Data Fields: The scrollable widget SELECT

FIELDS TO PLOT contains an entry for each of the 32 SeaWiFS engineering fields. When creating data plots, the

user must choose one or more of the fields by clicking on

the line containing each field of interest. At any time, the

current list can be cleared by pressing the DESELECT ALL

FIELD(S) button under the scrollable widget.

Data Quality Metric Fields: The scrollable widget entitled

SELECT METRICS TO PLOT contains an entry for each of the

11 data quality metric fields. When creating data plots,

the user must choose one or more of the fields by clicking

on the line containing each field of interest. At any time,

the current list can be cleared by pressing the DESELECT

ALL METRICS button under the scrollable widget.

Telemetry Type: The SELECT TELEMETRY TYPE button,

when pressed, displays a pull-down menu containing the

possible types of scenes for processing. The list includes

GAC, LAC, SOL (solar), LUN (lunar), TDI, IGC, and HRPT. If

the pull-down menu is not accessed, the telemetry type defaults to GAC. The telemetry type selected serves to limit

the subset of scenes to be processed from the archive directory, i.e., only the set with the given telemetry type will

be included for further processing.

Band to Plot: The SELECT A BAND TO PLOT button, when

pressed, allows the user to select one of the eight bands in

order to plot data.

7
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 3. This is the telemetry data display for the TELEMETRY.PRO program.

Plot Scales: The default abscissa plot scale for telemetry

data plots is POINTS ALONG ORBIT, that is, simply a sequential counter within the satellite scene. The user can

choose an abscissa of latitude via the X-AXIS PLOT SCALE

button. For the ordinate scale, the default is a scale encompassing not only the actual data limits, but the red limits

for the telemetry field as well (listed as BROAD SCALE in the

menu next to the DISPLAY TELEMETRY pull-down menu).

The user can also choose an EXPANDED SCALE which encompasses only the actual data limits. Finally, the user

can choose SPECIFIED LIMITS, which results in a prompt

for the minimum and maximum scale values to use.

Scenes to Include in Plots: For either display of satellite

tracks or of telemetry data, the user can specify the number

of scenes to include in the output. For satellite track display, the DISPLAY ORBIT TRACKS FOR LIMITS SPECIFIED

pull-down menu is used. The user can specify that a single scene’s data be displayed on each plot, that all scenes

in the specified spatial range be displayed, or that individual scenes be displayed and not erased as new ones are

added in sequence. For the single scene option, the user

must select a filename from a selection widget containing

all scenes within the desired temporal limits and telemetry type. The appropriate track, or tracks, is displayed

immediately following scene selection.

For telemetry data or data quality metric display, the

DISPLAY TELEMETRY pull-down menu is pressed and has

a similar set of choices as the satellite track display. The

primary difference is that, for sequencing through scenes,

there are two menu choices: using common scaling (i.e.,

the ordinate limits are chosen to encompass limits over all

scenes in the plotting subset) or using independent scaling (i.e., the ordinate will vary with each scene in the sequence). The actual limits to appear on each plot will be

tied to the selection of expanded, broad, or specific scaling.

All but the last three selections in the pull-down menu refer to plots of the raw telemetry data. The DISPLAY DATA

QUALITY METRICS selection plots the data quality metric data. The last two selections, DISPLAY STATISTICS

8
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

BY LATITUDE ZONE and DISPLAY STATISTICS BY ZENITH

ANGLE ZONE, allow the user to plot a time series of statistics by zones of latitude or the solar zenith angle within

a scene (the user chooses the file containing the statistics

from a scrollable list).

Projections: With the SELECT A PROJECTION button, the

user can select any of 12 specified map projections supported by IDL to serve as the background map base for

satellite track plotting. The default is a cylindrical equidistant map.

Grid Types: By default, no grid is placed on the satellite track map; however, the user can choose to have a

grid plotted, either with or without continental boundaries, with the GRID OPTIONS button.

Figure 3 illustrates a sample screen resulting from a

plot of the band 1/2 focal plane temperature and +21 V

servo power voltage for an entire scene. On the plot, the

lines at 5◦ and 45◦ for temperature, and approximately

20.5 V and 21.5 V for servo power voltage, represent the

red limits, while the other lines are the actual data (set to

a constant for the test data set used as input). Note the

button marked SEND TO PRINTER. The user can press this

to obtain a hard copy of the displayed screen on the default

printer. Next to the pull-down menu is a scrollable widget

listing the actions performed in preparing the displayed

plot. Under the button and scrollable widget is a text

widget indicating a default filename to contain a PostScript

representation of the displayed plot. The default name

uses the start and end data times, as well as the telemetry

type and indicator for whether the data falls within a scan

(_scans.ps) or represents statistics across multiple scenes

(_scene.ps). The PostScript file is saved to the user’s

current directory whenever a plot is sent to the printer.

9
SeaWiFS Calibration and Validation Quality Control Procedures

Chapter 2

SeaWiFS Calibration Verification

Robert E. Eplee, Jr.

Robert A. Barnes

Michael Darzi

General Sciences Corporation, Laurel, Maryland

Charles R. McClain

Goddard Space Flight Center, Greenbelt, Maryland

Abstract

The SeaWiFS CVE has undertaken a program to monitor the radiometric response of the SeaWiFS instrument

over the course of its five-year ocean color mission. This program will employ a combination of on-orbit calibration, in situ calibration, and sensor characterization techniques to track sensor performance. The procedures

and data sets that comprise the calibration verification program are described in this chapter.

2.1 INTRODUCTION

SeaWiFS is an eight-band, visible and near-infrared

radiometer with a spatial resolution of 1.1 km at nadir

(Hooker et al. 1992). SeaWiFS is a follow-on instrument to

the CZCS which operated from 1978–86 aboard NIMBUS7. The goal of the SeaWiFS Project, based at NASA

GSFC, is to produce a five-year ocean color data set with

a 5% absolute and 1% relative radiometric accuracy (McClain et al. 1992). The extensive effort to calibrate and

characterize the instrument prior to launch has been documented in Barnes et al. (1994a and 1994b), and Biggar

et al. (1994 and 1995).

As part of the quality control process of the SeaWiFS

archive data products, the CVE will perform a series of extensive calibration verification procedures to monitor the

SeaWiFS instrument’s response over the course of the mission, using a combination of vicarious (based on in situ

observations) and onboard calibration techniques. This effort addresses problems encountered in calibrating CZCS,

wherein the internal calibration, which is based on calibration lamps, proved to be unreliable. This limitation required the application of a vicarious calibration technique

which assumed constant mean normalized water-leaving

radiances (LWN ) at 520 and 550 nm for clear water in the

global ocean (Evans and Gordon 1994). While this restriction may not have been serious for CZCS, given that it was

a proof-of-concept mission, it undermines the objectives of

the SeaWiFS mission. Consequently, SeaWiFS will use imagery of the moon, data from a solar-illuminated diffuser

plate, and a mission-long field program to track the sensor

performance. An overview of the calibration verification

strategy is shown in Fig. 4.

The calibration verification effort has four major areas

of concern in assessing the performance of SeaWiFS:

1) Determining the stability of the radiometric calibration of the instrument;

2) Evaluating the atmospheric correction of the level-2

(L2) data at the vicarious calibration sites;

3) Characterizing any on-orbit changes in the instrument state of health; and

4) Investigating the influence of the South Atlantic

Anomaly (SAA) on the instrument and data.

The CVE will address these areas by analyzing the following data sets:

a) Lunar calibration data taken once per month when

the moon is at a phase of 7◦;

b) Solar diffuser calibration data taken approximately

once per week while the spacecraft is over the South

Pole;

c) L2 LAC scenes taken over vicarious calibration sites

(that is, marine optical buoys and high altitude calibration sites), along with contemporaneous in situ

data from those sites;

d) Level-3 (L3) global distributions of normalized

water-leaving radiances for clear water;

e) On-orbit detector, gain, and mirror-side calibration

data;

f) Spacecraft telemetry data; and

g) On-orbit dark count data.

10
Lunar Data

Sensor Calibration

Stability

On-Orbit

Calibration

Solar Data

Level-2 LAC and Buoy

Comparisons

Sensor Calibration Stability and

Atmospheric Correction

Vicarious

Calibration

Level-2 LAC and High

Altitude Comparisons

Level-3 Clear Water

Distributions

Check of Post-Detector

Electronics

Instrument

Characterization

Mirror Side Correction

Factors

Spacecraft

State of Health

Influence of South Atlantic

Anomaly

Check of Detectors

within Bands Detector Data

Gain Data

Mirror Side Data

Telemetry Data

Dark Count Data

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 4. This figure shows the calibration verification strategy for SeaWiFS. On-orbit calibration, vicarious

calibration, and sensor characterization data sets will be analyzed to assess the sensor calibration stability, the

atmospheric correction algorithm, and the on-orbit instrument state of health.

Merged analyses of the lunar and solar calibration data,

the L2 LAC vicarious data comparisons, and the L3 clearwater distributions will allow evaluations of the sensor calibration stability and the atmospheric correction to be

made.

2.2 AT-SENSOR RADIANCES

The calibration verification strategy requires that several of the level-1 data sets (lunar, solar, detector, and

gain data) are calibrated to at-sensor or top of the atmosphere radiances. These level-1b (L1b) data products are

generated from operational level-1a (L1a), or raw, data

files by the application of the sensor calibration model

(Darzi et al. 1995) and have units of mW cm−2μ m−1 sr−1.

The L1b data sets are produced for calibration verification

purposes and are not part of the SeaWiFS standard operational products. The data flow diagram for processing

L1b data is shown in Fig. 5.

2.3 ON-ORBIT CALIBRATION

Lunar and solar observations provide the primary way

of tracking the long-term radiometric sensitivity of the SeaWiFS instrument (Woodward et al. 1993).

2.3.1 Lunar Calibration

Lunar calibrations will be performed about once per

month when the moon is at a phase of 7◦ by pitching

the spacecraft across the moon and integrating the signal

across the lunar disk. The phase angle of 7◦ is chosen to

maximize the illuminated surface of the moon while minimizing the effects of the opposition effect, the surge in

11
SeaWiFS Calibration and Validation Quality Control Procedures

brightness of the light diffusely reflected from a surface

near zero phase [see Hapke (1986) for a discussion of the

opposition effect]. Two methods will be employed to track

the instrument response using the lunar data:

1) Comparing the integrated lunar radiance with the

predicted lunar radiances from a photometric lunar

model developed to calibrate the SeaWiFS instrument and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (Kieffer and Wildey

1996); and

2) Normalizing the integrated lunar radiance to a common sun-moon distance of one Astronomical Unit

(AU), a common SeaWiFS-moon distance of one

mean Earth-moon distance, and a common lunar

phase angle of 7◦.

The data flow diagram for processing lunar observations is

shown in Fig. 6.

The first method uses the time of the calibration and

the position of the spacecraft at that time to compute

model radiances for the moon in the eight SeaWiFS bands.

Variables in the photometric model include the sun-moon

distance, the SeaWiFS-moon distance, the phase of the

moon, and libration (or wobble) in the moon’s motion.

The second method normalizes the integrated radiances

over all of these parameters, except libration, to achieve a

uniform data set; libration will give rise to a periodic variation in the normalized radiances. Method one will be the

primary monitor, while method two will provide a check

on the gross properties of the photometric model. These

two sets of lunar radiances, which should track each other,

will provide a model-independent time series to monitor

the radiometric calibration of the instrument.

During lunar calibrations, SeaWiFS views the moon in

the same fashion that it views the Earth; however, there is

a complication in processing lunar data that does not occur

for any other data type. For Earth observations, the pitch

rate of the spacecraft matches its ground track speed so

that adjacent scan lines in a scene observe adjacent ground

swaths. During lunar calibrations, the pitch rate of the

spacecraft is slower than its lunar track speed, so the moon

is oversampled. Consequently, the lunar radiances must

be scaled by a pitch rate-dependent correction factor to

compensate for this oversampling. These scaled radiances

are compared to the photometric model in method one and

are then normalized for use in method two.

2.3.2 Solar Calibration

Solar calibrations will be performed at shorter intervals

between lunar calibrations, typically on a weekly basis, to

provide a more frequent calibration reference. The observations will record sunlight reflected by a uniformly illuminated solar diffuser plate while the spacecraft is over the

South Pole. The solar data will be normalized to a common sun-Earth distance of one AU for analysis. The data

flow diagram for processing solar observations is shown in

Fig. 7.

One set of parameters that is required for processing

solar data is the location of the diffuser plate in the scan

path of the instrument. Initially, these pixel indices are determined from solar scans obtained as part of the preflight

solar-based calibration of SeaWiFS (Biggar et al. 1995).

These indices will be revised, if necessary, based on the

initial on-orbit solar calibrations.

A time series analysis of the solar data should show two

trends. The first is a periodic variation in the bidirectional

reflectance distribution function (BRDF) of the diffuser

plate as the image of the sun moves seasonally across the

plate. The second trend is a slow exponential degradation

with time as photolyzed organic materials, outgassed from

the spacecraft, condense onto the surface of the diffuser.

This degradation can be approximated by a piecewise linear function between lunar calibrations. The solar data

will be normalized by the lunar observations to correct for

the degradation. A by-product of this process will be a

model of the solar diffuser degradation. The merged solar

and lunar calibration data will provide an on-orbit calibration time series for monitoring the sensor calibration

stability (Gordon 1987).

2.4 VICARIOUS CALIBRATION

There are two main methods of vicariously calibrating

the SeaWiFS data:

1. Comparing L2 LAC scenes with in situ buoy measurements, and

2. Analyzing global distributions of normalized waterleaving radiances for clear water.

2.4.1 L2 LAC and Buoy Comparisons

The primary method for the vicarious calibration of

SeaWiFS will be to compare L2 LAC scenes over the Marine Optical Buoy (MOBY) with in situ observations from

MOBY (McClain et al. 1992). MOBY will be located west

of the Hawaiian island of Lanai in open ocean, Case-1 water with low pigment concentrations. Average normalized

water-leaving radiances will be computed at the buoy site

in the L2 LAC scenes. These radiances will be compared

with radiances measured by MOBY at the time of the

spacecraft overflight. Overflights will occur every other

day. A significant percentage of the data will be lost to

cloud cover, but over the course of the mission, a substantial data set will accumulate. A time series analysis of

these comparison data will provide an in situ monitor of

the calibration stability of the instrument.

The data flow diagram for comparing L2 LAC and

MOBY data is shown in Fig. 8. The data quality flags

used in processing the L2 LAC data will typically be the

flags used in normal SeaWiFS data processing (McClain

et al. 1995). An analysis of the dependence of the error in

12
L1b Lunar,

L1b Solar,

and L1b TDI

Files

L1a Lunar,

L1a Solar,

and L1a TDI

Files

Calibration

Table

Sensor

Calibration

Program

Lunar Data Processor

Times of

Pitch

Command

Back-Orbit

Telemetry

Processor

Back-Orbit

Telemetry

Lunar

Pitch

Rate

L1b Lunar File

Distance and

Phase Normalizations

Normalized

Lunar

Radiances

Scaled

Lunar

Radiances

Normalized

Lunar Data

Processor

Normalized

Observation

Time Series

Scaled

Lunar Data

Processor

Predicted

Lunar

Radiances

Lunar

Calibration

Prediction

Photometric

Lunar

Model Model

Comparison

Time Series

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 5. This flow chart of sensor calibration shows that level-1b data products are produced by applying the

sensor calibration model to level-1a data sets.

Fig. 6. This flow chart of lunar data processing shows that lunar radiances are compared with a photometric

model and are normalized to a common observation state as independent methods of tracking the instrument

response.

13
SeaWiFS Calibration and Validation Quality Control Procedures

the L2 LAC scenes on the atmospheric optical path length

of the spacecraft data will yield an evaluation of the atmospheric correction algorithm. This algorithm may break

down for long optical paths. The data flow diagram for

this analysis is shown in Fig. 9.

Similar vicarious calibration techniques will be used for

any high-altitude calibration site, e.g., Lake Tahoe, that

become active over the course of the mission.

2.4.2 L3 Clear-Water Distributions

A second method for the vicarious calibration of SeaWiFS will involve the computation of global distributions

of clear water normalized water-leaving radiances. Clear

water is defined here to be open ocean Case-1 water with

a minimum depth of 1,000 m and low pigment concentrations. In this method, L2 GAC clear-water data are binned

on a daily basis to the SeaWiFS L3 grid. The distribution

of normalized water-leaving radiances is computed for each

daily file. A time series analysis of these distributions will

provide an additional in situ monitor of the instrument

calibration stability.

The data flow diagram for processing the clear-water

distributions is shown in Fig. 10. The data quality flags

used in processing the L2 GAC data will be those required

to select clear water. The L2 LAC and buoy comparison

time series and the clear-water distribution time series will

be compared and, if consistent, merged to produce an in

situ calibration time series for monitoring the sensor calibration stability.

2.5 CALIBRATION EVALUATION

The combined analyses of the on-orbit and vicarious

calibration data sets will yield evaluations of the SeaWiFS

calibration stability and atmospheric correction.

2.5.1 Sensor Calibration Stability

The primary method for monitoring the calibration stability of SeaWiFS will be to merge the on-orbit and in situ

calibration time series. An analysis of the merged time

series will test for any trends in the instrument response.

If trends are present, the CVE will recommend the incorporation of appropriate temporal correction factors into

the SeaWiFS calibration table (Barnes et al. 1994b). The

data flow diagram for merging the time series is shown in

Fig. 11.

A second monitor of the calibration stability is a check

on interband variations. The CVE will compute ratios of

the calibration time series for pairs of bands. Color ratio

time series will be generated for bands 1 and 2 (412 nm and

443 nm), for bands 2 and 3 (443 nm and 490 nm), for bands

2 and 5 (443 nm and 555 nm) and for bands 3 and 5 (490 nm

and 555 nm), the primary band ratios used in the SeaWiFS

bio-optical algorithms (Aiken et al. 1995 and Carder et al.

1996). Analysis of these time series will indicate whether

or not the sensitivities of individual bands are varying with

respect to each other.

2.5.2 Atmospheric Correction

The comparison of the on-orbit and in situ time series prior to merger will test the atmospheric correction

algorithm at the vicarious calibration sites: disagreement

between the two time series will indicate a deficiency in the

atmospheric correction of the L2 LAC data. This comparison of the two calibration time series, combined with the

path length analysis of the L2 LAC and buoy data comparisons will yield an evaluation of the performance of the

atmospheric correction algorithm.

2.6 SENSOR CHARACTERIZATION

The sensor characterization task of the calibration verification effort has two components:

1. Monitoring the instrument’s state of health, and

2. Assessing the influence of the SAA on the SeaWiFS

data.

2.6.1 Sensor State of Health

The on-orbit sensor characterization will look for

changes in the instrument’s state of health over the course

of the mission. Several data sets will be collected on a

routine basis for this purpose (Woodward et al. 1993).

Detector calibration data, or TDI data, will be recorded

on orbits immediately following solar calibrations by varying detector sequences for each band while observing the

solar diffuser plate. Radiance ratios will be computed for

the different detector sequences. A time series analysis

of these ratios will indicate any changes in the detectors

within each band. The data flow diagram for processing

TDI data is shown in Fig. 12. As with solar data, the

location of the diffuser plate within the scan path of the

instrument is required for processing TDI data.

Gain calibration data will be collected immediately following solar calibration or TDI calibrations by varying the

detector gain settings while injecting a fixed signal into

the postdetector electronics. Again, radiance ratios will

be computed for the different gain settings. The data flow

diagram for processing gain data is shown in Fig. 13. A

time series analysis of these ratios will indicate any changes

in the postdetector electronics for each band.

The SeaWiFS calibration table contains correction factors for differences in the reflectance of the two sides of the

half-angle mirror (Barnes et al. 1994b). The initial correction factors are based on prelaunch measurements of the

mirror. On-orbit correction factors are more easily computed from solar data than from other data types. Changes

in the correction factors from their prelaunch values would

imply that asymmetric degradation of the mirror has occurred. If such changes occur, the calibration table would

14
L1b Solar

Processor L1b Solar File

Pixel

Indices

Normalized

Lunar

Radiances

Mirror Side

Correction

Factors for

Each Band

Solar Data

Processor

Solar Time

Series

Mirror

Sides

Distance

Normalization

Mirror Side

Processor

Mirror

Side Time

Series

Measured

LWN at

Buoy Site

L2 LAC Scene

Processor L2 LAC File

Flags

to Mask

Average

LWN at

Buoy Site

Buoy

Location

L2 LAC

and Buoy

Comparator

L2 Buoy

Time Series

L2 Buoy

Path Length

Series

MOBY File MOBY File Processor

Time

Window

Merge

Path Length

Series

Atmospheric

Correction

Path Length

Series

L2 Buoy

Path Length

Series

L2 High

Altitude

Path Length

Series

Atmospheric

Correction

Analysis

Atmospheric

Correction

Evaluation

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 7. This flow chart illustrates solar data processing. Solar radiances provide a more frequent calibration

reference than is possible with lunar data and are analyzed to check for asymmetric degradation in the half-angle

mirror.

Fig. 8. This flow chart shows L2 LAC and buoy data comparison. Average L2 LAC radiances at the MOBY

site are compared with radiances measured by MOBY to monitor the instrument calibration stability.

Fig. 9. This flow chart shows the atmospheric correction evaluation. The atmospheric correction algorithm

may break down for long optical paths.

15
SeaWiFS L3

Processing L2 GAC File

L3 ClearWater Files

ClearWater Flags

L3 Clear-Water

Processing

L3 ClearWater Time

Series

L3 ClearWater

Distributions

L3 Clear-Water

Analysis

Solar and

Lunar

Time Series

In Situ

Time

Series

On-Orbit

Calibration

Processing

In Situ

Calibration

Processor

L3 HighAltitude

Time

Series

L2 Buoy

Time

Series

Solar

Time

Series

Lunar

Time

Series

L3 ClearWater Time

Series

Solar

Diffuser

Degradation

Model

Global

Calibration

Processor

Atmospheric

Correction

Evaluation

Color Ratio

Time Series

Color Ratio

Analysis

Interband

Stability

Calibration

Time Series

Calibration

Time Series

Analysis

Calibration

Temporal

Correction

Factor

SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 10. This flow chart shows clear-water distributions. The distributions of normalized water-leaving radiances

for clear water provide a monitor of the instrument calibration stability.

Fig. 11. This flow chart illustrates sensor calibration stability. The solar and lunar time series are merged

to form an on-orbit calibration time series. The L2 LAC and MOBY data comparison and the clear-water

distribution time series are merged to form an in situ calibration time series. The on-orbit and in situ time

series are merged to form a calibration time series and a color ratio time series. The on-orbit and in situ time

series are compared to evaluate the atmospheric correction of the L2 data at the vicarious calibration sites.

16
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 2. Strategy for organizing calibration verification data files in a directory structure, with a database

table pointing to the file locations.

Directory Structure Data Attributes

SeaWiFS Data Files Level-1a Lunar Time tags

Solar Lunar phase angle

TDI Prediction file name

Telemetry

Level-1b Lunar Time tags

Solar Lunar phase angle

TDI Prediction file name

Level-2 LAC Time tags

HRPT Buoy latitude and longitude

S/C solar zenith angles

MOBY file name

Level-3 Clear Water Time tags

Vicarious Data Files Lunar predictions Predicted irradiances Time tags

Model images Lunar phase angle

L1b file name

MOBY MOBY data files Time tags

Buoy latitude and longitude

Solar zenith angle

L2 file name

HRPT = High Resolution Picture Transmission S/C = Spacecraft

be updated with the new correction factors. Any symmetric degradation of the half-angle mirror would be absorbed

into the calibration temporal correction discussed in the

previous section.

Statistical analyses of the spacecraft telemetry data will

show any anomalies that occur in the instrument. For a

more detailed discussion of this subject, see Firestone et

al. (1996), in this volume, and McClain et al. (1995).

2.6.2 Influence of the SAA

A potential source of noise in the SeaWiFS data external to the instrument is the SAA. As the spacecraft passes

through the SAA, charged particle impacts on the detectors may increase the noise in the data. While it would be

difficult to distinguish this effect in the ocean data, the increased noise should show up as elevated dark counts. The

CVE will extract the dark counts from the L1a files and

bin the data to an L3 grid. If the SAA adversely affects the

SeaWiFS data, the binned dark counts will have elevated

values in the area of the SAA. The data flow diagram for

processing the dark count data is shown in Fig. 14. Sixteen

days of L1a data are binned together to provide complete

ground coverage for the analysis.

If the SAA turns out to be a problem for SeaWiFS,

a more detailed analysis of the effect will be required to

develop a strategy for dealing with the situation. A possible strategy would be to implement a data quality flag,

which would be set when the spacecraft is in the SAA.

These flagged data would not be included in the normal

SeaWiFS L3 processing. An analysis task would be to

determine the effective boundaries of the SAA to use in

setting this flag.

2.7 DATA ARCHIVING STRATEGY

One challenge that faces the CVE in performing calibration verification is keeping track of the data files that

are used or generated by the verification processing. These

data files include SeaWiFS data files in HDF format, vicarious data files (e.g., lunar radiance predictions and MOBY

files), and analysis output files (e.g., daily output of the

analysis routines discussed above), individual time series

files produced from the daily output, and merged time series files.

The initial strategy will be to set up a hierarchical directory structure that sorts files by data type. An overview

of this structure is shown in Tables 2 and 3. Eventually, a

relational database table will be set up that will point to

the files in this directory structure. Users will be able to

query the database for data sets defined by the attributes

listed in Tables 2 and 3.

17
L1b TDI

Processor L1b TDI File

Gain

Settings

TDI Ratios

for Each

Band

TDI Ratio

Processor

TDI Ratio

Time Series

TDI

Settings

Pixel

Indices

L1b Gain

Processor L1b Gain File

Gain

Settings

Gain Ratios

for Each

Channel

and Band

Gain Ratio

Processor

Gain Ratio

Time Series

TDI

Settings

Pixel

Indices

Extract Dark

Count Data

for Each

Band

L1 GAC Files

for 16 Days

Navigation

Data

Compute

Subsatellite

Latitude and

Longitude

Possible

SAA Data

Quality Flag

Bin Dark

Count Data

to L3 Grid

Dark Count

Data

L3 Dark

Count File

Dark Count

Analysis

Latitude and

Longitude

for Each

Pixel

SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 12. This is the TDI data processing flow chart. TDI data is analyzed to check for variations in the

detectors within each band.

Fig. 13. This is the gain data processing flow chart. Gain data is analyzed to check for variations in the

postdetector electronics within each band.

Fig. 14. This is the flow chart for dark count data processing. Dark count data is analyzed to assess the

influence of the SAA on the instrument and data.

18
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 3. Strategy for organizing calibration verification data files in a directory structure, with a database

table pointing to the file locations. The following files (Analysis Files) are derived products of those files listed

in Table 2.

Directory Structure Data Attributes

Daily Processing Lunar data Scaled radiances Time tags

Files Normalized radiances Lunar phase angle

L1b file name

Prediction file name

Solar data Normalized radiances Time tags

Gain ratios L1b file name

Mirror side correction

factors

TDI data TDI ratios Time tags

Gain ratios L1b file name

L2 LAC and buoy Average L2 LAC radiances Time tags

comparisons

Average MOBY radiances Buoy position

Error in L2 LAC radiances S/C solar zenith angles

L2 file name

MOBY file name

L3 clear water Histograms of normalized Time tags

distributions water-leaving radiances

Histograms of bio-optical L3 file names

parameters

Histograms of atmospheric

parameters

Binned dark count files Time tags

Individual Time Lunar data Scaled radiances Time range

Series Predicted radiances Phase angle range

Comparison of scaled,

predicted radiances

Normalized radiances

Solar data Normalized radiances Time range

Gain ratios

Mirror side correction

factors

TDI data TDI ratios Time range

Gain ratios

L2 LAC and buoy Average L2 LAC radiances Time range

comparisons Average MOBY radiances Path length range

Error in L2 LAC radiances Buoy position

L3 clear-water Means of distributions Time range

distributions Standard deviations of

distributions

Path Length L2 LAC and buoy Average L2 LAC radiances Time range

Series comparisons Average MOBY radiances Path length range

Error in L2 LAC radiances Buoy position

Merged Time On-orbit calibration series Time range

Series In situ calibration series Buoy position

Calibration time series

19
SeaWiFS Calibration and Validation Quality Control Procedures

Chapter 3

The Quality Control of SeaWiFS Ancillary Data

Brian D. Schieber

James K. Firestone

Wayne D. Robinson

Michael Darzi

General Sciences Corporation, Laurel, Maryland

Charles R. McClain

Goddard Space Flight Center, Greenbelt, Maryland

Abstract

Processing SeaWiFS data requires the use of external, i.e., ancillary, data products to derive the set of SeaWiFS

standard geophysical (level-2) parameters. Ancillary meteorological data products of total column ozone and

surface values of zonal and meridional wind speed, atmospheric pressure, and possibly relative humidity or total

precipitable water will be used in the level-2 processing. These ancillary data files are provided by NMC and the

TOVS Project; equivalent products may be obtained from other sources. The CVE developed procedures and

software to assure the quality of the input products processed using SDPS. Ancillary data files are converted

to a SeaWiFS defined specification and stored in HDF files. The HDF data undergo QC procedures using both

noninteractive and interactive programs to assess their validity. The data are then used for level-2 processing

and are distributed to the research community through the GSFC DAAC. This chapter describes the approaches

to QC of SeaWiFS ancillary files through software used by the SeaWiFS Project.

3.1 INTRODUCTION

The processing of SeaWiFS data from level-1a (uncalibrated radiances) to level-2 (derived products) requires

five near-real time (NRT) ancillary fields (Fig. 15):

1. Total ozone,

2. Surface values of zonal (east-west) wind speed,

3. Surface values of meridional (north-south) wind

speed,

4. Atmospheric pressure, and

5. Relative humidity;

which are incorporated into the atmospheric correction algorithm (relative humidity is not currently used). These

data products are converted to HDF files, according to the

specifications of the SeaWiFS Project (Darzi et al. 1995).

All verified ancillary data products are made available to

researchers through the GSFC DAAC.

To assure the validity of the ancillary data products,

two types of programs have been developed. The first is a

noninteractive or automatic program used for rapid, computer controlled statistical checking of the data and the

second is a user controlled interactive program that allows

an operator to view and modify data files. Both of these

programs are used by the CVE of the SeaWiFS Project

(McClain et al. 1992) and are explained in further detail

below.

3.2 NONINTERACTIVE QC

Noninteractive QC is designed to produce rapid statistical evaluations of NRT SeaWiFS ancillary data files

without the need for repetitive and time consuming operator interaction. The two programs used for this purpose

are METQC for meteorological data and O3QC, for ozone data.

Two programs are used because of the different formats of

the respective data and the difference in data availability

and processing times. Both programs are written in the

C language for use on the Project’s Silicon Graphics, Inc.

(SGI) UNIX workstations in the SDPS. METQC and O3QC

are executed via a UNIX shell script, which is started by

a call from the SDPS database whenever newly generated

products in need of QC are created. When completed, the

SDPS database is updated to reflect the result of the QC

operation. Depending on the results from the noninteractive QC, the file is declared either ready for use in SeaWiFS

level-2 processing, or it is declared as requiring operator

intervention to repair or replace the ancillary data.

20
Set QC Status

to

Autoapprove

Noninteractive

QC

(METQC or

O3QC)

Is

Ancillary

File

Good?

Can

Ancillary

File be

Repaired?

ASCII Report

and Difference

HDF Grid

Yes

No

Set QC Status

to

AutodisApprove

Daily NRT File

Climatology File

Threshold Values

Noninteractive QC

Set QC Status

to

Approve

Examine

Ancillary

Product

(ANCQC)

Is

Ancillary

File

Good?

Yes

No

Set QC Status

to

Disapprove

No

Repair Product

and Set QC

Status to

Approve

Yes

Designate an

Alternate

Product

Interactive QC Daily NRT File

Climatology File

Use Product

in Level-2

Processing

Initially,

all Files

Checked

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 15. This figure shows an overview of the ancillary data products and processing.

21
SeaWiFS Calibration and Validation Quality Control Procedures

The METQC or O3QC programs, depending on the input

data going through the QC process, compare an NRT HDF

ancillary file to the corresponding month in a climatology

(CLM) file, which was developed using multiyear averaging

of the ancillary parameters (Schieber and Firestone 1993,

and Firestone and Schieber 1994). The processing steps for

using the METQC or O3QC programs are as follows (Fig. 16):

1. An automatic process on the SDPS starts a UNIX

shell script that runs the METQC or O3QC with arguments for input and output file, directory, and QC

thresholds.

2. The shell script executes METQC or O3QC depending

on the ancillary data being processed.

3. The METQC or O3QC programs open and read the

NRT products and the corresponding monthly data

from the CLM file into memory and performs a statistical comparison between the two data sets.

4. An ASCII report is generated (Fig. 17) that shows

the number and percent of points in the NRT file

which fall within one, two, or three standard deviations (1–3σ) of the corresponding point in the

CLM file (based on latitude and longitude locations). Other values, such as the number of missing

points in the NRT or CLM file, are also reported.

This report is stored on the processing computer

and can be electronically mailed (e-mailed) to the

processing administrator for evaluation.

5. An HDF file is generated that contains the number

of standard deviations by which the NRT and CLM

data varies at each point in the compared grids.

Optionally, this output can be a simple numerical

difference between the two grids. This output QC

file can be utilized in the interactive QC (IQC) program to show the variation of individual NRT points

relative to the climatology and also serves as a data

record.

6. The calculated percentage of points falling within

1–3σ are checked against the three corresponding

thresholds provided to the program. If the percentage of points calculated in the program are lower

than any of the supplied threshold limits, the program will return a failed threshold flag to the calling

shell script.

7. The program returns control to the calling script.

The SDPS database is informed that there is a new

file ready for the IQC program by setting the QC

status code to a value of Autoapproved. If the

program’s return flag indicates the NRT data file

has failed the comparison test, the script informs

the database by setting the QC threshold flag to

a value of Autodisapproved. Products with the

Autodisapproved value require examination and

possible modification using the IQC program prior

to their use in the level-2 SeaWiFS image product

generation program.

3.3 Interactive QC

The ancillary QC program ANCQC provides a mechanism

for interactive viewing, manipulation, and modification of

the values in an ancillary HDF data file. The ANCQC program is written in IDL which provides a comprehensive

package for image display, image processing, and statistical analysis. In addition, IDL provides a high-level programming language and tools for building GUIs. Finally,

IDL provides support for HDF files which are used by the

Project.

The ANCQC program performs a number of interactive

functions on ancillary data. The primary functions of the

program are to view ancillary data files and to allow for the

substitution of data outliers with data from other data files

(temporal interpolation), climatology files, or by spatial

interpolation. Missing or erroneous data can be replaced

and documented using the tools in the ANCQC program.

The user also has the ability to define a region of interest

(ROI) on an image and modify only the data within or

outside that region.

Numerous other tools of the ANCQC program, used for

investigation of the data, are available. These are described in greater detail in the on-line help for the program.

A brief listing of ANCQC tools provided includes:

a) Clear and restore an image;

b) Change the color table and color palette;

c) Place a land mask over the image;

d) Show a bar plot of data scaling;

e) Animate a 12-month CLM file or a selected set

of NRT files;

f) Show header data (metadata) for a selected file;

g) Create an image of wind speeds from zonal and

meridional data grids;

h) Show a shaded 3-D surface plot of data;

i) Plot latitude and longitude grids over data;

j) Show modified points in a data grid;

k) Annotate an image with text and figures;

l) Contour data;

m) Show a spreadsheet of the data; and

n) Zoom in on the entire image or on a selected

region.

ANCQC interacts with the SDPS database to determine

which files will undergo QC and displays these files in its

file selection window. The program also interacts with the

SDPS database to update a QC status flag after a file has

been through QC and possibly modified.

The processing steps for ANCQC are as follows:

1. The user starts the ANCQC IDL program.

2. The ANCQC program queries the database for any

files marked with the Autodisapproved status on

startup and displays a list of filenames for selection.

22
Z and M Wind

Atmos. Pressure

Relative Humidity

Monthly Averages

(1946–90)

DAAC

COADS

CDF

Ozone

Monthly Averages

(1978–91)

TOMS

NIMBUS

ASCII

Z and M Wind

Atmos. Pressure

Relative Humidity

4 Times per Day

NMC

NOAA

GRIB

Ozone

2 Times per Day

TOVS

NESDIS

Binary

HDF

Conversion

Noninteractive

QC

Interactive

QC

Verified Data

Products

Climatology Near-Real Time

Parameters:

Time:

Source:

Project:

Format:

File Type:

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 16. This figure shows noninteractive and interactive ancillary QC processing with file status interactions

to the database.

Results of comparison of real-time and climatological files:

/usr/seadas/data/S19952741827608 TOVS.OZONE

/usr/seadas/data/S19891991 TOMS.OZONE

Month: October Parameter: Ozone

Total # values − missings: 44269

Total # points/percentage < −1 STD: 18236 (41.19 percent)

Total # points/percentage +/ − 1 STD: 24441 (55.21 percent)

Total # points/percentage > 1 STD: 1592 ( 3.60 percent)

Total # points/percentage < −2 STD: 6058 (13.68 percent)

Total # points/percentage +/ − 2 STD: 38027 (85.90 percent)

Total # points/percentage > 2 STD: 184 ( 0.42 percent)

Total # points/percentage < −3 STD: 1327 ( 3.00 percent)

Total # points/percentage +/ − 3 STD: 42899 (96.91 percent)

Total # points/percentage > 3 STD: 43 ( 0.10 percent)

Total # missing values: 7571

Total # missing real-time: 7571

Fig. 17. This is the ASCII report from the O3QC program showing the determined standard deviation percentages for comparing daily and climatology files.

Initially in SeaWiFS processing, even files marked

Autoapproved will appear for visual checks.

3. The user selects an NRT product to go through the

QC process.

4. The ANCQC program displays the data parameter(s)

for the product selected, and also displays the data

from the corresponding climatological month in an

adjoining display window. For total column ozone

data, only one NRT and one CLM grid are displayed. For meteorological data, the four meteorological data parameters are displayed along with

their four corresponding CLM images.

5. The user views the NRT parameters and can modify

data points using any of several possible modification methods provided by the ANCEDIT routine.

6. The modified NRT file is saved as a new HDF file.

Modified data files are documented internally by

using HDF header information (metadata) and by

modifying QC grids associated in a point-to-point

fashion with the actual data grids.

7. The SDPS database is informed by the user of the

new status of the NRT files. The new status will be

either: a) Approved, b) Approved (with modified

points), or c) Disapproved.

Once the file’s status is modified, is it eliminated from the

Files to QC list on the ANCQC user interface.

The ancillary data processing sequence is run daily on

four 6-hour meteorological and two 12-hour ozone ancillary

data files. Records are stored in the metadata of the NRT

files to log modifications and operator comments. In addition, generated reports are stored on the CALVAL computer

to log processing times and to compare results.

23
SeaWiFS Calibration and Validation Quality Control Procedures

Chapter 4

SeaWiFS Data Quality Control Software

Wayne D. Robinson

Michael Darzi

General Sciences Corporation, Laurel, Maryland

Charles R. McClain

Goddard Space Flight Center, Greenbelt, Maryland

Abstract

This chapter presents the procedures and software employed to monitor and control the quality of the geophysical

data from the SeaWiFS instrument aboard the SeaStar satellite. The QC programs consist of a set of automated

programs which verify that the data conforms to broad statistical guidelines, and interactive programs that allow

for more in depth investigation of problems, as well as a final level of approval for the data. The QC programs

are applied to the data in all three stages of processing: level-1a, level-2, and level-3. The procedures for the

efficient use of these programs are also discussed.

4.1 SOFTWARE OVERVIEW

The SeaWiFS data QC software is used by the CVE

to assure that only high quality SeaWiFS products are

archived in the GSFC DAAC. This goal is achieved by

applying interactive and automated checking procedures to

the data as they pass through all three levels of processing:

level-1a, -2, and -3. The checking varies depending upon

the data type and processing level and is described in detail

in the following sections.

The QC programs are designed to achieve three main

objectives:

1) Locate unexpected problems in the data coming

from the satellite;

2) Locate data problems created by the processing software; and

3) Allow the testing of alternate scientific algorithms

for the processing of data—this only applies to the

level-2 data.

The remainder of this section gives an overall description of the QC data flow. Sections 4.2, 4.3, and 4.4 describe

the purpose, features, input, and output of the level-1a, -2,

and -3 QC programs in more detail. Each section includes

a description of how to run the QC program, along with diagrams of the important interfaces and descriptions of their

features. Section 4.5 describes the automatic level-1a, -2,

and -3 QC programs. Section 4.6 presents a highly detailed

discussion of the data flow and the QC interactions.

Figure 18 shows the QC processing flow in relation

to the level-1a, -2, and -3 processing by the SDPS. The

SDPS first processes the raw SeaWiFS data into detector

counts and navigation information called level-1a (L1a).

The next processing step calibrates the counts to generate radiances, corrects the radiances for atmospheric absorption, and determines bio-optical quantities from the

corrected radiances to produce a level-2 product (L2). Finally, the data are binned from the line, pixel coordinate

system into a regular grid. This is accomplished on individual level-2 products to create level-3 space binned

products (L3S) which are then accumulated on a daily basis into a level-3 time binned product (L3T). Additional

binning is done to produce weekly, monthly, and yearly

binned products. Several segments of SeaWiFS data are

processed in a day from the raw form to L3S products; the

processing steps for each segment are called a stream.

In addition to this processing, browse images are created from the level-1a and -2 products. The L3T product is processed to create a standard mapped image of

certain geophysical parameters, and a browse product of

chlorophyll a is generated from the chlorophyll a standard

mapped image. These processing steps are not shown in

Fig. 18.

When SDPS completes a product, it is checked with

the automatic level-1a, -2, and -3 QC programs, which

run tests on the products to check their integrity and data

quality within established thresholds. A status report is

then generated if any problem is detected in any of the

products.

When the L3T product is created and checked, the interactive portion of the QC is started by members of the

24
L3S

Generate

L1a

L1a

Interactive

QC

Approve

Time Bin

and all

Parents

Yes

Bad

L1a

Generate

L2

Generate L3S

Generate L3T

L2

L3T

Automatic

L1 QC

Automatic

L2 QC

Automatic

L3 QC

Automatic

L3 QC

L3a

Interactive

QC

Good

Bad

Does

Navigation

Appear

Bad?

No

Good

L2

Interactive

QC

Bad

Inform MOPS

of Navigation

Error

Save Parameters for Analysis

and Future

Reprocessing

L0

Reprocess

L2

Good

Status Reports

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 18. The layout of the level-1a, -2, and -3 GAC processing and quality control is shown here.

CVE. First, any QC status reports are examined and the

associated product is checked. Then, the level-3 IQC program is run on the L3T product. An examination of the

L3T product gives an indication of the quality of most of

the level-1a, -2, and -3 products which were created during the day. The advantage of checking the L3T file is

that only one product needs to be checked instead of the

approximately 30 level-1a and -2 products that make up

the L3T. If a problem is detected in the L3T, either the

level-1a or level-2 IQC can be run on the parent product. The level-3 IQC program lists the parent products

for any point in the time binned product and can invoke

the level-1a or -2 IQC program on that product directly,

making it easy to examine the product in more detail.

Each IQC program checks certain aspects of the data

quality, as indicated in Fig. 18. The level-1a QC is designed to detect and measure navigation errors by determining coastline offsets between the image and the coastline drawn using the navigation information. These problems are then forwarded to the Mission Operations element

for study and correction so that global reprocessing can apply the correction later. The level-2 QC is designed to detect problems in the radiance calibration, the atmospheric

correction, flag and mask thresholds, and the derivation of

bio-optical parameters (Gordon and Wang 1994 and McClain et al. 1995).

The level-2 QC can aid in establishing improved performance of the level-1a to level-2 processing by noting the

results of reprocessing a subarea of the data from level-1a

to level-2 with different input processing parameters or

algorithms.

The level-3 QC verifys that the binning of the data is

performed correctly and detects problems in the level-1a

and -2 processing. The parent products can be identified

and the contributions to an individual level-2 bin can be

assessed. (Section 4.6 presents a more detailed discussion

of the QC procedures followed by SDPS and CVE during

the generation of operational products.)

4.2 LEVEL-1A QC PROGRAM

The main purpose of the level-1a QC program is to

detect and measure navigation errors in the GAC and LAC

products. It also allows for qualitative and quantitative

checking of the image quality, as well as monitoring the

sensor health.

25
SeaWiFS Calibration and Validation Quality Control Procedures

4.2.1 Summary of Features

The level-1a QC program has the following features:

1) Simultaneous display of all eight bands of level-1a

data (at reduced resolution);

2) Full resolution display of a selected band of data;

3) Graphic display of the coastline over the image data;

4) Display of any or all the engineering flags and instrument tilt states;

5) Display of metrics and other metadata;

6) Display of information at a point including location

(latitude, longitude, line, and pixel) and data values

in all eight bands;

7) Recording of the observed navigation offsets and

saving them to a file; and

8) Database connections to allow the selection of a

product and the approval or disapproval of the data

based on its quality.

4.2.2 Program Requirements

The level-1a QC processing requires two input files to

operate: the level-1a product that will go through the QC

process, and a file containing the coastline overlay. The

default coastline overlay file has a resolution of 12 km but

higher resolution files are also available.

The level-1a QC program has the following hardware

and software requirements:

a) It must run on an SGI workstation with the 24-bit

graphics option and the GL graphics library;

b) Although required only for software updates, the

User Interface Management/X-Windows (UIM/X)

GUI builder should be present; and

c) In order to use the Sybase database, the level-1a

QC program must have access to the Sybase client

software. This can either be the CALVAL computer,

which has Sybase, or any computer that can access

the client software via a network file services (nfs)

mount.

The level-1a QC program is started with the command

QCl1int. As an option, this can be followed by the file

name of the level-1 product to check. Upon startup, the

level-1a QC program displays the Main interface (Fig. 19).

Other than product queries, all controls for the level-1a

QC program are contained in this interface. The elements

in the interface are described below in the order that they

typically would be used.

The level-1a input product is specified first. It can be

specified at startup or it can be specified in the program

by querying the database from the File pull-down menu.

Either way, the selected level-1a product is immediately

loaded and displayed.

The level-1a QC program interface contains a large image area which displays a full-resolution image of SeaWiFS

band 1 after the level-1a product is selected. Scroll bars on

the sides control the portion of the image that is viewed at

any time. Nine smaller displays show reduced resolution

views of all the data in each of the eight SeaWiFS bands

and the coastline overlay itself. The buttons below each

band can be selected to display that band at full resolution

in the large image area.

Quantitative information about the level-1a data can

be displayed for any image point selected by the cursor.

The geographic location, the scan line, and scan element

and the counts in all eight bands are displayed. This information can be updated each time the cursor moves or

just when the mouse button is pressed.

Any of the engineering or tilt state flags may be overlaid on top of the full resolution image to determine any

correlations with data anomalies. The color of the flags

can be controlled and they may be easily toggled on and

off.

Navigation offsets can be selected and recorded by locating their corresponding points in the coastline seen in

the level-1a data and the graphic overlay of the coastline. These locations will be displayed as markers on the

screen and their line and pixel location will also be displayed. Pairs of coastline and map points can be collected

to record the observed navigation offsets. The differences

between these pairs can then be computed and displayed

in a registered targets list. The navigation offset information is output to a file by specifying the Save Registered

Points option in the File pull-down menu.

When the data quality has been determined, the QC

status of the product can be updated using one of the options in the Approve/Disapprove pull-down menu. (Section 4.6 has a detailed discussion of the QC status codes.)

Although both approved and disapproved products are

processed and archived, the Disapproved status is important because it marks the product as having a problem that

may have an impact on the level-2 and other downstream

products.

When the processing for this product is complete, the

Quit option can be invoked from the File pull-down menu.

4.2.4 Future Enhancements

The level-1a QC program satisfies all the basic requirements and is ready for operational use. As time permits,

the following features will be added: a) an ability to place

the cursor at a specified latitude and longitude; and b) an

improved interface for describing the engineering and tilt

flags to be shown. The latter feature includes a separate

interface for specifying the flags and a descriptive text for

the meaning of each flag.

4.3 LEVEL-2 QC PROGRAM

The main purpose of the level-2 QC program is to make

sure the level-1a to level-2 processing is working correctly.

This includes:

26
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 19. A picture of the level-1a QC Main interface is shown above.

i. Checking the general quality of the resulting products;

ii. Examining the flags and masks to insure that the

exclusion thresholds are not too restrictive or too

lax; and

iii. Testing new processing algorithms in order to observe their performance in relation to the operational algorithm. This operation will also be carried out in a more thorough manner in the data

match-up programs (Yeh et al. 1996).

The level-2 QC program may also be used to examine

problems in the level-1a data processing.

4.3.1 Summary of Features

The level-2 QC program has the following features:

1. Display any combination of the following in separate windows: a) Any level-2 parameter from the

level-2 product; b) Any band of the parent level-1a

product; and c) Any QC parameter from the associated level-2 quality control (level-2 QC) product.

2. Display the selected level-2 processing flags as an

overlay with selectable color.

3. Display the selected engineering flags and/or instrument tilt states as an overlay with selectable colors.

4. Display a zoomed portion of the image.

5. The cursor controls the area of interest.

6. The reprocessing function allows the level-2 processing of a subarea of the data with different input

parameter values or algorithms so that comparisons

of the results can be made. Data and/or flags can

be selected for this reprocessing.

7. The Sybase database connection allows the selection of a product and to approve or disapprove the

27
SeaWiFS Calibration and Validation Quality Control Procedures

product (and its level-1a parent) based on its quality.

4.3.2 Program Requirements

The level-2 QC program can use level-1a, level-2 QC,

and level-2 products during the QC process, although primarily, it uses the level-2 product. The level-1a parent

product is necessary if reprocessing will be done.

The level-2 QC program has the following hardware

and software requirements:

a. It can run on either an SGI workstation that has

8-bit color or an X-terminal with 8-bit color.

b. The host computer must have the IDL software and

an IDL license.

c. In order to use the Sybase database, the QC program must have access to the Sybase client software.

This can be either the calval computer, which has

Sybase, or any computer which can access the client

software via an nfs mount.

4.3.3 Program Operation

The level-2 QC program is started within IDL. To start

the program, enter the command: QCl2int. This command can be followed optionally by the file name of the

level-2 product to check.

4.3.3.1 General Interface Description

The level-2 QC program contains several interface windows (interfaces) which provide the specified functionality.

Four of the most important interfaces, which examine the

level-2 data and test the effects of modified data reprocessing, are described here.

Upon startup, the level-2 QC program displays the

L2CHK interface (Fig. 20). The L2CHK interface can call

many other interface panels for changing input parameters for reprocessing and viewing data. The primary interface panel called to view the data in image form is the

Level-2 Image and Flags interface (Fig. 21). Simultaneously, a level-1a band and a level-2 QC parameter can

be displayed in separate interfaces. While in the Level-2

Image and Flags interface, reprocessing of a selected section of the data with modified input can be started by invoking the Level-2 Reprocess Set Up and Information

interface (Fig. 22) to modify the input and the Level-2

Reprocess Display Window interface (Fig. 23) to view

the results.

The following sections describe each of the four interfaces in more detail.

4.3.3.2 The L2CHK Interface

The L2CHK interface (Fig. 20) contains many controls

for the selection of the level-2 data to be displayed. These

controls allow for the selection of any level-2 geophysical

parameter, level-2 QC parameter, or any band from the

level-1a parent product. Data quality, engineering, and

tilt flags can also be selected for display. The elements in

the interface are described below in the order that they

typically would be used.

The level-2 product is specified first. It can be specified

at startup or it can be specified in the program by using

the Database Query button. Either way, a selectable set of

level-2 parameters and navigation values are read so that

they are quickly available for display.

Once the product is specified, the desired band or parameter, and flag data are chosen for display as an image.

The image area and data subsampling may be chosen to

control the amount of data that can be viewed in the scrollable image area. Three pull-down menus are provided to

permit the selection of the level-1a band, the level-2 parameter, and the level-2 QC parameter to be displayed

in separate display interfaces. Controls are initially set to

produce an image of only the level-2 parameter, but these

can be modified to also produce the level-1a and -2 QC

images at the same time. The level-2 QC flags generated

during the level-1 to level-2 processing, can be selected for

display via a set of 16 toggle buttons. The four instrument

tilt states and the engineering flags can also be selected in

this way.

An image of the selected band and/or parameter can

be generated in a number of ways through the use of the

display action buttons. These buttons are also used to

update the Image and Flags interface displayed with different image or flag data. The buttons allow the display

of only the parameter, only the flags, or both the parameter and a graphic overlay of flags. The image data is

displayed or updated in the Level-2 Image and Flags

interface, which is described in the next section.

A number of other interfaces containing controls may

also be invoked from this interface. Among the functions

that can be performed are:

1) Animate a series of level-2 parameter and flag combinations;

2) Zoom in on an area of the image data;

3) Display a spreadsheet of the level-2 parameter values;

4) Adjust the color assigned to the flags; and

5) Adjust the colors applied to the image data.

When the data quality has been determined, the product’s QC status is updated by pressing either the Approve

button to approve the level-2 product or the Disapprove

button to disapprove the level-2 product. Section 4.6 discusses the details of the QC status values applied.

When processing for this product is complete, the Quit

button can be pressed to exit the level-2 QC program and

close all the interfaces.

28
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 20. This is the level-2 main interface: L2CHK.

29
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 21. This is the Level-2 Image and Flags interface.

30
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 22. This is the Level-2 Reprocess Set Up and Information interface.

31
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 23. This is the Level-2 Reprocess Display Window interface.

32
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

4.3.3.3 Level-2 Image and Flags Interface

The Level-2 Image and Flags interface (Fig. 21) is

invoked by the L2CHK main interface to display the selected

level-2 parameter and flags in image form. A subarea may

also be chosen from the image for performing level-2 reprocessing.

The image area of this interface shows the level-2 parameter in either grey shades or in false color. Superimposed upon this image are flag information or instrument

tilt states that were requested in the L2CHK interface. The

parameter value at the location of the cursor, as well as

geographic, line, and pixel location are displayed in text

areas above the image.

To perform reprocessing of the level-1a data to level-2,

a reprocessing region is first specified on the image by dragging an adjustable box over the desired portion of the image. The position and size of the region is changed with

the left and right mouse buttons. The location and size of

the box can be viewed by pressing the Box Info button.

Once the desired region is chosen, the reprocessing input

is specified by pressing the Process Info button to invoke the Level-2 Reprocess Set Up and Information

interface, described in the next section.

The Quit button is pressed to close the Level-2 Image

and Flags interface.

4.3.3.4 Level-2 Reprocess Set-Up Interface

The Level-2 Reprocess Set Up and Information

interface (Fig. 22) is used to specify the input parameters

to use during the reprocessing of a region of the level-1a

product to the level-2 form. The Reprocess Option buttons allow the reprocessing of either the data, the flags, or

both. If an alternate level-1a product is to be reprocessed,

it can be specified here. The controls that can be changed

for reprocessing come in the form of threshold values and

ancillary data files. Two lists are presented showing the

original input values that were used to create the level-2

product and an editable list of new input to use during

reprocessing.

Once the new reprocessing input values are chosen,

the Go button is pressed to begin the reprocessing and to

display the resulting product in the Level-2 Reprocess

Display Window interface, described in the next section.

The list of new thresholds and files is saved so that they

may be used for future reprocessing of the entire product.

The Quit button is pressed to close the Level-2 Reprocess Set Up and Information interface. No reprocessing

is performed.

4.3.3.5 Level-2 Reprocess Display Interface

The Level-2 Reprocess Display Window interface

(Fig. 23) is used to display and compare the old and newly

reprocessed level-2 parameters and flags.

An image area displays a chosen parameter and flags

of the original level-2 data. Inside the region, where reprocessing was specified, either the original or reprocessed

(new) data or flags may be viewed to determine the effect

of the reprocessing to the region in the context of the whole

data pass.

When examination of the reprocessed data is complete,

the Quit button is pressed to close the Level-2 Reprocess

Display Window interface.

4.3.4 Future Enhancements

The level-2 QC program is fully operational. The reprocessing portion will be updated in the future with new

level-2 processing algorithms as they become available.

4.4 LEVEL-3 QC PROGRAM

The main purpose of the level-3 QC program is to monitor the binning procedure used to place the level-2 data

values into the level-3 product (Campbell et al. 1995). Any

problems in the data or in the level-1a and -2 processing

can also be observed here. Capabilities include checking

the general quality of the data and its navigation, displaying the data for any bin, and determining the parent level-2

products from which the data originates.

4.4.1 Summary of Features

The level-3 QC program has the following features:

1) Displays any of the 12 parameters in the product

statistically (mean, median, etc.), in addition to displaying other statistical data;

2) Displays the coastline and geographic grid as a

graphic overlay;

3) Displays the data in any of 12 standard map projections;

4) Displays the boundaries, as a graphic overlay, of the

satellite passes that make up the product;

5) Controls the way the image, grid, and continent

data are displayed in the display window;

6) Provides the capability of loading a look-up table

(LUT);

7) Navigates a point on the screen with the ability to

place the cursor at a specific point;

8) Determines the level-2 parents of a data point;

9) Displaying all the information at a point in the data;

and

10) Having database connections to allow the selection

of a product and the approval or disapproval of the

data based on its quality (the approval condition is

automatically applied to the parent level-1a and -2

products, as well as associated browse and standard

mapped image products).

33
SeaWiFS Calibration and Validation Quality Control Procedures

4.4.2 Program Requirements

The level-3 QC program requires a level-3 product to

process. In order to generate the parent level-2 boundaries,

the parent level-2 products are also needed.

The level-3 QC program has the following hardware

and software requirements:

a) It can run on either an SGI workstation that has

8-bit color, or an X-terminal with 8-bit color;

b) The host computer must have the IDL software and

an IDL license;

c) In order to use the Sybase database, the QC program must have access to the Sybase client software.

This can either be the CALVAL computer, which has

Sybase, or any computer which can access the client

software via an nfs mount.

4.4.3 Program Operation

The level-3 QC program is started with the command

QCl3int. This can be followed (optionally) by the file

name of the level-3 product to check. Upon startup, the

level-3 QC program displays the Main interface (Fig. 24)

to select the parameters to display. The Main interface

calls the Display interface (Fig. 25) to display the data

in image form. More information about the image is displayed by calling the Information interface (Fig. 26) from

the Display interface.

4.4.3.1 Main Interface

The Main interface (Fig. 24) has the following functions:

selecting the level-3 product, choosing the parameter to

display and its method of display, and approving or disapproving the product in the Sybase database. The level-3

product is specified first. It can be specified at startup or

it can be specified in the program by using the Database

Query button.

Once the product is specified, a number of choices may

be made to select the data which is displayed in image

form. The parameter, such as normalized water-leaving

radiances at 412 nm, LWN (412)†, is chosen from among

the 12 standard level-3 parameters. The measure refers

to the statistical measure of the data to display with the

mean value as the default. The projection determines the

map projection in which to display the data. The projection, combined with the latitude and longitude boundaries,

determines the geographical portion of the data to view. A

coastline map and latitude–longitude grid can also be selected to overlay the image. The scaling specifies the range

of the numerical data values to be scaled into the image.

The default (1,−1) scales the data so that the minimum

and maximum of the data are linearly mapped into the

minimum and maximum value of the displayed image. If

† Represented in the GUI as nLw_412.

a LUT is chosen with the Load LUT button, the data values are displayed in false color, otherwise, a range of grey

values are assigned to the data values (black is assigned to

the lowest value and white to the highest).

An image of the chosen parameter is generated by pressing the Create button, which invokes the Display interface, described in the next section.

When the product has been examined and its quality

has been determined, the QC status of the product is updated by pressing either the Approve or Disapprove button. An approval of a level-3 product confers automatic

approval to all of the level-1a and -2 parent products (see

Section 4.6 for more detail on the QC status codes).

When all level-3 QC procedures are completed, the

Quit button is pressed to exit the level-3 QC program.

4.4.3.3 Display Interface

The Display interface (Fig. 25) displays the image of

the level-3 product and graphic overlays selected by the

Main interface. Access to the analysis and printing functions are also contained within this interface.

The image area displays the image of the selected parameter in grey values or in false color. A coastline map, a

latitude–longitude grid, and the boundaries of the parent

level-2 data sets can be displayed over the image to better

locate landmarks and the extent of the data.

The Function button selects three functions that can

be applied to the level-3 image. The Cursor Position

function invokes the Information interface (see the next

section), which shows quantitative information about the

level-3 product. The Postscript Output, and Save to

File functions are used to save the currently displayed

image in either PostScript form or as an HDF data set.

The Quit button is pressed to exit the Display interface.

4.4.3.4 Information Interface

The Information interface (Fig. 26) displays quantitative information about the currently viewed parameter in

the Display interface. It also allows the placement of the

cursor at a designated location. The major functions are

described here.

Many functions of the Information interface deal with

determining information about a specific point in the image of the selected parameter within the Display interface. The location is specified and indicated by placing

the cursor at the location on the image. The interface has

two modes of using the cursor for positioning. In the interactive mode, whenever the cursor is in the image, the

geographic-, line-, and pixel position of the cursor is updated in the interface’s text areas. In the mouse button

mode, the position is updated only when the left mouse

button is pressed. The cursor can also be positioned at

a particular latitude and longitude by entering the location in the latitude and longitude text areas and pressing

34
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 24. This is the level-3 QC Main interface.

Fig. 25. This is the level-3 Display interface.

35
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 26. This is the level-3 Information interface.

36
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

the Place Cursor button. The position in the latitude and

longitude text areas is used for many information functions

in this interface.

All the information at a level-3 bin specified by the

latitude and longitude can be displayed by pressing the

Display Point Information button, included are: geographic location, bin number, row and bin in row, number

of points in the bin, and all the statistical measures for the

12 level-3 parameters.

When the Information interface is invoked, the level-2

parent products are determined and displayed in a list

that is used to indicate the parent products of a selected

point (Contrib column) and to indicate the products whose

boundaries will be drawn on the image of the level-3 product (Outline column). Boundaries can be selected or deselected either by selecting the line in the list or by pressing

the buttons to turn on or off all of the outlines. The selected boundaries—the boundaries whose Outline column

contains a Yes—are drawn when the Draw Boundaries

button is pressed. Parent level-2 products of a selected

point are determined when the Flag Parents of Point

button is pressed, resulting in a Yes appearing in the Contrib column beside every level-2 product that could contribute to the point.

Finally, the level-1a, -2, or -3 QC may be invoked on

a parent product by selecting that parent from the list (its

name appears in the parent root area) and pressing the

button for running the appropriate QC function.

The Quit button is pressed to exit the Information

interface.

4.4.4 Future Enhancements

The level-3 QC program satisfies all of the basic requirements and is ready for operational use. As time permits, a feature will be added to display the ancillary field

data, such as surface pressure, ozone, and surface winds.

4.5 AUTOMATIC QC PROGRAMS

The automatic level-1a, -2, and -3 QC (AQC) program

performs the easily automated initial integrity and gross

data quality checks on the level-1a, -2, and -3 products

immediately after they are created by the data processing

programs.

The AQC program consists of two main functions. The

first function is to check the integrity of the product against

the specification for the product. This includes checking

the proper format for all components that make up the

product, and checking many of the items for consistency

and reasonableness. The second function is to check the

general data quality to verify that the data values and

flag amounts are within reasonable thresholds. This can

be easily done on SeaWiFS products because they include

general metrics on the data quality. The quality of the

level-3 product will be automatically checked by comparing the parameters to the average and standard deviation

of the parameter over the life of the mission.

4.5.1 Program Requirements

The AQC program requires, as input, the file name

of the product that will undergo the QC process and a

format file that describes the organization and contents

of the HDF data set that makes up the product (Darzi

et al. 1995). In addition to these files, the level-3 AQC

program requires a binned file containing all level-3 data

accumulated during the life of the mission.

The only hardware and software requirement for the

AQC program is that it has to run on an SGI machine and

have access to the required files.

4.5.2 Program Operation

The AQC program is invoked with the command,

fmt_check, followed by the type of data to undergo the

QC process: level-1a, -2, or -3 data; the version of the

archive specifications used (see Darzi et al. 1996); and the

file name of the product to go through the QC process.

Note that under operational conditions, the AQC program

is invoked as part of the processing stream, immediately

after the step that created the product.

Once started, the AQC program checks the product

integrity and determines if the data quality metrics are

within acceptable thresholds. It notes any problems in a

report and sets a system status value to 0 (zero) if the

product passed the QC checks; 1 if a program error occurred (faulty input files, etc.); 2 if a problem exists with

the product itself; and 3 if both problems have occurred.

This status is then used to update the product’s QC status

to either Approved or Disapproved by the AQC program.

The AQC program’s Approved status indicates a preliminary approval—the product must still be examined by the

IQC program to approve it for archiving by the DAAC

during normal operations. Section 4.6 discusses the QC

status in more detail.

4.5.3 Future Enhancements

The portions of the AQC program that checks the data

values will be implemented when there is more experience

with the real data. Checking level-3 values against the

binned values accumulated over the mission life must also

wait until sufficient operational data is accumulated.

4.6 QC PROCEDURE DETAILS

Fig. 27 shows a detailed flow diagram of the level-1a,

-2, -3, and ancillary data processing performed by both

the SDPS and CVE groups, and includes the AQC for each

step, as well as the processing of the browse and standard

mapped images. The contribution of ancillary data to the

processing is included in the figure and in the following

discussion because of its important interaction in the data

processing and QC process. Note that these procedures

will be changed as more experience is gained with the simulated and operational data.

37
L0 to L1

AutoQC

L0

L1

L1 to L2

AutoQC

L2

SpaceBin

AutoQC

L3s

TimeBin

AutoQC

L3t

L1 to Browse

AutoQC

L1brs

L2 to Browse

AutoQC

L2brs

L3t to Smi

AutoQC

L3smi

L3smi to

Browse

AutoQC

L3brs

Which

Data Looks

Bad?

L1 L3s

IntQC3

Bad Product

When daily TimeBin

is made, check

AutoQC reports.

Good, L3t: A3t and upstream. L3brs, L3smi,

L3s, L2, L2brs, L1, L1brs.

Do HRPT, LAC

with IntQC1

Bad, L3t: P3t.

L3smi, L3brs: P3t.

IntQC1 IntQC3

IntQC2

L2

Bad, P2 and downstream. L2brs, L3s, L3t,

L3smi, L3brs: P2 (Save for future reprocessing and have SDPS reprocess L3t without this stream).

Good, A1,

L1brs: A1.

Bad, AP, L1brs: AP

(Inform MOPS).

Good, A2, L2brs, L1,

L1brs: A2. Bad, P3s, L3t, L3smi,

L3brs: P3s

(Problem with binning;

have SDPS reprocess

L3t without this stream.)

Good, A3s, L2, L2brs,

L1, L1brs: A3s.

Done

AutoQC

Ancillary Data

If available,

use ancillary;

else, use

climatology.

Pass

Autoapprove

Fail

Autodisapprove

IntQ

If unusable,

Disapproved

New, approved Anc

Approved

Detail of

AutoQC

L1 to L2

Product from last

processing step.

Good: QA, approve for

further processing.

Bad: PA, suspend further processing on this

stream until IntQC can

To next processing be run.

step.

SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 27. Level-1a, -2, -3, and ancillary data processing are shown here. The QC status codes are explained in

Table 4 and in the text.

38
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 4. The codes that are important to QC processing.

Code Description

PA Problem found by the AQC.

QA Approved by the AQC, still needs approval by the IQC before it can be sent

to the DAAC.

A1 Approved by the level-1a IQC.

AP Interactively approved level-1a product with a navigation problem (processing continues).

A2 Approved by examining the level-2 product.

P2 Disapproved by examining the level-2 product.

A3S Approved by examining the level-3 space binned product.

P3S Disapproved by examining the level-3 space binned product.

A3T Approved by examining the level-3 time binned product.

P3T Disapproved by examining the level-3 time binned product.

Extra notes:

1. Approvals propagate upstream. For example, if a time binned product is approved, the parent level-3 space binned,

level-2, and level-1a products are approved.

2. Problems propagate downstream. For example, if a level-2 product has a problem, its children—the level-3 space

binned and level-3 time binned products—have the problem code set.

3. The process of creating browse and standard mapped products should not encounter any problems once the programs

are verified and the input data has the correct format. Thus, in normal operations, if a level-x product is approved,

its browse (and the standard mapped product for the level-3 time bin) are approved without direct examination.

The AQC program will be monitoring these products just in case.

4. Approvals and disapprovals propagate laterally—if a level-2 product is approved, the browse is also approved.

5. The propagation rules do not apply to the AQC program since they are unnecessary.

4.6.1 QC Codes

Although the real QC codes are numerical and there

are more codes than this (required by the SDPS), Table 4

shows the codes that are important to QC processing.

4.6.2 AQC Function

The AQC function can stop the processing of data if

it finds a problem. It stops the processing of one stream

but not others. Time binning also proceeds without the

stopped streams. The lack of ancillary data does not stop

level-1a to level-2 processing—climatology data are used

in this event (discussed in greater detail later).

The AQC function is the first to check the products

and is run by SDPS immediately after a product is created. It checks the format and any quality values against

thresholds. If any of these tests fail, that product will

be disapproved and the proper failure status code is set

(code PA). Otherwise, it is marked as in progress (code

QA) to indicate it has been approved by the AQC function.

The results of the AQC function (in the form of log files)

are made available to the CVE before the IQC function is

started.

At any point in processing, when the AQC function

fails, the processing for that stream is halted until the

IQC function can check it out. However, other processing

streams proceed, as does the time binning, without the

problem stream. If the problem can be repaired, or if the

IQC function determines that no problem exists, processing this stream can continue and the time binned product

can be reprocessed to include this stream.

The AQC function of level-1a, -2, and -3 products currently consists of file integrity checks. The format of the

data is checked and consistency between, and validity of,

metadata is also checked. The AQC function checking includes the browse and level-3 standard mapped products.

In the future, checks of the image data quality, such as

threshold checks and file metrics, will be added.

4.6.3 GAC Interactive QC

QC checking of the data always begins with a check of

the level-3 time binned product. Not only does this reduce

the amount of interactive QC required, but it ensures that

the status updates can propagate to all the products associated with the time binned product, i.e., all associated

products have already been created.

The level-3 QC software queries the database to find

the daily files that are ready (code QA). The Ready status

indicates the level-3 time binned product is ready for the

QC process and that the standard mapped product and

the browse product have been created. If the product is

approved, the approval is propagated to the browse and

standard mapped products and upstream. Note that it is

expected that at the start of operations, even the browse

39
SeaWiFS Calibration and Validation Quality Control Procedures

and standard mapped products will be examined often until the programs are verified.

If a problem is seen in a portion of the level-3 product, the parent stream for that portion is identified and

the interactive level-1a, -2, or -3 QC function is invoked

on those data. If the level-1 product is checked and has a

problem with navigation, its status code is set to AP, and

Mission Operations is informed but processing is not disrupted. The level-1a product is approved otherwise (QC

code A1 is set). Note that a gross navigation error (large

distance errors in the position of a point) can only be identified when a land mass is nearby. Such a problem would

most likely cause a rejection by the level-2 QC and the

data would not get binned. In order to insure that these

products do not inadvertently get binned, the level-2 QC

will be run on any products whose parent level-1a products

were assigned the QC code AP.

If the level-2 product is checked and has a problem that

cannot be repaired by modifying the reprocessing parameters, the level-2 product and the accompanying browse

and downstream files are given the QC code P2, indicating

a problem. The time binned product will be reprocessed

excluding this level-2 data. If and when new reprocessing parameters are derived, the parameter file name will

be given to the data processing group so it can do reprocessing to include the missing level-2 files. It is expected

that examination of a number of days of data will be required before a new set of parameters are considered for

reprocessing. Then, all the data will be reprocessed with

these new parameters so that a consistent set of products

(having the same controls) is obtained. Initially, reprocessing single files (fix-on-the-fly) will not be undertaken, but

will be incorporated once the processing procedures and

algorithms are stable.

A single file level-2 reprocessing may also be necessary if a better set of ancillary data can be supplied. This

can happen as the result of interactively approving ancillary data that were automatically disapproved, interactively modifying approved or disapproved ancillary data,

or by obtaining ancillary data that were not available at

processing time.

Once the checking of data in a stream is completed,

control is returned to the level-3 QC function so that problems can be checked in any other stream within the same

time binned product. In the situation where any product

in a stream is disapproved, the entire daily file is disapproved until reprocessing can be done to omit or repair

the bad parent products.

4.6.4 Interactive QC on Other Products

The level-1 and -2 QC will be able to access the LAC,

HRPT, and other nonbinned GAC data independently.

Remaining data, which have not been approved or disapproved, can also be checked. Note that only data to be

archived will have to be checked.

4.6.5 Ancillary Data QC

The QC status codes used are as follows:

1. Ready, the product is ready, but no QC has been

applied yet.

2. Autoapproved, the AQC ran and the product passed

all quality tests. The product can be used in the

level-1a to level-2 program.

3. Autodisapproved, the AQC ran and the product

failed one or more of the quality tests. The level-1a

to level-2 program will not use this product when

creating the level-2 product.

4. Approved, the product or an alternate product has

been passed by the IQC and can be used by the

level-1a to level-2 program and subsequently passed

to the DAAC.

5. Disapproved, no good products are available. The

level-1a to level-2 program should proceed using

other available ancillary data or climatology if no

satisfactory ancillary data is available.

The ancillary data QC processing will have these steps

and capabilities:

1. The AQC function is run by the SDPS immediately after the ancillary product is created; the AQC

function either approves or disapproves the product. The approval code is Autoapproved, and the

disapprove code is Autodisapproved. The AQC

function checks to see that the percentage of points

in the product that fall within 1, 2, and 3 standard

deviations of the climatological mean are less than

the specified thresholds.

2. CVE will use the interactive ancillary data QC program to check all ancillary data. For each product

it will either:

a. Determine that the product is good and give it

the code Approved;

b. Repair the ancillary data. The code Approved

will be given to the repaired product, which will

replace the original product. The original product will be renamed and given the status code

of Disapproved; or

c. Unconditionally disapprove the product and give

it the code: Disapproved. Level-1a to level-2

processing can proceed once the ancillary products are interactively quality controlled.

3. Level-1 to level-2 processing can use up to three

ancillary meteorological and ozone products. The

products are chosen by the following procedure.

a. First, only products that have been approved by

the IQC function are considered. From this set

of products, three ancillary products are chosen such that each of the products satisfies one

of the three following conditions (one product

40
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

satisfies one condition). The first possible ancillary product is the nearest one preceeding the

level-1a start time but is within 12 hours of the

start time (24 hours for ozone).

b. The second possible ancillary product is the closest one following the level-1a end time but is

within 12 hours of the end time (24 hours for

ozone).

c. The time of the third possible ancillary product

lies between the level-1a start and end times.

Under these conditions, from zero to three ancillary

products may be available. If only one ancillary

product is available, it is used with no interpolation. If two or three ancillary products are available, interpolation to the data time is done with the

appropriate files. If no files are found, climatology

files are used.

4. In order to ensure that sufficient ancillary data has a

chance to go through the interactive QC process and

be available for level-1a to level-2 processing, the

generation of level-2 products should not proceed

until either the optimum ancillary data is received

or a specified waiting period has expired. Due to the

limited length of this waiting period, interactive QC

of the ancillary data should be done as quickly as

possible.

5. CVE will receive the raw ancillary data from SDPS

and archive it for future use, such as reprocessing,

using better ancillary data repair algorithms.

4.6.6 Testing Modes

For testing purposes, changes can be made in the quantity of QC that is required before products can be sent to

the DAAC. Three levels can be set:

i) Send data to the DAAC only if the interactive QC

has approved the product (operational mode);

ii) Send data to the DAAC that has been approved by

the automatic QC; or

iii) Send all data to the DAAC.

41
SeaWiFS Calibration and Validation Quality Control Procedures

Chapter 5

SeaWiFS Derived Product Validation Software

Eueng-nan Yeh

Michael Darzi

General Sciences Corporation, Laurel, Maryland

Charles R. McClain

Goddard Space Flight Center, Greenbelt, Maryland

Abstract

The SeaWiFS derived product validation software was developed to compare SeaWiFS level-2 data with in situ

data in order to assist in evaluating the sensor performance and the accuracy of the level-2 algorithms. The

software will be used as part of an effort that will proceed continuously after launch to verify that the data

generated by the SeaWiFS Project for archiving and distributing meet the required accuracy. The software will

also be used to test algorithms alternative to those used operationally. An overview of this derived product

validation software and its use is presented herein.

5.1 INTRODUCTION

CZCS, which flew aboard the NIMBUS-7 satellite from

1978–86, was the first satellite instrument to collect ocean

color data. Although it was a proof-of-concept sensor,

CZCS was highly successful in demonstrating the scientific utility of such data; it also exposed a number of problems that must be addressed during future missions (McClain et al. 1992). As a second generation ocean color instrument, SeaWiFS provides important improvements over

CZCS with respect to sensor design and algorithms for the

derivation of geophysical (level-2) data. These improvements include:

1) A greater numerical dynamic range of the radiance measurements with digitization of 10 bits

instead of 8;

2) Onboard, postlaunch solar and lunar calibrations;

3) Sensor engineering telemetry data;

4) A higher signal-to-noise ratio; and

5) Greater spectral resolution with a higher frequency band (410 nm) to separate chlorophyll

a from degradation by-products, and lower frequency bands (765 nm and 865 nm) for atmospheric correction in turbid waters.

The maximum uncertainty goals for SeaWiFS data are 5%

for water-leaving radiances and 35% for chlorophyll a concentrations in Case-1 waters (Mueller and Austin 1995).

One important lesson learned from the CZCS mission

is that the sensor’s calibration should be monitored closely

and robust algorithms must be developed (Evans and Gordon 1994). For SeaWiFS, the sensor stability will be periodically checked by solar and lunar observations (Woodward et al. 1993 and Eplee et al. 1996). Vicarious calibration will also be performed to fine tune the satellite data

with in situ measurements to ensure proper sensor calibration. Some of the in situ measurements will be used for algorithm development and for vicarious calibration. Other

in situ data will be considered as sea-truth values and used

as independent measurements for satellite-derived product

validation, such as the analysis performed by Balch et al.

(1992) for the CZCS global data set.

This validation procedure requires that surface measurements be matched with concurrent SeaWiFS measurements. The derived product validation software was designed to perform comparisons between satellite and in

situ data in order to gauge the accuracy of SeaWiFS data

and to help evaluate the quality of the sensor calibration

and level-2 algorithms.

5.2 MATCH-UP METHODOLOGY

The validation of satellite data involves the spatial and

temporal matching of such data with in situ data for comparison. The surface observations can include measurements from ships taken along the ship course or at stations, and from drifting and fixed buoys. These data are

archived by the CVE and their metadata, e.g., time span

and areal coverage, are cataloged in the in situ database.

A detailed description of the in situ data can be found

in Hooker et al. (1994). The satellite image data will be

42
Repeat? No

Save Output

to a File

Run Matching

Procedure

Search Databases for Files

Satisfying the

Input Conditions

File

Found?

Yes

No

Exit

Input: Data

Types, Parameters, Ranges,

and Subranges

Yes

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 28. This schematic diagram indicates the logical steps involved in the SeaWiFS derived product validation match-up process. The allowed input are: observation data type, satellite data type,

parameters, temporal and spatial ranges, and temporal and spatial tolerance subranges.

produced by the SDPS and delivered to the GSFC DAAC

after they pass QC (Hooker et al. 1992 and Robinson et al.

1996). At the same time, the SDPS will maintain a master database to keep track of all processed satellite scenes.

The CVE also has a database of satellite scenes which will

be a subset of the SDPS database. This subset will contain scenes used primarily for derived product validation

match-up purposes.

Figure 28 depicts the general steps followed when performing the satellite derived product validation. The surface data are classified as along-track, buoy, cast, drifter,

or fixed mooring. The image data type can be a SeaWiFS

level-1 or -2 product of LAC or GAC resolution. The input parameter is used as a primary key to identify a unique

common field between surface and image data. Secondary

parameters, a list of SeaWiFS level-1 or -2 band names,

can be selected after the primary key is defined.

The specification of temporal and spatial ranges is required to seek surface and image data files from the databases. At least one surface data file and satellite scene

are required for the program to perform a matchup. The

specifications of temporal and spatial tolerance subranges

can relax the point-to-point data matching to point-withinregion matching. The results of the matching are saved

into an ASCII output file.

A user is required to input the data types, parameter,

temporal and spatial ranges, and the name of an output file

in which to save the match-up results. This information is

entered through widgets of an IDL GUI. The derived product validation program’s GUI is shown in Fig. 29. Each

entry has a default value to illustrate the proper input syntax. For the output file name, a user can either type in a

full file name or press the SELECT button to choose a file

path and name from existing files. If the output file exists,

results from the matchup will be appended to it, otherwise,

results will be saved to a new file.

A pull-down menu is used to enter the data type. From

the IMG button, a user has to select one SeaWiFS image data type and one primary parameter in order to run

a matchup (Fig. 30). The secondary (minor) parameter

menu will appear once the primary key is defined (Fig. 31).

This multiple choice menu of secondary parameters is a list

of either SeaWiFS level-1 bands or level-2 products. The

user may select, any, all, or none of the listed secondary

parameters. The purpose of the secondary keys is to generate additional means and standard deviations for these

parameters from the image file to assist in algorithm evaluation.

A time subrange may be entered to specify the temporal mismatch tolerance of data matchup. The default time

subrange is [−15,15] in units of minutes. This default range

will allow a data pixel viewed at 1200 Greenwich Mean

Time (GMT), for example, to be matched with a sea-truth

measurement made between 1145 and 1215. To specify simultaneous measurements, the time subrange should be

set to [0,0], making the time tolerance less than 30 seconds. The maximum allowable time subrange is [−60,60].

Similarly, an image area subrange may be entered to

specify the spatial tolerance in terms of pixels (X_SIZE in

the output file) and lines (Y_SIZE in the output file). The

default image area is [3,3], or 3 pixels × 3 lines, centered

over the surface position. Within this spatial range, the

mean and standard deviation for the satellite pixels will

be calculated in order to gauge the homogeneity of the

43
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 29. The main GUI of the derived product validation program is shown in this figure.

44
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 30. Shown here is the main GUI of the derived product validation program showing the IMG

pulldown menu.

45
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 31. The main GUI of the derived product validation program shows the secondary parameter and

level-2 flag selection menus.

46
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 5. Descriptions of fields (columns) for each result of a product validation matchup stored as a record in

an ASCII file.

Column Description

1 Satellite image file name with file path.

2 Year of image data.

3 Month of image data.

4 Day of image data.

5 Hour of image data.

6 Minute of image data.

7 Second of image data.

8 Time difference (minutes) between in situ and satellite values (VI and VS, respectively).

9 Solar zenith (degrees).

10 Solar azimuth (degrees).

11 Satellite zenith (degrees).

12 Satellite azimuth (degrees).

13 Satellite tilt (degrees).

14 Number of pixels, X SIZE, around matched image data.

15 Number of lines, Y SIZE, around matched image data.

16 Latitude (degrees).

17 Longitude (degrees).

18 Valid number of counts from X SIZE by Y SIZE domain.

19 Standard deviation calculated from X SIZE by Y SIZE of image domain.

20 Mean value calculated from X SIZE by Y SIZE of image domain.

21 In situ observation value (VI ).

22 Percent relative error between satellite and in situ values: 100(VS − VI )/VI .

23 Parameter name of primary parameter.

24 Condensed in situ observation file name with file path.

25 Original in situ observation file name.

26 Observed in situ data type (along track, station, drifter, buoys...).

27 Name of experiment or project during which in situ data were collected.

28 Name(s) of investigators responsible for in situ data.

29 Standard deviation of second parameter.

30 Mean of second parameter.

31 Name of second parameter.

...

. Standard deviation of Nth parameter.

. Mean of Nth parameter.

n Name of Nth parameter.

n + 1 Algorithm name of first level-2 flag.†

...

n + m Algorithm name of mth level-2 flag.†

† Level-2 pixels for which these flags were set were excluded from match-up calculations.

satellite data surrounding the surface point for comparison

with the sea-truth value. The allowable values for X_SIZE

and Y_SIZE are 0–15.

For level-2 products, each pixel is associated with a

16-bit quality flag field, l2_flags, each bit of which is

used to indicate quality conditions for that pixel (McClain

et al. 1995). In the derived product validation program,

quality flags may be selected such that, if they are set,

the associated pixels are excluded from the calculations of

the mean and standard deviation. Pixels with flag bits set

for land, cloud, or ice, for example, should obviously be

excluded in this manner. The level-2 quality flag selection

menu is also shown in Fig. 31.

All entered values can be saved by pressing the SAVE

button. The processing status will be displayed in the text

widget to indicate whether or not the selected command

was completed successfully. The saved values can also be

recalled by pressing the RESTORE button. Input, including

secondary parameters and level-2 quality flag selections,

will then be updated automatically.

When the RUN button is pressed, the program searches

the CVE database of satellite products and the in situ da47
SeaWiFS Calibration and Validation Quality Control Procedures

Table 6. Possible plots and associated statistical analyses for the evaluation of product validation matchup results. (The numbers under the Example column refer to figures found in this chapter.)

Plot Category Specific Plot Types Analyses Example

Plot Geolocation map Data Locations 7

Time Series Latitude plot 1 8

Longitude plot 1 8

Relative error plot 1 8

VS vs. VI Scatterplot 2 9

Cross correlation plot Data Shifting Test 9

Time series plot 1 3 9

Histogram 4 9

Relative Error (RE) Satellite data vs. RE plot 1 10

Latitude data vs. RE plot 1 10

Longitude data vs. RE plot 1 10

Solar zenith angle vs. RE plot 1 10

Solar azimuth angle vs. RE plot 1 10

Satellite zenith vs. RE plot 1 10

Satellite azimuth vs. RE plot 1 10

Time difference between VI and VS vs. RE plot 1 10

1 Correlation coefficient, linear fit, minimum, and maximum.

2 Correlation coefficient and linear fit.

3 Date and time, number of records, mean, variance, skewness, kurtosis, and standard deviation.

4 Bin size, number of bins.

tabase for scenes and data of the primary key that satisfy

the temporal and spatial restrictions. If some of both satellite and in situ data are found, the program calculates and

tabulates the results for output. If no matching data are

found, or if other errors occur, appropriate messages are

issued to the text window instead. Users can then either

enter new selections to continue data matching or press the

EXIT button to quit.

All in situ and image files used for matchups must be

entered in the CVE database. The program, however, will

also search the SDPS master database for scenes that are

not in the CVE database but that can be used for a given

matchup. If such scenes are found, a widget is displayed

listing the scenes available from SDPS and those available

from the DAAC, and advising the user on the need to

obtain these products.

Results from matched data points are saved to the user

specified file, which is in an ASCII column and row format.

The output will be appended to a file if the file already exists. Each column in the file is separated by a comma. The

columns (record fields) of the output file are listed in Table 5. By the selection of level-2 quality flags, it is possible

that within the X_SIZE by Y_SIZE image domain no valid

pixels exist. In such a case, the mean, standard deviation,

and percent relative error are written as 9999.0. Information concerning secondary parameters and level-2 flags

will be stored in the file only if some have been selected by

the user.

A future capability will be to allow a user to specify

a tolerence for the match-up results between level-2 images and in situ data. If a match-up difference is greater

than that value, the level-2 QC program would be automatically invoked with that image (Robinson et al. 1996).

This allows for visual inspection of the scene to see if the

in situ observations are near frontal boundaries, flagged or

masked pixels, or other irregular data. Also, the analyst

would then be able to use this program to reprocess the

level-2 image using alternate input parameters or other

algorithms implemented in that program for testing purposes. The reprocessed level-2 images could then be used

in the matchup to see if improved agreement with the in

situ data is obtained.

5.3 MATCH-UP EVALUATION

Results from matched satellite and in situ data points

need further evaluation to quantify the accuracy and the

limitations of the level-2 algorithms. Figure 32 depicts

the general steps followed when performing the match-up

evaluation. Based on the output file structure, shown in

Table 5, data records can be selected with the combinations

of ranges for spatial, temporal, and other variables. Once

desired data are selected, they can be analyzed by means

of plots and statistical analyses. Table 6 lists the 16 plots

that may be generated and the statistical analyses that

may be used in conjunction with each.

48
No

Yes

Product

Validation

Match-Up

Results

Data Selection

Criteria

Analysis Tools:

Data Plots

Statistical

Analysis

Output

Statistical

Results

Change

Criteria?

McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 32. A schematic diagram is presented, indicating the logical steps involved in the evaluation of

results from the SeaWiFS derived product validation match-up process.

Fig. 33. The main GUI of the product validation evaluation program is shown above.

49
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 34. The main GUI of the product validation evaluation program shows the geolocation map

obtained after an analysis run.

50
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 35. Latitudes, longitudes, and relative errors of match-up data are being evaluated, plotted against time.

51
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 36. A histogram, scatter plot, time trend, and cross correlation for satellite and in situ data are

used to evaluate the correlation of the two data sets.

52
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 37. a) A plot of the relative errors of satellite, time differential, latitude, and longitude versus

other variables are used to show correlations of error with these variables allowing the user to select

reasonable ranges for further analyses.

53
SeaWiFS Calibration and Validation Quality Control Procedures

Fig. 37 (cont.) b) As in Fig. 37a, although this is a plot of the relative errors of solar zenith, azimuth

satellite zenith, and azimuth versus other variables to show correlations of error with these variables

allowing the user to select reasonable ranges for further analyses.

54
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Fig. 38. The GUI shown is for evaluating match-up results using ranges obtained from a previous run

to restrict data in the following analysis.

55
SeaWiFS Calibration and Validation Quality Control Procedures

Table 7. SeaWiFS level-1 image database field names relevant to match-up processing.

Field Name Data Type Comment

l1 pathname string (≤128 char.) Image file directory path

l1 filename string (30 char.) Image file name

start time date/time Time of first scan line

datatype string (20 char.) LAC, GAC, HRPT

stop time date/time Time of last scan line

lower left lat 8-byte real

lower left lon 8-byte real

lower right lat 8-byte real

lower right lon 8-byte real

upper left lat 8-byte real

upper left lon 8-byte real

upper right lat 8-byte real

upper right lon 8-byte real

Table 8. SeaWiFS level-2 image database field names relevant to match-up processing.

Field Name Data Type Comment

l2 pathname string (≤128 char.) Image file directory path

l2 filename string (30 char.) Image file name

datatype string (20 char.) LAC, GAC, HRPT

l1 pathname string (≤128 char.) Image file directory path

l1 filename string (30 char.) Image file name

Table 9. Field names for the database table of in situ data.

Field Name Data Type Comment

start date string (9 char.)

start time string (9 char.)

end date string (9 char.)

end time string (9 char.)

start latitude 8-byte real

start longitude 8-byte real

end latitude 8-byte real

end longitude 8-byte real

investigator string (≤255 char.) Contact person(s)

affiliation string (≤255 char.)

experiment string (≤255 char.)

data type string (≤255 char.) Along track, station, drifter, buoys...

sequence number 4-byte integer For cast data

original file string (≤255 char.) Original filename

archive file string (≤255 char.) Condensed filename

column headers string (≤255 char.) Describes column content

south latitude 8-byte real Geographic extent of data

north latitude 8-byte real

west longitude 8-byte real

east longitude 8-byte real

56
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 10. Field names for the database table of validation match-up results.

Field Name Data Type Comment

create time date/time

pathname string (≤255 char.)

filename string (≤255 char.)

env type string (≤255 char.) Along track, station, drifter, buoys...

img level string (≤255 char.) Level-1, level-2 ̇

img type string (≤255 char.) LAC, GAC, HRPT.

primary string (≤255 char.) Primary parameter name.

secondary 1 string (≤255 char.) Secondary parameter name(s)

secondary 2 string (≤255 char.) (up to 11 names).

secondary 3 string (≤255 char.)

secondary 4 string (≤255 char.)

secondary 5 string (≤255 char.)

secondary 6 string (≤255 char.)

secondary 7 string (≤255 char.)

secondary 8 string (≤255 char.)

secondary 9 string (≤255 char.)

secondary 10 string (≤255 char.)

secondary 11 string (≤255 char.)

flag 1 string (≤255 char.) Level-2 pixels for which these flags (up to

flag 2 string (≤255 char.) 16) were set and which were excluded

flag 3 string (≤255 char.) from match-up calculations.

flag 4 string (≤255 char.)

flag 5 string (≤255 char.)

flag 6 string (≤255 char.)

flag 7 string (≤255 char.)

flag 8 string (≤255 char.)

flag 9 string (≤255 char.)

flag 10 string (≤255 char.)

flag 11 string (≤255 char.)

flag 12 string (≤255 char.)

flag 13 string (≤255 char.)

flag 14 string (≤255 char.)

flag 15 string (≤255 char.)

flag 16 string (≤255 char.)

start time date/time Data selection date and time range.

end time date/time

south latitude 8-byte real Data selection latitude range.

north latitude 8-byte real

west longitude 8-byte real Data selection longitude range

east longitude 8-byte real

sub time 1 4-byte integer Match-up time tolerance range.

sub time 2 4-byte integer

sub pixel 4-byte integer Match-up areal tolerance range (in pixels).

sub line 4-byte integer

57
SeaWiFS Calibration and Validation Quality Control Procedures

Table 11. Field names for the database table of match-up evaluation results files.

Field Name Data Type Comment

create time date/time

match-up file string (≤255 char.) Match-up results file name.

pathname string (≤255 char.) Evaluation output directory path.

filename string (≤255 char.) Evaluation output file name.

start time date/time Data selection date and time range.

end time date/time

south latitude 8-byte real Data selection latitude range.

north latitude 8-byte real

west longitude 8-byte real Data selection longitude range.

east longitude 8-byte real

data type 1 string (≤255 char.) In situ data types (along track,

data type 2 string (≤255 char.) station, drifter, buoys...; up to 7).

data type 3 string (≤255 char.)

data type 4 string (≤255 char.)

data type 5 string (≤255 char.)

data type 6 string (≤255 char.)

data type 7 string (≤255 char.)

experiment 1 string (≤255 char.) In situ collection experiment or

experiment 2 string (≤255 char.) project name (up to 7).

experiment 3 string (≤255 char.)

experiment 4 string (≤255 char.)

experiment 5 string (≤255 char.)

experiment 6 string (≤255 char.)

experiment 7 string (≤255 char.)

investigator 1 string (≤255 char.) Contact person(s) corresponding

investigator 2 string (≤255 char.) to each experiment name.

investigator 3 string (≤255 char.)

investigator 4 string (≤255 char.)

investigator 5 string (≤255 char.)

investigator 6 string (≤255 char.)

investigator 7 string (≤255 char.)

primary string (≤255 char.) Primary parameter name.

value 1 8-byte real Data value selection range

value 2 8-byte real for primary parameter.

r error 1 8-byte real Primary parameter relative error

r error 2 8-byte real selection range.

t diff 1 8-byte real Time difference selection range.

t diff 2 8-byte real

sun z 1 8-byte real Solar zenith angle selection range.

sun z 2 8-byte real

sun a 1 8-byte real Solar azimuth angle selection range.

sun a 2 8-byte real

sat z 1 8-byte real Satellite zenith angle selection range.

sat z 2 8-byte real

sat a 1 8-byte real Satellite azimuth angle selection range.

sat a 2 8-byte real

58
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Table 11. (cont.) Field names for the database table of match-up evaluation results files.

Field Name Data Type Comment

time 1 date/time Date and time selection range.

time 2 date/time

lat 1 8-byte real Latitude selection range.

lat 2 8-byte real

lon 1 8-byte real Longitude selection range.

lon 2 8-byte real

Figure 33 shows an IDL program that allows the analyst to select match-up records based on date, time, latitude and longitude for plotting and performing statistical

analyses. A map with latitudes, longitudes, and coastlines

may be displayed with the matched observation and satellite data points marked (Fig. 34). This map can help the

analyst to easily identify the region of interest. Time series

plots of latitude, longitude, and relative error not only provide trend analysis, but also identify spatial and temporal

outliers (Fig. 35). Two-variable plots focus on the comparison between satellite values and observed values (Fig. 36).

For a perfect matchup, the scatterplot will be a straight

line with a 45◦ angle and a correlation coefficient of 1. Relative error plots can help the analyst to graphically select

data (Fig. 37).

The EVALUATION button on Fig. 34 prompts the analyst

with another IDL GUI which contains more data selection

criteria (Fig. 38). There are four pull-down menus in which

data type, experiment, and investigator can have multiple

selections, and the primary key menu can have only one

selection. These pull-down lists are generated from valid

records which are spatially and temporally defined via the

GUI in Fig. 33. A valid range is listed for each data entry widget and can serve as a guide for specifying desired

values. Data selection criteria, statistical results, and the

final selected records may be saved into a file for reference.

The L2 QC button on Fig. 38 prompts the analyst to

get the level-2 QC program. This allows the analyst to

inspect a level-2 scene, or to reprocess the level-2 image

for testing purposes.

5.4 DATABASES

At least two input files are needed to perform SeaWiFS

derived product validation, one satellite file is identified

by the image database and one in situ file is identified by

the in situ database. The field names for the database

tables of the level-1 and -2 SeaWiFS image products and

in situ data are listed in Tables 7, 8, and 9, respectively.

Analyses can also produce two output files, one from the

product validation matchup and one from the match-up

evaluation.

Output files that store the results of these procedures

can be identified easily using the field names in the database tables listed in Tables 10 and 11. Note that all the

databases contain metadata, such as spatial and temporal

information, which are used by the database to select the

desired file paths and names.

5.5 CONCLUSIONS

Almost a decade after the end of the CZCS mission,

the ocean research community has gleaned about as much

as possible from that data set and is ready for the routine

collection of global ocean color data. With a significantly

improved sensor design and more systematic in situ observations, highly reliable data will be obtained. The sensor’s

performance will be carefully monitored to ensure that accurate calibrations are applied. To verify the accuracy of

SeaWiFS derived products, the derived product validation

software, discussed in this chapter, will be an important

tool.

Results from the matchup between sea-truth measurements and satellite derived products will be used to assess

the performance of the atmospheric correction and of the

bio-optical algorithm. Information such as location, time,

and viewing geometries, can assist scientists in identifying

the limitations of proposed algorithms in order to improve

their accuracy.

59
SeaWiFS Calibration and Validation Quality Control Procedures

Glossary

AMT Atlantic Meridional Transect

AQC Automatic Quality Control

ASCII American Standard Code for Information Interchange

AU Astronomical Unit

BATS Bermuda Atlantic Time-Series Station

BBSR Bermuda Biological Station for Research

BRDF Bidirectional Reflectance Distribution Function

CALVAL Calibration and Validation computer system

CHORS Center for Hydro-Optics and Remote Sensing

CLM Climatological ancillary data file

CVE Calibration and Validation Element

CZCS Coastal Zone Solor Scanner

DAAC Distributed Active Archive Center

e-mail Electronic Mail

FPAFocal Plane Assembly

GAC Global Area Coverage

GL SGI-specific Graphics Library

GMT Greenwich Mean Time

GSFC Goddard Space Flight Center

GUI Graphical User Interface

HDF Hierarchical Data Format

HRPT High Resolution Picture Transmission

IDL Interactive Data Language

IGC Intergain Calibration

IQC Interactive Quality Control

LAC Local Area Coverage

LAT Latitude

LUN Lunar

LUT Look-up Table

L1 Level-1

L1a Level-1a

L1b Level-1b

L2 Level-2

L3 Level-3

MLML Moss Landing Marine Laboratory (San Jose State

University)

MOBY Marine Optical Buoy

MODIS Moderate Resolution Imaging Spectroradiometer

NASA National Aeronautics and Space Administration

nfs Network File Services

NIST National Institute of Standards and Technology

NMC National Meteorological Center

NOAA National Oceanic and Atmospheric Administration

NRT Near-Real Time

OBS Observation

OSC Orbital Sciences Corporation

PML Plymouth Marine Laboratory

QC Quality Control

RE Relative Error

ROI Region of Interest

SAA South Atlantic Anomaly

SAT Satellite

SDPS SeaWiFS Data Processing System

SeaBASS SeaWiFS Bio-Optical Archive and Storage System

SeaDAS SeaWiFS Data Analysis System

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SGI Silicon Graphics Incorporated

SOL Solar

SST SeaWiFS Science Team

SZASolar Zenith Angle

TDI Time Delay and Integration

TIROS Television Infrared Observing Satellite

TOVS TIROS Operational Vertical Sounder

UCSB University of California at Santa Barbara

UIM/X User Interface Management/X-Windows

UNIX Not an acronym, but a computer operating system

developed by Bell Laboratory.

Symbols

LW N Normalized water-leaving radiance.

VI In situ observation value.

VS Satellite observation value.

λ Wavelength

σ Standard deviation.

References

Aiken, J., G.F. Moore, C.C. Trees, S.B. Hooker, and D.K.

Clark, 1995: The SeaWiFS CZCS-Type Pigment Algorithm. NASA Tech. Memo. 104566, Vol. 29, S.B. Hooker

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

Center, Greenbelt, Maryland, 34 pp.

Balch, W.M., R. Evans, J. Brown, G. Feldman, C. McClain,

and W. Esaias, 1992: The remote sensing of ocean primary

productivity–use of a new data compilation to test satellite

algorithms. J. Geophys. Res., 97, 2,279–2,293.

Barnes, R.A., W.L. Barnes, W.E. Esaias, and C.R. McClain,

1994a: Prelaunch Acceptance Report for the SeaWiFS Radiometer. NASA Tech. Memo. 104566, Vol. 22, S.B. Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 32 pp.

, A.W. Holmes, W.L. Barnes, W.E. Esaias, C.R. McClain,

and T. Svitek, 1994b: SeaWiFS Prelaunch Radiometric

Calibration and Spectral Characterization. NASA Tech.

Memo. 104566, Vol. 23, S.B. Hooker, E.R. Firestone, and

J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 55 pp.

Bigger, S.F., P.N. Slater, K.J. Thome, A.W. Holmes, and R.A.

Barnes, 1994: “Preflight solar-based calibration of SeaWiFS.” In: McClain, C.R., R.S. Fraser, J.T. McLean, J.K.

Firestone, F.S. Patt, B.D. Schieber, R.H. Woodward, En. Yeh, S. Mattoo, S.F. Biggar, P.N. Slater, K.J. Thome,

A.W. Holmes, R.A. Barnes, and K.J. Voss, 1994: Case

Studies for SeaWiFS Calibration and Validation, Part 2.

NASA Tech. Memo. 104566, Vol. 19, S.B. Hooker, E.R.

Firestone, and J.G. Acker, Eds., NASA Goddard Space

Flight Center, Greenbelt, Maryland, 25–32.

60
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

, K.J. Thome, P.N. Slater, A.W. Holmes, and R.A. Barnes,

1995: “Second SeaWiFS preflight solar radiation-based calibration experiment.” In: Mueller, J.L., R.S. Fraser, S.F.

Biggar, K.J. Thome, P.N. Slater, A.W. Holmes, R.A.

Barnes, C.T. Weir, D.A. Siegel, D.W. Menzies, A.F. Michaels, and G. Podesta, 1995: Case Studies for SeaWiFS

Calibration and Validation, Part 3. NASA Tech. Memo.

104566, Vol. 27, S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 20–24.

Campbell, J.W., J.M. Blaisdell, and M. Darzi, 1995: Level-3

SeaWiFS Data Products: Spatial and Temporal Binning

Algorithms. NASA Tech. Memo. 104566, Vol. 32, S.B.

Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 73 pp.,

plus color plates.

Carder, K.L., S.K. Hawes, and Z. Lee, 1996: SeaWiFS algorithm for chlorophyll a and colored dissolved organic matter in subtropical environments. J. Geophys. Res., (submitted).

Darzi, M., F.S. Patt, and L. Kumar, 1995: “Algorithm for the

application of the sensor calibration for SeaWiFS level-2

processing.” In: McClain, C.R., K. Arrigo, W.E. Esaias, M. Darzi, F.S. Patt, R.H. Evans, J.W. Brown, C.W.

Brown, R.A. Barnes, and L. Kumar, 1995: SeaWiFS Algorithms, Part 1. NASA Tech. Memo. 104566, Vol. 28, S.B.

Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 26–34.

, F.S. Patt, J.K. Firestone, B.D. Schieber, L. Kumar, and

D. Ilg, 1996: SeaWiFS Operational Archive Specifications,

NASA Tech. Memo. 104566, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, (submitted).

Eplee, R.E., Jr., M. Darzi, R.A. Barnes, and C.R. McClain,

1996: “SeaWiFS calibration verification.” In: C.R. McClain, M. Darzi, R.A. Barnes, R.E. Eplee, Jr., J.K. Firestone, F.S. Patt, W.D. Robinson, B.D. Schieber, R.H.

Woodward, and E-n. Yeh, 1996: SeaWiFS Calibration and

Validation Quality Control Procedures. NASA Tech.

Memo. 104566, Vol. 38, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 10–19.

Evans, R.H., and H.R. Gordon, 1994: Coastal zone color scanner “system calibration”: Aretrospective examination. J.

Geophys. Res., 99, 7,293–7,307.

Firestone, J.K., and B.D. Schieber, 1993: “The generation of

SeaWiFS near-real time ancillary data files.” In: C.R.

McClain, J.C. Comiso, R.S. Fraser, J.K. Firestone, B.D.

Schieber, E-n. Yeh, K.R. Arrigo, and C.W. Sullivan, 1996:

Case Studies for SeaWiFS Calibration and Validation, Part

2. NASA Tech. Memo. 104566, Vol. 19, S.B. Hooker and

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

Greenbelt, Maryland, 47–49.

, R.A. Barnes, F.S. Patt, M. Darzi, and C.R. McClain,

1996: “Engineering data display and quality control.” In:

C.R. McClain, M. Darzi, R.A. Barnes, R.E. Eplee, Jr.,

J.K. Firestone, F.S. Patt, W.D. Robinson, B.D. Schieber,

R.H. Woodward, and E-n. Yeh, 1996: SeaWiFS Calibration and Validation Quality Control Procedures. NASA

Tech. Memo. 104566, Vol. 38, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 4–9.

Gordon, H.R., 1987: Calibration requirements and methodology for remote sensors viewing the ocean in the visible.

Remote Sens. Environ., 22, 103–126.

, and M. Wang, 1994: Retrieval of water-leaving radiances

and aerosol optical thickness over oceans with SeaWiFS: a

preliminary algorithm. Appl. Opt., 33, 443–452.

Hapke, B., 1986: Bidirectional reflectance spectroscopy: 4. The

extinction coefficient and the opposition effect. Icarus, 67,

264–280.

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.

, C.R. McClain, J.K. Firestone, T.L. Westphal, E-n. Yeh,

and Y. Ge, 1994: The SeaWiFS Bio-Optical Archive and

Storage System (SeaBASS), Part 1. NASA Tech. Memo.

104566, Vol. 20, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 40 pp.

Kieffer, H.H., and R.L. Wildey, 1996: Establishing the moon as

a spectral radiance standard. J. Atmos. Ocean. Technol.,

13, 360–375.

McClain, C.R., W.E. Esaias, W. Barnes, B. Guenther, D. Endres, S.B. Hooker, B.G. Mitchell, and R. Barnes, 1992:

SeaWiFS Calibration and Validation Plan. NASA Tech.

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

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 41 pp.

, R.H. Evans, J.W. Brown, and M. Darzi, 1995: “SeaWiFS

quality control masks and flags: initial algorithms and implementation strategy.” In: McClain, C.R., K. Arrigo,

W.E. Esaias, M. Darzi, F.S. Patt, R.H. Evans, J.W. Brown,

C.W. Brown, R.A. Barnes, and L. Kumar, 1995: SeaWiFS

Algorithms, Part 1. NASA Tech. Memo. 104566, Vol. 28,

S.B. Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA

Goddard Space Flight Center, Greenbelt, Maryland, 3–7.

Mueller, J.L., and R.W. Austin, 1995: Ocean Optics Protocols

for SeaWiFS Validation, Revision 1. NASA Tech. Memo.

104566, Vol. 25, S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 67 pp.

Robinson, W.D., M. Darzi, and C.R. McClain, 1996: SeaWiFS

data quality control software. In: C.R. McClain, M. Darzi,

R.A. Barnes, R.E. Eplee, Jr., J.K. Firestone, F.S. Patt,

W.D. Robinson, B.D. Schieber, R.H. Woodward, and En. Yeh, 1996: SeaWiFS Calibration and Validation Quality Control Procedures. NASA Tech. Memo. 104566, Vol.

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

Space Flight Center, Greenbelt, Maryland, 24–41.

61
SeaWiFS Calibration and Validation Quality Control Procedures

Schieber, B.D., and J.K. Firestone, 1993: “The generation

of ancillary data climatologies.” In: C.R. McClain, J.C.

Comiso, R.S. Fraser, J.K. Firestone, B.D. Schieber, En. Yeh, K.R. Arrigo, and C.W. Sullivan: 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, 35–42.

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, 26 pp.

Yeh, E-n., M. Darzi, and C.R. McClain, 1996: “SeaWiFS Derived Product Validation Software.” In: C.R. McClain, M.

Darzi, R.A. Barnes, R.E. Eplee, J.K. Firestone, F.S. Patt,

W.D. Robinson, B.D. Schieber, R.H. Woodward, and En. Yeh, 1996: SeaWiFS Calibration and Validation Quality Control Procedures. NASA Tech. Memo. 104566, Vol.

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

Space Flight Center, Greenbelt, Maryland, 42–59.

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.B. Hooker, G. Mitchell, and R. Barnes, 1992: Calibration and Validation Plan for SeaWiFS. NASA Tech.

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

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 41 pp.

Vol. 4

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

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

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

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

Vol. 5

Mueller, J.L., and R.W. Austin, 1992: Ocean Optics Protocols

for SeaWiFS Validation. NASA Tech. Memo. 104566, Vol.

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

Space Flight Center, Greenbelt, Maryland, 43 pp.

Vol. 6

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

Report Series Cumulative Index: Volumes 1–5. NASA

Tech. Memo. 104566, Vol. 6, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 9 pp.

Vol. 7

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

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

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

Space Flight Center, Greenbelt, Maryland, 7 pp.

Vol. 8

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

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

Vol. 9

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

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

E.R. Firestone, and A.W. Indest, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 17 pp.

Vol. 10

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

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

of the SeaWiFS Solar and Lunar Observations. NASA

Tech. Memo. 104566, Vol. 10, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 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 Technical

Report Series Cumulative Index: Volumes 1–11. NASA

Tech. Memo. 104566, Vol. 12, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 28 pp.

Vol. 13

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

J.K. Firestone, B. Schieber, E-n. Yeh, and C.W. Sullivan, 1994: Case Studies for SeaWiFS Calibration and Validation, Part 1. NASA Tech. Memo. 104566, Vol. 13,

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

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

color plates.

Vol. 14

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

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

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 60 pp.

Vol. 15

Gregg, W.W., F.S. Patt, and R.H. Woodward, 1994: The Simulated SeaWiFS Data Set, Version 2. NASA Tech. Memo.

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

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

62
McClain, Darzi, Barnes, Eplee, Firestone, Patt, Robinson, Schieber, Woodward, Yeh

Vol. 16

Mueller, J.L., B.C. Johnson, C.L. Cromer, J.W. Cooper, J.T.

McLean, S.B. Hooker, and T.L. Westphal, 1994: The Second SeaWiFS Intercalibration Round-Robin Experiment,

SIRREX-2, June 1993. NASA Tech. Memo. 104566, Vol.

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

Space Flight Center, Greenbelt, Maryland, 121 pp.

Vol. 17

Abbott, M.R., O.B. Brown, H.R. Gordon, K.L. Carder, R.E.

Evans, F.E. Muller-Karger, and W.E. Esaias, 1994: Ocean

Color in the 21st Century: AStrategy for a 20 -Year Time

Series. NASA Tech. Memo. 104566, Vol. 17, S.B. Hooker

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

Center, Greenbelt, Maryland, 20 pp.

Vol. 18

Firestone, E.R., and S.B. Hooker, 1995: SeaWiFS Technical

Report Series Cumulative Index: Volumes 1–17. NASA

Tech. Memo. 104566, Vol. 18, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 47 pp.

Vol. 19

McClain, C.R., R.S. Fraser, J.T. McLean, M. Darzi, J.K. Firestone, F.S. Patt, B.D. Schieber, R.H. Woodward, E-n. Yeh,

S. Mattoo, S.F. Biggar, P.N. Slater, K.J. Thome, A.W.

Holmes, R.A. Barnes, and K.J. Voss, 1994: Case Studies

for SeaWiFS Calibration and Validation, Part 2. NASA

Tech. Memo. 104566, Vol. 19, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 73 pp.

Vol. 20

Hooker, S.B., C.R. McClain, J.K. Firestone, T.L. Westphal,

E-n. Yeh, and Y. Ge, 1994: The SeaWiFS Bio-Optical

Archive and Storage System (SeaBASS), Part 1. NASA

Tech. Memo. 104566, Vol. 20, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 40 pp.

Vol. 21

Acker, J.G., 1994: The Heritage of SeaWiFS: A Retrospective on the CZCS NIMBUS Experiment Team (NET) Program. NASA Tech. Memo. 104566, Vol. 21, S.B. Hooker

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

Center, Greenbelt, Maryland, 43 pp.

Vol. 22

Barnes, R.A., W.L. Barnes, W.E. Esaias, and C.R. McClain,

1994: Prelaunch Acceptance Report for the SeaWiFS Radiometer. NASA Tech. Memo. 104566, Vol. 22, S.B. Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard

Space Flight Center, Greenbelt, Maryland, 32 pp.

Vol. 23

Barnes, R.A., A.W. Holmes, W.L. Barnes, W.E. Esaias, C.R.

McClain, and T. Svitek, 1994: SeaWiFS Prelaunch Radiometric Calibration and Spectral Characterization. NASA

Tech. Memo. 104566, Vol. 23, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 55 pp.

Vol. 24

Firestone, E.R., and S.B. Hooker, 1995: SeaWiFS Technical

Report Series Cumulative Index: Volumes 1–23. NASA

Tech. Memo. 104566, Vol. 24, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 36 pp.

Vol. 25

Mueller, J.L., and R.W. Austin, 1995: Ocean Optics Protocols

for SeaWiFS Validation, Revision 1. NASA Tech. Memo.

104566, Vol. 25, S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 66 pp.

Vol. 26

Siegel, D.A., M.C. O’Brien, J.C. Sorensen, D.A. Konnoff, E.A.

Brody, J.L. Mueller, C.O. Davis, W.J. Rhea, and S.B.

Hooker, 1995: Results of the SeaWiFS Data Analysis

Round-Robin (DARR-94), July 1994. NASA Tech. Memo.

104566, Vol. 26, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 58 pp.

Vol. 27

Mueller, J.L., R.S. Fraser, S.F. Biggar, K.J. Thome, P.N. Slater,

A.W. Holmes, R.A. Barnes, C.T. Weir, D.A. Siegel, D.W.

Menzies, A.F. Michaels, and G. Podesta, 1995: Case Studies for SeaWiFS Calibration and Validation, Part 3. NASA

Tech. Memo. 104566, Vol. 27, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 46 pp.

Vol. 28

McClain, C.R., K.R. Arrigo, W.E. Esaias, M. Darzi, F.S. Patt,

R.H. Evans, J.W. Brown, C.W. Brown, R.A. Barnes, and

L. Kumar, 1995: SeaWiFS Algorithms, Part 1. NASA

Tech. Memo. 104566, Vol. 28, S.B. Hooker, E.R. Firestone,

and J.G. Acker, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 38 pp., plus color plates.

Vol. 29

Aiken, J., G.F. Moore, C.C. Trees, S.B. Hooker, and D.K.

Clark, 1995: The SeaWiFS CZCS-Type Pigment Algorithm. NASA Tech. Memo. 104566, Vol. 29, S.B. Hooker

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

Center, Greenbelt, Maryland, 34 pp.

Vol. 30

Firestone, E.R., and S.B. Hooker, 1996: SeaWiFS Technical

Report Series Cumulative Index: Volumes 1–29. NASA

Tech. Memo. 104566, Vol. 30, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 43 pp.

Vol. 31

Barnes, R.A., A.W. Holmes, and W.E. Esaias, 1995: Stray

Light in the SeaWiFS Radiometer. NASA Tech. Memo.

104566, Vol. 31, S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 76 pp.

Vol. 32

Campbell, J.W., J.M. Blaisdell, and M. Darzi, 1995: Level-3

SeaWiFS Data Products: Spatial and Temporal Binning

Algorithms. NASA Tech. Memo. 104566, Vol. 32, S.B.

Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 73 pp.,

plus color plates.

Vol. 33

Moore, G.F., and S.B. Hooker, 1996: Proceedings of the First

SeaWiFS Exploitation Initiative (SEI) Team Meeting.

NASA Tech. Memo. 104566, Vol. 33, S.B. Hooker and

E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, 53 pp.

63
SeaWiFS Calibration and Validation Quality Control Procedures

Vol. 34

Mueller, J.L., B.C. Johnson, C.L. Cromer, S.B. Hooker, J.T.

McLean, and S.F. Biggar, 1996: The Third SeaWiFS Intercalibration Round-Robin Experiment (SIRREX-3), 19–

30 September 1994. NASA Tech. Memo. 104566, Vol. 34,

S.B. Hooker, E.R. Firestone, and J.G. Acker, Eds., NASA

Goddard Space Flight Center, Greenbelt, Maryland, 78 pp.

Vol. 35

Robins, D.B., A.J. Bale, G.F. Moore, N.W. Rees, S.B. Hooker,

C.P. Gallienne, A.G. Westbrook, E. Mara ̃n ́on, W.H.

Spooner, and S.R. Laney, 1996: AMT-1 Cruise Report

and Preliminary Results. NASA Tech. Memo. 104566, Vol.

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

Space Flight Center, Greenbelt, Maryland, 87 pp.

Vol. 36

Firestone, E.R., and S.B. Hooker, 1996: SeaWiFS Technical

Report Series Cumulative Index: Volumes 1–35. NASA

Tech. Memo. 104566, Vol. 36, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland, (in press).

Vol. 37

Johnson, B.C., S.S. Bruce, E.A. Early, J.M. Houston, T.R.

O’Brian, A. Thompson, S.B. Hooker, and J.L. Mueller,

1996: The Fourth SeaWiFS Intercalibration Round-Robin

Experiment (SIRREX-4), May 1995. NASA Tech. Memo.

104566, Vol. 37, S.B. Hooker and E.R. Firestone, Eds.,

NASA Goddard Space Flight Center, Greenbelt, Maryland, 65 pp.

Vol. 38

McClain, C.R., M. Darzi, R.A. Barnes, R.E. Eplee, J.K. Firestone, F.S. Patt, W.D. Robinson, B.D. Schieber, R.H.

Woodward, and E-n. Yeh, 1996: SeaWiFS Calibration

and Validation Quality Control Procedures. NASA Tech.

Memo. 104566, Vol. 38, S.B. Hooker and E.R. Firestone,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 68 pp.

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 SeaWiFS Technical Report Series

Volume 38–SeaWiFS Calibration and Validation Quality Control Procedures

 Code 970.2

 July 1996 Technical Memorandum

 Elaine R. Firestone, Michael Darzi, Robert A. Barnes, Robert E. Eplee, James K. Firestone,

Frederick S. Patt, Wayne D. Robinson, Brian D. Schieber, Robert H. Woodward, and Eueng-nan Yeh: General Sciences Corporation,

Laurel, Maryland

 -

SeaWiFS, Oceanography, Quality Control, Procedures, Calibration, Validation, 64

Engineering Data, Ancillary Data, Quality Contol Software, Derived Product Validation

6. AUTHOR(S)

 Charles R. McClain, Michael Darzi, Robert A. Barnes, Robert E. Eplee,

 James K. Firestone, Frederick S. Patt, Wayne D. Robinson, Brian D. Schieber,

 Robert H. Woodward, and Eueng-nan Yeh

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

13. ABSTRACT (Maximum 200 words)

This document provides five brief reports that address several quality control procedures under the auspices of the Calibration and Validation Element (CVE) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1

describes analyses of the 32 sensor engineering telemetry streams. Anomalies in any of the values may impact sensor

performance in direct or indirect ways. The analyses are primarily examinations of parameter time series combined with

statistical methods such as auto- and cross-correlation functions. Chapter 2 describes how the various onboard (solar and

lunar) and vicarious (in situ) calibration data will be analyzed to quantify sensor degradation, if present. The analyses also

include methods for detecting the influence of charged particles on sensor performance such as might be expected in the

South Atlantic Anomaly (SAA). Chapter 3 discusses the quality control of the ancillary environmental data that are routinely received from other agencies or projects which are used in the atmospheric correction algorithm (total ozone, surface

wind velocity, and surface pressure; surface relative humidity is also obtained, but is not used in the initial operational

algorithm). Chapter 4 explains the procedures for screening level-1, level-2, and level-3 products. These quality control

operations incorporate both automated and interactive procedures which check for file format errors (all levels), navigation

offsets (level-1), mask and flag performance (level-2), and product anomalies (all levels). Finally, Chapter 5 discusses the

match-up data set development for comparing SeaWiFS level-2 derived products with in situ observations, as well as the

subsequent outlier analyses that will be used for evaluating error sources.