GOSAT / IBUKI Data Users Handbook

1st Edition

March 2011

Japan Aerospace Exploration Agency
National Institute for Environmental Studies
Ministry of the Environment

Preface
At the present stage of civilization, we are facing the big issue of global warming. We
may suffer a drastic environmental change in less than a few centuries if no effective
measures are taken. Efforts have been made worldwide to reduce greenhouse gases.
Japan also has a strong interest in reducing the gases and seeks steady means tomeasure the gas concentration.
However, only a limited number of observation points, dispersed not uniformly overthe globe, are available on the ground to measure greenhouse gases. In order toobserve the greenhouse gases (carbon dioxide and methane, principally)
concentration distribution over the whole globe periodically through a common
measuring method, Greenhouse gases Observing SATellite (GOSAT), so called“Ibuki”, project was started by Japan Aerospace eXploration Agency, National Institutefor Environmental Studies, and Ministry Of the Environment to launch the satellite on
the date of January 23rd, 2009. By accumulating the concentration distribution data
and the estimated uptake and release of greenhouse gases, carbon dioxide and/or
methane variation will be monitored and climate change in the future may come into
the scope of prediction.
The present handbook is meant for general users who are interested in using GOSAT
data and/or such users who have already been using the data with further interest for
better understanding of the data. GOSAT data are provided free of charge not only tothe limited number of governmental organization or researchers but also to the people
in general. However, no document has been provided for the users to clarify
systematically the overall of GOSAT with much emphasis on the outcome from thesatellite in service.
This handbook provides information necessary for GOSAT users, such as the naming
rule of the products, product format, and algorithmic explanation on the products in a
handy booklet to allow users to access information of their needs with ease. This
handbook, intended for introductory use rather than for specialists, only describes
characteristics of GOSAT standard products with expressions as easy as possible.
For further information beyond the scope of this document, please refer to thebibliographies recommended by the handbook.
We expect GOSAT data users, with the help of this handbook, through the extensive
use of GOSAT data, to clarify the global distribution and the temporal change of thegreenhouse gases, and to accumulate knowledge newly acquired about the carbon
circulation mechanism on the whole globe, and its influence on the climate change,
thereby contributing to the protection against global warming and environmental
conservation.
The Great East Japan Earthquake struck on March 11 during the process of creating
this handbook. However, both GOSAT satellite itself and Japan Aerospace
eXploration Agency’s ground system have kept the operation without damage. The
data processing facility of National Institute for Environmental Studies was almost
restored at the end of March.

GOSAT / IBUKI Data Users Handbook
First Edition
Contents

GOSAT / IBUKI Data Users Handbook
Contents
Chapter 1 Introduction ............................................................................................. 1-1
1.1 Purpose.......................................................................................................... 1-1
1.2 Scope and Composition ................................................................................. 1-1
1.3 GOSAT Mission Outline ................................................................................. 1-2
Chapter 2 GOSAT Spacecraft Outline...................................................................... 2-1
2.1 Configuration of the Spacecraft ...................................................................... 2-1
2.2 Mission Instruments Outline ........................................................................... 2-3
2.2.1 TANSO-FTS ............................................................................................ 2-3
2.2.2 TANSO-CAI ............................................................................................. 2-7
Chapter 3 GOSAT Mission Operation Outline.......................................................... 3-1
3.1 GOSAT Orbital Operations............................................................................. 3-1
3.1.1 Orbit Parameters ..................................................................................... 3-1
3.1.2 Orbit Control and Keeping ....................................................................... 3-1
3.2 TANSO-FTS / TANSO-CAI Operations .......................................................... 3-1
3.2.1 TANSO-FTS / TANSO-CAI, Functions and Performance......................... 3-2
3.2.2 Operation Mode....................................................................................... 3-3
3.2.3 On-orbit Operations ................................................................................. 3-6
3.2.3.1 Observation Pattern .......................................................................... 3-7
3.2.3.2 Constraints...................................................................................... 3-10
3.2.4 Summary of Nominal Operation .............................................................3-11
3.2.4.1 Routine Observation with no Sunglint Observation..........................3-11
3.2.4.2 Routine Observation with Sunglint Observation.............................. 3-13
3.2.4.3 Specific Point (1-point) Observation................................................ 3-16
3.2.4.4 Specific Point (Consecutive) Observation ....................................... 3-17
3.2.5 Operation of Lunar Calibration............................................................... 3-18
3.2.6 Operation of Blackbody / Deep-Space Calibration................................. 3-19
3.2.7 Operation of Solar Irradiance Calibration .............................................. 3-20
3.3 Setting of Sunglint Observation Region ....................................................... 3-20
3.4 Setting of Observation Gain ......................................................................... 3-20
Chapter 4 GOSAT Ground System.......................................................................... 4-1
4.1 Overview of GOSAT Ground System ............................................................. 4-1
4.2 JAXA System ................................................................................................. 4-1
4.3 NIES System.................................................................................................. 4-5
Chapter 5 GOSAT Ground System Operations ....................................................... 5-1i

GOSAT / IBUKI Data Users Handbook
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Contents

5.1 GOSAT Ground System Operations Outline .................................................. 5-1
5.2 GOSAT Data Acquisition and Transfer ........................................................... 5-1
5.3 GOSAT Data Processing................................................................................ 5-2
5.3.1 Level 1 Processing .................................................................................. 5-2
5.3.1.1 TANSO-FTS 1B Processing.............................................................. 5-2
5.3.1.2 TANSO-CAI Level 1B, 1B+ Processing............................................. 5-2
5.3.2 Higher Level Processing.......................................................................... 5-2
Chapter 6 GOSAT Products..................................................................................... 6-1
6.1 Product Unit ................................................................................................... 6-1
6.2 Products List .................................................................................................. 6-3
6.2.1 Level 1 Products...................................................................................... 6-6
6.2.2 Level 2 Standard Products....................................................................... 6-9
6.2.3 Level 3 Standard Products......................................................................6-11
6.2.4 Level 4 Standard Products..................................................................... 6-13
6.3 Definitions of Product File Names ................................................................ 6-14
6.4 Product Format ............................................................................................ 6-17
6.4.1 Data Storage Format ............................................................................. 6-17
6.4.2 Format Examples .................................................................................. 6-18
6.5 Level 1 Processing Algorithm....................................................................... 6-22
6.5.1 TANSO-FTS Level 1A Processing Algorithm ......................................... 6-22
6.5.2 TANSO-FTS Level 1B Processing Algorithm ......................................... 6-23
6.5.3 TANSO-CAI Level 1A Processing Algorithm .......................................... 6-28
6.5.4 TANSO-CAI Level 1B Processing Algorithm.......................................... 6-29
6.5.5 TANSO-CAI Level 1B+ Processing Algorithm........................................ 6-33
6.6 Higher level Processing Algorithm................................................................ 6-39
6.6.1 TANSO-FTS SWIR Level 2 Processing Algorithm for CO2 and CH4 Column
Amount ........................................................................................................... 6-39
6.6.2 TANSO-FTS TIR Level 2 Processing Algorithm for CO2 and CH4 Profiles....................................................................................................................... 6-43
6.6.3 TANSO-CAI Level 2 Cloud Flag Processing Algorithm .......................... 6-46
6.6.4 Processing Algorithm of TANSO-FTS SWIR Level 3 Global CO2 and CH4Distribution, and TIR Level 3 Global CO2 and CH4 Distribution ...................... 6-49
6.6.5 TANSO-CAI Level 3 Global Radiance Distribution Processing Algorithm(including cloudy segments) ........................................................................... 6-53
6.6.6 TANSO-CAI Level 3 Global Reflectance Distribution Processing Algorithm(Clear Sky) ..................................................................................................... 6-54
6.6.7 TANSO-CAI Level 3 Global NDVI Processing Algorithm ....................... 6-56

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Contents

6.6.8 Level 4 Processing Algorithm ................................................................ 6-60
6.7 Calibration and Validation............................................................................. 6-61
6.7.1 Calibration ............................................................................................. 6-61
6.7.1.1 Outline of Calibration Plan .............................................................. 6-61
6.7.1.2 Calibration Schedule....................................................................... 6-62
6.7.1.3 Calibration Items ............................................................................. 6-62
6.7.2 Validation ............................................................................................... 6-64
6.7.2.1 Summary of Validation Plan ............................................................ 6-64
6.7.2.2 Observation Experiments for Algorithm Validation .......................... 6-66
6.7.2.3 Validation of TANSO-FTS SWIR Products ...................................... 6-67
6.7.2.4 Validation of Parameters Related to SWIR Observation Error Factors.................................................................................................................... 6-72
6.7.2.5 Validation of TANSO-FTS Products................................................. 6-73
6.7.2.6 Validation of TANSO-CAI Products ................................................. 6-73
Chapter 7 GOSAT Data Product Distribution ........................................................... 7-1
7.1 Data Storage .................................................................................................. 7-1
7.2 Data Product Distribution Policy..................................................................... 7-1
7.2.1 Data Policy .............................................................................................. 7-1
7.2.2 User Category ......................................................................................... 7-4
7.2.3 Processing Version of a Product.............................................................. 7-5
7.2.3.1 Versions of TANSO-FTS Level 1B products...................................... 7-6
7.2.3.2 Versions of TANSO-CAI Level 1B, 1B+, and higher level products ... 7-6
7.2.4 Calibration stages and validation stages ................................................. 7-6
7.2.5 Purpose of data use ................................................................................ 7-8
7.3 How to search and get GOSAT data products................................................ 7-8
7.3.1 GUIG Functional Summary.................................................................... 7-10
7.3.2 Searching, ordering, and getting GOSAT data products........................ 7-12
Chapter 8 Point of Contact ...................................................................................... 8-1
8.1 About This Handbook..................................................................................... 8-1
8.2 About GOSAT Data ........................................................................................ 8-1
Appendix 1
Appendix 2
Appendix 3

Acronyms
Terminology
Bibliographyiii

GOSAT / IBUKI Data Users Handbook
First Edition
Contents

GOSAT / IBUKI Data Users Handbook
List of Tables and Figures[ Tables ]Table 2.1-1 GOSAT major specifications........................................................ 2-1
Table 2.2-1 TANSO-FTS Specifications ......................................................... 2-5
Table 2.2-2 TANSO-CAI specifications .......................................................... 2-8
Table 3.1-1 GOSAT nominal orbit parameters ............................................... 3-1
Table 3.2-1 TANSO-FTS operation mode ...................................................... 3-3
Table 3.2-2 TANSO-CAI operation mode ....................................................... 3-5
Table 3.2-3 CT scanning and observation cycle............................................. 3-8
Table 3.2-4 Time and location distances between observation points in AT and
CT directions ............................................................................................. 3-8
Table 6.2-1 GOSAT product list...................................................................... 6-5
Table 6.3-1 Product code of GOSAT products ............................................. 6-16
Table 6.4-1 Standard products and format documents................................. 6-19
Table 6.5-1 Map projection coverage ........................................................... 6-37
Table 6.7-1 TANSO-FTS calibration items ................................................... 6-62
Table 6.7-2 TANSO-CAI calibration items .................................................... 6-63
Table 7.2-1 User Categories .......................................................................... 7-4
Table 7.2-2 Definitions of the calibration stages for Level 1 standard products.................................................................................................................. 7-7
Table 7.2-3 Definitions of the validation stages for Level 2 standard products7-7
Table 7.2-4 Definitions of the validation stages for Level 3 standard products7-7[ Figures ]Fig. 1.3-1
Fig. 2.1-1
Fig. 2.1-2
Fig. 2.2-1
Fig. 2.2-2
Fig. 2.2-3
Fig. 2.2-4
Fig. 2.2-5

Roles of organizations in GOSAT project....................................... 1-2
GOSAT .......................................................................................... 2-1
GOSAT System configuration ........................................................ 2-3
Outside view of TANSO-FTS ......................................................... 2-4
Schematic diagram of TANSO-FTS optical systems ...................... 2-6
Data served by TANSO-FTS.......................................................... 2-7
Outside view of TANSO-CAI .......................................................... 2-8
Schematic diagram of observation by TANSO-CAI........................ 2-8

Fig. 3.2-1
Fig. 3.2-2
Fig. 3.2-3

TANSO-FTS operation mode transition diagram............................ 3-4
TANSO-CAI operation mode transition diagram ............................ 3-5
On-orbit operations of GOSAT ....................................................... 3-6

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Contents

Fig. 3.2-4 Schematic diagram of GOSAT observation(FTS is in 5-points
scan mode)................................................................................................ 3-7
Fig. 3.2-5 CT scanning pattern of FTS........................................................... 3-8
Fig. 3.2-6 Pointing mechanism movement and mirror angles permitted about
AT-axis and CT-axis .................................................................................. 3-9
Fig. 3.2-7 Synchronization of turnaround time with the CT-axis and AT-axis
settling times ........................................................................................... 3-10
Fig. 3.2-8 Example of a driving sequence in the 5-point observation mode,with a 300msec turnaround time ..............................................................3-11
Fig. 3.2-9 Example of routine observation (3 points) with no sunglint observation................................................................................................................ 3-12
Fig. 3.2-10 Example of routine observation with a sunglint observation ...... 3-14
Fig. 3.2-11 Example of sunglint operation span (winter solstice) ................. 3-15
Fig. 3.2-12 Example of sunglint operation span (summer solstice).............. 3-15
Fig. 3.2-13 Example of observation with a specific point (1-point) observation................................................................................................................ 3-17
Fig. 3.2-14 Example of specific point (consecutive) observation ................. 3-18
Fig. 4.1-1 Overall configuration of GOSAT ground system ............................ 4-1
Fig. 4.2-1 Overall Configuration of JAXA System........................................... 4-2
Fig. 4.3-1 Overall configuration of NIES GOSAT DHF ................................... 4-6
Fig. 6.1-1 Definition of FTS scene.................................................................. 6-2
Fig. 6.1-2 CAI scene and frame definition (Path 5) ........................................ 6-3
Fig. 6.2-1 Data Processing Flow of the GOSAT Products.............................. 6-6
Fig. 6.2-2 Example of FTS Level 1A product (interferogram) ......................... 6-7
Fig. 6.2-3 Example of FTS Level 1B product (spectra) andabsorption bandsof greenhouse gasses ............................................................................... 6-7
Fig. 6.2-4 Example of CAI Level 1B product .................................................. 6-8
Fig. 6.2-5 Example of CAI Level 1B+ product ................................................ 6-9
Fig. 6.2-6 Example of Level 2 CO2 column amount (SWIR) product (XCO2) 6-10
Fig. 6.2-7 Example of Level 2 CH4 column amount (SWIR) product (XCO4) 6-10
Fig. 6.2-8 Example of Level 2 cloud flag product ..........................................6-11
Fig. 6.2-9 Example of Level 3 global CO2 distribution (SWIR) product (XCO2).................................................................................................................6-11
Fig. 6.2-10 Example of Level 3 global CH4 distribution (SWIR) product (XCO4)................................................................................................................ 6-12
Fig. 6.2-11 Example of Level 3 global radiance distribution product ............ 6-12
Fig. 6.2-12 Example of Level 3 global reflectance distribution (clear sky) productv

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Contents................................................................................................................ 6-13
Fig. 6.3-1 File name definition of TANSO-FTS Level 1B product ................. 6-14
Fig. 6.3-2 File name definition of TANSO-CAI Level 1B product.................. 6-14
Fig. 6.3-3 File name definition of TANSO-CAI Level 1B+ product................ 6-14
Fig. 6.3-4 File name definition of TANSO-CAI Level 2 product .................... 6-14
Fig. 6.3-5 File name definition of TANSO-FTS SWIR Level 2 product ......... 6-15
Fig. 6.3-6 File name definition of TANSO-FTS TIR Level 2 product............. 6-15
Fig. 6.3-7 File name definition of TANSO-FTS SWIR Level 3 product ......... 6-15
Fig. 6.3-8 File name definition of TANSO-FTS TIR Level 3 product............. 6-15
Fig. 6.3-9 File name definition of TANSO-CAI Level 3 product .................... 6-15
Fig. 6.3-10 File name definition of TANSO-CAI Level 3 NDVI product......... 6-16
Fig. 6.3-11 File name definition of Level 4A product .................................... 6-16
Fig. 6.3-12 File name definition of Level 4B product .................................... 6-16
Fig. 6.4-1 Hierarchical Structure of HDF ...................................................... 6-18
Fig. 6.4-2 Group screen of GOSAT HDF Viewer (example of an FTS Level 1B
product) ................................................................................................... 6-21
Fig. 6.5-1 TANSO-FTS Level 1B processing flow ........................................ 6-24
Fig. 6.5-2 Interferogram and ZPD ................................................................ 6-26
Fig. 6.5-3 CAI Level 1B processing flow ...................................................... 6-30
Fig. 6.5-4 Frame separation for Level 1B processing .................................. 6-31
Fig. 6.5-5 Interposing observation location data .......................................... 6-33
Fig. 6.5-6 Concept of ortho rectification ....................................................... 6-33
Fig. 6.5-7 CAI Level 1B+ processing flow .................................................... 6-34
Fig. 6.5-8 Example usage of invalid value 0 ................................................ 6-36
Fig. 6.5-9 Calculate map projection area ..................................................... 6-37
Fig. 6.5-10 Lattice points in map coordinates and their projection on Level 1B+................................................................................................................ 6-38
Fig. 6.6-1 Processing flow for TANSO-FTS SWIR Level 2 CO2, CH4 column
amount .................................................................................................... 6-40
Fig. 6.6-2 Processing flow including the screening ...................................... 6-43
Fig. 6.6-3 Processing flow for TANSO-FTS TIR Level 2 CO2 and CH4 profiles................................................................................................................ 6-44
Fig. 6.6-4 Processing flow for TANSO-CAI Level 2 cloud flag...................... 6-47
Fig. 6.6-5 Level 3 processing flow for TANSO-FTS SWIR and TIR.............. 6-50
Fig. 6.6-6 Processing flow for TANSO-CAI Level 3 global radiance distribution................................................................................................................ 6-53
Fig. 6.6-7 Processing flow for TANSO-CAI Level 3 global reflectance distributionvi

GOSAT / IBUKI Data Users Handbook
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Contents(clear sky)................................................................................................ 6-55
Fig. 6.6-8 Processing flow of TANSO-CAI Level 3 global NDVI ................... 6-56
Fig. 6.6-9 Rectangles and rectangle numbers ............................................. 6-57
Fig. 6.6-10 Example of meshes placed at the northwest corner of rectangle 1(the angular distance between meshes is 15 seconds)........................... 6-58
Fig. 6.7-1 Schematic diagram of GOSAT products validation ...................... 6-65
Fig. 6.7-2 Example of browse data .............................................................. 6-74
Fig. 7.3-1 Website of GOSAT Project............................................................. 7-9
Fig. 7.3-2 GUIG top page............................................................................... 7-9
Fig. 7.3-3 User authentication window ..........................................................7-11
Fig. 7.3-4 Selection Menu window ................................................................7-11
Fig. 7.3-5 Flow to show searching, ordering, and getting of GOSAT data
products................................................................................................... 7-13
Fig. 7.3-6 GUIG Instruction Manual traced from the top page ..................... 7-14
Fig. 7.3-7 E-mail to inform the product generation completion..................... 7-15
Fig. 7.3-8 How to get GOSAT data product.................................................. 7-15
Fig. 7.3-9 Reference information on tools to display GOSAT data product .. 7-16

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GOSAT / IBUKI Data Users Handbook
First Edition
Chapter 1 Introduction

Chapter 1
1.1

Introduction

PurposeThis handbook intends to make the GOSAT (Greenhouse gases Observing
SATellite, so-called IBUKI) data be acknowledged by users in general and provides
the users with information about the GOSAT standard products as well as the
background knowledge of the spacecraft, sensors, ground systems, and so on;
thereby promoting a wide use of the data products and serving users withconvenience.
1.2

Scope and Composition

The present handbook is made of eight chapters with appendices as shown below.
Chapter 1:

Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6

:
:
:
:
:

Chapter 7
Chapter 8
Appendices:::

Describes the purpose, scope, and composition of the present
document the chapter also summarizes GOSAT mission.
Briefly describes GOSAT mission.
Briefly describes GOSAT mission operations.
Describes GOSAT ground systems.
Describes GOSAT ground system operations.
Describes specifications of GOSAT products and processing
algorithm for the products.
Explains the way the GOSAT products are provided.
Point of contact for the Handbook and GOSAT data products
Acronyms, terminology, and bibliography

Notes:The product specifications and processing algorithm are described here to give
readers essential perspectives as a whole; for details, please refer to the
documents listed in the appendix. “Algorithm Theoretical Basis Documents (ATBD)”,“Product format descriptions documents”, to name a few.
The data delivery service defined in chapter 7 deals with GOSAT data products
provided by National Institute for Environmental Studies (hereafter called NIES) for
general users1.

1

Please refer to 7.2.2 for the kinds of GOSAT users including general users.
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GOSAT / IBUKI Data Users Handbook
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Chapter 1 Introduction

1.3

GOSAT Mission Outline

GOSAT observes carbon dioxide and methane – two major green-house effectgasses – from space, a first satellite in the world for measuring the density of thegasses. It was launched on January 23, 2009, to conduct routine observation sinceApril 2009 after initial checkouts held in February through March. The expectedmission life is five years. (see Appendix A2 (5))
GOSAT data, being analyzed, serve to know how the carbon dioxide and methane
are distributed over the globe; and the green-house gas accounting – when andwherefrom the gasses are discharged or absorbed – is made to know its
geographical distribution and seasonal and/or yearly changes. Such knowledge
shall give deeper understanding in the science of behavior of carbon dioxide andmethane gasses – agent to cause global warming. The knowledge also serves as abasis for enhancing climate change predictions in the future, and for devisinganti-warming means such as carbon discharge reduction policy. GOSAT project is
promoted under the cooperative support of Ministry of the Environment (hereafter
called MOE), National Institute for Environmental Studies (NIES), and Japan
Aerospace eXploration Agency (hereafter called JAXA). Fig. 1.3-1 shows the role ofthe three organizations.

Fig. 1.3-1 Roles of organizations in GOSAT project

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GOSAT / IBUKI Data Users Handbook
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Chapter 2 GOSAT Spacecraft Outline

Chapter 2
2.1

GOSAT Spacecraft Outline

Configuration of the SpacecraftGOSAT is an Earth observation satellite to measure the greenhouse effect gasses,
carbon dioxide and methane in particular. The satellite was launched by H-IIA
launch vehicle on January 23rd, 2009 to the sun-synchronous sub-recurrent orbit
having an approximate altitude of 666 km. Fig. 2.1-1 shows a schematic diagram of
GOSAT, and Table 2.1-1 lists up the major specifications.

+X+Y
Travelling direction+Z
TANSO-FTS

Earth pointing direction

TANSO-CAI

Fig. 2.1-1 GOSAT
Table 2.1-1 GOSAT major specifications

Entry

Specifications
Frame body :Dimension

X (height)
3.7m
Y (width)
1.8m
Z (depth)2.0m(projections ignored)
Paddle ends distance 13.7m

Mass

1,750kgPower supply

3.8kw (at the end of mission life)

Mission life

5 years

Launch date

January 23, 2009

Earth observation mission oriented instruments GOSAT is equipped with are“Thermal And Near infrared Sensor for carbon Observation - Fourier Transform
Spectrometer” (hereafter called TANSO-FTS or FTS) and “Thermal And Near
infrared Sensor for carbon Observation Cloud and Aerosol Imager” (hereafter
called TANSO-CAI or CAI). Other mission oriented instruments are “TEchnical Data

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GOSAT / IBUKI Data Users Handbook
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Chapter 2 GOSAT Spacecraft Outline

Acquisition equipment” (hereafter called TEDA) and monitoring CAMera (hereafter
called CAM). Fig. 2.1-2 shows GOSAT system configuration.
TANSO-FTS is a Fourier transform spectrometer having three bands of observation
wavelength in ShortWave InfraRed frequencies (hereafter called SWIR) and one
band in Thermal InfraRed frequencies (hereafter called TIR). This gives 7 channelsof observed data simultaneously acquired, six of which are made of 2 polarizedcomponents (P-polarization and S-polarization) of respective SWIR three bands,
and TIR the remaining one.
TANSO-CAI is a push broom type optical sensor equipped with one-dimensionallyarrayed detectors and three telescopes to have four bands of observation
wavelengths ranging from ultraviolet to short wavelength infrared. Spatial resolution
in nadir view, with an observation scan width of about 1,000km, is about 500m forbands 1 through 3, and about 1,500m for band 4 with 750km of scan width.
Data captured by TANSO-FTS and/or TANSO-CAI are processed in Mission Data
Handling System (hereafter called MDHS) and recorded into Mission Data
Processor (hereafter called MDP) as per every Application Process ID (hereafter
called APID). The recorded data are played back above receiving stations totransmit them to the ground facilities using Direct Transmission system (hereafter
called DT) through X-band channel. The MDP, the recording apparatus, uses 48GB
(BOL:16GByte×3) semiconductor memories.
Robustness is secured for the mission data transmission by preparing a route to
bypass the MDP memory in case the memory bus meets some trouble. The data
for the route are made in the sensors by branching off the same mission data; thedata having bypassed the memory then multiplexed in MDHS as usual andtransmitted to the ground stations. The data thus prepared will stay not transmitted
under normal conditions; however in case of the memory bus failure they are sent
replacing the playback data mentioned above.

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Chapter 2 GOSAT Spacecraft Outline

GOSAT
Mission instruments
Fourier Transform Spectrometer (TANSO-FTS)
Cloud and Aerosol Imager (TANSO-CAI)

for observation mission

Technical Data Acquisition equipment (TEDA)
for mission in general
Monitor camera (CAM)
Mission Data Handling System (MDHS)
for mission data transfer

Direct Transmission (DT)BUS instruments
Telemetry Tracking & Control (TT&C)
Electric Power System (EPS)
Solar Paddle (PDL)
Attitude & Orbit Control System (AOCS)
Structure (STR)
Thermal Control System (TCS)
Reaction Control System (RCS)
Integration Hardware (INT)

Fig. 2.1-2 GOSAT System configuration

2.2

Mission Instruments Outline

This section explains briefly about the two mission instruments installed on GOSAT
for Earth observation.
2.2.1 TANSO-FTS(1) Outline
TANSO-FTS performs spectroscopic observation on both short wavelength infrared
sunlight reflected by the surface of the earth after it has come through theatmosphere, and thermal infrared light radiated from the atmosphere. Fig. 2.2-1
shows the outside view of TANSO-FTS, while Table 2.2-1 lists up its specifications.
Calculations based on observations of 2.0µm range CO2 absorption and of 1.6µm
range CO2 and/or CH4 absorption give an air-column quantity2, while its altitudinous2

Air-column quantity: Total amount of gasses in a vertical column having unit cross-section (number ofmolecules per unit area)
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GOSAT / IBUKI Data Users Handbook
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Chapter 2 GOSAT Spacecraft Outline

profile may be calculated from observations of thermal infrared range. Fourierinterferometer is used for spectroscopy which may provide high resolution of
0.2cm-1 over a wide span of wavelength. In normal operations, one interferogram isacquired every four seconds. Orientating mechanism about the Along Track(hereafter called AT)3 axis and Cross Track (hereafter called CT) axis4 allow thesensor to scan in the CT direction, to point to the sunglint spot and/or
predetermined locations, and to keep pointing a place during one wholeinterferogram capturing.
The Fourier interferometer is a double-cornered cubic type, while a long-life
semiconductor laser of 1.31µm wavelength is used for sampling in order to realize
the mission life of five years. The detectors make use of Si, InGaAs, and PC-MCT,
where a polarizing beam splitter is used with the bands 1 through 3 to observe thetwo polarized beams simultaneously.
On orbit calibration is conducted for SWIR using solar irradiance diffused by adiffuser plate, and for TIR sensitivity using a blackbody. Calibration making use of
the moon is also conducted. Further, semiconductor laser beam of 1.55µm
wavelength is utilized to calibrate the instrument functions for the equipment.
TANSO-FTS conducts geometrical evaluation using a view monitoring camera
installed in the TANSO-FTS and GCPs on the ground.

FTS
CAI

Fig. 2.2-1 Outside view of TANSO-FTS

3

Along Track: The direction a spacecraft travels, a coordinate axis forming the spacecraft-fixed
coordinates.
4
Cross Track: A direction perpendicular to along-track, an axis to form the spacecraft-fixed
coordinates.
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Table 2.2-1 TANSO-FTS Specifications

PointingmechanismInterferogram

Configuration

two-axes pointing (wholly redundant)

Scanning

CT (±35 deg）

View

IFOV <10.5 km scan width 790 km

Scanning
frequency

0.25, 0.5, or 1 interferogram/second

AT (±20 deg)

SWIR
Band

1

TIR

2

3

4

Polarization

applicableapplicableapplicable

N/A

Wavenumbers(cm-1)

12,900-13,200

5,800- 6,400

4,800- 5,200

700-1,8000.75 - 0.78

1.56 -1.72

1.92 - 2.08

5.5 -14.3

Wavelength (μm)-1

Resolution (cm )Detector
On-orbit
calibration-1

0.2 cm (scan on both sides) (MOPD +/-2.5 cm)
Si

InGaAsfor sensitivity: solar irradiance,
deep space, the moonfor instrument functions:semiconductor laser

PC-MCT
blackbody,
deep space(2) Observation procedure
Observations are conducted to follow the steps a. to g. described below; while Fig.
2.2-2 shows schematically how the optical system works, wherein symbols a to gcorrespond to the itemized paragraphs respectively.
a. Introduce the light beams to capture into sensors by orientating the pointing
mechanism toward the object to observe. The bands 1 through 3 capture thesunlight reflected from the atmosphere and the surface of the earth, while the band
4 captures the heat radiated from the atmosphere and the earth’s surface.
b. The beam-splitter of a Fourier interferometer splits the captured beams into two
directions.
c. The beams split into different directions are added once again to interfere eachother after travelling different lengths of optical path. The interference pattern thus
acquired is called an interferogram. (see Fig. 2.2-3 (a) )d. The input observation light thus made interfered by the Fourier interferometer isconcentrated into a slit, thereby forming a view field in common to all the bands(15.8mrad or 10.5km on the surface of the earth).
e. Observation light beams parallelized by optical equipment including the slit are
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separated, by dichroic filter placed one after another, into bands of frequencies
ranging from short waves to longer ones.
f. The band-separated light beams go through a band filter prepared for each band,by which extra signals outside the band frequencies be eliminated, and enters into
a detector; while the beams of band 1 to 3 are split into two polarized light beams(P-polarization and S-polarization) by a polarization beam splitter before entering
into the detector.
g. The detector, working as a photoelectric converter, converts the observation
signals (interferogram) to electric signals, and let them sent down to groundstations.
h. Information is extracted from the data captured on the ground andFourier-converted to get a spectrum of the observed light. (see Fig. 2.2-3 (b) )Deep spacecal. light
Observed lightBlackbodycal. light Solar irradiance cal. lighta. Main pointing mechanism
Monitoring camera

Light path changer
Redundant pointing mechanism
Corner cubeb. Beam splitterd. Slite. Dichroic filterc. Fourier interferometermechanism
f. Band passfilterBand passfilterBand passfilter
PC-MCT (band4)
detector

Polarized beam
splitterg. Si (band1) g. InGaAs (band2) g. InGaAs (band3)
P/S detector
P/S detector
P/S detector

Fig. 2.2-2 Schematic diagram of TANSO-FTS optical systems

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Chapter 2 GOSAT Spacecraft Outline(a) Interferogram(b) Spectra

Intensity

Radiance signal

Wavenumbers

Optical path difference (cm)Fig. 2.2-3 Data served by TANSO-FTS

2.2.2 TANSO-CAI(1) Outline
TANSO-CAI is a push-broom type optical sensor having four bands of frequencies
ranging from ultraviolet to shortwave infrared. Fig. 2.2-4 shows the outside view of
TANSO-CAI, while Table 2.2-2 lists up its specifications.
CAI, a sensor auxiliary to FTS, captures a picture image of the ground covering thearea observed by FTS. The CAI data are used to evaluate the validity of FTS data
and are used to correct them. When CAI data detect some dense cloud in the viewof FTS, FTS data may be discarded depending on the information derived from CAI.
Further, when CAI data detect aerosol and/or a cirrus cloud, FTS data are modified
using the aerosol and cirrus cloud attributes (characteristics and optical thickness)
estimated by the CAI data.
CAI, being equipped with electronic scanning imagers for a plurality of frequency
bands ranging from ultraviolet, through visible, to shortwave infrared, will conduct
highly accurate observation of cirrus clouds in high altitudes and the spread ofaerosol including the ones over land areas. It has a wide span of observation widthof 1,000km with ±35deg CT view angles. Band 1, 2, or 3 exhibits a spatial
resolution of about 500m at nadir, while band 4 does show about 1,500m.
Geometrical evaluation for TANSO-CAI is done making use of GCP (Ground
Control Point) on the ground.

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FTS
CAI

Fig. 2.2-4 Outside view of TANSO-CAI
Table 2.2-2 TANSO-CAI specifications

Band 1

Band 2

Band 3

Band 4

Central wavelength (m)

0.38

0.674

0.87

1.6

Wavelength band width (nm)

20

20

20

90

Spatial resolution (km)(at nadir)

0.5

0.5

0.5

1.5

Number of elements

2,056

2,056

2,056

512

(2) Observation method
TANSO-CAI composes its images from signals provided by CCD elements
arranged in line; these elements are prepared for each of the four bands ofobservation signals. Fig. 2.2-5 shows schematically how the CAI observation isconducted.
Conducting daytime observations on sunlit areas, CAI covers the whole globe inthree days with spatial resolution of 500m for the bands 1 to 3, and of 1,500m forthe band 4.
(a) band 1, 2, or 3(b) band 4

instantaneous FOV
instantaneous FOV

500m

・・・・・・・・・・・・・・・・・・・・

1,500m・・・・・・・・・・・

500m
1,000km・・・・・・・・・・・

1,500m
750km

flight direction

flight direction

Fig. 2.2-5 Schematic diagram of observation by TANSO-CAI

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Chapter 3 GOSAT Mission Operation Outline

Chapter 3
3.1

GOSAT Mission Operation Outline

GOSAT Orbital Operations

3.1.1 Orbit Parameters
Table 3.1-1 shows GOSAT nominal orbit parameters.
Table 3.1-1 GOSAT nominal orbit parameters

Parameter

Value

Orbit typesun-synchronous sub-recurrent orbit

Revolutions per day

14+2/3 revolutions/day

Days of recurrence

3 days

Altitude665.96km

Eccentricity

0.0Inclination

98.06 degrees

Period98.1 minutes approximately

Revolutions for a recurrence

44 revolutions

Local sun time at crossing
13:00 ± 15 minutes
the descending node
3.1.2 Orbit Control and Keeping
GOSAT has an attitude-orbit-control system that may keep its orbit autonomously
by monitoring how accurate the orbit is and by planning enough frequency ofmaneuvers to keep its orbit adjusted. As a result, sun synchronous sub-recurrent
orbit is kept with local descending time, altitude, period, and the like kept nearly
constant. This allows GOSAT to conduct sensor observations recurrently with arecurrence error of less than ±2.5km.
Based on GPS (Global Positioning System) data, GOSAT automatically calculates
such maneuver parameters as injection strength, duration, and injection timing of
the fuel; the parameters thus calculated onboard are sent down to ground stationsin telemetry data. The ground station sends a permission command for the plannedautonomous orbit maneuvers after it has confirmed that the maneuver parameters
are reasonable.
As of December, 2010, orbit maneuvers are conducted once in 6 to 9 days.
3.2

TANSO-FTS / TANSO-CAI Operations

This section describes the functions of TANSO-FTS and TANSO-CAI, and explains
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how they are utilized in operation.
3.2.1 TANSO-FTS / TANSO-CAI, Functions and Performance(1) Functions of TANSO-FTS
a. Observes the atmosphere by SWIR using frequencies ranging from visible toshortwave infrared, while TIR conducts the observation using thermal infrared
frequencies.
b. Observation direction is controllable by a pointing mechanism equipped with twoaxes of rotation (AT-axis, CT-axis) to allow observation as follows.
1) Scans along the CT direction with intervals of a predetermined angle.
2) In routine observation, observes predetermined number of points scanning 1, 3, 5,
7, or 9 points along the CT direction; the observed points will form a grid-likepattern on the earth’s surface when the scan is repeated at an interval along the
AT direction.
3) Keeps pointing the same place during the whole capture of an interferogram
which may last 1 to 4 seconds (exposure time).
4) In order to improve Signal to Noise Ratio (SNR), may observe a same place
repeatedly to sum the observed data up (3 times of repetition, or only once with norepetition).
5) Points to a specified place or a sunglint for observation (sunglint: a place where
the ocean surface reflects sunlight, like a mirror, toward the spacecraft).
c. Observes a same place every three recurrent days.
d. Conducts on-orbit calibration listed below.
1) The solar irradiance calibration for SWIR, and blackbody calibration for TIR.
2) Deep space calibration for both SWIR and TIR.
3) Orients the GOSAT +Z axis (usually pointing to the earth) to the moon andconducts annual calibration of sensitivity using the sunlight reflected by the moon.
(2) Functions of TANSO-CAI
a. Captures 1,000km observation width of images of the earth’s surface with spatial
resolution of 0.5 to 1.5km.
b. Serves data to estimate an amount of clouds and aerosol in the atmosphereobserved; based on this estimation, FTS data may be corrected or discarded.
c. Orients the GOSAT +Z axis (usually pointing to the earth) to the moon andconducts annual calibration of sensitivity using the sunlight reflected by the moon.

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3.2.2 Operation Mode
Table 3.2-1 lists up the operation modes of TANSO-FTS, while the transition among
the modes is shown in Fig. 3.2-1 TANSO-FTS operation mode transition diagram.
TANSO-FTS works in observation mode I or in specific observation mode, andcalibrates itself in calibration modes.
For TANSO-CAI, Table 3.2-2 lists up its operation modes, while the transition
among the modes is shown in Fig. 3.2-2. TANSO-CAI usually works in observationmode, and calibrates itself in calibration modes.
Transition time between modes will be minimized in so far as instruments are kept
in safer conditions.

Table 3.2-1 TANSO-FTS operation mode
Operation mode

All off modeStandby mode I

Standby mode II
Refrigerator standby
Refrigerator cools-down
modeLight Load Mode I(LLM-I)

Light Load Mode II(LLM-II)

OutlineThis mode is set effective right after the installation
into the spacecraft on the ground, and kept till the
primary power supply is switched on (100 minutes
after the launch). In Super Light Load Mode
(S-LLM), a mode for GOSAT to stay alive withserious damage, the sensor will be kept in thisAll-off-Mode. S-LLM demands least amount of
power consumption still lower than Light Load
Mode (LLM).
A mode to satisfy the conditions demanded by
Observation Mode I. The detectors for shortwave
infrared and thermal infrared are cooled down.
A mode to satisfy the conditions demanded by
Observation Mode II. The shortwave infrared
detector is cooled down.
A mode to satisfy the conditions to start therefrigerator.
Cool the thermal infrared detector with the signal
processer and refrigerator switched on; used in theinitial operational phase; while the refrigerator isbasically kept on.
A mode to keep TANSO-FTS in a state free fromany defects, failures, or unrecoverable degradationin case GOSAT is placed in abnormal attitude
and/or power supply is out of order; wherein the
refrigerator, interferometer mechanism, andpointing mechanism are switched off while survival
heaters and command reception circuits are kepton.
The LLM-I is set effective when the primary power
supply is switched on after the launch.
The survival hearer for the refrigerator radiator isset off while other survival heaters and command
reception circuits are kept on. This mode may be
applied in case a wing of the solar paddle pair isout of order.
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Chapter 3 GOSAT Mission Operation Outline
Operation mode

Observation
mode I

Daytimeobservation
Nighttimeobservation

Observation mode II

Diagnostic mode
Specific
observation mode
Solar irradiancecalibration

Calibration
mode

Lunar
calibration
Instrument
functioncalibration
Electricalcalibration

OutlineConduct observations using shortwave infrared(SWIR) and thermal infrared (TIR); black-bodycalibration and deep space calibrations are also
conducted.
Conduct observations using thermal infrared (TIR);
black-body calibration and deep space calibrations
are also conducted.
Stop operating thermal infrared (TIR) and freeze
pointing mechanism when power supply is
lowered. Observation using TANSO-FTS is
restricted to 10 minutes per revolution while
Standby Mode II is supposed to apply for the restof hours, and TANSO-CAI will be kept in All off
Mode.
Diagnosetherefrigerator
andremovecontaminations off the cooling device if necessary.
Observe specific places such as sites forverification and points along a pipeline. Sun glint
points are also included.
Perform calibration using the sunlight dissipated by
the sun irradiance diffuser plate at the time justbefore the ground surface is illuminated by thesun.
Calibrate sensitivity using the sunlight reflectedfrom the moon at its highest average brightness
while the spacecraft orient its +Z axis to the moon.
Calibrate instrument functions using the laser
beams emitted by the laser diode installed in thesensor.
Calibrate the signal processor including the analog
signal processing unit by applying standard signal
voltage.

specific
observation

Remarks
routineobservation
routineobservation

non-routine
observation

as required
routineobservation
once perrevolution
about oncea yearabout oncea monthabout oncea monthobservation I
calibration

LLM I

standby II

diagnosis

refrigerator standby
all off

heater off

standby II
refrigerator cool down

LLM II

observation II

Transition triggered bycommands
LLM command
S-LLM command

Fig. 3.2-1

TANSO-FTS operation mode transition diagram
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Table 3.2-2 TANSO-CAI operation mode
Operation mode

All off modeStandby mode I

Standby mode II

Light Load Mode (LLM)

Observation mode

OutlineThis mode is set effective right after the
installation into the spacecraft on the ground,and kept till the primary power supply isswitched on (100 minutes after the launch).
A mode for GOSAT to stay alive with serious
damage demanding a power consumption
smaller than Light Load Mode (LLM),
whereby the mission instruments are notensured to work operational. When GOSAT
is in Super Light Load Mode (S-LLM), thesensor will be kept in this All-off-Mode.
Keep the status necessary for conducting
observations. Keep the temperature of
sensor devices within the operational
acceptance limits.
Keep the temperature of sensor devices
within the acceptance limits.
A mode to keep the cloud-aerosol sensor ina state free from any defects, failures, or
unrecoverable degradation in case GOSAT
is placed in abnormal attitude and/or power
supply is out of order; wherein only survival
heaters and command reception circuits are
kept on.
The LLM is set effective when the primary
power supply is switched on after the launch.
Conduct observations

Lunarcalibration

Calibrate sensitivity using the sunlightreflected from the moon at its highest
average brightness while the spacecraftorient its +Z axis to the moon.

Signalprocessing
calibration
Nighttime
calibration

Calibrate the signal processor by applying
nominal signal voltage before the analog
signal processing unit.
Calibrate offset levels by conducting nightobservations.

Calibration
mode

calibration

observation

LLM

standby I

Remarks

Done about once a
year to calibrate
some
of
the
elements
linearly
arrayedwhereonthe calibrating lightilluminates.
about oncea monthabout oncea monthTransition triggered bycommands
LLM command
S-LLM command
all off

standby II

Fig. 3.2-2 TANSO-CAI operation mode transition diagram

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3.2.3 On-orbit Operations
Fig. 3.2-3 shows the on-orbit operations of GOSAT, and the summary of each
operation is described below ((1) to (5) in Fig. 3.2-3 respectively correspond toparagraphs (1) to (5) in the description of this section).

Reflected sunlight fromthe moonNighttime

DaytimeSunlight

GOSAT orbit(1) FTS (SWIR), CAI observation range(5) FTS, CAI lunar calibration(2) FTS (TIR) observation range(3) CAI nighttime calibration(4) FTS (SWIR) solar irradiance calibration

Fig. 3.2-3 On-orbit operations of GOSAT(1) FTS SWIR and CAI observation
Since FTS SWIR and CAI observe the sunlight reflected from the ground surface,observation is performed only during the daytime. FTS SWIR is operated in theobservation mode I or in the specific observation mode, while CAI is operated in theobservation mode. FTS SWIR performs deep-space calibration at a position
arbitrarily chosen on the orbit (performs it every revolution).
(2) FTS TIR observation
Since FTS TIR observes thermal radiation from the ground surface, the observationis performed during both the daytime and nighttime.
FTS TIR is operated in the observation mode I or in the specific observation mode.
FTS TIR performs blackbody calibration and deep-space calibration at a position
arbitrarily chosen on the orbit (performs it every revolution).
(3) CAI nighttime calibration
CAI performs offset-level calibration using the data acquired in the nighttime when
no incidental light may come into the optical system (performs approximately oncea month).
(4) FTS SWIR solar irradiance calibration
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Solar irradiance calibration is performed on FTS SWIR using the sunlight diffusedby a diffuser plate as a calibration source when the satellite is in sunlight and theground surface is in shadow (when passing above the north pole; performed every
revolution).
(5) FTS and CAI lunar calibration
Lunar calibration for both FTS and CAI is carried out in the revolution in which theaverage luminance of the moon becomes its maximum (carried out about once ayear).
3.2.3.1 Observation Pattern
In the routine observation, TANSO-FTS scans observation points in the CT
direction with 1, 3, 5, 7, or 9 points to observe; this makes an grid-like pattern ofobserved points to calculate the interferogram about the atmosphere above them.
On the other hand, TANSO-CAI captures images of the ground surface. Fig. 3.2-4
shows an schematic diagram of GOSAT observation, while Fig. 3.2-5 shows a CT
scanning pattern of FTS.

TANSO-CAI observation data

Flight direction(AT)

TANSO-FTS observation points( 5-points scan in this case)

Cross-track direction(CT)

Fig. 3.2-4 Schematic diagram of GOSAT observation(FTS is in 5-points scan mode)

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Five observation patterns:
Number of points per
cross-track scan is 1, 3, 5, 7
or 9.

GPS
GPS receiverStar tracker
GOSAT
Sensor (pointing mechanism)

88 - 800km

Flight (along-track) direction
Cross-track direction

Fig. 3.2-5 CT scanning pattern of FTS

Observation time, distances between the observation points, and the like differ
depending on the number of CT scanned points. Table 3.2-3 indicates the patternof an observation cycle for each scanned point. Table 3.2-4 shows the distance
between the observation points in the CT direction and the AT direction for eachobservation pattern.
Table 3.2-3
Number of CT scanned points
1-point observation
3-point observation
5-point observation
7-point observation
9-point observation

CT scanning and observation cycle
Observation duration at atime per point (sec)
4.0
4.0
4.0
2.0
1.1

It is permitted to lock the pointing mechanism immediately before the start time of a specified
observation so as to adjust the observation timing.
Number of repetitions on the same point: observation is made for the same point multiple times
to sum up the observed data to improve the accuracy of SNR.

Table 3.2-4

Time and location distances between observation points in AT and CT directions

Number of CT
scanned points

Horizontal
distance atlatitude 30
deg (km)

Verticaldistance atlatitude 30
deg (km)

Observation
time perobservation
point
(sec)

1-point observation
3-point observation
5-point observation
7-point observation
9-point observation

788.8
262.9
157.8
112.7
87.6

90.3
283.1
152.2
114.9
86.2

12.8
13.2
4.0
2.0
1.1



Number.of repetitions on thesame point
3
3
1
1
1

CT
settling
time
(sec)
N/A
0.6
0.45
0.4
0.4

AT
settling
time
(sec)
0.4
0.6
0.45
0.4
0.4

AT
interval
time
(sec)
13.2
41.4
22.2
16.8
12.6

AT
angularrange(deg(+/-))
3.7
12.1
6.5
4.9
3.7

Observation time per observation point: in the 1-point and 3-point observation modes, it
includes twice of the turnaround time (CT settling time = AT settling time) since interferogram issuperimposed three times.

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Chapter 3 GOSAT Mission Operation Outline
AT interval time = observation time per observation point × Number of CT observation points +CT settling time × (Number of CT observation points - 1) + AT settling time = (observation time
per observation point + turnaround time) × Number of CT observation points

The pointing mechanism performs Image Motion Compensation (IMC) about the
AT-axis during a scan in the CT direction, thereafter returns the mirror about the
AT-axis to do a subsequent scan after the primary scan.
Fig. 3.2-6 illustrates the operation of the pointing mechanism and the mirror angles
permitted about the two axes.
The pointing mechanism carries out the scan operation on both the AT-axis andCT-axis in synchronization with turnaround signals transmitted from theinterferometer controller (transmitted at the timing when the FTS scan mirror
returns back; see Fig. 3.2-7).
+Y+X
AT direction

AT direction

CT-axis actuator+Z
Earth pointing direction

AT-axisCT-axisFrom FTS

20°

20°

AT-axis cross-section+Y+X

CT direction scanby CT-axis rotation+Z
End of interferogram
acquisition

Start of interferogram
acquisition

35°

Cancellation of footprint movement by
AT-axis rotation (IMC function)

35°

CT-axis cross-section

Fig. 3.2-6 Pointing mechanism movement andmirror angles permitted about AT-axis and CT-axis

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Chapter 3 GOSAT Mission Operation Outline: Interferogram acquisition point

AT direction: Scan direction

AT-axis settling time
= turnaround time

X km movement

X km movement

CT-axis settling time

Y seconds

Y seconds= turnaround time

Neighboring orbit

Neighboring orbits distance(30deg) 789km

At nadirFig. 3.2-7 Synchronization of turnaround time with the CT-axis and AT-axis settling times

3.2.3.2 Constraints(1) Synchronization between the pointing mechanism and Fourier interferometerAs the pointing mechanism performs the scan operation synchronized to theturnaround signals transmitted from the Fourier interferometer, the following
periods of time must be kept the same.
 The time needed for the scan mirror of the Fourier interferometer to return back(= turnaround time) CT-axis settling time of the pointing mechanism AT-axis settling time of the pointing mechanism(2) Constraints of the Fourier interferometer Adjustable range of turnaround time: 300ms to 650ms(3) Settling time constraints of the pointing mechanism 1, 7, and 9-point CT observations:
400msec
 5-point CT observation:
450msec 3-point CT observation:
600msec
The turnaround time can be set in a range of 300 to 650msec (nominal 400msec).
An example of a driving sequence in the 5-point observation mode is shown in Fig.
3.2-8, in which all of the turnaround times take the smallest value (300ms).

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drive

0.3

Observation. drive

4.0

0.3

Observation drive

4.0

0.3

CT-axisCT-axisCT-axisCT-axisAT-axisObservation drive

4.0

Observation drive

0.3

4.0

AT-axisObservation drive

0.3

4.0

0.3

Observation

4.0

5-point observation, the shortest case
5 x (4.0+0.3) = 21.5sec

Fig. 3.2-8 Example of a driving sequence in the 5-point observation mode,with a 300msec turnaround time

3.2.4 Summary of Nominal Operation
3.2.4.1 Routine Observation with no Sunglint Observation(1) Operation overview
The routine observation with no sunglint is a pattern of operation frequently applied
to GOSAT; its summary is described below. The outline of the sunglint observationis mentioned in section 3.2.4.2.
 FTS and CAI carry out the observation in the observation mode I and theobservation mode, respectively.
 SWIR of FTS and CAI observe the ground surface in a sunlit condition.
 Start and end times for the daytime observation by SWIR of FTS and CAI are
specified by stored commands (command including a time as a parameter to be
triggered by the clock).
 TIR of FTS observes both sunlit and shadow regions all the time.
 For a routine observation of the FTS observation mode I, there are provided a
total of five modes each corresponding to each of the numbers of scanning points
in the CT direction, i.e., 1, 3, 5, 7, and 9.
 FTS receives the ascending node passing time from the satellite so as to adjust
the clock time (for adjusting FTS scan cycles).
 The same observation points, with the same number of CT scan points (1, 3, 5, 7,
and 9) and accompanied observation mode, are observed repeatedly every
three-day recurrent cycle (geolocational allowance: 4 km).
 At the initial stage of nominal operation, FTS started its observation with ascanning pattern of five points in the CT direction (scan time: 4.0 seconds per
point) resulting in a grid-like pattern of observed points mapped on the ground;on June 26, 2009 however, the scanning pattern was changed to a W-shaped
one.

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 On August 2, 2010, the number of scanning points in the CT direction waschanged from 5 to 3 (scan time: 13.2 seconds per point); since then, the scan
operation has been carried out with the three scanning points in the CT direction5.
(2) Example of operation pattern
CAI acquires images of the ground when the surface is sunlit. An example ofroutine observation (3-point observation) without sunglint observation is illustrated
in Fig. 3.2-9, wherein FTS works in the observation mode I with three scanningpoints in the CT direction.
One revolution of orbit(Ground surface in shadow, satellite in sunlight)(Ground in shadow, sat. in sunlight

Sunlit/shadow(Ground in shadow, sat. in shadow)(Ground in sunlight, sat. in sunlight)t(Ground in shadow, sat. in shadow)

Calibration of BB and DS

TANSO-FTS
SWIR

Observation mode I

TIR

Observation mode I
Solar irradiance cal. mode

Observation mode

TANSO-CAI
Above equator

Land

Land

Land

Above equator

Ground surface

Sea

Sea
AT

Satellite trajectoryCTon the grounda case with no sunglint
and with 3-points observation(Note: BB for blackbody, DS for deep-space)
Fig. 3.2-9 Example of routine observation (3 points) with no sunglint observation

5

The standard location of the points meshed by 5 and 3 scans are found on GUIG website by tracing"Products and Services"  "Path calendar". About GUIG (GOSAT data distribution website) further
explanation is given in chapter 7.
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3.2.4.2 Routine Observation with Sunglint Observation(1) Operation summary
FTS conducts a sunglint observation above the ocean as a specific observation
mode of the FTS. The observation mode applied to sunglint observation is similar
to the mode for specific point observation later explained (see section 3.2.4.3 and3.2.4.4). As seawater absorbs sunlight, it is usually difficult to observe reflection of
the sunlight above the oceanic areas. However, at a sunglint point wherefrom thesunlight is reflected towards the spacecraft just like it is reflected by a mirror,
sufficient amount of light is reflected to allow an observation.
The area for sunlight observation is set for each season and the observation isconducted at the places located on middle to low latitude above the ocean.
Observation time and angles of AT and CT are specified by the commands sentfrom the ground so that the observations of sunglint points are performed over a
strip-shaped region.
(2) Example of operation patternFig. 3.2-10 illustrates an example of routine observation including a sunglint
observation in the sunlit area. FTS switches from the observation mode I (5-point
observation) to the specific observation mode at the start of a sunglint to observe,
performs the sunglint observation, and returns back to the observation mode I.

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One revolution of orbit(Ground surface in shadow, satellite in sunlight)

Sunlit/shadow(Ground in shadow, sat. in shadow)(Ground in shadow, sat. in sunlight)(Ground in sunlight, sat. in sunlight)(Ground in shadow, sat. in shadow)

Calibration of BB and DS
Specific observation mode

Observation mode I

TANSO-FTS
SWIR
TIR
Solar irradiance cal.mode
TANSO-CAI

Observation mode

Above equator

Sea

Land

Land

Land

Sea

Above equator

Sea

Ground surface

AT

Satellite ground trajectoryCT

Sunglint area

(Note: BB for blackbody, DS for deep-space)
Fig. 3.2-10 Example of routine observation with a sunglint observation

Figs. 3.2-11 and 3.2-12 schematically illustrate the regions on the satellite paths
over which sunglint observation is performed (sunglint operation region) at the
winter solstice and summer solstice, respectively (purple colored bold-lines show
the sunglint region). A numeral written on a path indicates the number of sunglint
observations conducted for each path taking a series of observations onconsecutive points as a unit.

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Chapter 3 GOSAT Mission Operation Outline

Fig. 3.2-11 Example of sunglint operation span (winter solstice)
A numeral on each path is the number of consecutive
observation points in the same path on a land area.

Fig. 3.2-12 Example of sunglint operation span (summer solstice)
A numeral on each path is the number of consecutive
observation points in the same path on a land area.

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3.2.4.3 Specific Point (1-point) Observation(1) Operation summary
For observing a specific and relatively narrow region such as a calibration and/or
validation site, the specific observation mode is taken to carry out FTS specificpoint (1-point) observation. The observation mode applied to this observation is thesame as the one applied to sunglint observation (see section 3.2.4.2) and/or
specific points (consecutive) observation (see section 3.2.4.4). The observation
time and angles of AT and CT are specified by the commands sent from theground.
If the time for a specific point observation and the time for a blackbody /deep-space calibration (see section 3.2.6) overlap each other, the blackbody /deep-space calibration is given priority and executed. Accordingly, in order to carryout a specific point (1-point) observation, some of the times for blackbody /deep-space calibration must be changed beforehand.
(2) Example of operation patternFig. 3.2-13 illustrates an example of observation including a specific point (1-point)
observation on the sunlit area. FTS switches from the observation mode I (5-point
observation) to the specific observation mode at the point to observe, carries out
the specific point observation, and returns back to the observation mode I.

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Chapter 3 GOSAT Mission Operation Outline

One revolution of orbit(Ground in shadow, sat. in sunlight(Ground in shadow, sat. in sunlight)

Sunlit/shadow(Ground in shadow, sat. in shadow)(Ground surface in sunlight, satellite in sunlight)(Ground in shadow, sat. in shadow)

Calibration of BB and DS
Specific observation mode

TANSO-FTS

Observation mode I

SWIR
TIR
Solar irradiance cal. mode
Observation mode

TANSO-CAI

Above equator

Land

Land

Land

Above equator

Ground surface
Sea

Sea

Sea

Specific point observation target

AT

Satellite ground trajectoryCT

Sunglint area

(Note: BB for blackbody, DS for deep-space)
Fig. 3.2-13 Example of observation with a specific point (1-point) observation

3.2.4.4 Specific Point (Consecutive) Observation(1) Operation summary
For observing a specific points consecutively, a specific point (consecutive)
observation is carried out as a FTS specific observation mode. The specific point(consecutive) observation enables the consecutive observation of points spreading
wide region or the one along a line. The observation mode applied to thisobservation is the same as the one applied to sunglint observation (see section
3.2.4.2) and/or specific point (1-point) observation (see section 3.2.4.3). The
observation time and angles of AT and CT are specified by the commands sentfrom the ground.
If the time for a specific points observation and the time for a blackbody /deep-space calibration (see section 3.2.6) overlap each other, the blackbody /3-17

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deep-space calibration is given priority and executed. Accordingly, in order to carryout the specific point (consecutive) observation some of the times for blackbody /deep-space calibration must be changed beforehand.
(2) Example of operation patternFig. 3.2-14 illustrates an example of a specific points (consecutive) observation on
the sunlit area. FTS switches from the observation mode I to the specificobservation mode at the start of the region to observe, carries out the specific point
observation, and returns back to the observation mode I.
One revolution of orbit(Ground surface in shadow, satellite in sunlight)(Ground in shadow, sat. in sunlight)

Sunlit/shadow(Ground in shadow, sat. in shadow)(Ground in sunlight, satellite in sunlight)(Ground in shadow, sat. in shadow)

Calibration of BB and DS
Solar irradiance calibration mode

TANSO-FTS
SWIR
TIR

Specific observation mode

Observation mode I

Observation mode

TANSO-CAI
Above equator

Land

Land

Land

Above equator

Ground surface
Sea

Sea

Sea

AT
Specific points
along a line
CT

Specific points
spreading wide region

Satellite groundtrajectorySpecific point (consecutive) observation range(Note: BB for blackbody, DS for deep-space)
Fig. 3.2-14 Example of specific point (consecutive) observation

3.2.5 Operation of Lunar Calibration
GOSAT calibrates the sensitivity of FTS and CAI using the sunlight reflected from
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the moon surface as a calibration source; this type of calibration is performed about
once a year. The calibration source is the amount of light reflected from the wholesurface of the moon and integrated over a time.
Through this calibration CAI can calibrate the sensitivity for a limited number of
elements arrayed in line because only a portion of the arrayed elements is hit uponby the calibration light from the moon. The remaining elements are calibrated using
the light reflected from the ground as the surface of a desert; the sensitivity of suchelements is calibrated by relatively comparing the behavior of the elements with theones already calibrated. In case an element placed at the central portion of CAI had
a failure, an offset bias is given to the pointing direction of the satellite so as to
avoid using the element in failure.
The lunar calibration is performed in a revolution when the sun, earth, and satellite
make an angle of approximately 180 degrees, and at the time when the averageluminance of the moon reaches its maximum as viewed from GOSAT. During therevolution in which the lunar calibration is performed, the satellite is controlled tokeep the earth out of sight in order not to let the earth’s surface and the atmosphere
below 100km come into the view field of FTS (± 35deg in the CT direction and ±20deg in the AT direction measured from the GOSAT’s nadir).
For the lunar calibration of FTS, GOSAT orients its +Z-axis (earth pointing direction)
toward the center of the moon for more than two minutes, during which the wholemoon come into the view field of FTS. After that, in order to capture images for CAI,GOSAT rotates itself at a uniform speed of 0.04 ± 0.01deg/sec about the Y-axis witha range of ±1.3deg to cover the whole surface of the moon; this rotational motion isrepeated twice consecutively (4 scans).
(As for the definition of axes of GOSAT, see Fig. 2.1-1.)
3.2.6 Operation of Blackbody / Deep-Space Calibration
In the observation mode I or the specific observation mode of FTS, blackbody anddeep-space calibration operations are performed for every revolution at places
arbitrarily specified by the command transmitted from the earth (the specification ismade by the time to elapse since the satellite passes the ascending node; amaximum of 16 times of calibrations may be specified). The blackbody calibrationis performed on FTS TIR, while the deep-space calibration is performed on both
FTS SWIR and TIR. Figs. 3.2-9, 3.2-10, 3.2-13, and 3.2-14 illustrate the timing theblackbody and deep-space calibrations are carried out. The calibration timing may
be changed to meet the needs; if no changes are made, calibrations are performedat the same timing as in the preceding revolution.
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Chapter 3 GOSAT Mission Operation Outline

The blackbody and deep-space observations for calibration are carried out in thesame observation time (1.1, 2, or 4 seconds; see Table 3.2-3) as the observations
conventionally performed. Both the blackbody and deep-space calibrations needobservations of four points; in addition, a transition between a observation and acalibration takes the time almost the same as the time to observe one point;
however, data rate does not change because the detectors keep accepting the data
even in the transitions.
3.2.7 Operation of Solar Irradiance Calibration
In order to calibrate the sensitivity of FTS SWIR, GOSAT switches to the solar
irradiance calibration mode and performs the calibration for about two minutes,
once per revolution, immediately before its nadir comes into the sunlit area on thesurface of the ground (at the time when the sunlight hits upon the solar irradiancecalibration plate). The time of calibration is specified by the command for eachrevolution; no calibration is carried out if no commands are given.
Figs. 3.2-9, 3.2-10, 3.2-13, and 3.2-14 illustrate the timing the blackbody anddeep-space calibrations are carried out.
3.3

Setting of Sunglint Observation Region

In order to carry out the sunglint observations, the values defining the sunglint
regions (see of Appendix A2 (3)) and the sunglint operation span (see Appendix A2(4)) must be specified before planning the sunglint observation. These values arecalculated for every quarter of a year, or every season.
GOSAT observations are planned for every month based on observation requests
while the requests of sunglint observation are basically issued as an internal
observation request. If any change is required for the plan, the whole plan of themonth is reconfigured again.
3.4

Setting of Observation Gain

A gain is a factor to amplify an input signal to a voltage appropriate for signal
processing; it must be given by a command depending on the brightness (amountof light input) of the target to be observed. Both FTS and CAI of GOSAT can set thegain in three levels, L (Low), M (Middle), or H (High).
Observation gains for each of FTS and CAI are described below.

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Chapter 3 GOSAT Mission Operation Outline(1) Setting of TANSO-FTS gain
Three levels (Low/Middle/High) of gain setting are available for each polarization
component (P-polarization and S-polarization) in the case of SWIR (Bands 1, 2,
and 3). On the other hand, the gain for TIR (Band 4) is a fixed value.
Principal gain settings for FTS are shown below.
 Routine observation, specific point observation: Gain H
Note that the gain M is chosen, if necessary, to observe desert areas located in
low latitude with a high ground surface reflectance.
 Sunglint observation:
Gain H
Note that the gain M is chosen if necessary.
 Solar irradiance calibration:
Gain M (fixed)
 The gain Low is not used in principle.
In the following types of observation, the gain may be changed depending on paths
and an argument of latitude (see appendix A2 (6)).
 When the satellite passes through the predetermined range of argument oflatitude.
 When a sunglint observation is performed.
 When a specific point observation is performed.
(2) Setting of TANSO-CAI gain
As of December, 2010, the gain for CAI is controlled by adjusting the duration oftime, integration is carried out; while three levels (Low/Middle/High) of gain value
are applicable to CAI.
The integration time duration will be defined depending on paths and an argumentof latitude. The values of time duration thus assigned are kept as a static parameterand may be altered as required.

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Chapter 4 GOSAT Ground System

Chapter 4
4.1

GOSAT Ground System

Overview of GOSAT Ground System

The GOSAT ground system consists of the JAXA and NIES systems. The JAXA
system performs operations such as satellite control, data acquisition and primarydata processing, whereas the NIES system performs operations such as higher
level data processing and products distribution. In addition, a data acquisition
station located at high latitude (SvalSat / Norway) is utilized in order to increase
data acquisition opportunities.
The overall configuration of GOSAT ground system is illustrated in Fig. 4.1-1.
High-latitude
f oreign station

Computation
centerResearchers
Observ ation requests

Acquisition plan L0 preprocessed data
Orbit inf ormation

Processed result

Data transf er

L1 products
Observ ation plan

Users

NIES system

JAXA system
Observ ation requests
Standard products

Data distribution
Ref erence data

Reference data
providersFig. 4.1-1 Overall configuration of GOSAT ground system

4.2

JAXA System

The configuration of JAXA system is illustrated in Fig. 4.2-1, and general functionsof each component in the JAXA system are described below.

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Chapter 4 GOSAT Ground System

X-Band、S-Band
X-BandHigh-latitude foreign station(SvalSat)GOSAT
S-BandX-band acquis ition sys tem
L０ Preprocessed data

DACS
Ground networks

Recording sys tem（katsuura, Okinawa, Masuda, Kiruna, Santiago,

EOC（ Hatoyama ）HK dataRanging data

L0 preprocessed data
Acquisition plan
Orbit prediction

Perth）SMACS

Acquisition plan
Orbit prediction

Users

uFDS

Orbit prediction
Observ ation plan

EORC Information System（EIS）

Observ ation plan
Commands

GOSAT MMO
Data distribution

FTS L1A,L1B,CAI L1A
Calibration products
Processed result, Observ ation plan

High-lev el products
Orbit prediction
L1 products
Observ ation plan

Lev el 0 preprocessed data
Observ ation planL0 data
FTS L1A,L1B,
CAI L1A

Calibration products
Processed result

GOSAT data processing sys tem

CAI L1B、L1B+
Catalog inf ormation
Calibration data

GOSAT
data analysis
systemObserv ation requests
Gain setting
Sunglint region/
operation range

NIES
GOSAT
DHF

Observ ation
requests

Calibration data

GOSAT onboard
technology
Observ ation requests
evaluation system
L1 processing algorithm
Calibration coef f icients

TKSC（Tsukuba）

Fig. 4.2-1 Overall Configuration of JAXA System(1) X-band acquisition system The X-band acquisition system tracks GOSAT to capture X-band mission data
(via DT) from the satellite, amplifies the signal level of the acquired data to apredetermined level, and demodulates the signal data to transmit to the recording
system.
 This system is composed by adding a demodulator for GOSAT and a modulator
for test signal generation to the acquisition system for Advanced Earth Observing
Satellite "Midori" (ADEOS) and Marine Observation Satellite-1 "Momo-1"(MOS-1) placed in the Earth Observation Center (may called hereafter EOC).
GOSAT shares the X-band acquisition system with Advanced Land Observing
Satellite "Daichi" (hereafter called ALOS) which is in operation as of December
2010.

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Chapter 4 GOSAT Ground System The X-band acquisition system is installed in the EOC.
(2) Recording system The recording system receives the demodulated signals outputted from the
X-band acquisition system, carries out packet synchronization processing inaccordance with the CCSDS (Consultative Committee for Space Data System)
recommendation, and creates the APID sorted data (called hereafter Level 0
preprocessed data) to record them in a hard disk. The recording system also
records the demodulated signals directly after digital conversion (hereafter called
RAW data).
 The recorded GOSAT Level 0 preprocessed data are transmitted to the GOSAT
Data Processing System via the EORC Information System (may called hereafter
EIS).
 The recording system is installed in the EOC.
(3) Foreign stations on a high-latitude (SvalSat / Norway)
 In order to acquire the global observation data, the Svalbard Satellite station(hereafter called SvalSat), operated by Kongsberg Satellite Services (hereafter
called KSAT, Norway), is utilized as an overseas data acquisition station locatedat high latitude.
 When mission data are downlinked from a satellite on a sun-synchronous orbit,
only a limited number of satellite passes are visible from the stations in Japanbecause Japan is located at middle latitude to cover a small portion of satellite
passes. On the other hand, all of the satellite passes are visible to the stations ina high-latitude country; accordingly, a number of satellite passes far greater thanin Japan are available for data acquisition.
 SvalSat acquires X-band mission data from the satellite, creates Level 0
preprocessed data, and records the created data together with RAW data in a
hard disk.
 The recorded GOSAT Level 0 preprocessed data are transmitted to the GOSAT
Data Processing System via EIS.
 SvalSat is also utilized as a backup station for S-band operations.
(4) EOC Data Acquisition Control System
 An operational conflict between ALOS and GOSAT takes place because dataacquisition operations for these satellites are performed simultaneously at EOC.
The EOC Data Acquisition Control System must resolve such conflict.

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Chapter 4 GOSAT Ground System The system examines and resolves the conflict to produce acquisition plans foreach of the satellites and manages the operation schedules of the X-band
acquisition system, the recording system, etc. The system distributes theoperation plans as well.
 The EOC Data Acquisition Control System is installed in the EOC.
(5) GOSAT Data Processing System The GOSAT Data Processing System performs Level 0 processing of GOSAT
mission data, performs Level 1 processing of TANSO-FTS and TANSO-CAI
mission data, and creates calibration data.
The system is installed in the Tsukuba Space Center (may called hereafter
TKSC).
(6) GOSAT Onboard Technology Evaluation System The GOSAT Onboard Technology Evaluation System accepts observation
requests of TANSO-FTS from NIES; requests from the Science Team are also
included.
 The system puts together the observation requests from NIES and observation
requests from the GOSAT operation team of JAXA to coordinate them, andtransmits the coordinated result to the GOSAT Mission Management andOperation system.
 The GOSAT Onboard Technology Evaluation System is installed in the TKSC.
(7) GOSAT Mission Management and Operation system (GOSAT MMO)
 This system schedules and manages observation plans and downlink plans of
TANSO-FTS and TANSO-CAI.
 The system accepts observation requests from NIES via the GOSAT Onboard
Technology Evaluation System to reflect them in the GOSAT observation plan,
which is provided to NIES.
 GOSAT MMO is installed in the TKSC.
(8) SMACS (Spacecraft MAnagement Control System) and uFDS (unified Flight
Dynamics System) SMACS and uFDS generate operation commands for the satellite based on the
GOSAT observation plan made by GOSAT MMO, and transmit them to thesatellite through the domestic and overseas tracking control stations (Ground
Networks).

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Chapter 4 GOSAT Ground System

 SMACS and uFDS acquire House Keeping and ranging data from the satellite tomonitor the conditions of the satellite and sensors in orbit, and also determine theorbit to create orbit information such as orbit data predictive.
 SMACS and uFDS are installed in the TKSC.
(9) EORC Information System (EIS) This system manages input / output operations from / to external systems suchas the GOSAT Data Processing System and GOSAT MMO.
 EIS archives and manages L0 data of TANSO-FTS and TANSO-CAI as masterdata. Further, EIS archives and manages TANSO-FTS Level 1A and 1B products,
TANSO-CAI Level 1A products, and their calibration products, all of them being
processed by JAXA.
 Furthermore, EIS archives and manages TANSO-CAI Level 1B, 1B+, and higher
level products; and TANSO-FTS higher level products. The products mentioned
here are processed by NIES and provided to JAXA.
 EIS is installed in the TKSC.
(10) GOSAT Data Analysis System
 In the GOSAT Data Analysis System, research activities on the use of GOSAT
data are carried out making use of such data and products as follows, i.e. Level 1
products and Level 1 calibration products created in the GOSAT Data Processing
System, and TIR input / output data set and Grid Point Value (GPV) data
provided by NIES; the creation of GOSAT research products is also included in
the activity.
 The system obtains the calibration data, not contained in Level 1 calibration
products created in the GOSAT Data Processing System, from the GOSAT
operations team of JAXA and provides them to NIES.
 The GOSAT Data Analysis System is installed in the TKSC.
(11) Ground Networks
 The Ground Networks help exchanging data among JAXA ground stations fortheir tracking and controlling of the satellite.
4.3

NIES System

In the NIES System, the GOSAT Data Handling Facility (hereafter called NIESGOSAT DHF) deals with GOSAT-related data (excluding some part of processing).
Fig. 4.3-1 illustrates the overall configuration of NIES GOSAT DHF. General
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Chapter 4 GOSAT Ground System

functions of NIES GOSAT DHF will be described below.
Data transf er

Computation
center

Processing control
Processed result
Start up

TIR input / output data Set

Processed result
StatusProcessed result

Data
processing

Processed result

Input data

Researchers
Observ ation requests

CAI L1B,L1B+
High-lev el products
Observ ation requests

CAI L1B, L1B+
High-level products

JAXA
cooperation FTS L1A,L1B,

JAXA system

FTS L1A,L1B,
CAI L1A
Calibration products
Observ ation planData
distribution
Data distribution

Users

Data distribution

CAI L1A
Calibration products
Observ ation plan
Observ ation requests

GPV data

Ref erence data

Reference dataacquisition

Ref erence data
providers

Data searchDatamanagement

Operations
management

NIES GOSAT DHF

Ref erence data

Fig. 4.3-1 Overall configuration of NIES GOSAT DHF(1) JAXA cooperative subsystem The JAXA cooperative subsystem puts together GOSAT observation requests
from the MOE, NIES, the Science Team, Research Announcement Investigators(RAs), and so on; coordinates these requests and presents the coordinatedresult to JAXA in a predetermined form of observation request.
 Compares the observation request thus presented with a corresponding
observation plan made by and sent from JAXA.
 The subsystem obtains the following products from JAXA: TANSO-FTS Level 1A,
Level 1B products; TANSO-CAI Level 1A products; TANSO-FTS Level 1A, 1B
calibration products; and TANSO-CAI Level 1A calibration products. In addition, it
obtains the calibration data that are not contained in Level 1 calibration products.
 Among the TANSO-CAI Level 1B, 1B+, and higher level products that areprocessed by NIES, the products that are classified as a standard product ofstage C (as for the stages, see section 7.2.4) are provided to JAXA with theircatalogue.
 The subsystem provides JAXA with dataset files storing the input/output data of
the TANSO-FTS TIR gas concentration calculation processing, and GPV data
which have been acquired as reference data.

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Chapter 4 GOSAT Ground System(2) Reference data acquisition subsystem Acquires reference data necessary for the GOSAT higher level processing fromthe organizations that supply the reference data.
 Acquires validation data necessary for the validation of GOSAT higher levelproducts from the organizations that supply the validation data.
(3) Processing control subsystem Controls operations of data processing such as starting-up, terminating, andscheduling of the process.
 Manages conditions for data processing.
 The subsystem also controls the data processing carried out in computer centersother than NIES GOSAT DHF.
(4) Data processing subsystem The subsystem inputs TANSO-FTS Level 1A, 1B products, TANSO-CAI Level 1A
products, Level 1 calibration products of TANSO-FTS and TANSO-CAI, andreference data; and performs the following higher level processing to output theresults.
 TANSO-CAI Level 1B, 1B+ processing
 TANSO-CAI Level 2 processing
 TANSO-FTS SWIR Level 2 processing
 TANSO-FTS TIR Level 2 processing
 Further, the subsystem inputs TANSO-FTS Level 2 products and reference data,and performs the following higher level processing to output the results.
 Level 3 processing
 Level 4A processing
 Level 4B processing Part of the data processing is done in the computer centers other than NIESGOSAT DHF.
(5) Data management subsystem The subsystem archives and administers the products and data, which include
those provided by JAXA, i.e. TANSO-FTS Level 1A, Level 1B, TANSO-CAI Level
1A, their calibration products, and those processed by NIES; i.e. TANSO-CAI
Level 1B, 1B+ and higher level products, and reference data and validation datanecessary for data processing.

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Chapter 4 GOSAT Ground System(6) Data distribution subsystem
 Distributes the created higher level products to users.
(7) Operations management subsystem
 Monitors the operation status of computer systems installed in NIES GOSAT
DHF.

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Chapter 5 GOSAT Ground System Operations

Chapter 5
5.1

GOSAT Ground System Operations

GOSAT Ground System Operations Outline

NIES collects observation requests at NIES GOSAT DHF and sends them to JAXA.
JAXA makes observation and operation plans, based on the observation requests
sent from NIES and the observation requests issued by the GOSAT operations
team of JAXA, and transmits them in the form of commands to the satellite.
GOSAT carries out the observation in accordance with the observation plan, andsends the observed data down to EOC and/or SvalSat as specified in the operation
plan; the data downlink is conducted every two passes approximately,
The ground station that has acquired the data performs, after demodulating thesignals, packet synchronization and APID sorting. Thereafter, the processing forthe skipped data is executed by referring to the header portions of the acquired
data. Then Level 0 data are created, and level 1 processing is also performed
according to the scene definition for the Level 1 products. The Level 1 products
thus generated are sent to NIES GOSAT DHF for higher level processing, andbecome ready for distribution to users.
5.2

GOSAT Data Acquisition and Transfer

This section explains briefly how the GOSAT data are acquired and transferred.
See chapter 4 for overall configuration of the GOSAT systems.
 The X-band acquisition and recording systems installed in EOC of JAXA acquire
two to four passes of downlink data from GOSAT every day.
 SvalSat in Norway acquires about six passes of downlink data from GOSAT
every day. Svalsat is run by KSAT in Norway.
 Each of the stations that has acquired the observation data applies digitalconversion to the demodulated signals and performs packet synchronization
processing and APID sorting so as to generate Level 0 preprocessed data, which
are transmitted to the GOSAT Data Processing System via EIS.
 In addition, the RAW data, which are obtained by applying digital conversion to
the demodulated signals, and the Level 0 preprocessed data are both archived
for a certain period of time in each station for use in cases such as
re-transmission, re-processing, and the like.
 The GOSAT Data Processing System at JAXA process the Level 0 preprocesseddata to produce Level 0 data (the processing is done for skipped data by referring
to primary and secondary headers, etc.). The created Level 0 data (TANSO-FTS,
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TANSO-CAI, TEDA, CAM, MDP, HK (House Keeping), etc.) are archived in EIS
together with the processing result. The Level 0 data registered at EIS are copied
to and archived also in EOC for disaster backup.
5.3

GOSAT Data Processing

Data processing operations for GOSAT standard products are described below.
5.3.1 Level 1 Processing
5.3.1.1 TANSO-FTS 1B Processing The GOSAT Data Processing System, installed in TKSC of JAXA, inputs Level
1A products to create Level 1B products. The system also creates calibration
products of TANSO-FTS Level 1B. Upon completion of the Level 1 processing fora scene, the products are transmitted online one after another to NIES GOSATDHF via EIS.
 Processing result files are made as soon as the corresponding Level 1 products
are generated, and sent also to NIES GOSAT DHF via EIS.
 The products thus created are archived and managed at both EIS and NIESGOSAT DHF.
5.3.1.2 TANSO-CAI Level 1B, 1B+ Processing
 NIES GOSAT DHF creates Level 1B and 1B+ products from TANSO-CAI Level
1A products JAXA provided.
 The created products are archived in a database of NIES GOSAT DHF. In
addition, a data distribution server provides, via Internet, services for search anddistribution of the archived data.
5.3.2 Higher Level Processing
 NIES GOSAT DHF collects, through the routine operation, such reference data
as meteorological data which are necessary for higher level processing; thesedata are collected from various organizations such as Japan Meteorological
Agency, European Center for Medium-Range Weather Forecasts (ECMWF),
National Oceanic and Atmospheric Administration (NOAA), and so on. NIESGOSAT DHF also manages the validation data necessary for validation of the
products.
 NIES GOSAT DHF creates higher level products using some of the standard
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products and reference data; the standard product will be FTS Level 1B acquired
from JAXA or CAI Level 1B and 1B+ created by NIES. For this processing, inaddition to the facilities in NIES GOSAT DHF, computer centers inside andoutside of NIES (including a supercomputer of NIES, and Information Technology
Center of the University of Tokyo) are used for such processes as retrieval
processing which requires a lot of computation power.
 The created products are archived in a database of NIES GOSAT DHF. In
addition, a data distribution server provides, via Internet, services for search anddistribution of the archived data.

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Chapter 6
6.1

GOSAT Products

Product Unit

A GOSAT product unit is defined depending on sensors and processing levels.
Typical product units are explained below.
(1) FTS scene
FTS scene of Level 1 product is defined to have a span covered by the observation
performed in a time 1/60 of the one-revolution period; the start of the first scene
corresponds to the ascending node passing time. A scene of FTS data is the unit toarchive FTS Level 1 products. Fig. 6.1-1 shows schematically how the FTS scenes
are defined.
If the time to end a scene comes before completing an interferogram, theinterferogram shall be included in the scene the observation was started.
An FTS Level 1 product is created for each respective scenes; no overlaps
between two adjacent scenes, accordingly, no data are shared by different productunits. If a change in sensor's observation mode (daytime observation, nighttime
observation, sunglint observation, and specific point observation) takes place withina scene, the scene is divided at the place the mode changes. The divided scenes
are named as sub-scene, and a product is composed of each of the sub-scenes.
However, if sub-scenes, made by a calibration observation being interposed
between them, have the same observation mode, they are concatenated to make asingle sub-scene. Scenes will not be divided to sub-scenes even when observation
parameters of FTS such as exposure time (1, 2, or 4 seconds) and/or scan mode (1,3, 5, 7, or 9 points observation) are changed. On the contrary, multiple times ofobservation of the same place may be separated into different sub-scenes when
the observations were conducted using different modes such as daytime / nighttime
observations.
(2) FTS scan
An interferogram obtained in a single observation is defined as an FTS scan. The
FTS scan is a minimum unit of FTS observation. One scene of the FTS Level 1
product includes 22 to 23 FTS scans.
(3) CAI scene
A CAI scene is defined to have a span covered by the observation performed in
one-revolution; the start of the scene corresponds to the ascending node. A scene

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Chapter 6 GOSAT Productsof CAI data is the unit to archive CAI Level 1A products. TANSO-CAI usuallyacquires data of the daytime area on the ground; accordingly, a CAI scene has astretch of data for the continuous daytime area (nighttime areas are not included).
Fig. 6.1-2 shows schematically how the CAI scenes are defined.
(4) CAI frame
A frame of CAI is defined by dividing the whole length of GOSAT’s trajectory
mapped on the ground surface into 60. A frame of CAI data is the minimum unit toarchive CAI Level 1B, Level 1B+, and most of Level 2 products. As shown in Fig.
6.1-2, the center of the 31st frame is so located as it corresponds at the descending
node on the equator.
(5) Miscellanies
TANSO-FTS Level 2 product data are stored on-demand basis in accordance withconditions indicated by a user, with one FTS scan taken as a basic archive unit. On
the other hand, Level 3 and Level 4 product data are archived for the whole globe
as a unit in general. However, the Level 3 global normalized difference vegetationindex data are provided for each of the rectangles (see chapter 6.6-7).
GOSAT along-track direction(AT)
Scene 2

One scanScene 1
Acending nodeCreated product

Scene 60

ex. Observation mode I(3 points observation)

Fig. 6.1-1 Definition of FTS scene

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Fig. 6.1-2 CAI scene and frame definition (Path 5)(Numerals in the figure are frame numbers.)

6.2

Products List

Each GOSAT product has its own level. The level signifies the processing stage theproduct has undergone. To be more specific, Level 1 products are generated bytransforming voltage and current values measured by the sensors into physicalquantities; Level 2 products, such as greenhouse gas column amount, aregenerated by processing the Level 1 product; FTS Level 3 products are obtained byapplying statistical processing to the FTS Level 2 products covering a certain
period of time to know the distribution over the globe; and Level 4 products(absorption and emission of the GHG and their three-dimensional concentration)
are obtained through the processing of the level 2 products.
In addition, the GOSAT products are classified into three categories (standard,
research, internal); any of the GOSAT products is a member of one of thesecategories. The definitions of product categories are described below; Table 6.2-1
is a list of the GOSAT products; and Fig. 6.2-1 shows processing flow of the
products.
Since this handbook mainly focuses on the standard products, descriptions on the
research and internal products are mentioned only to help understand the standard
products.

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Chapter 6 GOSAT Products Standard products
Provided to all users upon completion of calibration, validation, or comparison6.
JAXA, NIES, and MOE guarantee the accuracy of the products.
 Research products
Provided to limited users for their researches on calibration/validation, dataprocessing algorithms, data application, various fields of science, etc.
The research products are not provided to general users.
 Internal products
Provided to limited number of researchers and research organizations who are
engaged in collaborative research on the method for calibration or on the FTS
Level 1 processing algorithm; these products are made for internal use of JAXA
and/or NIES.
The internal products are not provided to general users.

6

Details of the calibration and validation are described in section 6.7. Comparison here means amethod of validating Level 3 or Level 4 products which is equivalent to the method of Level 2 validation.
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Table 6.2-1 GOSAT product list
Sensor /Band

Product
Level

L1A
FTS
L1B

SWIR

L2
TIR

SWIR
L3
TIR

FTS scene

FTS L1A lunar calibration data

Internal

FTS scene

FTS L1B data

Standard

FTS scene

FTS L1B calibration data

Internal

FTS scene

FTS L1B lunar calibration data

Internal

FTS scene

L2 CO2 column amount (SWIR)

Standard

L2 CH4 column amount (SWIR)

Standard

L2 H2O column amount (SWIR)

Research

L2 CO2 profile (TIR)Standard

L2 CH4 profile (TIR)Standard

L2 CO2 column amount (TIR)

Research

L2 CH4 column amount (TIR)

Research

L2 temperature profile (TIR)

Research

L2 H2O profile (TIR)

Research

L2 H2O column amount (TIR)

Research

L3 global CO2 distribution (SWIR)

Standard

L3 global CH4 distribution (SWIR)

Standard

L3 global CO2 distribution (TIR)Standard

L3 global CH4 distribution (TIR)Standard

Globe(monthly average)

Internal

CAI scene

Internal

CAI scene

CAI L1A lunar calibration data

Internal

CAI scene

L1B

CAI L1B data

Standard

L1B+

CAI L1B+ data

Standard

L2 cloud flag

Standard

L2 cloud property

Research

L2 aerosol property

Research

L3 global radiance distribution
L3 global reflectance distribution (clearsky)
L3 global cloud property

Standard

Research

L3 global aerosol property

Research

L3 global NDVIStandard

L4A global CO2 flux

Standard

L4A global CH4 flux

Research

L4A

Standard

Data
formatOption(on demand)

CAI L1A calibration data

L3

HDF5

CAI frameGlobe(every 3 days)
Globe(monthly average)
Rectangle (latitude 30˚× longitude 60˚) (every
15 days)Global 64 regions(annually)

Text /Net
CDF

GlobalNet
2.5˚×2.5˚mesh
CDF
L4B global CH4 distribution
Research(monthly)
Yellow-shaded products are standard ones available for general users as of December 2010.
Release schedule of the standard products, which is not open to the public, is shown in below.
FTS L2 CO2/CH4 profile (TIR): RA is open now. In the fall of 2011, it will be open to the public.
FTS L3 global CO2/CH4 distribution (TIR): In the fall of 2011, it will be open to the public.
CAI global reflectance distribution (clear sky): RA is open now. In the summer of 2011, it will be open to
the public.
CAI L3 global NDVI: RA is open now. In the summer of 2011, it will be open to the public.
L4A global CO2 flux: The public release is not determined.
L4B global distribution: The public release is not determined.
L4B

Internal

CAI L1A data

L2-

FTS scene

FTS L1A calibration data

Product unit

L1A

CAI

-

FTS L1A data

Product
category
Internal

Product name

L4B global CO2 distribution

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Chapter 6 GOSAT Products

CAI L1B+

CAI L1A data

FTS L1B dataprocessing

spectrum

CAI L1B+ data

CAI L1B

CAI L1B dataprocessing

Aerosoltransport model
simulation(SPRINTARS)CAI L1B
Internal file

L1B

Note 1

FTS preprocessing

aerosol property

Filtering processing

L2

cloud screening (CAI)
cloud screening (TIR)
cirrus & aerosol screening (2 micron)high solar zenith angle exclusionrough terrain surface exclusion

Minimum reflectance processing
CAI L2Cloud flag processing

cloud flag

Aerosol properties
retrieval

Cloud properties
retrievalInitial data setting

Input data set (SWIR)CAI L2

Input data set (TIR)aerosol
property

Greenhouse gas
retrieval (SWIR)

aerosol
match-up
file

CAI L2cloud
property

cloud
match-up
fileGreenhouse gas
retrieval (TIR)
Note 2

Note 2Global mapping of

Screening

Screening

FTS L2 (SWIR)
CO2, CH 4 & H 2O column amount

Note 1FTS L2 (TIR)
CO2, CH 4 & H 2O column amountCO2, CH 4, H2O & temperature profile

Global mapping of
FTS L2 data

CO2 & CH4 inverse
model calculation

CAI L1B, L1B＋ & L2 data

Atmospherictransport model
simulationGas
profiles

CAI L3
L3: Products

L4A
Global CO2 & CH 4 flux

: Internal data

Note 1

L3

L4

FTS L3Global CO 2 & CH 4 distribution (SWIR)
Global CO 2 & CH 4 distribution (TIR)

Global radiance distribution(all pixels, clear sky)
Global aerosol distribution
Global cloud distribution
Global NDVI

Atmospherictransport model
simulation
Note 1

L4B
Global CO 2 & CH 4 distribution

Note 1: performed by a supercomputer of NIES
Note 2: performed at Information Technology
Center of the University of Tokyo
Processing without a note is done by GOSAT DHF.

Fig. 6.2-1 Data Processing Flow of the GOSAT Products

Outlines of the standard products, which are available for general users, aredescribed below (note that some products are not available as of December 2010).
Although Level 1A products are not standard ones, descriptions for the Level 1A
products are also given because they are essential to Level 1B and higher levelprocessing as the basic input data.
6.2.1 Level 1 Products(1) TANSO-FTS Level 1A product
TANSO-FTS Level 0 data have, in addition to the observed interferogram data (seeFig. 6.2-2), GPS data, attitude data, and so forth. Based on these data,
TANSO-FTS Level 1A product is made by appending geolocational data of theobserved point, radiometric correction information, etc. to the interferogram.
Daytime/nighttime observation products are created by a unit of scene as defined
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Signal Strengthin Section 6.1. As for the specific observation product, a series of specificobservation data are combined into one product to make a specific observation
product. However, if a specific point observation is conducted crossing theboundary of sunlit/shadow areas, the product is divided into two at the boundary.
The TANSO-FTS Level 1A products are not provided for general users.

Optical Path difference

Fig. 6.2-2 Example of FTS Level 1A product (interferogram)(2) TANSO-FTS Level 1B productThe interferogram data of TANSO-FTS Level 1A product are transformed into
spectral data of each wavenumber through the Fourier transform, and thereafter
undergo radiometric correction to create a TANSO-FTS Level 1B product. The
Level 1B product includes spectral information of the calibration data applied to theradiometric correction. One Level 1B product is created from a Level 1A product.
Fig. 6.2-3 shows an example of FTS Level 1B product (after initial calibration) andabsorption bands of greenhouse gasses. The spectrum on the top is the result of
simulation integrating the spectra of Bands 1, 2, and 3.

Fig. 6.2-3 Example of FTS Level 1B product (spectra) andabsorption bands of greenhouse gasses

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Chapter 6 GOSAT Products(3) TANSO-CAI Level 1A Product
TANSO-CAI Level 1A product is made by appending geolocational data of theobserved point, radiometric correction information, etc. to a TANSO-CAI Level 0
data. The product is created by a unit of CAI scene as defined in Section 6.1.
The TANSO-CAI Level 1A products are not provided for general users.
(4) TANSO-CAI Level 1B Product
TANSO-CAI Level 1B product is a product having radiance information made froma Level 1A product through the conversion process using calibration coefficients.
The TANSO-CAI Level 1B product includes band-to-band registration andgeometric correction (map projection conversion not applied yet). The product isgenerated for each unit of CAI frame as defined in Section 6.1.
Fig. 6.2-4 shows an example of CAI Level 1B product. The data was observed on
July 17, 2010 (after initial calibration) covering mainland Japan. This image is
generated by assigning bands 1, 2, and 3 to Blue, Red, and Green respectively.

Fig. 6.2-4 Example of CAI Level 1B product(5) TANSO-CAI Level 1B+ Product
TANSO-CAI Level 1B+ product is a product of radiance data obtained from a
TANSO-CAI Level 1B product by applying band-to-band registration correction andgeometric correction including map projection. The product is generated for each
unit of CAI frame as defined in Section 6.1.
Fig. 6.2-5 shows an example of CAI Level 1B+ product. The data was observed on
July 17, 2010 (after initial calibration) covering mainland Japan. This image is
generated by assigning bands 1, 2, and 3 to Blue, Red, and Green respectively.

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Chapter 6 GOSAT Products

Fig. 6.2-5

Example of CAI Level 1B+ product6.2.2 Level 2 Standard Products(1) Level 2 CO2 column amount (SWIR) and Level 2 CH4 column amount (SWIR)
These two products respectively represent the column amount of carbon dioxide(CO2) and methane (CH4), processed from the spectra of shortwave infrared(SWIR) data (Bands 1 to 3) of TANSO-FTS, and the column-averaged dry air mole
fractions of CO2 and CH4 (hereinafter referred to as XCO2 and XCH4 respectively),
calculated by dividing the total column amounts of CO2 and CH4 by the dry air
column amount. The products are generated on the demand from a user specifying
the region and time of his/her interest; all the scans of interest are searched out andrecorded in a file as a product.
Fig. 6.2-6 shows an example of Level 2 CO2 column amount (SWIR) product(XCO2), a global distribution map calculated by averaging the data of cloud-freeobservations for every mesh of 2.5 x 2.5 degrees. Likewise, Fig. 6.2-7 shows anexample of Level 2 CH4 column amount (SWIR) product (XCH4). Both of them arecalculated from the data observed in July, 2010; the blank portions indicate the datathat were not processed due to the cloud etc.
As shown in Fig. 6.2-6 and Fig. 6.2-7, the actual column amount calculated fromobservation data is about 2-3% of the total observations due to the cloud etc. The
XCO2 included in these products have negative bias of 2 ~ 3 % against thevalidation data and standard deviation of 1 ~ 2 %. The XCH4 also has negative biasof 1 ~ 2 % and standard deviation of 1 ~ 2 %.

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Fig. 6.2-6 Example of Level 2 CO2 column amount (SWIR) product (XCO2)

Fig. 6.2-7 Example of Level 2 CH4 column amount (SWIR) product (XCO4)(2) Level 2 CO2 profile (TIR) and Level 2 CH4 profile (TIR)
These two profiles represent vertical distribution of the concentration of carbon
dioxide (CO2) and methane (CH4) respectively; the profiles are obtained using aspectrum of thermal infrared (TIR/band 4) of TANSO-FTS.
(3) Level 2 cloud flag
Level 2 cloud flag product contains clear-sky confidence level which is the basic
information to determine cloud flags; each of the confidence levels is stored foreach of the pixels taken by CAI based on the radiance information of CAI Level 1B
data.
Fig. 6.2-8 shows an example derived from CAI Level 2 cloud flag product byassuming the threshold to be 0.3. The data was observed on July 17, 2010 (after
initial calibration) covering mainland Japan. The blackened parts represent clouds
on the background image of CAI Level 1B introduced by Fig. 6.2-4.

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Fig. 6.2-8 Example of Level 2 cloud flag product6.2.3 Level 3 Standard Products(1) Level 3 global CO2 distribution (SWIR) and Level 3 global CH4 distribution (SWIR)
These products are generated from the level 2 column amount products (SWIR).
By applying a statistical method called kriging method7 to the Level 2 column
average concentration data, a monthly average of global concentration distribution(2.5 × 2.5 degrees of grid as a unit) of greenhouse gasses can be estimated for aregion near the observation point even when the region itself has no processed
point.
As an example of Level 3 global XCO2 distribution (SWIR) product, Fig. 6.2-9
shows a global distribution map in which the data of the product are visualized andmapped. Likewise, Fig. 6.2-10 shows an example of Level 3 global XCH4
distribution (SWIR) product. Both of the observation data were acquired on July,
2010, and the whitened portions represent the places where the data do not exist
within 500km measured from the processed points.

Fig. 6.2-9 Example of Level 3 global CO2 distribution (SWIR) product (XCO2)

7

A method to estimate a value with the least error for a position using the known values in its neighbor.
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Fig. 6.2-10 Example of Level 3 global CH4 distribution (SWIR) product (XCO4)(2) Level 3 global CO2 concentration (TIR) and Level3 global CH4 concentration (TIR)
These products are generated from the TIR Level 2 concentration profiles.
Distribution of GHG concentration on multiple equi-pressure planes supposed in
the atmosphere is estimated by a statistical method derived by using the kriging
method.
(3) Level 3 global radiance distribution (with cloud)
Level 3 global radiance distribution product is a product generated from Level 1B+
data of three consecutive days observed by TANSO-CAI. It is a global radiancemap product to demonstrate the global distribution of radiance from the earth
surface and cloud.
Fig. 6.2-11 is an example of Level 3 global radiance distribution product. The image
was generated from the observation data of three consecutive days, i.e. July 15
through 17, 2010; bands 1, 2, and 3 are assigned to colors Blue, Red, and Green
respectively.

Fig. 6.2-11 Example of Level 3 global radiance distribution product(4) Level 3 global reflectance distribution (clear sky)Level 3 global reflectance distribution (clear sky) product is a global map product ofground surface reflectance generated from TANSO-CAI Level 1B data. This

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Chapter 6 GOSAT Products

product is generated by taking a minimum reflectance derived from TANSO-CAI
data for a month. As a result, the data seems to have no cloudy pixel.
Fig. 6.2-12 is an example of Level 3 global reflectance distribution (clear sky)product. The image is generated from the data acquired on July 1st through 31st,
2010; bands 1, 2, and 3 are assigned to colors Blue, Red, and Green respectively.

Fig. 6.2-12 Example of Level 3 global reflectance distribution (clear sky) product(5) Level 3 global NDVIThis product is a global map product of Normalized Difference Vegetation Index(NDVI) that is calculated from the radiance data of TANSO-CAI bands 2 and 3
observed for five recurrent cycles (15 days). The whole globe is divided into
rectangles of 60 × 30 degrees (6 divisions in the longitudinal direction, and 6
divisions in the latitudinal direction); each rectangle is composed of meshes of 0.05
× 0.05 degrees (14,400 × 7,200 meshes).
6.2.4 Level 4 Standard Products(1) Level 4A Global CO2 flux
The uptake and release (flux) of CO2 in each of 64 sub-continental regions isestimated from CO2 column-averaged mixing ratios (stored in the Level 2 FTS
SWIR product) and CO2 observational data collected in a network of ground-based
monitoring stations. This product is generated by using an atmospheric tracer
transport model that simulates the advection of CO2 by wind.
(2) Level 4B global CO2 distribution
The Level 4B product stores three-dimensional distributions of CO2 concentration(6-hourly; 2.5×2.5 degrees horizontal resolution) that are derived from the Level
4A global CO2 flux data. These distributions are obtained with an atmospheric
tracer transport model.

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Chapter 6 GOSAT Products

6.3

Definitions of Product File Names

File name definitions of the standard products available for general users are given
below.
For the product code of the products, see Table 6.3-1. For the details of theprocessing version, see Section 7.2.3.
(1) TANSO-FTS Level 1B productFile name of TANSO-FTS Level 1B product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T F T S Y Y Y Y M M D D H H m m P P P S S S X _ 1 B a b c d A A A P P P . 0 1
Satellite

SensorObservation date

Processinglevel
Sub scene No.

Pass No. Scene No.

Scene ID

Productcode

Processing
versionExtension

Product ID

Fig. 6.3-1 File name definition of TANSO-FTS Level 1B product(2) TANSO-CAI Level 1B productFile name of TANSO-CAI Level 1B product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T C A I Y Y Y Y M M D D H H m m P P P F F F 0 _ 1 B a b c d V M M N N 0 . h 5
Satellite

SensorObservation date

Pass
No.

Frame
No.

Processing
level

Productcode

Processing
versionExtension

Fig. 6.3-2 File name definition of TANSO-CAI Level 1B product(3) TANSO-CAI Level 1B+ productFile name of TANSO-CAI Level 1B+ product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T C A I Y Y Y Y M M D D H H m m P P P F F F 0 _ 1 B a b c d V M M N N 0 . h 5
Satellite

SensorObservation date

Pass
No.

Frame
No.

Processing
level

Productcode

Processing
versionExtension

Fig. 6.3-3 File name definition of TANSO-CAI Level 1B+ product(4) TANSO-CAI Level 2 productFile name of TANSO-CAI Level 2 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T C A I Y Y Y Y M M D D H H m m P P P F F F 0 _ 0 2 a b c d V M M N N 0 . h 5
Satellite

SensorObservation date

Pass
No.

Frame
No.

Processing
level

Productcode

Processing
versionFig. 6.3-4 File name definition of TANSO-CAI Level 2 product

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Chapter 6 GOSAT Products(5) TANSO-FTS SWIR Level 2 productFile name of TANSO-FTS SWIR Level 2 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T F T S Y Y Y Y M M D D _ 0 2 a b c d V M M N N R y y m m d d n n n n 0 . h 5
Satellite

SensorStart date of search

Processing
level

Productcode

Processing
version

Product order No. (Productordering date + serial No.)

Extension

Fig. 6.3-5 File name definition of TANSO-FTS SWIR Level 2 product(6) TANSO-FTS TIR Level 2 productFile name of TANSO-FTS TIR Level 2 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

G O S A T T F T S Y Y Y Y M M D D _ 0 2 a b c d V M M N N R y y m m d d n n n n 0 . h 5
Satellite

SensorStart date of search

Processing
level

Productcode

Processing
version

Product order No. (Productordering date + serial No.)

Extension

Fig. 6.3-6 File name definition of TANSO-FTS TIR Level 2 product(7) TANSO-FTS SWIR Level 3 productFile name of TANSO-FTS SWIR Level 3 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

G O S A T T F T S Y Y Y Y M M D D y y y y m m d d _ 0 3 a b c d V M M N N . h 5
Satellite

SensorObservation start dateObservation end date

Processing
level

Productcode

Processing
versionExtension

Fig. 6.3-7 File name definition of TANSO-FTS SWIR Level 3 product(8) TANSO-FTS TIR Level 3 productFile name of TANSO-FTS TIR Level 3 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

G O S A T T F T S Y Y Y Y M M D D y y y y m m d d _ 0 3 a b c d V M M N N . h 5
Satellite

SensorObservation start dateObservation end date

Processing
level

Productcode

Processing
versionExtension

Fig. 6.3-8 File name definition of TANSO-FTS TIR Level 3 product(9) TANSO-CAI Level 3 productFile name of TANSO-CAI Level 3 product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

G O S A T T C A I Y Y Y Y M M D D y y y y m m d d _ 0 3 a b c d V M M N N . h 5
Satellite

SensorObservation start dateFig. 6.3-9

Observation end date

Processing
level

Productcode

Processing
versionFile name definition of TANSO-CAI Level 3 product(10) TANSO-CAI Level 3 NDVI productFile name of TANSO-CAI Level 3 NDVI product is defined as shown below.

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

G O S A T T C A I Y Y Y Y M M D D y y y y m m d d _ 0 3 a b c d V M M N N Z Z Z . h 5
Satellite

SensorObservation start dateFig. 6.3-10

Observation end date

Processing
level

Productcode

Processing ID (If one dataset
Extensionis divided)
versionFile name definition of TANSO-CAI Level 3 NDVI product(11) Level 4A productFile name of Level 4A product is defined as shown below. The Level 4A product will
be provided in NetCDF format as well as in text files introduced here; however, filename rules for the NetCDF is not fixed yet.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41

G O S A T T F T S Y Y Y Y M M D D y y y y m m d d _ 4 A a b c d V M M N N . t x tSatellite

SensorStart date of flux
estimation

End date of flux
estimation

Processing
level

Productcode

Processing
versionExtension

Fig. 6.3-11 File name definition of Level 4A product(12) Level 4B productFile name of Level 4B product is defined as shown below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

G O S A T T F T S Y Y Y Y M M D D y y y y m m d d _ 4 B a b c d V M M N N . n cSatellite

SensorStart date of forward
calculation

Fig. 6.3-12

End date of forward
calculation

Processing
level

Productcode

Processing
versionFile name definition of Level 4B product

Table 6.3-1 Product code of GOSAT products
Product code

Product name

<L1>
OB1D
OB1N
OB2D
SPOD
SPON
TRB0
TRBP

FTS observation mode I, Sunlit observation data
FTS observation mode I, Shadow observation data
FTS observation mode II, Sunlit observation data
FTS specific observation mode, Sunlit observation data
FTS specific observation mode, Shadow observation data

C01S
C02S
C03S
C01T
C02T
P01T
P02T
TMPT
P03T
C03T
CLDM
CLDP
AERP

L2 CO2 column amount (SWIR)
L2 CH4 column amount (SWIR)L2 H2O column amount (SWIR)
L2 CO2 column amount (TIR)
L2 CH4 column amount (TIR)
L2 CO2 profile (TIR)
L2 CH4 profile (TIR)
L2 temperature profile (TIR)L2 H2O profile (TIR)L2 H2O column amount (TIR)
L2 cloud flag
L2 cloud property
L2 aerosol property

C01S
C02S

L3 global CO2 distribution (SWIR)
L3 global CH4 distribution (SWIR)CAI L1B data
CAI L1B+ data

<L2>

<L3>

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Product code
P01T
P02T
TRCL
TRCF
CLDP
AERP
NDVI

Product nameL3 global CO2 distribution (TIR)
L3 global CH4 distribution (TIR)
L3 global radiance distribution
L3 global reflectance distribution (clear sky)
L3 global cloud property
L3 global aerosol property
CAI global NDVI

<L4>
F01M
F02M
P01M
P02M

6.4

L4A global CO2 flux
L4A global CH4 flux
L4B global CO2 distribution
L4B global CH4 distribution

Product Format

6.4.1 Data Storage Format
GOSAT products for general users are stored in the format of HDF, text, or NetCDF,
as shown in Table 6.2-1, and provided. Outlines of HDF and NetCDF are described
below.
(1) HDFHDF8,9 (Hierarchical Data Format) is a self-descriptive generic file format designedby the National Center for Supercomputing Applications (NCSA) of U.S.A. HDF is aplatform independent file format and stores multiple types of data objects
necessary for data analysis and associated files into a single file, while images,
charts, annotations, image palettes, etc. are included in the objects mentioned
above. Meta-data, describing data types, positions of the data in the file, and so on,
are also included in the file.
HDF has a hierarchical structure; the physical file format to store the data is definedas the lowest layer, while the upper layers include applications to perform
operations such as HDF file management, data manipulation, validation, andanalysis. HDF is not prepared for simply defining a file format but is composed ofvarious kinds of supporting software to facilitate operations such as data storing,searching, visualizing, analyzing, and managing with the HDF file. The hierarchicalstructure of HDF is illustrated in Fig. 6.4-1.
HDF5, version 5 of HDF, adopted to the GOSAT products, has resolved the
problems in the preceding versions; storing limit of 20,000 for the number of data
sets, file size limit of 2GB for file generation, and so forth.

89Illustrative Remote Sensing, revised edition, p. 305, 2001
The HDF Group, http://www.hdfgroup.org/
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Fig. 6.4-1 Hierarchical Structure of HDF10(2) NetCDF
NetCDF11 (Network Common Data Form) is a self-descriptive, array-oriented fileformat, which was designed in 1989 led by Unidata of USA. NetCDF storesmeta-data in addition to regular data. Like HDF5, NetCDF is not only a file format
but is composed of software libraries.
Multidimensional array data can be stored in the data storage layer; the GOSAT
Level 4B global CO2 distribution product, which is three-dimensional data, isprovided to users in NetCDF. There exists a close relationship between HDF5 andNetCDF. That is to say, NetCDF of version 4.1 and later adopts HDF5 format to thedata storage layer, and allows read-in access to the data in HDF5.
6.4.2 Format Examples
In order to display and/or analyze a GOSAT product, it should be read in
accordance with its data format. As libraries are available for HDF5 and NetCDF,
the products are read-in using the libraries as a common practice.
Table 6.4-1 lists up the document names and sections explaining the format of thestandard products. Further, as an example of most frequently used products, FTS
Level 1B and CAI Level 1B are introduced in the paragraphs below.

1011

http://www.hdfgroup.org/products/hdf4/whatishdf.html
Unidata, NetCDF-3 Users Guide for C (Japanese version) ;http://www.unidata.ucar.edu/software/netcdf/old_docs/
Copyright © 1997 University Corporation for Atmospheric Research, Boulder,Colorado.
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Table 6.4-1 Standard products and format documents
Already
provided

Document name

RelatedsectionFTS L1B product√

TANSO Level 1 Product
Description Document(technical document number:
MAS-1000067)

Section 3 ofTANSO-FTS
Part ,CAI L1B product
CAI L1B+ product
L2 CO2 column amount (SWIR)
L2 CH4 column amount (SWIR)
L2 CO2 profile (TIR)
L3 global CH4 distribution (TIR)
L2 cloud flag
L3 global CO2 column average
concentration (SWIR)
L3 global CH4 column average
concentration (SWIR)
L3 global CO2 distribution (TIR)
L3 global CH4 distribution (TIR)
L3 global radiance distribution
L3 global reflectance distribution (clearsky)
L3 global NDVI
L4A global CO2 flux
L4B global CO2 distribution

√
√
√
√

Product name




6.1
6.2
6.3
6.4
6.5
6.6

-

√
√
√
-

NIES GOSAT productformat Description(document number:
NIES-GOSAT-PO-006)

6.7
6.8

√

6.9
6.10

-

-

-

-

Documents in the table can be obtained from the NIES GOSAT products distribution site GUIG. For further
information please refer to Section 7.3.1.
The symbol "√" for the column “Already provided” indicates that the product is available as of December
2010, whereas the symbol "-" means the product is not available yet. The symbol "-" for the column“Related section” indicates that the product format is not open to the public as of December 2010.

(1) An example of FTS Level 1B product
Among the various data sets of the FTS Level 1B products, as the ones frequently
made use of, explanation follows for the geometric information and radianceinformation of the observed point to help understand how they are configured.
Further details are available in Section 3 of the Part TANSO-FTS in "TANSO Level
1 Product Description Document (technical document number: MAS-100067)."
a. Geometric information of the observation point"Geometric information of the observation point" is configured as described below
to indicate observation locations and conditions.
 Latitude of observation point : /exposureAttribute/pointAttribute/geometricInfo/centerLat
 Longitude of observation point :/exposureAttribute/pointAttribute/geometricInfo/centerLon
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Chapter 6 GOSAT Products Incidence angle of observation point :/exposureAttribute/pointAttribute/geometricInfo/AOI

 Azimuth of observation point : /exposureAttribute/pointAttribute/geometricInfo/AZ
 Solar azimuth of observation point : /exposureAttribute/pointAttribute/sun/AZ
 Solar elevation of observation point : /exposureAttribute/pointAttribute/sun/EL
 Land or sea flag : /exposureAttribute/pointAttribute/geometricInfo/landTypeb. Radiance information of the observation point"Radiance information of the observation point" is configured as described below topresent observation data. Although a conversion table is necessary to express thedata in the unit of radiance, conversion tables for Bands 1-3 are not stored in the
products. Accordingly, the conversion tables are to be obtained separately from the
NIES website12.
 Band 1 spectral data (observation component) : /Spectrum/SWIR/band1/obsWavelength Band 2 spectral data(observation component) : /Spectrum/SWIR/band2/obsWavelength Band 3 spectral data (observation component) : /Spectrum/SWIR/band3/obsWavelength Band 4 spectral data (observation component) : /Spectrum/TIR/band4/obsWavelength(2) An example of CAI Level 1B product
Among the various data sets of the CAI Level 1B products, as the ones frequently
made use of, explanation follows for the geometric information and radianceinformation of the observation point to help understand how they are configured.
Further details are available in Section 6.1 of " NIES GOSAT product format
Description (document number: NIES-GOSAT-PO-006)."a. Geometric Information of the observation point"Geometric information of the observation point" to indicate observation locations
and conditions is configures as described below.
 Latitude of observation point : /Data/geolocation/latitude

 Longitude of observation point : /Data/geolocation/longitude Height of observation point : /Data/geolocation/height Solar zenith angle of observation point : /Data/geolocation/solarZenth Solar azimuth of observation point : /Data/geolocation/solarAzimuth
 Satellite zenith angle of observation point : /Data/geolocation/satelliteZenith
12

https://data.gosat.nies.go.jp/GosatUserInterfaceGateway/guig/techInfo/TFTSRadCnv.html

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 Satellite azimuth of observation point : /Data/geolocation/satelliteAzimuth
 Land or sea flag : /Data/geolocation/landSeaMask
b. Radiance information of the observation point"Radiance information of the observation point" is configured as described below topresent observation data.
Band 1 radiance data : /Data/radiance/band1Radiance
Band 2 radiance data : /Data/radiance/band2Radiance
Band 3 radiance data : /Data/radiance/band3Radiance
Band 4 radiance data : /Data/radiance/band4Radiance(3) An example of GOSAT HDF Viewer display
A simple GOSAT data viewer "GOSAT HDF Viewer" is provided free13 as a display
tool for the GOSAT products (HDF5 format).
The viewer reads in the data in HDF5 format and displays a group screen listing thestored data in a tree structure as shown in Fig. 6.4-2. Fig. 6.4-2 is an example
reading in an FTS Level 1B product and selecting the spectrum of band 1 (acomponent of the observed data stored at /Spectrum/SWIR/band1/obsWavelength)
as described in "6.4.2 (1) b. Radiance information of the observation point”.
For the usage of GOSAT HDF Viewer, refer to the operation manual, which is open
to the public together with the Viewer.

Fig. 6.4-2 Group screen of GOSAT HDF Viewer (example of an FTS Level 1B product)

13

Research Institute of Systems Planning, Inc./ISP, http://remote-sensing.isp.jp/GOSAT-HDF/
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6.5

Level 1 Processing Algorithm

Brief descriptions follow for the processing algorithm of the Level 1 product. The
reference manual describing the details of the algorithm will be obtained from the
NIES GOSAT products distribution website GUIG (GOSAT User Interface
Gateway). The method to obtain the document is explained in Section 7.3.1.
6.5.1 TANSO-FTS Level 1A Processing Algorithm
TANSO-FTS Level 1A processing is performed on the Level 0 by adding some
information to the interferogram output from the sensor. Major specifications of theappended information are listed below.
[Information appended] Digital count to analog value conversion factors for interferogram Time Mission telemetry data (temperature of sensor component, pointing angle of a
tracking mechanism) Geolocation of observed points
 Position of the sun and the moon Land or sea flags
 Data quality information (temperature, abnormality flags concerning orbit and/or
attitude data to indicate that the data are outside the threshold value, etc.)
 Ancillary data of the Level 0 data Information concerning orbit and attitude Interferogram of calibration data (of the most recent occasion for the same path;otherwise, of the next occasion to come; and still otherwise, the further next) be
stored as available.
 Quality flag of interferogram Saturation flag (ZPD saturation, amplitude of low-frequency components)
 Spike noise flag (classified into 14 types, including existence / nonexistence) Flag to indicate pointing mirror settlement (the angular error within 0.1 degrees,etc.), and so son
 Nonlinear correction coefficients Calculation method for Fourier transform14
A product of observation mode I holds one sixtieth of the data captured by one
14

Processing to extract, from data signals, the information of frequency components (wavenumbers
and their respective intensity).
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revolution, whereas, in the case of specific observation mode, a product is made ofa series of consecutive observation data. It is to be noted that Level 1A data areclassified as an internal product and not open to the public.
6.5.2 TANSO-FTS Level 1B Processing Algorithm
TANSO-FTS Level 1B processing transforms the interferogram information of FTS
Level 1A into spectral information through the complex Fourier transform. SWIR istransformed into spectral information in the unit of voltage per wavenumber [V/cm-1],
while TIR is transformed, after calibration processing, into spectrum of spectral
radiance having the unit of [W/cm2/cm-1/sr].
With the spectral transformation, various kinds of correction (such as nonlinear
correction and phase correction) are made, and additional information is appended;
then, the product, thus processed per FTS scene, is stored in a file format of HDF5.
Fig. 6.5-1 is a flow of the Level 1B processing. Major specifications of theappended information and the summary of the processing shown in the processing
flow are described below.
[Information appended] Digital count to analog value conversion factors for interferogram Time Mission telemetry data (temperature inside equipment, pointing angle of a
tracking mechanism) Location of observed points
 Location of the sun and moon Land or sea flags
 Data quality information (temperature, abnormality flags concerning orbit and/or
attitude data to indicate that the data are outside the threshold value, etc.)
 Ancillary information of the Level 0 data Information on orbit and attitude Phase correction information
 The range of wavenumbers or the range of differences between the light pathdistances which were applied to the phase correction.
 Quality flag of interferogram Saturation flag (existence / nonexistence of ZPD saturation, integrated
amplitude sizes of low-frequency components
 Spike noise flag (classified into 14 types, including existence / nonexistence) Flag to indicate pointing mirror settlement (the angular error within 0.1 degrees,
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




etc.), and so son
Fringe count position with spike noises corrected
Nonlinear correction coefficients
Wavenumbers of spectrum (maximum, minimum, and number of elements)
Calibration method for Fourier transform
FTS L1A product(interferogram (DN))(1) Count-to-value conversion(DN→voltage[V]); nonlinear correction(2) ZPD detection;
remove low-frequency components

SWIR

TIR
Band

(3) Phase correction;
Fourier transform(4) Spectra output

SWIR observation
data spectra-1(V/cm )

(3) Fourier transform(4) Radiance spectra
creation; spectra output

Blackbody correction
data; deep-spacecorrection data

TIR radiancespectra2-1(W/cm /cm /sr)Fig. 6.5-1 TANSO-FTS Level 1B processing flow

(1) Count-to-value conversion and nonlinear correction
a. Data input
FTS Level 1A product storing the interferogram is read in.
b. Count-to-value conversion
The interferogram given as digital data is converted to analog data using acount-to-value conversion coefficient. The equation for conversion is given as alinear function.

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I ANA mb  

I DN mb   Bb, g Ab, g 

IANA[m](b)IDN[m](b)A(b,g)
B(b,g)b

Eq. 6.5-1: Interferogram of each band (analog value (voltage); output): Interferogram of each band (digital value; input): Conversion coefficient per band, and per gain
: Offset value per band, and per offset: Band (b1P, b1S, b2P, b2S, b3P, b3S, b4AC, b4DC)
 P: P-polarization light, S: S-polarization light, AC: Alternating Current, DC: Direct Currentgm: Gain (L, M, H): Fringe countThe number of data of SWIR interferogram (Bands 1-3) is 76,336, whereas in thecase of TIR (Band 4), the numbers of data of AC components and DC components
are given separately, and they are 38,168 and 38, respectively.
c. Nonlinearity correction
In the case of TIR, due to the high sensitivity of PC-MCT detector, signal output ofthe detector tends to become nonlinear response when strong energy enter tosaturate the detected signal. Accordingly, nonlinearity correction is applied to theinterferogram of TIR. On the other hand, in the case of SWIR, nonlinear responses
are not observed, although the nonlinear correction function itself is provided inprocessing.
d. Saturation checkSet the saturation flag on when a value of the interferogram, before thecount-to-value conversion, exceeds the threshold value.
(2) Detection of ZPD and removal of low-frequency components
a. Removal of DC component
In general, the interferogram is composed of DC and AC components; a spectrum
obtained by applying Fourier transform to the interferogram with a DC component
shows a peak at the frequency of zero. In order to reduce such a peak, the DC
component, being regarded as the one represented by a linear function, is removedby eliminating the linear function component, whereas the AC components,
considered to be the oscillating ones, remain to undergo further processing.

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GOSAT / IBUKI Data Users Handbook
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Chapter 6 GOSAT Productsb. Detection of ZPD and data extraction
After the removal of DC component, a position at which the interferogram has the
maximum value is selected as the zero optical path difference point, hereafter
called "ZPD". (see Fig. 6.5-2).
Next, the data shall be extracted in a way bilaterally symmetric with respect to ZPD.
In order to speed up the Fourier transform that is to be executed subsequently, thenumber of data shall be extended to 76,545 for SWIR, and 38,400 for TIR15. The
values for the points in the portions newly extended will be filled by 0 (zero).

ZPD (maximum; zero optical path difference)

Fig. 6.5-2 Interferogram and ZPDc. Spike noise detection and correction
Various kinds of abnormality that appear on the interferogram are processed in alump as a spike noise. When such spike noise is detected, it is so classified as toset a noise flag on. Only in the case, however, when gain switching is detectedduring interferogram acquisition, correction is made using the data sampled justbefore the gain switching.
Since spike noises that appear on orbit are usually composed of low-frequency
components, they will be removed by the low-frequency correction later discussed
in the paragraph ’e’ to have the defects corrected before generating the spectrum.
d. Fourier Transform
Prior to the low-frequency components elimination processing discussed in thenext subsection, spectra are to be calculated from the interferogram throughFourier transform.
Since the interferogram is composed of N points of discrete signals lined up at
equal intervals, the following equation of discrete complex Fourier transform isused. Each spectrum is calculated as a complex number having a real part and an
15

Fast Fourier Transform is available by taking a larger exponent.
4
7
3
9
2
76,336 (=2 ×13×367) → 76,545 (= 3 ×5×7), 38,168 (=2 ×13×367) → 38,400 (=2 ×3×5 )6-26

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imaginary part.

S [ n] Iin[m]S[n]N

1 N 1
I in [m]e  2i ( mn / N )N m 0(n = 0,…, N-1; m = 0,…, N-1)

Eq. 6.5-2: Interferogram: Spectrum: Number of datae. Low-frequency component check and correction
Unexpected low-frequency components, which shall theoretically be zero, may
appear in the spectral data when the jitter of the sensor field of view or
micro-vibration of the pointing mechanism during the scanning are occurred.
Accordingly, after the Fourier transform discussed in the preceding subsection, thespectral output must be checked to find if there exist any low-frequency
components; and if there were some, the following correction is applied to suppress
the components in the output of spectral data.
To start with, compose the spectral data that include only the low-frequency
components of the spectral output; then perform inverse Fourier transform on the
spectral data thus composed to generate an interferogram of the low-frequency
components.
Next, subtract the generated low-frequency interferogram from the original raw
interferogram.
(3) Fourier transform and phase correction (spectrum calculation)a. Phase information extraction
With the ideal Fourier interferometer, an acquired interferogram will have its
maximum alternating current component at ZPD, and its shape shall be bilaterally
symmetric with respect to ZPD as seen in Fig. 6.5-2. However, in actual practice,interferograms are shaped asymmetric due to the shifts in phase caused by various
factors. Therefore, phase correction is applied to the interferogram to recover its
symmetry.
After the low-frequency correction being applied, some of the interferogram datanear ZPD are sampled out symmetrically with respect to ZPD; then Fouriertransform is performed on the sampled data with a given window function to
calculate a phase angle from the values of real part and imaginary part. This is thephase information held by the spectrum after the Fourier transform and before thephase correction.

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Chapter 6 GOSAT Productsb. Fourier transform and phase correction
Perform Fourier transform on the entire interferogram, to which the low-frequency
correction has already been applied, to calculate spectral data. Then rotate thecalculated spectrum by the phase angle obtained through the processing defined in
the preceding subsection to obtain a phase-corrected spectrum in real part.
It is to be noted that phase correction is applied only to SWIR observation data, but
not to TIR observation data. Instead, the calibration processing discussed in thesubsection "(4) b" is applied.
(4) Generation and output of radiance spectraa. Output of SWIR spectral data
The SWIR spectral calculation are to be processed for SWIR observation data,
deep-space calibration data, blackbody calibration data, and an instrument linefunction calibration data. However, to avoid the calculation failure (e.g. division byzero) met in the calculation for the region of wavenumbers outside the significant
range, SWIR radiance spectra are not calculated; and the observation data spectra[V/cm-1] are provided as a final output.
The Level 1B product contains the complex spectral information in real part andimaginary part. The saturation flag is set when the value of the interferogram at
ZPD exceeds the threshold value.
b. Output of TIR spectral data
The TIR spectral radiance [W/cm2/cm-1/sr] are calculated through the calibration
processing, which is combined with 3 spectra of TIR observation data, deep spacecalibration data, and blackbody calibration data.
The Level 1B product contains the complex spectral information in real part andimaginary part. The saturation flag is set when the value of the interferogram at
ZPD exceeds the threshold value.
6.5.3 TANSO-CAI Level 1A Processing Algorithm
Level 1A processing is a process to generate a Level 1A product using
unprocessed image data output from the sensors. In the processing, 12-bit pixel
data output of a sensor is converted to 2-byte digital data and stored line by line foreach band. A product holds the data corresponding to one-sixtieth-length of theground trajectory of a revolution of the satellite. The following information is stored
in the product as well as the image data.
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Chapter 6 GOSAT Products[Information appended] Count-to-value conversion coefficients
 Geolocation information
 Position of the sun and the moon
 Data quality information (temperature of sensor component, abnormality flags
concerning orbit and/or attitude data to indicate that the data are outside thethreshold value, etc.)
 Ancillary information of TANSO-CAI Level 0 data Information on orbit and attitude Information on calibration
Note that the Level 1A products are classified as an internal product and not open
to the general users.
6.5.4 TANSO-CAI Level 1B Processing Algorithm
The TANSO-CAI Level 1B processing algorithm presented here is for Ver. 00.90 of
the CAI Level 1B. In this version of CAI Level 1B product, the physical quantity
conversion described in 6.5.4 (2) is performed, but the zero level correction,
performed for CAI Level 1B+, is not performed. Therefore, the radiometric data of
CAI Level 1B have different values from the CAI Level 1B+. However, in the higher
level processing using the CAI Level 1B, zero level correction is performed in anintermediate step of the higher level processing.
The CAI Level 1B processing performs frame separation and physical quantity
conversion on a CAI level 1A product. Furthermore, band-to-band registration
correction is carried out based on band 3 with no interpolation involved. Attention
must be paid to the points listed below.
 Spatial resolution at the nadir of the satellite is 0.5 km for bands 1, 2, and 3, and1.5 km for band 4.
 The number of pixels is 2,056 for bands 1, 2, and 3, and 512 for band 4.
 Observation swath (given as a product of the spatial resolution and the number ofpixels) is approximately 1,000km for bands 1, 2, and 3; while the swath for band
4 is approximately 750km, narrower than that of bands 1, 2, and 3.
The product of CAI Level 1B is provided to users by a unit of CAI frame (see6-29

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Section 6.1 (4) for details) in a file recorded in the form of HDF5 (see Section 6.3 fordetails) with some number of adjacent lines of data added to the frame.
Fig. 6.5-3 is a CAI Level 1B processing flow, and the brief explanation of theprocessing follows.
CAI Level 1A
product(1) Frame separation(2) Count-to-value conversion(3) Band-to-band registration(4) Ortho rectification ofobservation locations

CAI Level 1B
product

Fig. 6.5-3 CAI Level 1B processing flow

(1) Frame separation
The source data of the CAI Level 1B processing is a CAI Level 1A product file
(holds a scene of observation data covered by a revolution starting from anascending node to end at the next ascending node) and a scene of CAI Level 1A
data is divided into the unit of frames commonly applied to Level 1B product; thismakes it easy to keep the resolution of the source data through the processing. The
central position of a frame is defined in accordance with the GOSAT nominal orbit
and fixed to the ground. The average interval time between the observations of two
adjacent frame centers is 98.18 seconds.
One frame usually contains TANSO-CAI observation data of 2,048 pixels × 1,355
lines (including 18 lines of an overlap with each of the adjacent frames). Fig. 6.5-4
illustrates schematically how the frame separation is made.

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Preceding frame

Satellite along-track direction
Line
Frame
(a predetermined number of lines
are included, 18 lines of data
overlapped with adjacent frames)

Next frameFig. 6.5-4 Frame separation for Level 1B processing(2) Physical quantity conversion
The physical quantity conversion processing converts CAI Level 1A product data
(12-bit digital data, each ranging from 0 to 4,095) to radiance data. Further, thesaturation flag is added as quality information of the CAI radiance data.
The method of converting Digital Number (DN) to radiance is described below.
R i , j ,k  DN i , j   Dark i , j Responsei , j 
IntegrationTime k 

Eq. 6.5-3

i: Band (1-4)

j: Element number (1 - 2,056 for bands 1-3; 1 - 512 for Band 4)k: Integration time ID (0 - 31)

R(i, j, k): Radiance [ W/m 2/sr/µm ]DN (i, j): CAI Level 1A product (digital value) [ -- ]Dark(i, j): Count-to-value conversion coefficient (the level in darkness) [ -- ]Response (i, j) : Count-to-value conversion coefficient (responsive term)[ W msec/m 2/sr/µm ]Integration Time (k) : Integration time [ msec ]Since the integration time ID in the CAI L1A is shifted in time one line backward andnext line data is stored as of the corresponding digital number, this shift is correctedin the L1B data. However, for the first line of the CAI scene, since no integration
time ID corresponding to its digital number exists, the integration time ID for the
next line is used instead.
When an observed target is extremely bright like the clouds near the equatorreflecting strong light, TANSO-CAI may become saturated. The saturation of CAI

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Chapter 6 GOSAT Productsmeans that the digital value of the CAI Level 1A product reaches its maximum of
4,095. However, as the CAI Level 1B product is generated as a result of converting
digital values to radiance, it is difficult to know whether or not saturation has
occurred by only referring to the CAI Level 1B radiance data. Therefore, asaturation flag is set for each pixel of every band of L1B data and attached as
information supplemental to the CAI L1B radiance data.
(For the details of the physical quantity correction, please refer to the ATBD of
GOSAT-TANSO CAI Level 1B: NIES-GOSAT-PO-009)(3) Band-to-band registration correction
In the band-to-band registration correction of CAI, the line-of-sight vector of a pixelof band 3 is taken as the reference direction; then a pixel of the band 1, whoseline-of-sight vector direction is considered closest to the reference direction, isselected. Then, a pixel in band 2, and then in band 4, are selected in the same
fashion.
However, band 4, having a resolution different from band 1, 2, or 3, shows a shift in
the AT direction to a certain extent (several pixels’ shift depending on the even/odd
of a pixel). This fact was found after the launch. Accordingly, additional
band-to-band registration correction processing is applied to band 4 through which
pixels are shifted in the AT direction by the amount depending on the parity of pixel
numbers.
(4) Ortho rectification of observed location
For a CAI Level 1B product, geometric information such as latitude and longitude iscalculated taking the altitude of the location into account. This geometric correction,
called ortho rectification, is carried out by calculating the position at which aline-of-sight vector intersects the surface of the Digital Elevation Model (DEM,
GTOP30) and the calculated position is regarded as a point actually observed;
while, in the case of CAI Level 1A, the location is calculated by calculating theintersection of the line-of-sight vector against the earth ellipsoid model. In addition,
after calculating the actual location observed by each pixel, land-sea flag is given toeach of the pixels to show which type of the ground, land or water (sea, lake, river),is being observed. For the data source of land-sea flags, Land-Sea Mask data isemployed, which is released open to the public from the Global Land 1-KM AVHRR(Advanced Very High Resolution Radiometer) Project of the United States
Geological Survey (USGS).

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Since the location data in the CAI Level 1A product is given only to a pixel out of 10
x 10 pixels, the location data for each remaining pixels of CAI band 3 shall be
generated by linear interpolation so that all the pixels of band 3 have observation
location data (see Fig. 6.5-5).

Pixels with location information
are blacked out
Calculate location information
for all the pixels of band 3

Fig. 6.5-5 Interposing observation location data

Fig. 6.5-6 illustrates schematically how the ortho rectification is conducted. The
point (X' in Fig. 6.5-6) at which a line-of-sight vector intersects the ground surface
defined by DEM is calculated to give the observed location corrected with thealtitude taken into account. When, as in a mountainous region, the line of sightvectors intersect with several terrain surfaces, the one closest to the GOSAT
satellite is selected as the observed location X'.
(As for GTOPO30, see the website of the Geographical Survey Institute.

GOSAT
TANSO-CAI
Line of sight vector

X’ : Observation location of CAI Level1B data(location actually observed)

Digital elevation model (GTOPO30)

X : Observation location recorded in CAI Levl1A product(location on the earth ellipsoid）

Fig. 6.5-6 Concept of ortho rectification

6.5.5 TANSO-CAI Level 1B+ Processing Algorithm
Level 1B+ processing includes frame separation, radiometric correction, andgeometric correction (including ortho rectification, band-to-band registration
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correction, map projection) on a TANSO-CAI L1A product to generate a CAI L1B+
product by a unit of CAI frame on a file recorded in the form of HDF5. Checks on
the data continuity and abnormal values are also conducted to correct the data.
Fig. 6.5-7 shows the CAI Level 1B+ processing flow, and the brief explanations of
the processing will follow.
CAI Level 1A
product(1) Frame separation(2) Radiometric correction(3) Geometric correction(4) Abnormal data correction

CAI Level 1B+
product
Fig. 6.5-7 CAI Level 1B+ processing flow

(1) Frame separation
The method of separation is basically the same with that of the CAI Level 1B
processing. Overlapping parts between frames are 65 lines. For further information
please refer to Section 6.5.4 (1).
(2) Radiometric correction
Radiance is calculated for each element of each of the bands from a digital countby using the physical quantity conversion coefficients stored in a TANSO-CAI Level
1A product.
First, physical quantity conversion, involving zero level correction and vicarious
calibration correction, is performed on each element. Next, radiance is expressedin a 2-byte integer (DN value) for the places defined through the geometriccorrection (including band-to-band registration correction).
a. Physical quantity conversion (radiance)

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Each DN value of the Level 1A product is converted to a radiance value (realnumber) using radiometric correction coefficients. Refer to Section 6.6.4 (2) for theoutline of the processing.
b. Zero level correction
Some pixel elements placed at the edge of CAI bands 1 through 3 have noobservation light coming into them because they are not in the sensor’s view. The
value these elements hold is taken as the level of zero and used to correct thevalues held by the rest of the elements receiving the light in. This processing iscarried out only for Bands 1 through 3.
c. Correction by vicarious calibration coefficients
Vicarious calibration correction is a correction applied per band using the equation
below. Vicarious calibration coefficients used in the equation were calculated after
the launch of GOSAT, through the comparison with MODIS (MODerate resolution
Imaging Spectroradiometer) sensors on board the satellite Aqua of the National
Aeronautics and Space Administration (NASA).

R 'ij  Rij slope  offset

Eq. 6.5-4

i : Band number, j : Element number,
R : Radiance (W/m2/μm/sr)
R ’ :Radiance after vicarious calibration (W/m2/μm/sr)
slope : Vicarious calibration coefficient (element sensitive term)
offset : Vicarious calibration coefficient (offset term)d. Physical quantity conversion (DN value)
DN values after the correction are obtained using the equation below. This step iscarried out during the re-sampling processing.
 Rij Coi 
DN ij  int C gi C gi 

( DN ij  1 )Eq. 6.5-5

i : Band number, j : Element number
DN : DN value of Level 1B+
int : Conversion to integer
Cg : Conversion factor for converting DN value of L1B+ to radiance (gain term)
Co : Conversion factor for converting DN value of L1B+ to radiance (offset term)

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Here, Cg and Co are given as external parameters.
The value of DN is set to 1 if the calculated result of DN is less than 1, while it is set
to 65,535 if the calculated result exceeds 65,535. The value 0 is used to indicatethat the pixel is not valid. Fig. 6.5-8 shows an example of the case that the value 0
is utilized. If there is any blank in the image data after geometric correction, theinvalid value 0 is set as DN value.

N

DN ≧ 1

DN = 0 → invalid value

Fig. 6.5-8 Example usage of invalid value 0(3) Geometric correction
Ortho rectification and transformation for map projection are applied to the data
after the radiometric correction.
Location observed by each of the elements is calculated by determining precisely
the line-of-sight vector of each pixel of each band. The pixel value, to be assigned
to the positions newly defined as a result of ortho rectification and map projection,is calculated through the interpolation using the bilinear method; band-to-bandregistration correction is carried out as a consequence.
a. Ortho rectification
The correction method is basically the same with that of the CAI Level 1B
processing. For the details of the processing, see 6.5.4 (4).
b. Transformation for map projection
Mercator projection or Polar Stereo projection is applied depending on the latitudeof the frame center. In the Mercator projection, distances and areas are enlarged
not proportionally when moving to higher latitude. Therefore, in the CAI L1B+
processing, the map projection is switched to the Polar Stereo projection as viewed
from the North or the South Pole for the data of 60 degrees latitude or higher. For
either of the map projections, the latitude on which the scale of the map is defined

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Chapter 6 GOSAT Products(called the reference latitude) and the central longitude of the map shall be
specified as parameters. The parameters are set as follows.
Table 6.5-1

Map projection coverage

Map projection

Latitude  range[deg]

Reference latitude

Mercator's projection0≤ |  |  60

Equator (fixed)

Frame center (fixed)60≤ |  | ≤ 90

North latitude 90 degrees North(for frames in northernhemisphere frames)
South latitude 90 degrees South(for frames in southernhemisphere frames)

Frame center (fixed)

Polar stereo projection

Reference longitude(orientation of map
projection)

Explanation on the procedure follows.
1) Setting of map coordinates
Following the specified projection method and parameters, geographic coordinates
for the frame of each band of a Level 1A image are calculated; namely, four corner
points of the frame and four middle points of the sides; a rectangular area
circumscribing the four sets (each set for each band) of the eight reference points
defines the area to be used for a frame. (see Fig. 6.5-9). In addition, pixel size isdefined so that it has the same spatial resolution on the reference latitude.

Point A(λA, A)

Point A' (XA' , YA' )

Pixel

Line
y
8 points on observation data
per band (total of four bands)x

8 points after map projection, and map projection area:
the rectangular region circumscribing the 8 points
about all of the four bands

Fig. 6.5-9 Calculate map projection area

2) Calculation of Level 1B+ coordinates with regard to map coordinates
Each pixel’s latitude / longitude data are calculated by the reverse map projection.
In this way, line-pixel coordinates of the Level 1B+ data are associated to thelatitude / longitude data. Since the reverse mapping calculation is time-consuming,
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the calculation is conducted for a limited number of points as called lattice points;
for intermediate pixels pseudo-affine transformation is applied (see Fig. 6.5-10).
Pixel

Line

y

Observation data as presented in L1B+ productx: Lattice points

On the map projection area in map coordinates

Fig. 6.5-10 Lattice points in map coordinates and their projection on Level 1B+

3) Re-sampling
In order to calculate the pixel value after the geographic mapping and to conduct
band-to-band registration, bilinear re-sampling is used for interpolation.
(4) Correction for data anomaly
Abnormal data detection is conducted by the method listed below. When abnormal
data are detected, they are replaced by the value calculated through theinterpolation using the values on the lines before and after the scan.
(For further details, please refer to “ALGORITHM THEORETICAL BASIS
DOCUMENT (ATBD) of GOSAT TANSO-CAI Level 1B+ (NIES-GOSAT-PO-011,
section 5)”.
 Threshold examination: set the maximum and minimum values considered to bereasonable, and check if the data value is within the range.
 Continuity examination: check data continuity within a frame, a scan, etc; theprimary purpose of this test is to detect errors caused during data transmission.
 Variability examination: when a plurality of data are included for the same item ina scan, data variability is examined; the primary purpose of the variability
examination is to detect errors caused during data transmission.
(5) Miscellanies
Calculate a solar zenith and azimuth angles, and a satellite zenith and azimuth
angles.

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6.6

Higher level Processing Algorithm

Processing algorithm for the standard products of Level 2 or higher is outlined
hereafter. For the details of algorithm, please refer to the ATBDs prepared for eachalgorithm.
The ATBDs are obtained from the NIES GOSAT products distribution website GUIG.
How to obtain the ATBDs is explained in section 7.3.1.
6.6.1 TANSO-FTS SWIR Level 2 Processing Algorithm for CO2 and CH4 Column
Amount
The Level 2 processing has FTS SWIR Level 1B data as input, then performs
pre-processing, filtering, retrieval processing16, and screening to calculate column
amounts of carbon dioxide (CO2) and methane (CH4). A column amount is thenumber of molecules contained in a column from the earth surface up to the top of
atmosphere per unit area.
Level 2 products that meet the user’s demands (observation period, observation
range, etc.) are stored in a file in the form of HDF5 and provided to users. Averagecolumn concentrations are included in the products in addition to the column
amounts. The column-averaged dry air mixing ratio of carbon dioxide (XCO2) andmethane (XCO4) are calculated from the respective column amounts of carbon
dioxide (CO2) and methane (CH4) by dividing them by the column amount of dry air.
Fig. 6.6-1 shows a flow of the processing. And the outline of the processing follows.
For the details of the algorithm, refer to ALGORITHM THEORETICAL BASIS
DOCUMENT (ATBD) FOR CO2 AND CH4 COLUMUN AMOUNTS RETRIEVALFROM GOSAT TANSO-FTS SWIR (NIES-GOSAT-PO-014). As for the details of
the processing flow, refer to "Data Processing Flow for the FTS SWIR Level 2 CO2and CH4 Data Products (Ver.01.xx)." Both documents are open to the public andavailable from GUIG.

16

An analytical method to calculate various kinds of physical quantities from spectrum (such as height
distribution of temperature and of gas molecules).
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FTS SWIR Level 1B(1) Pre-processing(2) Filtering(3) Retrieval processing(4) Screening
FTS Level 2 CO2, CH4column amountFig. 6.6-1 Processing flow for TANSO-FTS SWIR Level 2 CO2, CH4 column amount(1) Pre-processing
Before performing the retrieval processing to calculate the column amounts ofcarbon dioxide and methane using an FTS Level 1B product (radiance spectra),some preliminary processing is required.
As the FTS Level 1B product is made by the unit of a scene (see section 6.1 (1)),
the product must be divided into units of a scan (see section 6.1 (2)) before being
used as input data to Level 2 processing, while abnormal data are removed in thisprocess.
And the time and location to the observation are calculated, then reference datasuch as weather information are interpolated to get the match-up data for the timeand location thus identified.
(For the details of the pre-processing, see section 2 of "ALGORITHM
THEORETICAL BASIS DOCUMENT (ATBD) FOR CO2 AND CH4 COLUMUNAMOUNTS RETRIEVAL FROM GOSAT TANSO-FTS SWIR(NIES-GOSAT-PO-014)".)(2) Filtering (Pre-data selection)
First, some particular scans of data suitable for retrieval processing must be
selected.
FTS SWIR daytime observations are conducted for about 9,000 scans per day. But
not all of the data are suitable for retrieval processing. In order to get a result ofhigh quality, the data for the processing must be confined to such data that are
qualified by passing through the filtering conditions listed below.

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Chapter 6 GOSAT Products(For the details of the filtering, see section 3 of "ALGORITHM THEORETICALBASIS DOCUMENT (ATBD) FOR CO2 AND CH4 COLUMUN AMOUNTSRETRIEVAL FROM GOSAT TANSO-FTS SWIR (NIES-GOSAT-PO-014)”).
 L1 quality check (check the quality flags such as saturation flag and spike noiseflag) Solar zenith angle check Ground surface undulation check CAI cloud coverage check TIR cloud coverage check(3) Retrieval processing
The column amounts of carbon dioxide and methane are obtained by the retrieval
processing.
The total column amounts of carbon dioxide and methane are estimated from theradiance spectra in a wavenumber range of 12,950 to 13,200 cm-1 of FTS Band 1(oxygen sub-band), a wavenumber range of 5,900 to 6,150 cm-1 of FTS Band 2(methane sub-band), and a wavenumber range of 6,180 to 6,380 cm-1 of FTS Band2 (carbon dioxide sub-band). The total column amount is calculated by summing up,
for all the layers, the value obtained by multiplying the average mixing ratio
estimated for each layer and the corresponding dry air column amount. In addition,
the column averaged volume mixing ratio (XCO2, XCH4) are obtained by dividing
the total column amount of carbon dioxide or methane by the total column amountof dry air.
Along with the mixing ratios of carbon dioxide and methane for every layer, suchphysical quantities are simultaneously estimated as the average mixing ratio ofwater vapor for each layer, optical thickness of aerosol, atmospheric pressure on
the ground, and the temperature shift.
In the calculation for the estimation mentioned above, initial values of concentration
profile at the points of observation are set as the a priori data given by a simulation
using the atmosphere transport model, while initial values of the aerosol are given
by a simulation using the aerosol transport model SPRINTARS. Calculations arecarried out repeatedly until the spectral values at the points of observation,
estimated from the initial values and reference data using the analytical method,
become close enough to the observed data.
(For the details of retrieval processing, see sections 4 through 8 of "ALGORITHM

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THEORETICAL BASIS DOCUMENT (ATBD) FOR CO2 AND CH4 COLUMUNAMOUNTSRETRIEVAL
FROM
GOSAT
TANSO-FTS
SWIR(NIES-GOSAT-PO-014)".)(4) Screening (Post-screening)
Screening selection process is conducted for the data resultant from the retrieval
processing described above. Only the data of good quality are selected through thescreening based on the results of error evaluation, and are provided for external
users as a TANSO-FTS SWIR Level 2 product. The screening conditions are cited
below. Further, a processing flow including the screening is illustrated in Fig. 6.6-2.
(For the details of screening, see section 9.2 of "ALGORITHM THEORETICALBASIS DOCUMENT (ATBD) FOR CO2 AND CH4 COLUMUN AMOUNTSRETRIEVAL FROM GOSAT TANSO-FTS SWIR (NIES-GOSAT-PO-014)".)
 Select the data whose SNR of the synthesized polarized light is larger than 100.
The SNR is defined here as a ratio of the maximum radiance of the polarization
bands used in the retrieval processing to the average noise level.
 Select the data whose DFS (Degree of Freedom for Signal) is larger than 1.
 Select the data whose root mean square error of the residual spectrum is lessthan 3.
 Select the case where either a land area or water area is present in the sight viewof TANSO-FTS (exclude the case where both a land area and water area arepresent in the sight view of TANSO-FTS).
 Check the presence of scattering materials of the 2-μm band.
 Select the case where the retrieval processing has converged in less than 20
times of iteration.
 Select the case where the optical thickness of aerosol, estimated with thegaseous concentration, is less than 0.5.
 With the data over the sea, select the case where the calibration coefficientadjustment value, estimated with the gaseous concentration, does not reach its
upper limit 1.15 (exclude the case where the value reaches the upper limit).
 Exclude the data of Greenland and the Antarctic.
 Select the case where the index value that normalizes the evaluation function isless than 5, while the estimation of physical quantities is done through the
optimization of the evaluation function.

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FTS L2 SWIR
(for RA users)

FTS
L1B

Scan
separation

Filtering by checking1) Quality flag2) Solar zenith angle
3) Undulation(ups and downs of
the ground)4) Cloud

SWIR
Retrieval

Screening (2)1) Number of iteration < 202) Retrieved AOT (Aerosol
Optical Thickness) < 0.5
3) STD of CAI Radiance (CAI
Coherent test)4) Exclude Greenland and theAntarctic5) Radiometric Adjustment Factor
for Band 1 and 2 (over the sea)6) SNR in Band 1 > 100
7) Chi^2 < 58) Residual spectra RMS < 39) Residual spectra RMS for O2A
Band < 3

CAI L2
Cloud
flag

CAI
L1B

Data
Processing

Screening (1)1) SNR in Band 2 > 100
2) DFS (Degree of freedom for
Signal) > 1
3) Residual RMS (Root meansquare) < 5.0
4) Co-existence of land and sea5) Scattering materials in 2m

Frame
separation

Product
CAI
L1A

FTS L2SWIR (GU)Fig. 6.6-2 Processing flow including the screening

6.6.2 TANSO-FTS TIR Level 2 Processing Algorithm for CO2 and CH4 Profiles
The Level 2 processing inputs FTS TIR Level 1B spectra (band 4), then performs
pre-processing for retrieval, filtering by cloud screening, estimation of surface
temperatureand emissivity, retrieval processing, and screening by error
evaluation to calculate vertical profiles and distributions of carbon dioxide andmethane concentrations. A broad-band spectrum, ranging from 5.5 to 14.3μm
wavelength, is acquired for the thermal infrared region; the CO2 retrieval
processing uses the absorption spectrum in 14μm band, while the CH4 retrieval
processing uses in 7μm band.
Level 2 products that meet the user’s demands (observation period, observed area,etc.) are recorded in a HDf5 file and provided. Here, the profile data are calculated
in seven pressure levels, which vertically change in 1,000, 700, 500, 300, 100, 50,
and 30hPa of pressure height and thereabouts. However, the number of layers andthe fixed layer values of pressure height recorded in Level 2 products are yet to be
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determined.
The processing flow is shown in Fig. 6.6-3; and the outline of the processing follows.
Note that part of the pre-processing and part of the filtering are the same as thoseof the SWIR Level 2 processing.
For the details, see the algorithm theoretical basis documents for the TIR Level 2
processing (not available as of December 2010).
FTS TIR
Level 1B
(1) Pre-processing(2) Filtering(3) Estimation of surface
temperature and emissivity(4) Retrieval processing(5) Screening
FTS Level 2
CO2 , CH4
concentration profile

Fig. 6.6-3 Processing flow for TANSO-FTS TIR Level 2 CO2 and CH4 profiles(1) Pre-processing
Preparation shall be made before performing the retrieval processing to obtain CO2
and CH4 concentration profiles using spectral radiance of an FTS Level 1B product.
Most of the TIR pre-processing is commonly used with that of SWIR Level 2;
meteorological data are of GVP, while the data initially given to the retrieval as aconcentration of CO2 and CH4 are the predictive estimation using the NIES
atmospheric transport model. For the TIR processing, climatological data are
additionally required; the data listed below are prepared in the pre-processing.
Sea surface temperature data (MODIS sea surface temperature)
Ozone data (OMI (Ozone Monitoring Instrument) total ozone)
Land-cover data (MODIS land-cover classification)
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Chapter 6 GOSAT Products Snow ice data (Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sea
ice concentration)(2) Filtering (Pre-data selection)
The data selection for TIR retrieval processing follows suit of the SWIR filtering;
namely, the data of dayside observation are adopted in the clear-sky condition
based on the CAI cloud screening (CAI Level 2 cloud flag product). On the other
hand, in nightside, where no CAI cloud flag is available, the TIR data for the
retrieval processing are selected based on the TIR cloud screening result obtained
from the TIR spectrum analysis. The slicing method and the split-window method
are known for the cloud screening using TIR spectra.
(3) Estimation of surface temperature and emissivity,
Radiation from the land area changes depending on the soil type, snow and ice
coverage, NDVI, etc., while on the sea area it changes depending on the sea-ice
concentration, the influence of whitecaps under the sea surface wind, and so on.
Therefore, the surface temperature must be estimated by supposing the initialvalues of the land surface emissivity based on the radiation databases (MODIS and
ASTER database) with land-cover classification incorporated. The land surface
temperature and emissivity thus estimated are used as an initial surface condition
for the CO2 and CH4 retrieval processing.
(4) CO2 and CH4 retrieval processing
The average mixing ratios of CO2 and CH4 in the dry air are calculated for eachlayer of altitude.
In order to estimate the CO2 and CH4 concentration profiles from TIR data, theMaximum A Posteriori estimation (MAP estimation) based on Bayes' theorem is
employed. The MAP estimation is a method to obtain a solution from the observed
spectra with errors showing normal distribution by maximizing a posteriori
probability while a priori probability is given as expressed by the error variance andcovariance matrix. An optimum state of the atmosphere is obtained by minimizing
the cost function. A nonlinear MAP estimation using Gauss-Newton algorithm isapplied repetitively till the solution converges.
For the calculation of the forward spectrum used in the estimation, Line-By-Line
Radiative Transfer Model (LBLRTM) and HITRAN database (HIgh resolution
TRANsmission molecular absorption database) are applied so as to simulate theabsorption lines of gasses in high accuracy. As a means to improve the processing

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speed, retrieval channels are selected in order on the basis of information contentsof the target gas and layer profile.
(5) Screening (Post-screening)
Only the data of good quality are selected through the means called screening
based on the results of error evaluation, and are provided for users as a
TANSO-FTS TIR Level 2 product.
6.6.3 TANSO-CAI Level 2 Cloud Flag Processing Algorithm
Clear-sky confidence level, which comprises a cloud flag, is calculated from CAI
Level 1B data as an input. The results are stored in a file by a unit of CAI frame in
the form of HDF5.
To decrease the error in the FTS Level 2 processing, accurate cloud estimation isnecessary, and the clear-sky confidence level calculated above is referred to by the
FTS Level 2 processing in its filtering process with predetermined values used as a
threshold to discriminate clear / cloudy conditions.
Fig. 6.6-4 is a processing flow and outline of the processing follows.
For the details of algorithm, refer to "Algorithm Theoretical Basis Document for
GOSAT TANSO-CAI L2 cloud flag (NIES-GOSAT-PO-016)."

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CAI sensor information(1) Data ingest

Scan geometry information
Algorithm specificinformation(2) Pre-processing

Ancillary information

NDSI check to identify
snow-covered surface

Yes (snow)

Append snow flagNo(3) Calculation of clear-sky confidence
through the stages of judgment tests(4) Calculation of overall
clear-sky confidence(5) Output cloud check
results

CAI L2 cloud flag

Fig. 6.6-4 Processing flow for TANSO-CAI Level 2 cloud flag(1) Data ingest
The following data are ingested.
 CAI instrument information: CAI Level 1B data (radiance), saturation flag
 Scan’s geometry information: solar zenith angle, satellite zenith angle, relative
azimuth angle; latitude and longitude on the World Geodetic System (WGS84);
observation time date.
 Algorithm specific information: threshold values for various judgment tests (see(3))
 Ancillary information: ground surface reflectance database for Band 2 or 3, andglobal land-sea flag (the 1km Land-Sea Mask supplied by United States
Geological Survey). As an alternative to the former data, climatological data
generated from GLI data of MODIS, ADEOS-II, etc. are used in some cases.

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Identify day or night, land or water, and sunglint region from the input data.
In addition, calculate the reflectance from the radiance observed by CAI and solar
irradiance, and the reflectance shall be used in the judgment tests explained in theparagraph (3). In the tests of (3), if any one of the saturation flags of all the bands ison, the synthetic clear-sky confidence is set to 0 (zero) because the radiance value
must be saturated by cloud.
Further, check if the surface may be covered by snow using NDSI (Normalized
Difference Soil Index).
(For the details of pre-processing, see section 6 (b) of "Algorithm Theoretical Basis
Document for GOSAT TANSO-CAI L2 cloud flag (NIES-GOSAT-PO-016)".)(3) Calculation of clear-sky confidence levels for each component
For the following components, clear-sky confidence level F1 is calculated.
(For the details of clear-sky confidence level calculation in each discrimination test,
refer to section 6(c) of "Algorithm Theoretical Basis Document for GOSATTANSO-CAI L2 cloud flag (NIES-GOSAT-PO-016)".)

Test 1 : R(B1) (the land area) or R(B3) (the water area) → confidence level F1Test 2 : R(B3) / R(B2) → confidence level F2
Test 3 : NDVI = (R(B3) - R(B2)) / (R(B3) + R(B2)) → confidence level F3
Test 4 : R(B3) / R(B4) (only on the land area) → confidence level F4
R : ReflectanceB : BandFn : Confidence level(4) Calculation of synthetic clear-sky confidence
The synthetic clear-sky confidence level Q is calculated from the results ofrespective clear-sky confidence levels Fn mentioned above in the following way:Q  1  ( 1  F1 )( 1  F2 )( 1  F3 )(1  F4 )Eq. 6.6-1

If confidence level Q is equal to 1, the data is considered clear. If 0, the data is
considered cloudy. If one of Fn is 1, Q becomes 1, regardless of other components.
The determined clear-sky confidence level is stored in the product as a 4-byte real

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number.
(5) Output of the cloud flag product
Cloud flags are created including the integrated clear-sky confidence level andother outputs expressed by bits. Thirty-two bits are assigned to a pixel.
(For the details of cloud flag output, see section 6 (e) of "Algorithm Theoretical
Basis Document for GOSAT TANSO-CAI L2 cloud flag (NIES-GOSAT-PO-016)".)6.6.4 Processing Algorithm of TANSO-FTS SWIR Level 3 Global CO2 and CH4Distribution, and TIR Level 3 Global CO2 and CH4 Distribution
For the FTS Level 3 products, the whole surface of the earth is supposed to be
divided into meshes of 2.5 × 2.5 degrees in the FTS Level 3 product XCO2 or XCH4
data estimated for each of the meshes.
These values for meshes are calculated by the kriging method using the FTS Level
2 data for a month (SWIR CO2, CH4 column amount, and TIR CO2, CH4 profile) as
input.
The product is stored in a file by a unit of month in HDF5 format. As for the TIR
Level 3 global CO2 and CH4 concentration product, the whole data are divided into
seven levels based on the atmospheric pressure in vertical direction (for 1,000, 700,
500, 300, 100, 50, and 30hPa) and the data for each of the levels are separately
stored; the number of layers and the pressure values to separate the layers are yet
to be determined.
Fig. 6.6-5 shows the processing flow, and the outline of data processing follows.
For the details of algorithm, refer to "Algorithm Theoretical Basis Document for
GOSAT TANSO-FTS L3 (NIES-GOSAT-PO-017)."

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Chapter 6 GOSAT Products(1) Ingest FTS L2 product

FTS L2 product(2)FTS L2 product screeningYes
Use estimated interpolation model
parameters ?

No
Ingestparameter file(3) Estimation of interpolation parameters(land area, sea area)

Search range
definition fileNo
Estimation successful ?

Usepredeterminedparameters

Yes(4) Interpolation calculation<Kriging (1st stage)>Yes
All meshes interpolated ?

No(5) Interpolation calculation<Kriging (2nd stage)>
Re-calculate interpolation using thedata firstly interpolated

Yes
All meshes interpolated ?

No(6) Third stage of interpolation
Interpolation calculation using
average of at least four mesh points inthe neighborhood(7) Statistical value calculation(an average of FTS L2 datain each of the meshes)(8) Mask generation

FTS L3 product output

FTS L3 productFig. 6.6-5 Level 3 processing flow for TANSO-FTS SWIR and TIR

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Chapter 6 GOSAT Products(1) Ingesting FTS Level 2 product
FTS Level 2 product data for a month are ingested.
(2) Screening of FTS Level 2 product
When some of the observed points in the FTS Level 2 product have a value
extremely apart from the ones in their vicinity, it will have the worst effect on theaccuracy of interpolation presented by the kriging method; therefore, suchobservation points are eliminated. This eliminating process is called screening. The
screening shall be repeated till the FTS Level 2 data, thus processed, become
close to normal distribution (Gaussian distribution).
(For the details of screening, see section 2.2.5 (2) of " Algorithm Theoretical Basis
Document for GOSAT TANSO-FTS L3 (NIES-GOSAT-PO-017)".)(3) Estimation of interpolation model parameters
As there exists a big difference between the distribution patterns of the greenhousegasses in "land area" and in "water area," interpolation model parameters shall be
respectively estimated for the land area and water area to effectively conduct theFTS Level 3 processing.
(For the details of the estimation of interpolation model parameters, see section
2.2.5 (3) of " Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3(NIES-GOSAT-PO-017)".)(4) Interpolation calculation < Kriging (1st stage) >For all of the meshes, values are calculated by applying the interpolation model
parameters.
Theoretically, kriging interpolation calculates values using all of the observed points(all the points in a known stochastic field). However, in the FTS Level 3 processing,kriging interpolation of the first stage is conducted on a restricted number ofobservation points that exist within a predetermined distance from a target mesh;
the observed points, used for the interpolation, are selected by searching such
points starting from the ones closest to the mesh.
However, this way of limiting the number of observation points may leave some of
the mesh points with no values assigned; interpolation calculation repeated in theprocessing described in the paragraphs (5) and (6) are done to remove such
defects by giving them values newly interpolated.
(For the details of the interpolation calculation < Kriging (1st) >, see section 2.2.5(4) of "Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3

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Chapter 6 GOSAT Products(NIES-GOSAT-PO-017)".)(5) Interpolation calculation < Kriging (2nd stage) >The second stage of kriging interpolation is applied only to the meshes where novalues are given by the first stage of interpolation. On the contrary to the first stageof interpolation, there is no limit of the number of points to be used in the Kringing
interpolation.
(For the details of the interpolation calculation < Kriging (2nd) >, see section 2.2.5(5) of "Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3(NIES-GOSAT-PO-017)".)(6) Interpolation Calculation < Kriging (3rd stage) >The third stage of interpolation is made for the meshes left with no values evenafter the second stage of kriging interpolation. For this occasion, linear interpolation
is applied using values of at least four meshes (already filled by values) near themesh of the concern to give it the values.
(For the details of the interpolation calculation < Kriging (3rd) >, see section 2.2.5(6) of "Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3(NIES-GOSAT-PO-017)".)(7) Calculation of statistical values
With respect to the observed points, located in a mesh of 2.5 × 2.5 degrees,
statistical parameters of the values analytically obtained are given including themean value, maximum, minimum, median (the middle value), mode (the value that
occurs most often), and standard deviation.
(For the details of the calculation of statistical values, see section 2.2.5 (7) of"Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3(NIES-GOSAT-PO-017)".)(8) Mask Generation
FTS Level 3 processing can estimate values for all the meshes on the globe.
However, it may be less reliable when a mesh has few observation points in its
vicinity; the estimated values of such meshes must be excluded from data products.
Therefore, masking process is conducted for such a mesh that has no FTS Level 2
observation point within the predetermined distance from its center. The length isset to 500km.

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6.6.5 TANSO-CAI Level 3 Global Radiance Distribution Processing Algorithm(including cloudy segments)
CAI Level 3 global radiance distribution product is generated using, as an input,
CAI Level 1B+ products for three consecutive days. The generated product isrecorded in a file by a unit of the whole globe (every three days) in the form of
HDF5,. As a result, the image of this product may represent the cloud status of theworld.
Fig. 6.6-6 is the processing flow, and the outline of processing follows.
CAI Level 1B+ product forthree consecutive days

(1) Ingest data

(2) Adjustment of swath(3) Map projection and pixel selection(4) Orbit selection in polar regions(5) Select pixels out of multiple paths

CAI Level 3 global radiancedistribution productFig. 6.6-6 Processing flow for TANSO-CAI Level 3 global radiance distribution(1) Data ingest
Ingest a set of CAI Level 1B+ product data observed in three consecutive days; as
GOSAT is on the orbit of three recurrent days, the whole globe is covered in threedays. A set of CAI Level 1B+ products is prepared for each of the satellite paths
covered by a day.
(2) Adjustment of swath for each band
The swath of CAI band 4 is narrower than those of other three bands. In order togenerate a Level 3 product by combining the data of multiple paths, the swaths of
all the bands for each path must be the same. Therefore, the data near the edge ofthe observed swath of band 1 to 3 are cut off to make the widths equal to that of
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band 4, the narrowest.
(3) Map projection and pixel selection
The global radiance distribution product is generated as a set of data with values
for a mesh of 0.125 × 0.125 degrees as projected on an equidistant cylindrical map.
As the CAL Level 1B+ products, which is the input of the processing, applies
Mercator projection at lower latitude and polar stereo projection at higher latitude,
conversion to an equidistant cylindrical projection from either of these two
projection shall be performed. In practice, the value of Level 1B+ products, at thelocation closest to the point (in latitude and longitude) defined by a mesh on theLevel 3 product as the central point of the mesh, is stored for the mesh of the Level
3 product.
(4) Orbit selection in a polar region
Only the data of the descending orbit are used because the solar elevation angle of
the ascending orbit is lower than that of the descending orbit to bring poor
brightness.
(5) Pixel selection out of multiple paths' data
When there are several paths for the central point of a mesh of 0.125 × 0.125
degrees, the pixel value of the most recent observation is adopted to be stored in
the file. In other words, the value is overwritten by the latest observation data.
6.6.6 TANSO-CAI Level
Algorithm (Clear Sky)

3

GlobalReflectanceDistribution

Processing

CAI Level 1B products for a month are used as input. First, the minimum
reflectance in a day is selected in all pixels in each of the mesh of 0.125 × 0.125
degrees. This calculation is repeated for all the days in the month, and theminimum reflectance in the month becomes its output.
The product is stored in a file by a unit of the whole globe (by shifting every threedays) in the form of HDF5.
The processing flow is given in Fig. 6.6-7, and the outline of processing follows. As
a result, the image of this product looks clear sky.

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One month's worth of
CAI Level 1B product(1) Daily minimum reflectance calculation(2) Monthly minimum reflectance calculation

CAI Level 3 global
reflectance distribution
product

Fig. 6.6-7 Processing flow for TANSO-CAI Level 3 global reflectance distribution (clear sky)

(1) Calculation of daily minimum reflectanceA set of CAI Level 1B products for a whole day is prepared to calculate the least
reflectance in the day. For the first step, minimum value of radiance data are
extracted from a mesh of given size (0.125 x 0.125 degrees). Then, for the second
step, the radiance is converted to the reflectance, This process starts with band 2.
If several paths of the day have their pixels in the same mesh, all the pixels of thepaths are considered to determine the minimum reflectance.
As for the minimum reflectance of bands 1, 3, and 4, the one corresponding to thesame time and position where the band 2 takes the minimum reflectance are
adopted as the minimum reflectance of respective bands. The band 2 is given
priority because the reflectance of band 2 especially shows a smaller value on aland than the value on a cloud; these characteristics effectively used to remove thecloud.
For the conversion from radiance to reflectance, solar irradiance, solar zenith angle,
and the distance between the sun and the earth are taken into account.
Since a mesh in the coastal zone may include land and sea, two kinds of theminimum reflectance are calculated for land and sea. The daily minimum
reflectance data for the sea area are made from the CAI pixels located in each of
the meshes of 0.125 × 0.125 degrees dimensions, and identified as a sea pixel
based on the USGS land-sea flag data (with approximately 1km resolution; seas,lakes, and rivers considered). Similarly, the daily minimum reflectance data for theland area are made from the CAI pixels located in each of the meshes of 0.125 ×
0.125 degrees dimensions, and identified as a land pixel based on the USGS
land-sea flag data.

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Chapter 6 GOSAT Products(2) Minimum reflectance calculation for a montha. Prepare daily minimum reflectance data for a specified number of days
Prepare the daily minimum reflectance data for a number of days specified. The
files holding the daily minimum reflectance data for the past 30 days including theobservation day are specified.
b. Minimum reflectance calculation
The minimum reflectance data are calculated from the 30 days of daily minimum
reflectance data starting with the band 2 in the same way as in the calculation of thedaily minimum reflectance.
6.6.7 TANSO-CAI Level 3 Global NDVI Processing Algorithm
As the Level 3 global NDVI (Normalized Difference Vegetation Index) data is large
in volume, the product is provided by a unit defined as rectangle covering the 1/36
of the surface of the whole globe. Each rectangle is composed of meshes of 15
seconds in latitude and 15 seconds in longitude. Minimum reflectance data ofbands 2 and band 3 are calculated every day (approximately 15 paths). Thereafter,
minimum reflectance of each mesh is determined using the data accumulated for
15 days; then, the atmospheric correction is applied to the determined minimum
reflectance so as to obtain NDVI.
15 observation days' worthof CAI Level 1B product(1) Separation of rectangle(2) Set location data of meshes(3) Calculate minimum reflectanceand interpolation about meshes(4) Atmospheric correction(5) NDVI calculation

CAI Level 3
NDVI productglobalFig. 6.6-8 Processing flow of TANSO-CAI Level 3 global NDVI

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Chapter 6 GOSAT Products(1) Separation of rectangle
The surface of the globe is divided into 36 rectangles, by 60 degrees longitudinally
starting with 25 degrees West, and by 30 degrees in latitudinally starting with 90
degrees North. A number is given to each of the rectangles as shown in Fig. 6.6-9.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

Fig. 6.6-9 Rectangles and rectangle numbers(2) Set location data of meshes
Each rectangle is composed of meshes having the same angular distance of 15
seconds in both the longitudinal and latitudinal directions. This makes 14,400 ofmeshes in longitude, and 7,200 of meshes in latitude. The mesh placed at thenorthwest corner of a rectangle is aligned with the corner lines of the rectangle, andmeshes of the same size are placed side by side to fill up the rectangle. Fig. 6.6-10
shows a portion of the northwest corner of rectangle 1.

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Fig. 6.6-10 Example of meshes placed at the northwest corner of rectangle 1 (the angulardistance between meshes is 15 seconds)(3) Calculate minimum reflectance, and interpolation about meshesa. Calculate minimum reflectance1) Get land-sea mask covering the central point of a mesh as defined above byreferring to Land-Sea-Mask, which is open to the public by USGS Global Land
1-KM AVHRR Project.
2) Check if each of the meshes is a land area or a sea area. For the sea area, theinvalid value is set as a flag; for the meshes regarded as land, the following
processing is carried out.
3) Find the mesh in which the central location of a pixel of CAI Level 1B band 2 lies.
Then, calculate the reflectance from the radiance of band 2 and band 3 by theequation 6.6-1. As a next step, try to find the minimum reflectance for 15
consecutive days (for five recurrent times.). Provided the mesh is already filled bya reflectance value of band 2, replace it only when the new reflectance value you
are going to set is smaller. With this replacement, reflectance data of band 3, solar
zenith and azimuth angles, satellite zenith and azimuth angles, ozone
concentration17, and the ground atmospheric pressure are also replaced.
The reflectance is obtained as follows, taking into consideration the distance
between the sun and the earth.

17

If the ozone concentration is not actually measured, a value in the climatological data (300 D.U.) is
set.
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rad R 2
ref 
irad cos RθEq. 6.6-1: Distance between the sun and the earth (A.U.): Zenith angle (rad)ref : Reflectancerad : Radiance (W/m2/µm/sr)
irad : Solar irradiance (W/m2/µm)
4) If no data are available from the possible 5 trials for a mesh, the invalid value isset to the mesh.
5) The minimum reflectance values for band 3 are selected for the pixel which has
the same location as band 2.
b. Interpolation for a mesh
Some meshes will remain with no values after the process mentioned above; i.e.
assigning of values of a CAI Level 1B pixel to the mesh in which the center of the
pixel is located. This is caused by the fact that the pixel width of Bands 2 and 3 isapproximately 500m while the longitudinal distance viewed by an angle of 15
seconds at the equator is approximately 460m. As for the rectangle 1st ~ 6th(northto lat. 60deg.), assign the value of CAI Level 1B pixel, which is in any of 24 meshes
next to the blank mesh and has a shortest distance from the mesh as measured
between the centers. As for the rectangle 7th ~ 30th, assign the value of Level 1B
pixel, which is in any of 8 meshes next to the blank mesh and has a shortest
distance from the mesh as measured between the centers. As for the rectangle
31st ~ 36th, invalid value is set.
(4) Atmospheric correction
To save the calculation time, atmospheric correction is conducted at this step foreach of the meshes before the calculation of NDVI.
(5) NDVI calculationa. Calculation method
NDVI for each mesh is calculated by the equation below.

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NDVI 

ref 3  ref 2
ref 3  ref 2

Eq. 6.6-2

NDVI : Normalized Difference Vegetation Index
ref2, ref3 : Minimum reflectance of Bands 2 and 3
b. Invalid value setting
If any of the following conditions are satisfied, the invalid value is set to NDVI.
NDVI is less than - 0.2.
NDVI is greater than 1.
Minimum reflectance of Band 2 or Band 3 is negative.
The sum of minimum reflectance of Bands 2 and 3 is zero.

6.6.8 Level 4 Processing Algorithm
There are two types of Level 4 products, Level 4A and Level 4B. Level 4A productrecords monthly quantities of carbon dioxide absorption and emission in 64
sub-continental-scale regions (each of which has a size of a few thousand
kilometer square) into which the earth is divided. On the other hand, Level 4B
product is three-dimensional carbon dioxide concentration distribution which is
calculated based on the Level 4A products.
The absorption and emission of the region stored in a Level 4A product arecalculated based on the carbon dioxide concentration data of the FTS Level 2
product and of the ground-based observation stations by applying the inverse
model analysis. In the inverse model analysis, absorption and emission for a regionis estimated through the calculation based on Bayes’ theorem. This calculation
adjusts the a priori absorption and emission quantities in such a way that carbon
dioxide concentration distribution in the atmosphere calculated using theatmospheric transport model converges to the observed values at places whereobservation has been conducted. The data thus estimated are provided as a Level
4A product to present absorption and emission.
Furthermore, these absorption and emission data are used as input to theatmospheric transport model to calculate the global three-dimensional
concentration distribution of carbon dioxide. The carbon dioxide distribution data at
typical altitudes ranging from the ground surface to the top of the atmosphere areopen to the public as a Level 4B product.
Since the Level 4 processing algorithm is under adjustment as of December 2010,
further details are not discussed in this handbook.
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6.7

Calibration and Validation

Calibration is performed on Level 1 data, while validation is performed on Level 2
and higher level data. Calibration and validation results are posted up on the NIESGOSAT products distribution website GUIG (GOSAT User Interface Gateway),
explained later (refer to section 7.3.1 (4) for the access to the website).
6.7.1 Calibration
6.7.1.1 Outline of Calibration Plan
Calibration is an evaluation process to clarify the characteristics of the sensors andto confirm that the radiometric and geometric accuracies, spectral and image
qualities, etc. satisfy the conditions given to their accuracy, and is performed on
Level 1 data produced as a standard product. Such evaluations are carried out by
characterization in Pre-Flight Test (PFT), on-orbit calibration after the launch using
calibration mode data, and vicarious calibration using observation data.
Calibration coefficients are updated to improve the accuracy, and the update isreflected in the improvement of the Level 1 processing algorithm.
Listed below are excerpts from the updates on the processing and parameters.
 FTS
 Improved SWIR processing algorithm (optimization of the window function forphase correction, delay-match optimization of the gain M data of band 1)
 Improved TIR processing algorithm (improved the method to selectdeep-space and/or blackbody calibration data, improved the calibration
equations considering the polarization reflectance of the pointing mirror,
appended time interpolated calibration data)
 Refined the spike noise flag
 Optimized the saturation flag (improved the threshold value for ZPD saturation
check, and appended a check for the saturation by low-frequency components)
 Improved low-frequency correction
 CAI
 Changed the coefficients of geometric model used in calculation of geolocation(derivation of line-of-sight vector)
 Vicarious calibration coefficients (have already been applied to the L1B+ andL2 processing)
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6.7.1.2 Calibration Schedule
Evaluation of the calibration data was carried out during the initial functionalverification operation phase (for the three months after the launch), while
evaluation using the observation data was carried out during initial calibration andvalidation phase (three to six months after the launch). Evaluation results werereflected in the Level 1 products; the Level 1 products after the initial calibration
were opened to the public nine months after the launch.
Thereafter, in the normal observation operation, calibration evaluation on andupgrade of the Level 1 products have been carried out regularly, and the datanecessary for calibration are acquired in accordance with the normal operation plan.
Regarding the frequency of the calibration operation, please refer to chapter 3.
6.7.1.3 Calibration Items
Calibration of TANSO-FTS is performed from three points of view: radiometry,geometry, and spectral characteristics. Summaries of the individual calibration
items are described in Table 6.7-1. For the radiance, evaluation method differs fromband to band because SWIR measures the radiance of scattered solar light, while
TIR measures the radiance of radiation temperature.
TANSO-CAI calibration is carried out from another three points of view: radiometry,geometry, and image quality. Summaries of the individual calibration items aredescribed in Table 6.7-2. For the details of calibration operation, please refer to
Chapter 3.
Table 6.7-1 TANSO-FTS calibration items
Evaluation item
Electrical calibration

ObjectRadiometric evaluation
Check the electrical calibration data for each banddetector, and for each gain setting

Solarirradiancecalibration

Check the solar irradiance calibration data for eachband detector

Lunar calibration

Evaluate an absolute amount of radiance from thewhole moon surface by pointing to the moon when the
average radiance of the moon surface takes its
maximum.
Evaluate data characteristics in darkness and stability,
for each band detector, and for each gain setting.
Evaluate temperature dependency
Evaluate the data observing an object with uniform
radiance; for radiance intensity high and low

Output in darkness

Linearity

Absolute radiometricaccuracy (vicarious

Evaluate calibration coefficients and radiometriccalibration

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Data, time, place, etc.
PFT data
L1 calibration data (electricalcalibration)
PFT data
L1 calibration data (solar
irradiance calibration)
PFT data
L1 lunar calibration data
Still image taken by FTS viewmonitoring camera
PFT data
L1 calibration data
(deep-space), etc.
PFT data
L1 observation data
(deep-space, sea, desert, etc.)
PFT data
L1 observation data (calibration

GOSAT / IBUKI Data Users Handbook
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Chapter 6 GOSAT Products
Evaluation item
calibration)

Relative radiancecomparison between
sensors
Absolute geometricaccuracy. (pointing
accuracy)
Orientation stability

Sensor-to-sensor
relative registration

Band-to-bandregistration(for reference)
Instrument
function
Wavelength
calibration

ObjectCalibration using in-situ data (calibration along with aground surface reflectance measuring experiment)
Calibration using global data (calibration using DB,
sensors of other satellites, routine observation, etc.)
Synchronized observation with other sensors (with asensor of equivalent wavelength)
Relative evaluation of 1.6µm band (FTS Band 2 andCAI Band 4)
Geometric evaluation
Evaluate orbit / attitude determination accuracy, long
period stability of alignment accuracy (bias andfluctuation component), and resolver precision ofpointing mechanism.
Evaluate, during the acquisition of an interferogram,alignment variation, precision of image motion
compensation against pointing mechanism, and mirror
settlement accuracy.
Evaluate relative registration between the referential
bands of FTS and CAI when the simultaneous
observations are conducted.
Evaluate relative registration between FTS reference
band and each of the other bands

line

Spectral characteristics evaluation
Evaluate 1.55µm wavelength laser output (band 2)
Evaluate the spectral positions of known atmosphericabsorption lines

Polarization
sensitivity

Evaluate, for each band, observation data of a target
whose polarization characteristics are known.

Wavelength stability

Evaluate sampling jitter, and temperature dependency(especially the relation with the monitoring
temperature of 1.31µm sampling laser)
Evaluate observation data of a uniform object for eachband detector, and for each gain setting
Evaluate temperature dependency.

SNR

Data, time, place, etc.
site)
Calibration experiment data
Reflectance DB
Data of other satellites

PFT data
L1 observation data (FTS, CAI)PFT data
L1 observation data
Image taken by FTS
monitoring camera
L1 observation data
Image taken by FTS
monitoring camera

view

view

PFT data
L1 observation data (FTS, CAI)
Image taken by FTS viewmonitoring camera
PFT data

PFT data
L1 calibration data
PFT data
L1 calibration data
L1 observation data
PFT data
L1 calibration data (solar
irradiance calibration)
PFT data
L1 calibration data
L1 observation data
PFT data
L1 observation data (desert,
etc.)

Table 6.7-2 TANSO-CAI calibration items
Evaluation item
Electrical calibration

Lunar calibration

OffsetLinearity

Absolute radiometricaccuracy (vicarious
calibration)

ObjectRadiometric evaluation
Check electrical calibration data for each banddetector, and for each gain setting
Evaluate an absolute amount of radiance from thewhole moon surface by pointing to the moon when the
average radiance of the moon surface takes its
maximum.
Evaluate optical black output characteristics,
characteristics in darkness, and stability for each banddetector, and for each gain setting.
Evaluate temperature dependency.
Evaluate the data observing an object with uniform
radiance; for radiance intensity high and low.
Evaluate calibration coefficients and radiometriccalibration
Vicarious calibration experiment (ground surface
reflectance measurement)

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Data, time, place, etc.
PFT data
L1 calibration data (electricalcalibration)
PFT data
L1 lunar calibration data

PFT data
L1 calibration data (nighttime)
L1 observation data (band 4
optically black element)
PFT data
L1 observation data (nighttime,sea, desert, etc.)
PFT data
L1 observation data
Experiment data
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Evaluation item

Relative
radiancecomparison between
sensors
Absolute geometricaccuracy.
(pointingaccuracy)
Band-to-band relative
registration
Sensor-to-sensor
relative registration

Sensitivity calibration
among pixels
MTF (for reference)

SNR

ObjectCalibration using global observations and DBs (use
AERONET, SKYNET, and reflectance DB)
Synchronized observation with other sensors (with asensor of equivalent wavelength)
Evaluate relative radiance of 1.6µm band (CAI band 4
and FTS band 2)
Geometric evaluation
Evaluate orbit / attitude determination accuracy, long
period stability of alignment accuracy (bias andfluctuation component).
Evaluate relative registration between CAI reference
band and each of the other bands
Evaluate relative registration between the referential
bands of CAI and FTS when the simultaneous
observations are conducted.
Image quality evaluation
Remove stripe noise

Evaluate the modulation transfer function about theimage after geometric correction for each banddetector, and for each gain setting• Line image distribution function (edge spectrum)• Point image distribution function (point spectrum)
Evaluate observation data of a uniform object for eachband detector, and for each gain setting
Evaluate temperature dependency.

Data, time, place, etc.

PFT data
L1 observation data (CAI, FTS)

PFT data
L1 observation data

PFT data
L1 observation data
PFT data
L1 observation data (CAI, FTS)
Image taken by FTS viewmonitoring camera
PFT data
L1 observation data (desert,
etc.)
PFT data
L1 observation data (coastline,
island, etc.)

PFT data
L1 observation data (desert,
etc.)

6.7.2 Validation
6.7.2.1 Summary of Validation Plan
“Validation” for GOSAT products is to evaluate uncertainty (bias, variation, etc.) in
the Level 2 products by referring to data more reliable and acquired independentlyof the GOSAT products. The validation is carried out using the data acquired byground observation, air-borne observation, and so on. The concept of validation is
illustrated in Fig. 6.7-1.
Regarding the validation of Level 3 and Level 4 products, confirmation of thecalculation process and comparison with other data are carried out.

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Fig. 6.7-1 Schematic diagram of GOSAT products validation

While the validation is intended for the quality evaluation of GOSAT products, it also
help evaluate the validity of data processing algorithm. If something uncertain were
found not negligible, the causes are clarified through investigation to improve thealgorithm and the like as necessary.
Considering that the Level 3 and Level 4 products shall be estimated using theLevel 2 products, adopted models, and so forth, the evaluation of Level 2 products
has vital importance. Accordingly, priority is given to validation activities in the order
as follows.
(1) Level 2 SWIR CO2 column amount, and Level 2 SWIR CH4 column amount(2) Level 2 TIR CO2 profile, and Level 2 TIR CH4 profile(3) Level 3 SWIR global CO2 distribution, and Level 3 SWIR global CH4 distribution(4) Level 4A global CO2 flux(5) Level 4B global CO2 distribution
For validation, it is preferable to use a variety of observation data, which areroutinely acquired across the world. Furthermore, a plurality of specific observation
points are selected to organize a super-site (a site installed with observationequipment necessary for validation, and focused on the continual observations) for
the validation. In addition, campaign observations are carried out including an
air-borne observation under various meteorological conditions.
The data to be validated are those which shall be obtained under the following

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geographical and meteorological conditions. Note that locations covered with thickclouds are not in the scope of validation.
Land area with clear sky
Sea area with clear sky (sunglint observation)
Land area with thin cirrus clouds and aerosols
Sea area with thin cirrus clouds and aerosols (sunglint observation)

The validation results on the processing of version V01.xx are posted on GUIG; soplease refer to the website as desired.
6.7.2.2 Observation Experiments for Algorithm Validation
The processing algorithm to calculate the FTS Level 2 CO2 column amount isvalidated through experiments simulating the satellite observation. Suchexperiments are conducted by observing the sunlight reflection from the earth
surface with a Fourier transform spectrometer (similar to the sensor on board thesatellite) installed at a high-elevation ground point or on board an airplane. Brief
explanations follow about the experiments.
(1) Observation at a high elevation on the groundAn experiment is carried out using a Fourier transform spectrometer (hereinafter
called the spectrometer) which is similar to TANSO-FTS; the spectrometer is set atplaces including a mountain top. In order to validate the CO2 concentration
calculated from the observed results of the spectrometer, an air plane equippedwith a CO2 concentration meter is flied gradually increasing its altitude to measure
the CO2 concentration directly. Then the measured data are compared with thedata derived from the spectrometer.
The experiments carried out in the year of 2005 and 2006 near the top of Mt.
Tsukuba (800m) have demonstrated that the CO2 column amount, in theatmospheric layers with an altitude of 3km or lower, is well observed by thespectrometer with an accuracy of approximately 1%.
(2) Air-borne observation
The spectrometer and a CO2 concentration meter are installed on board an airplanethat flies in the sky at a high altitude, and the data observed by the spectrometerand the data measured by the CO2 concentration meter are compared so as tovalidate the processing algorithm. This method of validation has an advantage
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compared to the fixed point observation done at a high-elevation ground point
because the observation from an airplane will be conducted, similar to the case of asatellite, with a downward view, although the vibration of aircraft remains as aproblem.
(3) Campaign observation
Synchronized to an observation from the satellite, CO2 column amount iscalculated with high accuracy from the CO2 concentration measured directly by anairplane able to reach a high altitude; then evaluation is done to see if there may
exist any secular change with the precision of instruments. Aerosol, which acts as
an error factor, is also measured directly.
The CO2 concentration above the altitude an aircraft can reach varies with thealtitude of the tropopause. Therefore, it is essential to know the altitude of thetropopause precisely; observation data simultaneously taken by a rawinsonde, theobjective analysis data, etc. are used for this purpose.
Regarding the CO2 concentration near the ground, lower than the altitude anairplane may fly along, the concentration value measured on the ground surface isextrapolated.
6.7.2.3 Validation of TANSO-FTS SWIR Products(1) Validation of CO2 and CH4 column amounts observed by SWIR
The instrument to be used in the observations for the validation of CO2 and CH4column amounts must have an accuracy of approximately 1% or better, with nobiases; and the instrument must be the one developed based on the fully
established techniques to present highly reliable quality of data. As a means toobserve a column amount in a straight-forward way, the absorption method thatmakes use of direct sunlight as a light source is the best method, and a highresolution FTS, installed on the ground, is the most appropriate instrument in themeasuring instruments available at present. The FTS will complete an observation
anytime in about 10 minutes as long as direct beams of sunlight are kept comings.
The data collection policy for the validation data is as follows.
 Install instruments (high-resolution FTS, lidar, and sky radiometer) for
observation at a plurality of specific observation points to perform observations
intensively at these super-sites.
 For the validation of data observed outside the support of super-sites, campaign
observations including aircraft may effectively cover the ground areas having
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rough terrain and/or under bad meteorological conditions.
 To cover the whole globe observed by GOSAT, the observation data routinely
acquired are utilized, such as data taken by an existing high-resolution FTS
installed on the ground, air-borne observation data, and ground observation data(from WDCGG (World Data Center for Greenhouse Gases) of WMO (World
Meteorological Organization)).
 On the sea, the column amount is obtained from a sunglint observation. As theconcentration variation is rather small on the sea compared to the land, the dataof a land validation site in coastal areas can be used with wind direction
considered. In addition, observation data acquired on islands and by vessels canalso be used for indirect evaluation.
Based on the policies above, validation data are acquired for typical observation
points; while the observation points actually used are selected following the criteria
listed below.


LatitudeAmount of water vapor
AlbedoAerosols: low , middle , high: large, small: uniform, non-uniform: variant, invariant

At present, 10 observation points equipped with FTS, and another 10 points
observed by an aircraft, are supposed to be enough for validation to satisfy theminimum requirements. However, if a handy instrument for the validation
observation satisfying the validation requirements becomes available, a larger
number of observation points will be selected extensively for validation.
The data acquired for each observation point are evaluated with spatial variations
and temporal fluctuations being considered so as to clarify the uncertainties the
products may have. However, in order to evaluate bias components, roughly threemonths of observations shall be repeated at the place where seasonal variation israther small, while six months of observations are required in general. Quality
assurance is given, based on evaluation thus conducted, to a set of products
grouped by the criteria listed above. If this way of evaluation is considered difficult
to apply, such alternative method may effectively work as a trajectory analysis withtemporal and spatial variations, and/or a validation and analysis based on theregional CO2 transport model.

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Concrete plans for observation and validation data acquisition are as follows.
a. Validation by FTS observation
1) Observation by ground-based high resolution FTS
Conduct routine observations using a ground-based high-resolution FTS at aplurality of observation points in Japan. In the validation, it will be useful to make anevaluation by analyzing the FTS observation data using the processing algorithm of
TANSO-FTS (radiative transfer equation).
2) Utilization of the data of ground-based high resolution FTS networks and the like
The data of ground-based high resolution FTS observation networks shall be used.
The GOSAT operations team of JAXA will arrange the usage of these data throughdirect negotiation with the pertinent data providers, RA-based research cooperation,and so forth.
For the sites to acquire the validation data, considering that the footprint of
TANSO-FTS is rather wide to be 10.5km, a place flat and uniform to that extent of
FTS footprint is preferable. Such places will not involve many factors to cause
errors, and suitable for a validation observation point at the initial stage. Accordingly,
the validation sites are selected based on the following conditions.
 Seasonal variation: start with little variation (the Southern hemisphere), thento larger ones (the Northern hemisphere) Air pollution:
start with little pollution, then toward serious places Land surface: start with simpler shape, then to more complex one
The options are:
 Sunglint
 Snow and ice3) Observation by smaller FTS
Provided mobile observations are necessary, small-sized FTS instruments will be
used after the evaluation of data quality as accuracy, and operational stability.
b. Validation by air-borne / balloon-borne observation
1) Utilization of data from the air-borne observations
A CO2 concentration measuring equipment on board an aircraft observes data
continuously to acquire not only the spatial (horizontal) distribution of CO2

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concentration at very high altitudes, when the aircraft flies horizontally, but also theCO2 concentration profile around the airport as the aircraft ascends from ordescends to the airport..
However, at ascending from an airport, an aircraft moves horizontally about 100km
before it reaches up to the altitude of about 10km where it flies horizontally, and atdescending from the cruising altitude of 10km, it moves 200 to 300km before
landing on the ground; therefore, such spatial difference must be considered tomake the use of the observed data for analysis. Atmospheric tracer transport model
can be applied to the analysis. Furthermore, since the concentration in the lower
atmosphere near an airport tends to rise under the influence of the urban air inmany cases, wind direction must be considered to make the use of data effectively.
Moreover, the fluctuation of the CO2 concentration in the layers above the highest
altitude that an aircraft can reach must also be evaluated. So far, the findings fromballoon-borne observation of the stratosphere have revealed that the fluctuation of
the column amount is within 0.5% when roughly estimated. Further details will be
investigated in the continued studies.
2) Data acquisition by balloons
Balloon-borne observation data, including the past data, must be obtained in order
to ascertain the characteristics of the variation of the CO2 column amount in thelayers above the upper limit of air-borne observation.
c. Miscellanies
1) Observation by small balloons
The CO2 sonde installed on board a small-sized balloon is under development,
which will be used for the validation after evaluating its data quality such asmeasurement accuracy, operational stability, etc., and ensuring that it is practical interms of cost and the like.
2) Observation by compact spectrometer
The Fabry-Perot Etalons based spectrometer is under development, which will be
used for the validation after evaluating its data quality such as measurement
accuracy, operational stability, etc., and ensuring that it is practical in terms of cost
and the like.

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Chapter 6 GOSAT Products(2) Comparison in the global distribution of CO2 and CH4 column amounts based on
SWIR observation
The calculation proceedings of the L3 processing led by statistical algorithm shallbe confirmed. It should be noted that the L3 products do not require dedicatedevaluation means because they are derived from the validated L2 products throughstatistical calculations taking averages spatially and temporally.
(3) Comparison of CO2 flux
A Level 4A product presents estimated monthly average of CO2 flux for a region as
defined by dividing the whole surface of the globe into 64 regions.
The data observed by ships are useful to compare with the data presented by Level
4A products because the flux is supposed to be nearly uniform on the sea about an
area of latitude 5°x longitude 5°.
As for the flux on the land, the flux distribution is calculated per mesh of 1°latitude x
1°longitude with a distribution pattern initially assumed for the region mentioned
above. However, it is difficult to use observed values of CO2 flux for the validation of
Level 4A products of the land because observation of CO2 flux can be done only ona limited number of points while the flux varies much depending on a district, andon a location. To cope with the issue thus identified, a scale-up procedure using theland ecosystem model is required. The scale-up procedure has been investigatedin a number of countries including Japan.
(4) Comparison of the global distribution of CO2 concentration
The product to be distributed as a Level 4B product is a monthly average ofthree-dimensional concentration distribution in a mesh of latitude 1° × longitude 1°.
The comparison of a Level 4B product with other observation data is made using a
one-hour value or monthly average value of a latitude 1°× longitude 1° mesh, whichis the base data of the Level 4B products. As the data for comparison, the data
used in the Level 2 validation (column amount acquired by a ground-based FTS or
the like, concentration profile acquired by air-borne observation), the data acquiredby other kinds of ground and marine observations, and so on, are comprehensively
utilized.
(5) Comparison with other satellites
Comparison with other satellites that observe CO2 and CH4 column amounts isuseful for the evaluation of data quality of the GOSAT products. A typical example is
SCIMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric

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CHartgraphY) on board the environment observation satellite Envisat .
6.7.2.4 Validation of Parameters Related to SWIR Observation Error Factors
As parameters to cause errors in SWIR observations, what follows are being
considered.
(1) Aerosols and thin cirrus clouds
In order to evaluate the appropriateness of the Level 2 processing algorithm for
TANSO-FTS (SWIR) data, in addition to the validation of the product data quality,
the parameters related to error factors, namely the optical characteristics ofaerosols (such as optical thickness, wavelength index, and single scattering
albedo), height profiles, etc. are used for the evaluation.
Furthermore, it is necessary to install sky radiometers and lidars at the locations
where ground-based FTS or air-borne observation is carried out. The lidar canmeasure the vertical distribution of aerosols and thin cirrus clouds with an accuracyof approximately 15m, and distinguish sphericity from non-sphericity by checking
the degree of extinction of polarization, thereby identifying the substance as rain
cloud, cirrus cloud, or sand dust. The sky radiometer measures the direct sunlightand the forward scattering in the sky. The measurements can also be used for
determining not only the optical thickness, particle size distribution, and complex
refractive index, but also the primary scattering albedo and phase function. These
data are planned to be used for the validation of TANSO-CAI products.
(2) Ground surface reflectanceThe data acquired by MODIS and ASTER, of the area having homogeneous
ground surface characteristics in particular, shall be used to check the accuracy of
the ground surface reflectance calculated as a result of the SWIR retrieval
operation.
(3) Oxygen column amountThe oxygen column amount, acquired from Band 1 (O2 A-band), shall be validated.
a. Ground atmospheric pressure and rawinsonde data
Observation will be performed, as necessary, to make use of the aerologicalobservation data routinely taken. The rawinsonde data may also be used for thevalidation of other physical quantities.
b. Objective analysis data
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Objective analysis data shall be used for the validation in order to complement the
aerological observation data, which are not provided so uniformly over the globe;
they are rather sparse above the ocean, polar regions, and developing countries.
6.7.2.5 Validation of TANSO-FTS Products
The data acquired for the validation of SWIR CO2 and SWIR CH4 products are also
used for the validation of Level 2 TIR CO2 and Level 2 TIR CH4 products. The
validation will be conducted more effectively when the profiles of temperature,atmospheric pressure, and humidity, and the infrared radiation rate are also
considered. Regarding the nighttime data acquired, they will be utilized as much as
possible.
6.7.2.6 Validation of TANSO-CAI Products
CAI measures such parameters as cloud coverage and aerosol amounts, which willcause errors in the data of FTS products. Before generating an FTS Level 2
product, cloud information on the sight line the sensor observes shall be checked to
see whether or not the observed FTS data are of effective use. This is done byreferring to CAI Level 2 cloud flag products. Accordingly, the validation of the CAI
Level 2 cloud flag product has been performed.
The validation results have clarified that the algorithm, used for the calculation of
the CAI Level 2 cloud flag product, has no serious problem and gives reasonable
cloud coverage in most cases except for the polar regions and sunglint areas; thevalidation is done by comparing visually the cloud flags with the original CAI
images.
Cloud coverage conditions at the FTS footprints can be confirmed by referring to
FTS browse data. The FTS browse data are generated from CAI observation data.
Fig. 6.7-2 shows an example of FTS browse data; the red circle signifies the view
range of FTS, the green arrow shows the direction GOSAT travels, and the orange
arrow shows the direction the sun lies.

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Fig. 6.7-2 Example of browse data

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Chapter 7
7.1

GOSAT Data Product Distribution

Data Storage

NIES GOSAT DHF stores and administers data products of Level 1 or higher for users.
The total data volume for the five years of GOSAT mission is estimated to amount asmuch as 400TB including the data for validation and for reference such as
meteorological ones.
7.2

Data Product Distribution Policy

7.2.1 Data Policy(1) Backgrounda. The GOSAT data will be distributed on the “non-discriminatory” basis as provided
for in the Principles Relating to Remote Sensing of the Earth from Space issued by
the United Nations.
b. The GOSAT data will be processed in a prompt manner with the help from insideand outside Japan and will be provided at large, thereby promoting the use of the
GOSAT data.
c. The GOSAT Data Policy refers to how to utilize the GOSAT data to be obtained
after the launch, with a view to the evolution of research and development into the
future, while maintaining the balance between international cooperation andnational interests.
d. The GOSAT Data Policy takes into consideration the following missions of Japan
Aerospace Exploration Agency (hereinafter referred to as “JAXA”), National
Institute for Environmental Studies (NIES), and Ministry of the Environment ofJapan (MOE) (hereafter collectively called as the “Three Parties”), to the maximum
extent possible.
1) JAXA, as a space agency, promotes the use of the GOSAT data inside andoutside of Japan by providing all GOSAT data users with the data in a substantial
quantity in a prompt manner, for best results of the Project.
2) NIES, as an institute for the sciences, promotes the use of the GOSAT data
especially in scientific fields by distributing reliable data products to the users upon
carefully evaluating the data quality, for best results of the Project.
3) MOE will use the GOSAT data in its environmental administration through thedata use inside and outside of Japan for scientific purposes and consequently theminimizing of uncertainties with respect to global warming, while maintaining thebalance between international cooperation and national interests.

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Chapter 7 GOSAT Data Product Distribution(2) Policies on when to start the distribution
a. The data distribution to all users will start immediately after the completion of thecalibration and validation work.
b. The data will be provided with priority to internal users, research investigators or
research organizations approved by research announcement activities (RA users),
the members of the Science Team, and Alliance Organizations, which arecollaborating in the aspects of sensor development, scientific research, dataprocessing, and necessary data distribution, earlier than the other users, in cases
where such data distribution is necessary for data processing tasks in terms ofcalibration, validation, etc. and where such data distribution contributes to thedevelopment of the GOSAT sensor or the research on utilization of the GOSAT
data.
(3) How to distribute the GOSAT data
Data users shall conclude an arrangement with JAXA or NIES in the forms ofagreement, contract, agreeing to the terms and conditions online, etc. before
receiving data products on line, in principle, in accordance with the stipulations set
forth in Article 14 hereunder.
When a large number of data products are to be provided, there will be a possibility
that JAXA or NIES may provide the data through a private data distributer selectedby JAXA or NIES.
(4) Pricing of GOSAT data productsa. For research purposes in the fields of earth observing system development andEarth science Users will be charged actual expenses necessary for reproduction of
the data, etc. In case of on-line distribution, however, the data will be provided
free of charge.
Incidentally, a limited number of products will be distributed for free for the
purposes of promotion and education that contribute to the activities of the Three
Parties.
b. For purposes other than those that fall under (a) above (commercial purposes)
Users will be charged, in addition to actual expenses necessary for reproduction of
the data, etc., usage fees in accordance with the number of products provided.
(5) Rights associated with the GOSAT data
a. The Three Parties shall own all intellectual property rights including but not limited
to copyrights in relation to all the data they provide.

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b. When a user has generated a higher-level, value-added data product18, the Three
Parties shall not exercise their copyrights, i.e., rights as the copyright holders of theoriginal data, to the derivative data and the user may use the value-added data
based on his/her own copyrights as the developer of the data. However, a certain
payment shall be collected as a license fee or the like for a commercial use of sucha product, as described in (4) b. above.
(6) Terms and conditions concerning the use of the GOSAT data
a. The use of the data for any purpose in opposition to peaceful use is prohibited.
b. The use of the data for any other purpose than the user’s purpose of data use isprohibited.
c. Redistribution of the data to any third party is prohibited. (The data distributors
who have signed a data distribution agreement with JAXA or NIES may redistributethe data to third parties, but the third parties who obtained the GOSAT data fromsuch a data distributor are prohibited to redistribute the data to any third party.)d. Any publication of outcomes obtained in consequence of the use of the data mustbe accompanied by any of the following indications.
 ©JAXA/NIES/MOE Copyright: JAXA/NIES/MOE @Japan Aerospace Exploration Agency / National Institute for Environmental
Studies / Ministry of the Environment
 Copyright: Japan Aerospace Exploration Agency / National Institute forEnvironmental Studies / Ministry of the Environment
Incidentally, the user is also required to indicate that the original data are provided
by JAXA/NIES/MOE, if he or she has generated higher-level, value-added data andwishes to provide a third party with the value-added data or publish them.
e. Use of the GOSAT data and/or higher-level, value-added data under themechanisms of the Kyoto Protocol, namely the Joint Implementation (Article 6
thereof), Clean Development Mechanism (Article 12 thereof), and the International
Emissions Trading (Article 17 thereof), is prohibited without consent of the Three
Parties. Any use for such a purpose may be allowed if the PI obtains an approvalof and concludes a contract with the Three Parties in advance.
f. Users who obtain the GOSAT data for the purpose of earth observing system

18

High-level, value-added products are, of modified products, those that have been modified byapplying high-level data processing and which are irreversible to the original data. High-level dataprocessing here includes data analyses or a combination of satellite data acquired by different missions,image processing based on external information other than the original data, conversion to physicalquantities, and so forth.
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development and geoscience research are required to report on or publish theirresearch results. In a case where a user wishes to publish his/her outcomes fromthe use of the data from three (3) to nine (9) months after the launch, he or she isrequired to send a copy of the outcomes to the Three Parties.
g. The Three Parties shall not be liable for any missing data, degradation of data
quality, delay in data delivery, or any other situation in which the data cannot beprovided, as a result of problems that occur to the spacecraft or the groundfacilities.
(7) Handling of the personal information
JAXA and NIES shall not exchange the personal information of their users witheach other. If necessary, JAXA or NIES will inform the other of statisticalinformation on the types of users and products with regard to the data provided.
7.2.2 User Category
Table 7.2-1 shows the categories of GOSAT data user.
Table 7.2-1

User Categories

User Category

Description

Project Staff (PS)

Researchers, scientists, staff members, etc. who belong to
the GOSAT Project implementation body (Three Parties) andengage in the GOSAT Project or those who belong to otherorganizations but engage in the GOSAT Project ascontractors to the Three Parties.

RA Investigator (RA)PI and CI19 approved and registered by the Three Parties.

RA* Investigator (RA*)

An RA Investigator who is engaged in a research theme in
the algorithm or calibration/validation fields and is approved
and registered by the Three Parties.

Science Team
Member (ST)A member of the GOSAT Science Team organized by theThree Parties.
(Includes leaders and sub-leaders of working groups.)

19

PI stands for Principal Investigator representing a research theme approved by the Three Parties asa result of the RA selection. CI stands for Co-investigator participating in a research theme approved by
the Three Parties as a result of the RA selection.
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User Category

Description

Science Team
Member* (ST*)

A member of the GOSAT Science Team who is engaged in a
research theme in the algorithm or calibration/validation
fields and is approved and registered by the Three Parties.

Alliance
Organizations1(sensor development,
research, dataprocessing, provisionof necessary data)(AO1)

An organization which has signed a cooperative agreementwith the Three Parties concerning the collaboration in the
aspect of sensor development, research, and dataprocessing or provision of data necessary for GOSAT dataprocessing.
Note that an investigator20, contracted by an AO1 solely forthe purpose of carrying out the above-mentioned activities
and recognized by the Three Parties as such, is regarded asa member of the AO1.

Alliance
Organizations1*(research on
algorithms, calibrationand validation) (AO1*)Of AO1s, an organization which has signed a cooperative
agreement with the Three Parties for the collaboration in the
aspect of research on algorithm, calibration, or validation.

Alliance
Organizations2(data distribution)(AO2)

An organization which has signed a cooperative agreementwith the Three Parties for the collaboration in the aspect of
distribution of GOSAT data.

General User (GU)All data users other than the above-defined users.

Product types available for users depend upon the category.
section 6.2 for details.

Please refer to7.2.3 Processing Version of a Product
Processing algorithm is modified based on calibration and/or verification results.
Any modification accompanies the version change of GOSAT product processor
and/or processing parameter. Major or minor version is changed depending on thekind and scale of changes in the processor algorithm.
GUIG, a graphical web interface for GOSAT product distribution explained later insection 7.3, provides information about "Difference of the Standard Product byversion" and "Relationship between obs. period and version". There may exist
20

An investigator here may include a user of higher-level data processed by an AO1.
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products of different versions for a same day because data of the past are
reprocessed in a batch by a processor of a new version. Therefore GUIG users are
expected to have this in mind when he/she specifies a processing version in the
search of GOSAT data.
GOSAT products have a file name as defined to include the processing version to
distinguish themselves. Refer to section 6.3 for the details of file name definition.
The sections to follow describe the versions of standard products being available
for general users.
7.2.3.1 Versions of TANSO-FTS Level 1B products
The version for TANSO-FTS Level 1B product is defined as follows.
[ AAAPPP ]AAA : Algorithm version
PPP : Parameter Version
The first digit of AAA or PPP stands for major version, while the second and thethird digits represent minor version.
7.2.3.2 Versions of TANSO-CAI Level 1B, 1B+, and higher level products
The version for TANSO-CAI Level 1B, 1B+, and higher level product is defined asfollows.
[ VMM.NN ]V: FixedMM : Major version
NN : Minor version
7.2.4 Calibration stages and validation stages
Standard products are provided at different stages in accordance with the progressof calibration, validation and comparison. There are four calibration stages for Level
1 standard products, four validation stages for Level 2, and three validation stages
for Level 3 standard products. Each stage of calibration and validation is defined inTable 7.2-2 through Table 7.2-4, respectively. (As for Level 4 products, stages havebeen defined yet.) As for the Research and Internal products, there is no suchstage to be defined.

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Table 7.2-2

Definitions of the calibration stages for Level 1 standard products

Calibration stage

Definition

Unchecked (U)Products generated
observation data.

Preliminarily
checked(P)Products visually checked and taken as reliable.

Calibrated (Ca)

Products made after the initial sensor calibration
activity and taken as reasonable.

Confirmed (C)Calibrated products having been used by a limited
number of users for a certain period of time and the
problems reported by the users already fixed, if any.

Table 7.2-3

bysimplyprocessing

theDefinitions of the validation stages for Level 2 standard products

Validation stage

Definition

Unchecked (U)Products simply made from Level 1.

Preliminarily
Validated (P)Products made from Level 1 and taken as reliable
after a visual check.

Validated (V)Products taken as reasonable through the comparison
with such verification data as the ones observed on
the ground.

Confirmed (C)Validated products having been used by a limited
number of users for a certain period of time and the
problems reported by the users already fixed, if any.

Table 7.2-4

Definitions of the validation stages for Level 3 standard products

Validation stage

Definition

Unchecked (U)Products generated by simply processing Level 1 data
or Level 2 data.

Evaluated (E)Products regarded reliable as made by processing
Level 1 or Level 2 data.

Confirmed (C)Evaluated products having been used by a limited
number of users for a certain period of time with noproblems reported.

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7.2.5 Purpose of data use
The purposes of using the GOSAT data are categorized as follows:(1) Development of Earth observing systems and Earth science researches(non-commercial use) including:a. Technical development
Evaluation of the spacecraft and sensors to help develop the Earth observation
technology, enhancement of analysis techniques, and contribution to
next-generation Earth observing satellites and ground systems.
b. Research on and demonstration of exploitation of the data
Research on and demonstration of exploitation of the data in the Earthenvironmental studies.
c. Research on Earth science, etc.
Research which will contribute to the development of Earth science and to thesolution to global environmental issues, by clarifying Earth environment changemechanisms, etc.
d. Other purposes that are relevant to the activities of JAXA, NIES, and MOE
Use of the data contributing to the activities of the Three Parties, such as public
relations and educational activity for the spread and enlightenment of the schemesof Three Parties.
(2) Other purposes than those described in item (1) above (commercial use)
7.3

How to search and get GOSAT data products

Researchers whose research subject is officially adopted, researchers of Alliance
Organizations, and general users will order GOSAT data via GUIG. Explanations
below are for general users.
GUIG is served from the top page of “GOSAT Project” (see Fig. 7.3-1). “GOSAT
Project” also provides up-to-date information about GOSAT, Technical Information,
and Project Results. The URL is shown below.
GOSAT project

http://www.gosat.nies.go.jp/index_e.html

By clicking the portion circled red as shown in Fig. 7.3-1, you are introduced to
GUIG (see Fig. 7.3-2).
You can search GOSAT data and order them from GUIG. You may get suchtechnical information as GOSAT product specifications as well.

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One click leads
you to GUIG.

Fig. 7.3-1 Website of GOSAT Project

Fig. 7.3-2 GUIG top page

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7.3.1 GUIG Functional Summary(1) Managing user information
Let users register or change their information. User password may be reissued.
These services are made on the user authentication window as shown in Fig. 7.3-3.
(2) Searching and ordering GOSAT data products
Let users specify conditions to search products from the GOSAT database. Users
may order any of the products thus searched.
These services are available from the Selection Menu window shown in Fig. 7.3-4
by selecting “L1 and L2 Product Search and Order” or “L3 and L4 Product Searchand Order”.
(3) Downloading the ordered data products
Let users download the data product ordered. This service is available from theSelection Menu window shown in Fig. 7.3-4 by selecting “Product Download”.
(4) Providing Information
Give users such information as GOSAT product specifications, algorithm togenerate the products, and GOSAT path calendar. This service is available fromthe Selection Menu window shown in Fig. 7.3-4 by selecting “Documents” or“Observational Information”. Most of the documents referred to in this document
are available from the site.
Information available as of December, 2010 includes:a. Document (downloadable by GUIG)
1) ATBD (Algorithm Theoretical Basis Documents), Product Format Descriptions,
Product Description, Results of Validation,2) Difference of the Standard Product by version
3) Products list under distribution, Relationship between observational period andversion4) Remarks on monthly FTS SWIR Level 2 Productb. Observational Information (shown on GUIG web pages)
1) Path Calendar
2) Observational Schedule3) SWIR L2 Global Distribution Map

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Guest users are also able to access the documents and information listed above.

Fig. 7.3-3 User authentication window

Fig. 7.3-4 Selection Menu window(Shows up when you via User authentication window shown in Fig. 7.3-3)

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7.3.2 Searching, ordering, and getting GOSAT data products
Fig. 7.3-5 is a flow you have to follow when you get GOSAT data products. In orderto specify the data you order, some search operation must precede. Input search
conditions such as a product type, observation dates of your concern, and an
observed area of interest (AOI) then select from the searched results what you
have to order. You may take another way of searching if you know the observation
IDs of your interest. Just specify the IDs then GUIG will lead you to the next step.
A user who has logged in as a guest may also search the product data althoughhe/she will not be able to order them.

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GOSAT User Interface
User Authentication
Select Menu
Search Conditions

Product Search (Step1)
Specify targets (mandatory)Specify Observation ID

Product Search (Step2)
Specify Product Version

Specify observation period (mandatory)

Product Search (Step3)
Specify AOI (mandatory)
Product Search (Step4)
Additional search conditions (optional)

Search Results

Confirm your orderYour order accepted

E-mail arrives to tell that the
products you ordered areready for delivery.
Get the data
Fig. 7.3-5 Flow to show searching, ordering, and getting of GOSAT data products

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For further information about searches and orders, please refer to the Instruction
Manuals. You can get them by clicking “How to use this website” on the top page of
GUIG. (seeFig. 7.3-6)

Fig. 7.3-6 GUIG Instruction Manual traced from the top page

When the products you ordered are made ready, an E-mail as shown in
Fig. 7.3-7 is automatically sent to you at the address you registered. Please log in
to GUIG once again and download the generated products. (see Fig. 7.3-8)

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ID: test@nies.go.jp
User Group: RA
Thank you for using the GOSAT data downloading service.
The data products you have ordered throughthe GOSAT User Interface Gateway (GUIG)[Order ID: 1004140002] are now downloadable
by following the procedures below.
Importantly, the uploaded data are available only for seven days.
As they will be removed from the site afterwards,
please download the products during the seven-day period.
Procedures:
1. Please log in to GUIG through the link below.
https://data.gosat.nies.go.jp/gateway/gateway/MenuPage/open.do
2. You will be navigated to the "Ordered product list"by clicking "Product Download"on the Selection Menu page.
3. Then, select the data products you want to download from the list.
*******************************************************************************************
This e-mail was generated automatically, so please do not reply to this address.
*******************************************************************************************
Should you have any questions or require further assistance in using GUIG,
please e-mail us at gosat-support@nies.go.jp. If you find this mail unknown, pleasekindly notify us.
GOSAT Support

Fig. 7.3-7 E-mail to inform the product generation completion

Fig. 7.3-8 How to get GOSAT data product

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Regarding the image browser for the product you retrieved, click “Tools” on the top
page of GUIG. (seeFig. 7.3-9)

Fig. 7.3-9 Reference information on tools to display GOSAT data product

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Chapter 8 Point of Contact

Chapter 8
8.1

Point of Contact

About This Handbook

Satellite Applications and Promotion Center,
Space Applications Mission Directorate, Japan Aerospace Exploration Agency
2-1-1, Sengen, Tsukuba-city, Ibaraki 305-8505 Japan
TEL: +81-29-868-4097, FAX: +81-29-868-5987
E-mail: GOSAT@jaxa.jp
8.2

About GOSAT Data

GOSAT Project Office, National Institute for Environmental Studies
16-2, Onogawa, Tsukuba-city, Ibaraki 305-8506 Japan
Acceptance time: 10:00-17:00 (JST), weekends and holidays excluded Whole (General content)
TEL: +81-29-850- 2035, E-mail: gosat-prj1@nies.go.jp
 RA relation
TEL: +81-29-850- 2035, E-mail: gosat-prj1@nies.go.jp
 About GOSAT product and service
TEL: +81-29-850- 2035, E-mail: gosat-support@nies.go.jp

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Appendix

Appendix 1

Acronyms

ADEOS
ADEOS-II
ALOS
AMSR-E::::

ADvanced Earth Observing Satellite
ADvanced Earth Observing Satellite -II
Advanced Land Observing Satellite
Advanced Microwave Scanning Radiometer-EOS

AO1:

Alliance Organization 1

AO1*

:

Alliance Organization 1*

AO2
AOCS
AOI
APID
ASP
ASTER

:
:
:
:
:
:

AT

:

Alliance Organization 2
Attitude & Orbit Control System
Area of Interest
Application Processor ID
Analog Signal Processor
Advanced Spaceborne Thermal Emission and Reflection
radiometer
Along Track

ATBD

:

Algorithm Theoretical Basis Documents

AVHRR

:

Advanced Very High Resolution Radiometer

CAM:

CAMeraCCSDS:

Consultative Committee for Space Data System

CI:

Co Investigator

CT:

Cross Track

DEM:

Digital Elevation Model

DN:

Digital Number

DT:

Direct Transmission

ECMWF

:

European Centre for Medium-range Weather Forecasts

EIS:

EORC Information System

EOC:

Earth Observation Center

EPS:

Electrical Power System

FFT:

Fast Fourier Transform

GCP:

Ground Control Point

GLI:

GLobal Imager

GOSAT

:

Greenhouse gases Observing SATellite

GOSAT MMO:GOSAT Mission Management and Operation system

GPS:

Global Positioning System

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Appendix

GU:

General User

GPV
GUIG
HDF5
HITRAN

:
:
:
:

HK

:

Grid Point ValueGOSAT User Interface Gateway
Hierarchical Data Format Version 5
HIgh resolution TRANsmission
database
House Keeping

IMC:

Image Motion Compensation

InGaAs:Indium Gallium Arsenide

INT:

INTegration hardware

JAXA

:

Japan Aerospace eXploration Agency

KSAT

:

Kongsberg Satellite Services

L

:

Level

LBLRTM:

Line-By-Line Radiative Transfer Model

LLM:

Light Load Mode

MAP:

Maximum A Posteriori

MDHS

:

Mission Data Handling System

MDP:

Mission Data Processor

MODIS

:

MODerate resolution Imaging Spectroradiometer

MOE:

Ministry Of the Environment

MOS-1

:

Marine Observation Satellite-1

NASA

:

the National Aeronautics and Space Administration

NCSA

:

National Center for Supercomputing Application

NDSI

:

Normalized Difference Soil Index

NDVI

:

Normalized Difference Vegetation Index

NetCDF:

Network Common Data Form

NIES

:

National Institute for Envionmental Studies

molecular

NIES GOSAT :
DHF
NOAA
:

NIES GOSAT Data Handing Facility

OMI:

Ozone Monitoring Instrument

PC-MCT:

PhotoConductive -Mercury Cadmium Tellurium

PDL:

PaDdLePFTPI

National Oceanic and Atmospheric Administration

Pre-Flight Test:

Principal Investigator
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AppendixPS:

Project Staff

RA:

Research Announcement, RA InvestigatorRA*:

RA* Investigator

RCS:

Reaction Control Subsystem

SCIAMACHY

:

Si

:

SCanning Imaging Absorption spectroMeter for Atmospheric
CHartographY
Silicone

S-LLM:

Super Light Load Mode

SMACS

:

Spacecraft MAnagement Control System

SNR:

Signal to Noise Ratio

ST:

Science Team member

ST*:

Science Team member *STR:

STRucture

SvalSat:Svalbard Satellite station

SWIR

:

ShortWave InfraRed

TANSO

:

Thermal And Near infrared Sensor for carbon Observation

TANSO-CAI:TANSO-Cloud and Aerosol Imager

TANSO-FTS:

TANSO-Fourier Transform Spectrometer

TCS:

Thermal Control System

TEDA

:

Technical Data Acquisition Equipment

TIR:

Thermal InfraRed

TKSC

:

TsuKuba Space Center

TT&C

:

Tracking Telemetry and Command

TTC-DH:

Telemetry Tracking and Control subsystem-Data Handling

TTC-RF:

Telemetry Tracking and Control subsystem-Radio Frequency

uFDS

:

unified Flight Dynamics System

USGS

:

United States Geological Survey

WDCGG

:

World Data Center for Greenhouse Gases

WMO:

World Meteorological Organization

ZPD:

Zero Path Difference

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Appendix

Appendix 2 Terminology(1) Interferogram
A pattern of light intensity produced by a Fourier interferometer, which splits an
incoming light beam into two paths and makes the two split beams meet again tointerfere each other while the distance for one light beam to travel is graduallychanged to make a difference from the distance for the other light beam.
(2) Sunglint
Sunglint generally means a specular reflection phenomenon seen on the surface ofwater reflecting the sunlight. A suglint point is in a plane defined by the three points,
i.e. the sun, the sensor, and the sunglint point itself, at the location where incident
angle and reflection angle have the same value. Sunglint observations by FTS are
conducted including the neighborhood of the sunglint point wherefrom enoughstrength of reflected light comes in to the sensor.
(3) Sunglint region
Sunglint region is an area geographically defined on the earth’s surface where
sunglint is expected to occur; conventionally, ocean surface is specified as theregion. The definition of such regions are given in the form shown below.
 As a polygon whose vertices are located on the surface of the earth, and theirpositions defined by the geographical latitude and longitude.
 Latitude and longitude are defined based on WGS84.
 Sides of the polygon is defined as a straight line connecting adjacent vertices ona Equidistant Cylindrical map.
(4) Sunglint operation span
A sunglint operation span is a stretch of the spacecraft trajectory wherefrom thesunglint operation is conducted.
Conventionally, nadir of the satellite is supposed to face the ocean when it is in the
span. The definition of such spans are given in the form shown below.
 A pair of argument of latitudes is given to define the places to start and to stop thesunglint observation for each of the 44 passes of revolution. Further, different
spans of observation can be assigned to different observation modes having
different number of scanned points. For instance, five different pairs may be
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prepared for a path1 for each of the different modes of observation (i.e. 1, 3, 5, 7,
and 9 point scans) to define an argument of latitude to start observation and anargument of latitude to stop observation. The values of argument of latitude here
are the ones measured as true argument of latitude.
(5) Operation stages
Operation Stage

Description
Since the establishment of JAXA tracking andcontrol team, until 4 hours after the launch.
Since 4 hours before the launch, until satellite
separation from the vehicle.

Launch Preparation Phase
Launch Phase
InitialOperation
Phase
RegularOperation
Phase

PeriodCritical operation period
On-orbit checkout
operation period
Initial Validation andCalibration Operation
PeriodRegular Operation
PeriodPost Operation Phase

The initial checkout operations are conducted.

for 3 months

The initialconducted.

for 3 months

validation and calibration are

Routine operations are conducted.

for 4.5 years

Operations after regular operation phase.

Start at 5 years after
the launch(6) Mean argument of latitude
A mean argument of latitude (m) is an angle measured from the ascending nodeand taken as a value proportional to the time elapsed since the passing of thenode; described mathematically as follows.
 m = 2 x t/T (rad) m：Mean argument of latitude (rad) t：Elapse time from ascending node (sec) T：Revolution period (sec)Elapse time from ascending
node: t (sec)Satellite

Equatorial
Plane

Ascending
Node
Earth

Period:T (sec)

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Appendix(7) True argument of latitude
A true argument of latitude (f) is an angle measured from the ascending node;described mathematically as follows.
 f = + f f：True argument of latitude (rad) ：Argument of perigee (rad) f：True anomaly (rad)Satellite
Argument of perigeef (rad)(rad)Equatorial Plane

Ascending Node

EarthSatellite orbit

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Appendix

Appendix 3

Bibliography

 Bibliography concerning Specification of GOSAT Products
 TANSO Level 1 Product Description Document (Document No.：MAS-1000067)
 NIES GOSAT Product Format Descriptions(Document No.：NIES-GOSAT-PO-006)
 Greenhouse gases Observing SATellite (GOSAT) Data Policy Bibliography concerning processing algorithm ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD) FOR CO2 AND CH4
COLUMUN AMOUNTS RETRIEVAL FROM GOSAT TANSO-FTS SWIR
(Document No.：NIES-GOSAT-PO-014)
 Algorithm Theoretical Basis Document for GOSAT TANSO-FTS L3(Document No.：NIES-GOSAT-PO-017)
 Algorithm Theoretical Basis Document for GOSAT TANSO-CAI L2 cloud flag
(Document No.：NIES-GOSAT-PO-016)
 Research Announcement Appendix B
GOSAT/TANSO Calibration andValidation Plan and Overview of Processing Algorithms
 Bibliography concerning GOSAT data service
 Instruction manual of the GOSAT User Interface Gateway (GUIG)

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