Foreword
The Fourth Assessment Report issued by the Intergovernmental Panel on Climate Change (IPCC) in2007 states that most of the observed increase in global average temperatures since the mid-20th century is very
likely due to the observed increase in anthropogenic Green House Gas (GHG) concentrations. The drastic
increase in the concentration of GHGs, particularly carbon dioxide (CO 2), caused directly and indirectly by humanactivities, is attributed to the fact that the emission of CO 2 into the atmosphere in the process of the massconsumption of fossil fuel, deforestation, etc., significantly surpasses the absorption by the land ecosystem and theoceans. Thus, it is imperative to balance the emission due to human activities and the absorption by the nature,in order to stabilize the climate for the future.

In the meantime, however, we, humans, have not grasped, to a

sufficient level, the mechanisms of the absorption by land ecosystem and ocean, and the climatological feedbackin the carbon cycle involving atmosphere, land ecosystem and ocean. This lack of understanding comprises a
substantial part of the uncertainty in predicting future climate change.

The clarification of these problems involves not only an ascertainment of the spatial and temporalvariations in the CO2 emission from human activities but also a calculation of the spatial distribution and temporalvariation of CO2 and also methane (CH4), which is the second largest contributor to global warming after CO 2,
and the spatial distribution and temporal variation of the source and sink in land ecosystem and oceans, based onearth observation, and ultimately an attainment of adequate scientific knowledge on the underlying mechanisms.
These efforts to observe GHG concentrations and to analyze the causes of their variations at some locations are,though still limited, in progress. On top of these attempts, it is vital to observe the distributions of CO 2, CH4, andother GHG concentrations, which fluctuate both spatially and temporally, on the global scale, using satellite
platforms, in a continuous and systematic manner, and to elucidate the current issues, with a goal to elevate thereliability of prediction of future climate change and climate system models effective for assessing theconsequences of climate change.

Aiming for fulfilling the above requirements, the Japan Aerospace Exploration Agency (JAXA), theNational Institute for Environmental Studies (NIES) and the Ministry of the Environment (MOE) (hereinafterreferred to as the “Three Parties” collectively) have started the GOSAT (Greenhouse gases Observing SATellite)
Project. The Three Parties shall make the third announcement on an opportunity for research using the dataacquired by the Thermal And Near infrared Sensor for carbon Observation (TANSO) sensor onboard GOSAT on
August 20, 2010.

This third research announcement (hereinafter referred to as RA) is initiated for soliciting proposals on
advanced research using actual data acquired for a year and a half by GOSAT, which was successfully launched
on January 23, 2009. The details of the RA are provided in the following RA documents. Note that the RA
Office is set up inside NIES.

RA Document

GOSAT Research Announcement (main text)
Appendix A

Outlines of GOSAT and TANSO Sensor

Appendix B

GOSAT/TANSO Calibration and Validation Plan and Overview of Processing
Algorithms

Appendix C

Operation Policies of GOSAT and Basic Observation Plan of the TANSO Sensor

Appendix D

Contents of Research Proposal and Application Forms

Appendix E

General Contractual Conditions for the Joint Research on the GOSAT data

Appendix F

User Category, Glossary and Abbreviation List

Schedule for the 3rd RA (Current RA)

Launch of GOSAT
rd

January 23, 2009

Release of the 3 RA

August 20, 2010

Deadline for submission of proposals

October 29, 2010

Notification of the selection results

January 31, 2011

Sign up of the agreement

February 1, 2011 or laterrd

3 PI meeting/workshop

Scheduled sometime between May andAugust, 2011 (TBD)

Submission of interim reports

January 31, 2012

For more information, please contact:

GOSAT Project Office
Center for Global Environmental Research
National Institute for Environmental Studies
16-2 Onogawa, Tsukuba-shi, Ibaraki
305-8506 JapanWeb page: http://www.gosat.nies.go.jp/eng/proposal/proposal.htm
TEL: +81-29-850-2035 FAX: +81-29-850-2219
E-mail: gosat-prj1@nies.go.jp
Acceptance time: Weekday (excluding Japanese national holidays) 10:00-17:00

August, 2010
Japan Aerospace Exploration Agency (JAXA)
National Institute for Environment Studies (NIES)
Ministry of the Environment (MOE)Thermal And Near infrared Sensor for carbon Observation (TANSO)
onboardthe Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

August 2010

Japan Aerospace Exploration Agency (JAXA)
National Institute for Environment Studies (NIES)
Ministry of the Environment (MOE)Japan

GOSAT/TANSO Research Announcement
CONTENTS
1. Introduction ........................................................................................................................1
2. Definitions of the GOSAT/TANSO Research Announcement (RA) ................................3
2.1 GOSAT Project..............................................................................................................3
2.2 Purpose..........................................................................................................................3
2.3 Scope..............................................................................................................................3
2.4 Basic Policies ................................................................................................................4
2.5 Implementing Organization of the GOSAT/TANSO RA ...........................................5
3. Outline of GOSAT and TANSO Sensors ...........................................................................6
3.1 Outline of GOSAT.........................................................................................................6
3.2 Outline of GOSAT/TANSO-FTS ..................................................................................6
3.3 Outline of GOSAT/TANSO-CAI...................................................................................6
4. GOSAT/TANSO Data Policies ...........................................................................................7
5. Data Distribution of GOSAT/TANSO Products and Standards for their Use ............. 11
5.1 List of Products to be Distributed ............................................................................. 11
5.2 Data Format and Distribution Media....................................................................... 11
6. Funding............................................................................................................................ 12
7. Qualifications .................................................................................................................. 13
8. Rights and Obligations of the Principal Investigator (PI) ........................................... 14
8.1 Rights ......................................................................................................................... 14
8.2 Obligations ................................................................................................................. 15
8.2.1 Interim reporting ................................................................................................ 15
8.2.2 Final reporting and termination of the contract .............................................. 15
9. Preparation and Submission of Research Proposals .................................................... 16
9.1 Notes to the preparation of research proposals ...................................................... 16
9.2 Language.................................................................................................................... 16
9.3 Volume........................................................................................................................ 16
9.4 Contents to be included in research proposals and the preparation procedure ... 16
9.5 Submission of research proposals ............................................................................ 16
10. Selection of Research Proposals ................................................................................... 18
10.1 Evaluation and Selection Procedure ...................................................................... 18
10.2 Evaluation Criteria ................................................................................................. 18
10.3 Post-selection Procedure ......................................................................................... 18
11. Cancellation and Postponement of RA ........................................................................ 19
12. Expected Research Topics............................................................................................. 20
12.1 Research Topics conducted or targeted by the GOSAT Project ........................... 20
12.2 Expected Research Topics to be proposed in the RA ............................................ 21
13. Schedule......................................................................................................................... 22
13.1 1st Announcement .................................................................................................... 22
13.2 2nd Announcement ................................................................................................... 22
13.3 3rd Announcement (Current Announcement) .......................................................... 22
14. Contact Information ..................................................................................................... 23iAppendices
Appendix A
Appendix B
Appendix C
Appendix D
Appendix E
Appendix F

Outlines of GOSAT and Overview of TANSO Sensors
GOSAT/TANSO Calibration and Validation Plans and Overview ofProcessing Algorithms
Operation Policies of GOSAT and Basic Observation Plans of the
TANSO Sensors
Contents of Research Proposal and Application Forms
General Contractual Conditions for the Joint Research on the GOSAT
data
User Category, Glossary and Abbreviation Listii

1. Introduction
The Fourth Assessment Report issued by the Intergovernmental Panel on Climate Change (IPCC) in2007 states that most of the observed increase in global average temperatures since themid-20th century is very likely due to the observed increase in anthropogenic Green
House Gas (GHG) concentrations. The drastic increase in the concentration of GHGs,
particularly carbon dioxide (CO2), caused directly and indirectly by human activities, is attributed to
the fact that the emission of CO2 into the atmosphere in the process of the mass consumption offossil fuel, deforestation, etc., significantly surpasses the absorption by the land ecosystem and theoceans. Thus, it is imperative to balance the emission due to human activities and the absorption by
the nature, in order to stabilize the climate for the future. In the meantime, however, we, humans,
have not grasped, to a sufficient level, the mechanisms of the absorption by land ecosystem andocean, and the climatological feedback in the carbon cycle involving atmosphere, land ecosystemand ocean. This lack of understanding comprises a substantial part of the uncertainty in predicting
future climate change.
The clarification of these problems involves not only an ascertainment of the spatial and temporalvariations in the CO2 emission from human activities but also a calculation of the spatial distribution
and temporal variation of CO2 and also methane (CH4), which is the second largest contributor to
global warming after CO2, and the spatial distribution and temporal variation of the source and sinkin land ecosystem and oceans, based on earth observation, and ultimately an attainment of adequate
scientific knowledge on the underlying mechanisms. These efforts to observe GHG concentrations
and to analyze the causes of their variations at some locations are, though still limited, in progress.
On top of these attempts, it is vital to observe the distributions of CO2, CH4, and other GHG
concentrations, which fluctuate both spatially and temporally, on the global scale, using satellite
platforms, in a continuous and systematic manner, and to elucidate the current issues, with a goal toelevate the reliability of prediction of future climate change and climate system models effective forassessing the consequences of climate change.
Under such circumstances, the GOSAT (Greenhouse gases Observing SATellite) Project was
initiated and has been promoted jointly by the Japan Aerospace Exploration Agency (JAXA), theNational Institute for Environmental Studies (NIES) and the Ministry of the Environment (MOE)(hereinafter referred to as the “Three Parties” collectively). The mission of the Project is to increase
the accuracy of the flux (source and sink) estimation of the GHGs on the sub-continental basis (afew thousand kilometers square), thereby to contribute to environmental administration efforts suchas ascertainment of fluxes per region and evaluation of the carbon balance in forests. The Projectwill further contribute, through research on applications of the data acquired by GOSAT, to an
accumulation of scientific knowledge regarding the global distribution of GHG concentrations andits temporal variations as well as the global carbon cycle mechanism and its impact on climatechange, which will assist the prediction of climate change and evaluation of consequences therefrom.
At the same time, the Project aims to maintain and further evolve conventional earth-observing
technologies to develop new methodologies to measure GHGs and enable engineering development
necessary for future earth-observing satellites.
To achieve these goals, JAXA takes charge of developing and launching the satellite with the sensors
on board, calibrating and operating the sensors, acquiring observation data, and processing the1acquired data to Level 1 (spectral) products, whereas NIES undertakes the examination ofrequirements for the sensor specifications, development and operation of the higher-level productprocessing system, development of the data processing algorithms, generation of Level 2 (GHG
concentrations), Level 3 & 4 (global distribution of GHG concentrations, and distribution of carbon
source/sink based on them, etc) products, validation of data quality, and storage and provision of thegenerated data products. Furthermore, the MOE supplements the development of the sensors andbears the responsibility for utilization of the GOSAT data in its environmental administration
through the acquisition of validation data and scientific use of mission data. The Three Parties havebeen and will continue to be vigorously carrying forward the research and development necessary
for fulfilling these tasks with the help and advice from the GOSAT Science Team, which wasestablished and is administered by the Three Parties.
The Research Announcement to be made herein (hereinafter referred to as the “RA”) solicits
proposals for research on the data processing algorithms, calibration, validation, carbon balance
estimation/atmospheric transport models, and scientific use with respect to the GOSAT data from thepublic, on top of the basic research and development topics to be performed by the Three Parties,
with an aim to make the outcomes of the Project more effective. All research teams responding tothis RA whose proposals are selected by the Three Parties based on the results of evaluation by the
RA Selection and Evaluation Committee (hereinafter referred to as the “Committee”) will be granted
a priority in data distribution, the right to make observation requests (within a predetermined scope),
accommodation in obtaining other related data, and so forth. Incidentally, the Committee will consistof the members selected and requested by the Three Parties from among Japanese and non-Japaneseexperts and specialists.
The succeeding chapters in this document describe the contents of the GOSAT Project in detail,including items ranging from the equipment onboard the satellite, overview of data processing
algorithms, calibration and validation plans to data utilization plans. Applicants to this RA are
encouraged to read the contents of this document carefully and make active efforts to write research
proposals.

22. Definitions of the GOSAT/TANSO Research Announcement (RA)
2.1 GOSAT Project
GOSAT carries an observing instrument called Thermal And Near-infrared Sensor for carbon
Observation (TANSO). The GOSAT/TANSO is composed of two sensors called Fourier Transform
Spectrometer (FTS), which measures greenhouse gases (GHGs), and Cloud and Aerosol Imager(CAI), which collects information on cloud and aerosol.
The primary purpose of GOSAT is to measure the global distribution of GHG concentrations and its
temporal variation and to increase the accuracy of the flux estimation of GHGs on the
sub-continental scale, thereby contributing to the sustention and development of systemized
observation in accordance with the Kyoto Protocol, while at the same time facilitating theenvironmental administration efforts, including ascertainment of the flux per region and evaluationof the carbon balance in forests during the first period (2008-2012) as specified by the Protocol. In
the meantime, the Project is intended to develop GHGs-measurement technologies and othertechnologies necessary for future earth-observing satellites, by standing on and further evolving theexisting earth-observing technologies.
2.2 Purpose
The purpose of the RA is to open to public an opportunity for researching on the data processing
algorithms, calibration, validation, carbon balance estimation/atmospheric transport models, andscientific use of the GOSAT data, in addition to the basic research and development topics to be
performed by the Three Parties, with a goal to make more use of the outcomes from the Project. The
research topics selected by the Committee and adopted by the Three Parties will be subject topreferential data distribution, the right to make observation requests (of reasonable amount), andaccommodations in obtaining other related data, etc.
The implementation of the RA is expected to bring about additional researches by other parties than
JAXA and NIES, which will supplement the research to be conducted in accordance with thecalibration and validation plans of the Project, facilitation of studies on the processing algorithms,
carbon balance estimation/atmospheric transport models, and utilization of the GOSAT/TANSO data,
objective evaluation of the research concerning the effectiveness and usefulness of the data,
expansion of opportunities for researchers and scientists inside and outside Japan to access the
GOSAT data, and so on.
2.3 Scope
The GOSAT/TANSO RA is open to all countries across the world, not limited to Japan. All
individual researchers, educational organizations, research institutes, and governmental bodies who
are willing to use the GOSAT data for non-profit and peaceful purposes are entitled to participate in
the RA. In this manner, private companies are also qualified for submitting research proposals aslong as their themes are for non-profit and peaceful purposes.
Investigators involved in carrying out the research themes selected in the RA are called “RA3

Investigators” for the purpose of the RA. A team of RA Investigators working on a research theme
will elect one principal investigator (hereinafter referred to as “PI”) who will represent the team.
The PI will act as the contact person with the Three Parties in carrying out the research on theselected theme, such as communication, data transfer, submission of necessary documents, etc. In
principle the research organization (hereinafter referred to as “RO”) to which the PI belongs shallalso be responsible for signing the joint research contract with the Three Parties, as provided inAppendix E hereto, when selected for the RA. The signer may be the PI himself/herself only in caseif the PI does not belong to any organization.
Incidentally, the research teams selected for the RA may be requested to conclude a separate contract
in order to strengthen the cooperative relationship between the team and the Three Parties.
2.4 Basic Policies
The GOSAT/TANSO RA will be conducted based on the following policies:
1) The Three Parties will establish a committee to select the research proposals and to follow theirresults. This committee will be referred to as “the Committee” hereinafter. Research proposals
submitted in response to the RA will be evaluated by the Committee, and they will be selected by
the Three Parties based on the evaluation results by the Committee. The Committee shall be
responsible for not only evaluating the submitted proposals but also, as shown in Chapter 8.2.1
hereof, evaluating the progress and adequacy of the adopted researches.
2) The research period shall be the operational period of GOSAT/TANSO plus the operational periodof its ground system — five years after the launch, in principle (until January 22, 2014) —. Any
long-term research to be conducted, which goes beyond one year, will be subject to interim
reporting to the Three Parties, basically once a year.
3) The GOSAT/TANSO RA took place in April to July 2008 for the first time and in April to June2009 for the second time, whereas the third RA, this time, is in action from August to October2010. Next RA opportunities will be determined based on the status of applications to these threeRAs.
4) PI of a research team may make multiple research proposals on different themes during themission period. (In other words, a single person may submit proposals on more than one research
themes to be carried out under this RA scheme.)
5) The PI may submit observational requests to the extent determined by the Committee per research
theme.
6) The PI may request for distribution of GOSAT data free of charge to the extent designated by theCommittee per research theme.
7) Applications for the GOSAT/TANSO RA and research plans shall be submitted via the Websites
run by the RA Office or by e-mail, in principle; those documents sent by conventional mail orother means may also be accepted according to the situation.
8) Research themes to be conducted under the RA scheme were selected in August 2008 for the first
RA and in July and August 2009 for the second RA. The third RA selection will be evaluated in
January 2011. Likewise, in the future, the selection will be administered at each time the RA ismade.
9) Proposal titles and names of PIs and their ROs will be disclosed on the Websites run by the RA
Office when their research themes are selected for the RA.
10) Outcomes of the GOSAT/TANSO RA must, in general, be disclosed to the public in the form of4

papers published on academic journals and other media and at the same time be reported at the
research result reporting meetings held by the Three Parties.
11) The Three Parties do not provide any financial assistance to PIs, in principle, under the RA
scheme.
12) RO (or PI in case if he/she does not belong to any organization) must conclude the joint
research contract, as provided in Appendix E, with the Three Parties prior to the start of research
activities on the selected research theme.
2.5 Implementing Organization of the GOSAT/TANSO RA
The Three Parties have set up an office in charge of the RA within the NIES GOSAT Project office,for firm and efficient implementation of the GOSAT/TANSO RA. The RA Office carries out thefollowing tasks in accordance with the basic policies set forth by the Three Parties.
1) Prepares the RA procedures and release them to the world.
2) Carries out administrative works as the secretariat of the Committee.
3) Accepts proposals submitted in response to the RA and requests the Committee for due evaluation
for selecting research themes.
4) Notifies the selection results to all PIs who submitted research proposals and assists those selected
PIs in signing the joint research contract (see Appendix E) necessary for carrying out the
research.
5) Receives the outputs of the research from the PIs by the deadline designated in the contract anddistributes them among the Three Parties.
6) Assists in organizing the research result report meetings to be held by the Three Parties.
7) Notifies the completion of the joint research agreement to the RO (or the PI in case if he/she does
not belong to any organization) in writing when the Committee confirms and accepts the
Research Report submitted by the PI in accordance with section 8.2.2 of this Research
Announcement.
See Chapter 14 hereof for the contact information of the RA Office.

5

3. Outline of GOSAT and TANSO Sensors
3.1 Outline of GOSAT
An outline of GOSAT is provided in Chapter A.1 of Appendix A hereto.
3.2 Outline of GOSAT/TANSO-FTS
GOSAT/TANSO-FTS is one of the two sensors onboard GOSAT and is a Fourier interferometer
which observes GHGs such as CO2 and CH4. An outline of TANSO-FTS is provided in Chapter A.2of Appendix A hereto.
3.3 Outline of GOSAT/TANSO-CAIGOSAT/TANSO-CAI is one of the two sensors onboard GOSAT and is an imager which collects
cloud and aerosol information. An outline of TANSO-CAI is provided in Chapter A.3 of Appendix A
hereto.

6

4. GOSAT/TANSO Data Policies
Each PI is entitled to obtain the GOSAT data necessary for his/her respective research activities (upto a limited number) without any cost, from the Three Parties on the condition that he or she agrees
to the following provisions:
1)
2)
3)
4)
5)

The use of the data for any purpose in opposition to peaceful use is prohibited.
The use of the data for any other purpose than his/her research purpose is prohibited.
Redistribution of the data to any third party is prohibited.
The data obtained can only be distributed among the PI and RA Investigators.
Any publication of the outcomes obtained in consequence of the use of the data must be
accompanied by an indication of the data source.
6) The use of the data under the mechanisms of the Kyoto Protocol, namely the Joint
Implementation (Article 6 thereof), Clean Development Mechanism (Article 12 thereof), and theInternational Emission Trading (Article 17 thereof), without consent of the Three Parties is
prohibited, provided that any use for such a purpose may be allowed if the PI obtains anapproval of and concludes a contract with the Three Parties in advance.
The data to be distributed will be subject to the operational status of the satellite and the physicalrestrictions of the sensors. The invisible areas by FTS and CAI are explained in Chapters A.2 andA.3 of Appendix A hereto, respectively.
The Three Parties shall not be liable for any missing data, degradation of data quality, delay in datadelivery, or any other situation in which the data cannot be provided, as a result of problems that
occurs to the spacecraft or the ground facilities.
The ownership of the original data acquired with GOSAT/TANSO belongs to the Three Parties.
The “original data” here means the products provided by JAXA or NIES and should be distinguishedfrom the data obtained by RA Investigators as an outcome from their research activities.
RA Investigators are entitled to access the GOSAT data prior to the release of the data to the public.
They are also entitled to use the data planned to be acquired in accordance with the Basic
Observation Plan of the TANSO sensor attached hereto as Appendix C.
Although the RA Investigators and the Three Parties shall confer with respect to the content of new
observation requests after the selection, the RA Investigators drawing up research plans in responseto the RA should carefully examine the “Operation Policies of GOSAT and Basic Observation Planof the TANSO Sensor”, as provided in Appendix C, and plan acquisition and distribution requests for
the GOSAT data, with due consideration given to the constraints of each sensor in its observation(more concretely, invisible areas, observation mode switching, etc.)
RA Investigators are entitled to access the following data products:
1) Standard products (See Table 1.)
The “standard” products mean the calibrated Level 1B products, and all Level 2 or higher levelproducts generated from the validated L1B products and are released to general users. There are four7

calibration stages for L1B and four validation stages for L2 products, and they are explained in Table
2 and 3, respectively. All L1 and L2 products are released to general users at the “Confirmed” stage.
2) L2 Research products (See Table 1.)
The research products are the data products intended to be used in the research fields of calibration,
validation, data processing algorithms, data application, and other scientific researches. Theirvalidation stage goes up until (V) “Validated” and no further. They are available to RA Investigators,
to an extent necessary for their respective researches, at suitable timing.
3) L3 Products
L3 products are the global-scale products generated from L2 products. Validation stages are notapplied to L3 products, but they are released to RA Investigators prior to public for preliminary
evaluation.
4) JAXA’s satellite data other than the GOSAT data
Those selected PIs who are willing to use the satellite data owned by JAXA, other than the GOSAT
data, may so request to JAXA.

8

Table 1. List of GOSAT/TANSO data products
Processing

Sensor /

Level

Band

Product Designation

Product

Product Provision

Data

Category

Unit

FormatFTS

FTS L1A data

Internal (*)

per FTS scene

CAI

CAI L1A data

Internal (*)

per CAI scene

FTS

FTS L1B data

Standard

per FTS scene

CAI

CAI L1B data

Standard

CAI

CAI L1B+ data

Standard

L2 CO2 column amount (SWIR)

Standard

L2 CH4 column amount (SWIR)

Standard

L2 H2O column amount (SWIR)

Research

L2 CO2 profile (TIR)Standard

L1A

L1B
per CAI flame
L1B+

FTS SWIRL2

FTS TIRCAI

L2 CH4 profile (TIR) (*2)

Standard

can be selected

L2 CO2 column amount (TIR)

Research(on-demand)

L2 CH4 column amount (TIR) (*2)

Research

L2 temperature profile(TIR) (*2)

Research

L2 H2O profile (TIR) (*2)

Research

L2 H2O column amount (TIR) (*2)

Research

HDF5

L2 cloud flag

Standard

L2 cloud property

Research

L2 aerosol property

Research

L3 global CO2 distribution (SWIR)

Standard

L3 global CH4 distribution (SWIR)

Standard

Global

L3 global CO2 distribution (TIR)Standard(per month)

L3 global CH4 distribution (TIR) (*2)

Standard

L3 global radiance distribution (all pixels)

Standard

Global

L3 global reflectance distribution (clear sky)Standard(per 3 days)

L3 global cloud property

Research

L3 global aerosol property

Research

per CAI flame

FTS SWIRFTS TIR

L3

CAI

Global (per month)
30°x 60°
L3 global NDVIStandard(lat. X lon.)

L4A global CO2 flux

Standard

Global (64 regions)

L4A global CH4 flux

Research(per year)

L4A global CO2 flux

Research

Global (64 regions

L4A global CH4 flux

Research

L4B global CO2 distribution

Standard(per 15 days)
Text
L4A

-

and per 1°)(per month)GlobalNetCDF

2.5°x 2.5°grid
L4B

L4B global CH4 distribution

Research(lat. X lon.)(per month)(*) Internal products are available only to investigators and organizations which are in cooperation
with the GOSAT Project in the field of calibration.
(*2) These products are delayed in delivery.

9

Table 2. Definitions of the calibration stages for L1 standard products
Calibration
Stage

Definition

Unchecked (U)Data products generated by simply processing the observational data.

Preliminarily
checked (P)Data products visually checked and judged as reliable.

Calibrated (Ca)

Data products of which their appropriateness are verified after thesensors being calibrated.

Confirmed (C)Calibrated data products for which no problem was reported after being
used for a certain period of time by a limited community of users.

Table 3. Definitions of the validation stages for L2 standard products
Validation Stage

Definition

Unchecked (U)Data products generated by simply processing the observational data.

Preliminarily
validated (P)Data products visually checked and judged as reliable.

Validated (V)Data products which were compared with other observational dataacquired by higher-accuracy methods (e.g., ground-based observation)and judged as sufficiently accurate accordingly.

Confirmed (C)Validated data products for which no problem was reported after being
used for a certain period of time by a limited community of users.

(Above definitions of the validation stages are also applied when major changes in theprocessing algorithms and in the product version are implemented.)10

5. Data Distribution of GOSAT/TANSO Products and Standards for theirUse
5.1 List of Products to be Distributed
Table 1 outlines the GOSAT/TANSO products, by product type, for which RA Investigators can
submit data distribution requests.
5.2 Data Format and Distribution Media
1) Data format
Of the GOSAT data, L1 to L3 products will be provided in the following format, which is commonlyused for distributing earth-observing sensor data.
- HDF 5 (Hierarchical Data Format 5)Higher-level data (L4 products) will be provided in the following format, considering that it is usedby TRANSCOM.
- NetCDF- Text2) Distribution media
The GOSAT data will be distributed online via the Internet, in general.

116. Funding
The Three Parties do not provide any kind of financial assistance to PIs, in principle.

12

7. Qualifications
As long as the research proposals are designed for peaceful and non-profit purposes, any research
institute, educational organization, governmental body, private company or individual researcher
who belongs or does not belong to any sort of organization, in any country, can apply for the RA,
regardless of nationality, group or individual.

13

8. Rights and Obligations of the Principal Investigator (PI)As explained in Chapter 2.3 above, the PI (one person) shall be responsible for communicating with
the Three Parties when applying for the RA and also researching on the research theme, if adopted.
Furthermore, as described in 12) of Chapter 2.4 above, the RO to which the PI belongs shallconclude the joint research contracts, attached hereto as Appendix E, with the Three Parties, withrespect to the implementation of the research on the theme selected in the RA. The signer may be thePI himself/herself only in case if the PI does not belong to any organization.
8.1 Rights
The PI shall be entitled to the following rights:
1. Submitting requests for new data acquisition necessary for the implementation of the research on
the selected theme.
2. Requesting a delivery of standard products without any cost, before the release to the public. (Thisapplies when major changes in the processing algorithms are implemented and version of the
product is changed.)
3. Requesting a delivery of research products without any cost.
(Note that the number of such requests will be determined in consideration of the conformity to theresearch purpose.)
4. Requesting a forced processing of FTS L2 data products by applying no strict filtering andscreening and a distribution of its results, if L2 products are not generated by any reasons. For
making such request, browse images including the targeted observational point shall be visuallyconfirmed beforehand that there is no cloud over the point. The request is possible only in case if
those data are necessary for his/her RA research.
5. In addition to the FTS L2 data products (column abundances of CO2, CH4, and H2O (SWIR)), PIs
can obtain additional information, so-called “sub-datasets” of these products.
6. PIs are entitled to participate in the “PI Meeting” being held by the Three Parties.
In addition, Table 4 below summarizes the respective categories and calibration/validation stages of
products to be distributed to the RA* Investigators, (who carry out researches concerning thecalibration or validation) the RA+ Investigators, (who conduct researches on data application or
investigation on carbon balance estimation and atmospheric transport models) and general users.
Table 4 Data distribution conditions for standard/research products
User Category
Standard productResearch product (*)
RA*
To be released at the P (preliminarily To be released at the P (preliminarily
Investigator
checked) stage
checked) stage
RA+
To be released at the Ca (calibrated: L1) To be released at the V (validated)
Investigator
and V (validated :higher than L2) stage
stage
General user
To be released at the C (confirmed) stage
Not available(*) The research products are made available to RA Investigators, to an extent necessary for theirrespective researches, at suitable timing. The Three Parties do not guarantee product quality.

148.2 Obligations
8.2.1 Interim reporting
PI shall report the progress of his/her RA research, once a year in principle, in the way
designated by the Three Parties, such as submitting the report in writing or presenting thereport at GOSAT-related workshops, symposiums, interim report meetings, andconferences to be held by the Three Parties. The Three Parties shall evaluate the Research
Results and the progress reports in the Interim Evaluation based on the results ofdeliberation by the Committee and notify the evaluation results to the RO (or the PI if the
PI does not belong to any organization) in accordance with Article 2 of the General
Contractual Conditions for the Joint Research on the GOSAT data.
Moreover, if the Committee deems the research purpose or data application of the RA
Investigators as deviant from the initial research plan or in breach of the joint researchcontract, as a result of the examination of the progress reported, the Three Parties may
terminate the said agreement.
8.2.2 Final reporting and termination of the contract
When the research period scheduled and stated in the research proposal comes to the end,
all PIs are required to submit the final reports (= “the Research Report”) to the Three
Parties in accordance with the instructions provided in the contract. Timing of thesubmission is generally within one year from the last interim report result. When the RA
Office receives the final reports from the PI and the Committee confirms and accepts thereports, the RO will be informed (or the PI if the PI does not belong to any organization)
about the completion of the joint research agreement in writing. The reports shall be
prepared in English.

15

9. Preparation and Submission of Research Proposals
9.1 Notes to the preparation of research proposals
The documents to be submitted in response to the RA must be prepared in accordance with thefollowing procedures. Those proposals that are prepared in disregard of these conditions may be
excluded from the succeeding evaluation process. In addition, none of the submitted documents will
be returned to the proposers for any reason whatsoever.
---Prepare a research proposal in accordance with the procedure for submission defined in this
Chapter and the “Contents of Research Proposals and Application Forms” provided as Appendix
D hereto. The application forms in Appendix D will be selected and used as necessary, except
Forms 1a, 1b and 2 that are mandatory for all applicants.
Submit your research proposal in the PDF format, in the way that it is ready for printing in A4 or
letter size, together with necessary references, such as relevant theses, via e-mail to the
GOSAT/TANSO RA Office’s e-mail address (gosat-prj1@nies.go.jp). Note that the size of thesubmission e-mail should not exceed 10 MB, including the main text. Should your proposal
exceed this limit, prepare six copies of the proposal documents as well as the references, record
the proposal in the PDF format on an electric medium, such as CD-R, and send the whole
package to the RA Office by conventional mail.
Letters on the documents should all be typed in 10- to 12-point size.
Indicate the page number at the bottom center and the name of applicant in the upper rightcorner on each page of the documents.

9.2 Language
The research proposal and accompanying reference documents must all be prepared in either English
or Japanese. Those who are native speakers of Japanese shall prepare and submit Forms 1a and 1b of
Appendix D, which are cover sheets of the proposal, in both English and Japanese.
9.3 Volume
The research proposal must be compiled in the most simplified way, focusing on the minimallynecessary contents. The total volume of the proposal, excluding appendices, must be 20 pages or less.
See Appendix D for further specific rules.
9.4 Contents to be included in research proposals and the preparation procedure
See Appendix D.
9.5 Submission of research proposals
As mentioned in Chapter 9.1 above, the applicants for the RA should submit the proposal and othernecessary documents basically via e-mail. However, in a case that the applicant is unable to use
e-mail, insert all documents necessary for the application in an envelope, and send it to the following
address by conventional mail no later than October 29, 2010.
16

GOSAT RA Office
Center for Global Environmental Research (CGER)
National Institute for Environmental Studies (NIES)
16-2 Onogawa, Tsukuba-shi, Ibaraki
305-8506 Japan
TEL: 81-29-850-2966 (Japanese)
TEL: 81-29-850-2035 (English)
FAX: 81-29-850-2219
E-mail: gosat-prj1@nies.go.jp

1710. Selection of Research Proposals
10.1 Evaluation and Selection Procedure
The research proposals submitted in response to the RA will be evaluated by the Committee. The
Three Parties will make a final decision on the selection of research themes, based on the evaluation
results of the Committee. The applicants may be requested to modify or rectify the contents of the
proposed research plan, in the course of the selection by the Committee, with a view to enriching the
expected scientific results from the proposed research. In addition, the Committee may solicit adviceof the GOSAT Science Team in the process of evaluation. All applicants will be notified of theselection results by January 31, 2011.
10.2 Evaluation Criteria
The submitted research proposals will be examined and selected based on the following evaluation
criteria.
1) The contents of the proposed research conform to the purpose of the RA.
2) The methods and approaches adopted in the proposed research are appropriate and the underlying
concept is original and/or innovative.
3) The RA Investigators, including the PI, are qualified in terms of research capability, experience,
facility/equipment, and skills necessary for accomplishing the purpose of the proposed research.
4) The proposed research is consistent and relevant with the purpose of the GOSAT Project.
5) The purpose of the proposed research can be accomplished within the research period.
10.3 Post-selection Procedure
The RO of the selected PI shall sign the joint research contract with the Three Parties, in principle,
based on the “General Contractual Conditions for the Joint Research on the GOSAT data”, attached
as Appendix E hereto. The RO and the PI shall observe all the clauses, in connection with theperformance of the research, as stipulated in the General Contractual Conditions.
The RA Office shall carry out the administrative work necessary for concluding such a contract, inline with the intentions of the Three Parties.

18

11. Cancellation and Postponement of RA
The Three Parties reserve the right to cancel the RA and joint research projects based on the RA by
notifying in writing, and shall not be liable for any delay in the RA schedule or cancellation of the
RA program itself or to those who did not receive any notice regarding such delay or cancellation.

19

12. Expected Research Topics
The Three Parties have been and will be continually promoting the GOSAT Project by playing therespective roles in the research and development deemed as necessary for achieving its purpose withthe advice and help from the GOSAT Science Team. The specific research and development
activities within the Project include; the calibration of the GOSAT/TANSO equipment, validation ofhigher-level products (observation and analysis for validation), development and improvement of thedata processing algorithms, development of atmospheric transport models and land ecosystemmodels, generation of source inventories, and development of carbon flux estimation models, etc.
Also, the analysis methods for such basic phenomena that have influence on evaluation of thecharacteristics and quality of data such as temporal variation of concentrations and carbon balance
distributions are studied. Furthermore, with the GOSAT Project, research on advanced application of
the GOSAT/TANSO data, for example, detection of CH 4 leakage from natural gas pipelines or local
forest fires, and so forth, is conducted. More details are provided in the succeeding section.
Through the implementation of the RA, the GOSAT Project expects to benefit from the RA researchoutcomes for developing higher level data products. At the same time, the Project wants to see theresearch field of data application being further facilitated, and the data acquired by the GOSAT willcontribute to resolve the global-warming issues through the effective utilization. Therefore, the
GOSAT Project is open and willing to accept new research proposals from all parts of the world.
In this Chapter hereunder is provided a summary of research topics to be or to have been carried out
in the GOSAT Project. It is anticipated that a large number of research themes, that will supplement
the research topics of the GOSAT Project, that will utilize the applicant’s own validation data, or thatare based on very original and unprecedented perspectives, will be proposed.
12.1 Research Topics conducted or targeted by the GOSAT Project1) Calibration
The calibration-related research topics conducted or targeted by the GOSAT Project include
calibration (including wavelength calibration) when interferogram is transformed into spectra,
calibration in relation to correction of the variation of the observation sensors’ field of view,
instrument function calibration, radiance calibration, etc. as for TANSO-FTS, and radiometriccalibration, geometric correction, calibration of the sensor sensitivity, etc. as for TANSO-CAI.
2) Data processing algorithms
The processing algorithm-related research topics conducted or targeted by the Project include
development of fast data processing algorithms, sunglint observation data processing methods,
processing algorithms using polarized data, and algorithms to extract parameters fromthermal-infrared data, evaluation of spectral parameters of gaseous molecules and sunlight
spectra, combined use of short wavelength infrared and thermal infrared data, etc.
3) Carbon flux estimation, atmospheric transport models
The model-development-related research topics conducted or targeted by the Project include
development and refining of source inventory databases, refining of atmospheric transport andland ecosystem models, etc., development of carbon flux estimation models with hightemporal/spatial resolution, etc.
4) Validation20

*Before the launch
The research topics targeted by the GOSAT Project included validation by ground-based
high-resolution and by small-sized FTSs with airborne in-situ instruments, evaluation of sunglint
observation algorithms using airborne or ground-based FTSs, development of validation
methods based on data taken by LIDAR, sky radiometers or other equipment for validating
aerosol, etc.
*After the launch
The research topics conducted or targeted by the GOSAT Project include acquisition andanalytical validation of data taken at validation sites on land and on ocean (including island andcape), analytical validation of data taken by instruments on board private aircraft, comparison
with data taken by other satellites or computed by models, etc., for the purpose of validating thequality of data on the CO2 and CH 4 column abundances, as well as validating the quality of dataon vertical distributions of CO2 and CH4 concentrations to be derived from the thermal-infrared
data. Validation of CAI data products is also included.
5) Data application
FTS: The research topics conducted or targeted by the Project include analysis of basic
phenomena that have influence on evaluation of the characteristics and quality of data such as
temporal/spatial variation of concentration distributions and carbon balance distributions,
possible advanced applications, such as detection of CH 4 leak from pipelines and local
high-volume exhaust due to forest fires, possibility of observing atmospheric trace components,
such as N2O, CFC, etc., and so on.
CAI: Generation and utilization of the global vegetation index map based on the CAI data, andothers.
12.2 Expected Research Topics to be proposed in the RA
1)
2)
3)
4)
5)

Calibration
Data processing algorithm
Carbon balance estimation, atmospheric transport models
Validation
Data application

21

13. Schedule
13.1 1st Announcement
Release of RA
Deadline for submission of proposals
Notification of the selection results
Sign up of the agreement
PI meeting/workshop
Launch of GOSAT
Submission of interim reports

April 7, 2008
July 7, 2008
August 29, 2008
August 30, 2008 and later
November 5-7, 2008
January 23, 2009
December 28, 200913.2 2nd Announcement
Release of RA
Deadline for submission of proposals
Notification of the selection result
Sign up of the agreement
2nd PI meeting/workshop
Submission of interim reports

April 7, 2009
June 1, 2009 for RA* users
June 23, 2009 for RA+ users
July 31, 2009 for RA* users
August 28, 2009 for RA+ users
August 3, 2009 or later for RA* users
August 31, 2009 or later for RA+ users
Scheduled in early 2010
September 30, 201013.3 3rd Announcement (Current Announcement)
Release of RA
Deadline for submission of proposals
Notification of the selection result
Sign up of the agreement
3rd PI meeting/workshop
Submission of interim reports

22

August 20, 2010
October 29, 2010
January 31, 2011
February 1, 2011 and later
Sometime between May and August, 2011
March 1, 2012

14. Contact Information
GOSAT RA Office
Center for Global Environmental Research (CGER)
National Institute for Environmental Studies (NIES)
16-2 Onogawa, Tsukuba-shi, Ibaraki
305-8506 Japan
TEL: 81-29-850-2966 (Japanese)
TEL: 81-29-850-2035 (English)
FAX: 81-29-850-2219
E-mail: gosat-prj1@nies.go.jp

23

Thermal And Near infrared Sensor for carbon Observation (TANSO)
On board
the Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

Appendix A

Outlines of GOSAT and TANSO Sensor

GOSAT (Greenhouse gases Observing SATellite) carries an observing instrument called
Thermal And Near infrared Sensor for carbon Observation (TANSO), which is composed of a
Fourier Transform Spectrometer (TANSO-FTS) and a Cloud and Aerosol Imager (TANSO-CAI)

A.1 Outline of GOSATGOSAT is scheduled to be launched into space by JAXA’s H-IIA rocket in early 2009
and will acquire data on the global distribution of carbon dioxide (CO2) and methane(CH4) (column abundance and altitude distribution) for at least five years.

Twoobservation sensors, TANSO-FTS and TANSO-CAI, are placed in the earth-facing (+Z)
plane of the satellite and operated by a three-axis attitude control system in such a waythat the sensors keep looking toward the geocentric direction.

GOSAT secures power

supply needed for the operation of itself and the sensors on board with two sets of solar
paddle to be deployed facing towards the sun, records and playbacks the mission dataacquired by the sensors on the Mission Data Processor (MDP) subsystem, and transmits
the data down to the ground stations.
Figure A.1-1, Table A.1-1 and Table A.1-2 show an overview of GOSAT in orbit, itsmajor specifications and orbital parameters, respectively. Figure A.1-2 represents
nominal orbits of GOSAT.

Figure A.1-1 Overview of GOSAT in orbit

A-1

Table A.1-1 Major Specifications of GOSAT
Specification items

Description

Size

Main body: H3.7m(X) × W1.8m(Y) × D2.0m(Z)(except for its extrusions)
Wing span: 13.7m

Mass

1,750 kg

Power

3.8 kw (EOL)Life time

5 years

Launch schedule

January 23, 2009

Table A.1-2 Orbital Parameters of GOSATParameters

Description

Orbit typeSun-synchronous, quasi-recurrent

Altitude against the earth

666 km at Equator

Inclination angle

98.06 deg

Orbits/day

14 + 2/3 revolutions/day

Orbits/recurrence

44 revolutions/3 days

Descending node time

13 hours ±15 minutes

Figure A.1-2 GOSAT’s nominal orbits

A-2

A.2 Outline of GOSAT/TANSO-FTS
A.2.1 Outline of TANSO-FTS
Table A.2-1 below provides an outline of TANSO-FTS.
Table A.2-1 Outline of TANSO-FTS
Observation method

Earth-looking observation

Method ofSpectral measurement of atmospheric absorption by the Fouriertransform interferometermeasurement
Functions

1. Observes the atmosphere in visible, short wavelength infrared andthermal infrared bands looking toward the earth center.
2. Carries out observation over the land on lattice points.
3. Observes

the

same

footprint

duringone

interferogrammeasurement while the satellite is moving.
4. Multiple observations are carried out for a same footprint toimprove SNR.
5. Observes at a fixed angle (or fixed distance) interval in cross-track
direction during the lattice observations.
6. Returns to the same footprint after three days.
7. Observes sea area where sunglint is expected, using the two-axis(AT/CT) mechanism.
8. Conducts a combination of observations in lattice point, sunglint
and specific point modes.
9. Performs the following in-orbit calibrations:(1) Solar irradiance calibration in the visible and short wavelength
infrared bands and blackbody calibration in the thermal infraredband(2) Deep-space calibration in the visible-, short wavelength- andthermal-infrared bands(3) Annual lunar calibration on the sensitivity by pointing the satellite
and the two sensors to the moon
TANSO-FTS is composed of the following three units:(1) TANSO-FTS Optical Unit
(2) TANSO-FTS Control Unit
(3) TANSO-FTS Electrical Circuit Unit

Figure A.2-1 shows a block diagram of TANSO-FTS.

Considering that the mission ofthis Project is to get useful results, redundancy is employed in the design of sensors
wherever possible.

Figure A.2-2 shows an overview and the internal structure of the

optical unit of the sensor.

A-3

Figure A.2-1 Block Diagram of TANSO-FTS

Figure A.2-2 Overview and Internal Layout of the Optical Unit of TANSO-FTS.

A.2.2 Specifications of TANSO-FTS(1) Fourier interferometer mechanism
Table A.2-2 summarizes the specifications of the Fourier interferometer mechanism andoutlines the scanning method.

A-4

Table A.2-2 Outline of the specifications of the Fourier interferometer and its scanning method
Spectroscopy

Fourier interferometerNo. of ports

2 (single-pass)

Scanning method

Two corner cubes are attached to the ends of the V-shaped
swing arm. The arm swings to scan with the supported flexible
blades acting as the axis. (See Figure A.2-4.)

Data acquisition method

Scanning on both sides and data acquisition on one way

Beam splitter

ZnSe (without coating)

Sampling

Sampling by laser diodes

Signal processing

Interferogram data are transmitted down to the earth.

Figure A.2-3 illustrates the structure of the scanning mechanism.
stability required is 1％ or lower.

The scanning speed

The interferometer acquires interferogram on bothsides of the zero (optical) path difference (ZPD) location.
Max. path difference

ZPD

180.0

=±2.5cm

6300.0Interferometer turnaround6800.07300.07800.08300.08800.09300.0-20.0

Incoming path
Return path
Figure A.2-3 Scanning by the Fourier interferometer

Figure A.2-4 Layout of the double corner cubes, swing arm and flexible blades

A-5

(2)Band configuration
TANSO-FTS has detectors for four bands, all of which have the same field of view(FOV). Table A.2-3 tabulates the wave number range, spectral resolution, and otherparameters for each band.
Table A.2-3 Wave number range and spectral resolution of the four bands used by FTS
Band

Band 1

Band 2

Band 3

Band 4

Band name

Visible

SWIR

SWIR

TIR

Polarimetric

Yes

Yes

Yes

No

observation
Wave number

5800 -

12900 -1

Range

-1

6400 cm

13200 cm

700 -

4800 -1

5200cm1800 cm-1(Note 5)(Note 1)Out-of-band

TransmittanceTransmittanceTransmittanceTransmittancecharacteristics

of 0.1% or lessof 0.1% or lessof 0.1% or lessof 0.1% or less

(Note 2)in the ranges ofin the ranges ofin the ranges ofin the ranges of<12700cm-1<5000cm-1<4500cm-1<600cm-1>13400cm-1>6800cm-1>5500cm-1>3800cm-1

0.2 cm-1

0.2 cm-1

0.2 cm-1

0.2 cm-1

0.6 cm-1 or less

0.27

Spectral resolution(Note 3)
FWHM

of

the

instrument

cm-1

or

less

0.27

cm-1 or

0.27cm-1 or lesslessfunction (Note 4)
Targetsofthemeasurement(O2)

CO2, CH4, H2O

CO2, CH4,

CO2, CH4,→information

H2O,

H2O, etc.

on air pressure

information on& cirrus cloud

cirrus cloud

Note 1: 80% or above of the maximum efficiency can be achieved within the wave number
ranges of Bands 1, 2 and 3.

As for Band 4, 60% or above of the maximum efficiency

can be achieved in the designated wave number range by converting the sensitivity ofthe detector into the quantum efficiency. The efficiency here means the product of theefficiency of the optical unit, the quantum efficiency of the detector, and the response of
the amplifier.
Note 2: In the wave number range corresponding to the signal turn-around in the Fouriertransform, less than 0.01% is assumed.
Note 3: The spectral resolution is defined as (1 / (2 * Max. path difference)).

A-6

Note 4: The full width at half maximum (FWHM) of the instrument function is defined as the
FWHM when radiation from a monochromatic light source is introduced in the full
FOV and the measured data are inverse-Fourier-transformed without apodization.
Note 5: In Band 2, the transmittance must be 0.1 or higher when the laser wavelength is
1.55μm (6460 cm-1), which is for measuring the instrument function in orbit.
(3) Methods of optics, band splitting and polarimetric observation
Table A.2-4 lists the summary of specifications for TANSO-FTS in terms of optics,
spectroscopy and polarization, whereas Figure A.2-5 provides an overview of the opticalsystem.
Table A.2-4 Summary of specifications for optics, band splitting and polarization
Effective aperture

φ68 mm (Bands 1-3), φ60 mm (Band 4)

F value

F=2 (F value for the optics-detector system to be installed
between the FTS sensor and the detector.)

Optical system

Reflective optical system. However, a refractive optical system
is used in the case of focusing on the detectors for Bands 1-3.

Aperture control

As for Bands 1-3, the corner cubes provide a control of theaperture.

Optics

While the aperture diameter is 68 mm, the movement of light
flux in association with FTS’s scanning remains within 1 mm
in the direction perpendicular to the optical path.
For Band 4, an aperture control is introduced inside the opticalsystem of the detector so as to suppress background light.
FOV control

The FOV is determined with the slit common to all bands, after
the light is modulated by the Fourier interferometer andconcentrated. (15.8 mrad: corresponds to 10.5 km when
projected on the earth’s surface.)

Band splitting

After FOV being narrowed through the slit and the light

Band splitting

collimated, the light is splitted through the dichroic filter one
after another starting with Band 1.
Removal of

A narrow band pass filter is set up at the optical system of theout-of-band lightdetector for each of Bands 1-3.

A-7

Polarization

For Bands 1-3, the polarization beam splitter is installed in the

Polarization

optical system of the detector for simultaneous observation of
two polarizations.

光路切替機構Figure A.2-5 Overview of the optical system(4) Band-to-band/sensor-to-sensor registration
Band-to-band/sensor-to-sensor registrations are determined as follows:(1) Band-to-band registration within FTS: 0.05 pixels or less(2) Registration between TANSO-FTS and TANSO-CAI: 0.5 pixels of TANSO-CAI or
less(3) A monitoring camera (for checking the FOV of FTS) is attached at the light entrance
section of FTS for the sake of determining registration with TANSO-CAI.

A.2.3 Observation mechanism of TANSO-FTS(1) Principles of TANSO-FTS observation
The sun can be regarded as a blackbody light source which has an absolute temperatureof slightly less than 6,000 K.

It emits light mainly in the range covering from
A-8

ultraviolet to visible and short wavelength infrared bands. Most of visible and shortwavelength infrared light emitted by the sun reaches the earth’s surface while some isabsorbed and scattered by clouds and aerosols on the way. An earth-observing satellite
detects light reflected by the ground and returned to the satellite through the atmosphere.
The measured light provides information on the concentrations of CO2, CH4, and water
vapor (H2O), whose absorption bands are in the visible and short wavelength infrared
range.
The ground surface and clouds radiate thermal infrared waves with intensities
commensurate with their temperatures and their own wavelength characteristics.

There

are numerous absorption bands of major and minor atmospheric constituents in thesebands.

Each atmospheric constituent has its own absorption bands within the visible

and short wavelength infrared bands or thermal-infrared band.

Though the strength ofabsorption varies with spectra of each constituent, the use of databases established inlaboratories will help identify the relationship among the wave number within theabsorption bands, absorption strength, and constituent concentration.

The basicprinciple of molecular spectroscopy goes as follows: spectroscopic observation is
performed by detecting the absorption spectra of the atmospheric molecules of interest,
the detected light is converted into electric signals (photoelectric transfer), radiance perspectrum is calculated, and the amount of atmospheric molecules is derived from theradiance level.

A space-borne observing sensor points its scanning mirror at the target to be observed,
introduces the observed light into the system, converts it into electric signals at thedetector assigned to each bandwidth through the diffraction grating, interferometer oranother types of spectrometer, and transmits electric signals onto the ground. The data
received on the ground will be analyzed to extract necessary information, which willthen be transformed into spectral data, based on which the volume of each atmosphericconstituent is calculated.
(2) Principles of the Fourier interferometer
The Fourier interferometer first splits the light with its beam splitter (BS) into two withdifferent optical path lengths, which interfere with each other. It acquires the spectra of
the light source by inverse-Fourier-transforming the interferograms obtained whilechanging continuously the path length difference.
This method is characterized by the following two factors:(1) High gain of the lightA-9

(2) Acquisition of spectra over a wide wavelength range at a high spectral resolution
The Fourier interferometer has come into practical use owing to the development ofadvanced computers, which has made inverse Fourier transform faster, andhigher-accuracy mechanical scanning by means of laser range finders. Figure A.2-6
shows a diagram describing the principles of the Michelson interferometer.

Typically,

M1 and M2 are a fixed mirror and a moving mirror, respectively.

In case of

TANSO-FTS, however, M1 and M2 are installed on a single swinging arm so that thetwo mirrors move by the same distance with opposite phases. As a result, the path
difference is doubled, making it possible to scan faster. Thus, the interferometer canachieve both a high spectral resolution and a high spatial resolution without sacrificing
one or the other.

M1: Fixed mirror

Light source

M2: Moving mirror
When the moving distance is d,
the path difference is 2d.

Detector

Figure A.2-6 Principles of Michelson Interferometer
Further, space-borne interferometers are designed with attention paid to the vibration
environment while being launched on rockets and the thermal environment in outerspace.
The Fourier interferometer acquires signals called interferogram as shown in Figure
A.2-7 below.

A-10

Radiance
signalofDistance traveled by the movable mirror
Figure A.2-7 Interferogram data
When this interferogram is inverse-Fourier-transformed, the spectra absorbed in the air
are obtained, as shown in Figure A.2-8. The spectra depicted here are those of thesunlight absorbed by H2O, CO2, and CH4 in the atmosphere as observed by the GOSAT
ground test model in November 2005.

CH4 absorption

H2O absorption

Intensity
CO2 absorption

Wavelength [µm]Figure A.2-8 Atmospheric scattering spectra observed by the GOSAT groundtest model at the top of Mt. Tsukuba in November 2005
Since the satellite can acquire observation data fairly frequently, the amounts ofatmospheric constituents can be derived from the above spectral data and plotted into a
global distribution diagram, as shown in Figure A.2-9.
example of global distribution data provided by satellites.

A-11

There has been no such

Figure A.2-9 Global distribution of carbon dioxide (CO2)
The global distribution of net CO2 flux, as shown in Figure A.2-10, can also be derived
from the satellite data referred to above, and by using atmospheric inverse transportmodels.

←SourcegC/m2/day

Sink→

Figure A.2-10 Global distribution of net CO2 flux
A-12

Furthermore, a global distribution of CO2 can also be obtained, as shown in Figure
A.2-11 in three-dimensional (3D) image, using the above net CO2 flux distribution andatmospheric transport models.
January

August← Low density

High density →Figure A.2-11 3D global distribution of CO2 obtained based on
the net CO2 flux distribution using atmospheric transport models(3) Observation by GOSAT
In case of GOSAT, Figure A.2-12, GOSAT observes visible and SWIR radiation of thesun reflected by the earth’s atmosphere and by the earth surface and thermal radiation in
TIR band from the earth surface and the atmosphere.

【TIR】
Figure A.2-12 Observation by GOSAT
A-13

TANSO-FTS observes the light reflected by the earth in the range covering from visible
0.76 μm to thermal infrared 4.3 μm. (See Figure A.2-13.)

The vertical distribution of

air temperature is measured in TIR bands, whereas the air pressure can be obtained fromthe absorption by oxygen molecules (O2) and the air column abundance is derived byreferring to the absorption by O2, which has much higher concentration remaining
constant than CO2.

GOSAT Spectral Coverage

250

Band 2

Band 120

100

Spectral Radiance（W/str/m2/micron）

200

10

50
0
0.758

O2
0.763

0.768

CO2

0
1.57

0.773

CH4
1.62

1.67

150
Band 3
10

100

CO2

5
0
1.98

50

2.03

Band 4

2.08

CO2
O3

CH4

0
0

3

6

9

12

15

Wavelength (micron)Figure A.2-13 Observation band of TANSO-FTS and air absorption bands

A-14

A.3 Overview of GOSAT/TANSO-CAI
A.3.1 Overview of TANSO-CAI
Table A.3-1 below explains the purposes of the TANSO-CAI sensor.

Purpose 1

Table A.3-1 Purposes of TANSO-CAI
Assessment of theDetermines whether data should be discarded or not in

effectiveness ofcase there is a thick cloud. It is desirable that the cloud

FTS footprint area

thickness can be assessed in addition to the cloudPurpose 2

coverage.
Detection of clouds

Provides information necessary for correcting the errors

and aerosols in FTS

caused by clouds and aerosols in FTS footprint area.

footprint area and

Evaluates the characteristics of cloud and aerosol (e.g.

correction of

optical thickness, type). Thus, it is desirable that theresulting errors

spectral characteristics of aerosol can be derived.

TANSO-CAI is expected to derive the types and optical thickness of aerosol of each type.
To this end, the bands selected for CAI observation must be those where there is noabsorption by atmospheric dominant constituents, and, consequently where the best
signal-to-noise ratio (SNR) is attained, and where the spectral characteristics of the optical
thickness of aerosols can be observed. In addition, scattering by aerosols is significantly
polarized, in general; thus polarimetric observation is preferred.
However, as
TANSO-CAI observes at a fixed angle very close to the nadir, the degree of polarization isquite low, which makes it difficult to estimate the aerosol amount. Therefore, morestress is put on securing enough number of bands than polarimetric observation inchoosing the bands.
Given these considerations, the four bands shown in
Table A.3-2 were selected for TANSO-CAI.

A-15

Table A.3-2 Observation bandwidth of TANSO-CAI and selection criteria
Criteria
Band 1 (0.380 μm)

No O3 absorption in the ultraviolet range wherereflectance is low on the ground

Band 2 (0.674 μm)

No interference between the rise of reflectance on thevegetation and absorption by O2 B and H2O bands.

Band 3 (0.870 μm)

No interference with absorption by H2OBand 4 (1.60 μm)

The maximum wavelength width is achieved while
avoiding the absorption by H2O, provided that theabsorption by CO2 and CH4 can be corrected.

At thesame time, the band should be free of any impact ofpossible effect on the detector cut-off due to temperaturefluctuation.
TANSO-CAI is composed of the following two units.
(1) TANSO-CAI Optical Unit
(2) TANSO-CAI Electrical Circuit Unit
Figure A.3-1 is a block diagram of TANSO-CAI.

Figure A.3-1 Block diagram of TANSO-CAI
An overview of TANSO-CAI is given in Figure A.3-2 below.

Figure A.3-2 Overview of TANSO-CAI

A-16

A.3.2 Specifications of TANSO-CAI(1) Bandwidth and performance
Table A.3-3 below summarizes the specifications of TANSO-CAI.
Table A.3-3 Specifications of TANSO-CAI
Band 1

Band 2

Band 3

Band 40.380 ± 0.005

0.674 ± 0.005

0.870 ± 0.005

1.60 ± 0.01

<0.02

<0.02

<0.02

<0.10

Out-of-band

1％ or lower in the

1％ or lower in the

N.A.

1％ or lower incharacteristics (i)ranges of <0.36 andranges of <0.658

the(μm)(Note 2)>0.4

and >0.692<1.0 and >1.69

Out-of-band

N/A

1％ or lower in the

1％ or lower inrange of >0.696

the ranges ofCenterwavelength(μｍ)(Note 1)
Wavelength width(μｍ)(Note 1)characteristics (ii)(μm)(Note 2)<0.840ranges

of

N/A

and

>0.890Out-of-band

0.15％ or lower incharacteristics (iii)the range of >0.45

N/A

N/A

N/A

N/A

N/A

N/A

(μm)(Note 3)
Out-of-band

0.03％ or lower incharacteristics (iv)the range of >0.7(μm)(Note 3)
Polarization

None

Note 1: The center wavelength and wavelength width are specified based on the first andsecond moments, taking into consideration the spectral characteristics of the
optical system, filters and detectors for an overall efficiency.
Note 2: The sensitivities in the range specified in ‘out-of band (ⅰ)’ should be lower than
1% of that at the central wave length, and the sensitivity in the range specified in‘out-of-band (ⅱ)’ should be lower than 0.1% of that at the central wave length inorder to avoid the H2O absorption band in the above described bands.
Note 3: The sensitivity in the range specified in ‘out-of-band (iii)’ must be 0.15% or lower
and in the range specified in ‘out-of-band (ⅳ)’ 0.03% or lower, of that at thecorresponding center wavelength.
(2) Instantaneous FOV and the look angle in the cross-track direction
The instantaneous FOV is set at 500 m (in Bands 1, 2, 3) and 1.5 km (in Band 4) at thenadir point. The look angle in the cross-track direction is set at ±35 degrees, with which

A-17

the sensor can observe the entire globe during daylight hours in three days except band 4.
Figure A.3-3 below illustrates the geometries of the instantaneous FOV and the normal
FOV.

【Bands 1, 2, 3】【Band 4】

Figure A.3-3 Instantaneous and normal FOV of TANSO-CAI

A.3.3 Observation mechanism of TANSO-CAIThe column abundances of CO2 and CH4 are derived from the amount absorbed in the
optical path between the sun, the ground surface and the satellite.

The path length isobtained through the amount of absorption for the 0.76 μｍ band by O2 whose density is
known, with TANSO-FTS.

As cloud or aerosol on the path affect the effective path

length, correction is needed if there is any.

In order to improve the accuracy ofcorrecting errors caused by clouds and aerosols, electronic scanning imagers withmultiple bands covering ultraviolet, visible and short wavelength infrared bands are
installed, which also make it possible to observe cloud coverage and aerosols over theland and ocean areas.

The FOV in the cross-track direction is used for ascertaining the

spatial distribution of aerosols over a wide range (1,000 km).
Registration between TANSO-FTS and TANSO-CAI data should be performed after thelaunch using the FOV check camera installed in the TANSO-FTS sensor. Figure A.3-4
shows a sample of CAI observation data.

A-18

Figure A.3-4 A CAI observation image (equivalent to Band 2)
generated based on MODIS data

A-19

Thermal And Near infrared Sensor for carbon Observation (TANSO)
on board
the Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

Appendix B
GOSAT/TANSO Calibration and Validation Plan and Overview of Processing Algorithms

B-1 GOSAT/TANSO Calibration Plan
B-1.1 Outline“Calibration” is an evaluation process to clearly characterize the sensor and to ensure that theaccuracies of radiance, geometry, spectral characteristics, image quality, etc. meet the target values,
using Level 1 (L1) products out of the standard products. The specific methods of evaluation
include:・ Evaluation of performance in ground tests (before the launch, using ground test data)
・ In-orbit calibration (after the launch, using cal-mode data), and・ Vicarious calibration (after the launch, using actual observation data, etc.)
Based on the results of these calibration activities, L1 products will constantly be upgraded byreflecting the revised calibration coefficients and the corrected L1 processing algorithm in the
ground processing system.
B-1.2 Calibration Schedule
The evaluation of the sensor performance on the ground will be completed by approximately one
year before the launch. The initial in-flight calibration will be carried out during theoperational phase, between three and six months after the launch. The calibrated Level 1
products will be released as Version 1, expectedly within six months from the launch. Thus,
the data to be collected and examined during the initial calibration period only covers a periodof less than a year, and it is important to thoroughly examine match-up conditions, etc. for dataacquisition during this period.
B-1.3 Pre-launch Performance Test
The main functions and capabilities of TANSO-FTS and TANSO-CAI will be evaluated before
the launch. The evaluation is basically conducted by checking the following items in groundtests.
(1) Sensitivity and signal-to-noise ratio (SNR)
The sensitivities of FTS at short wavelength infrared bands and CAI, an indicator for thephotoelectric conversion efficiency, and SNR are calibrated and evaluated by using an evaluatedintegrating sphere. The evaluation of the integrating sphere is carried out by using a comparative
spectrometer in comparison with a fixed point blackbody furnace coated with such material aszinc. The sensitivity calibration for FTS thermal infrared (TIR) band and SNR evaluation are
performed by using a blackbody cavity at the thermal vacuum test.
(2) Polarization sensitivity
The polarization sensitivity of FTS at short wavelength infrared bands and CAI will be carriedout in the following steps: i) install a polarizer at the exit port of the integrating sphere to form
linearly polarized light, ii) rotate the phase of the linearly polarized light by rotating the 1/2
wavelength plate attached behind, and iii) introduce rotating linearly polarized light so as toB-1

obtain the polarization sensitivity. In case of TANSO-FTS, the incoming light is polarized
mainly at the reflector of the pointing mechanism and the beam splitter of the Fourierinterferometer mechanism.
(3) Instrument function
FTS’s instrument function serves as an indicator for the spectral resolution. The function is
obtained by introducing diffused light from a tunable laser for each band. As for CAI, thespectral characteristics are obtained by introducing monochromatic light.
(4) Field of View (FOV) and Modulation Transfer Function (MTF)
The FOVs of FTS and CAI, which serve as indicators for optical capabilities, and the MTF of
CAI are evaluated by setting up a point light source and a slit light source at the collimator.
The alignment to the sensor reference axis and band-to-band/pixel-to-pixel alignment are also
evaluated at the same time.
In addition, FTS is equipped with a high-resolution monitoring camera (CAM) to check its FOV.
The CAM has the same look direction as FTS. The alignment of the CAM to the sensor
reference axis will also be evaluated.
B-1.4 Post-launch calibration
Calibrations after the launch will be carried out in two modes: in-orbit calibration and vicarious
calibration. The former is performed on the calibration mode data, whereas the latter uses
actual observation data.
The cal-mode data acquired during in-orbit calibration are precisely defined in Chapter C-2.4.3“Operation in the calibration mode” of Appendix C ”Operation Policies of GOSAT and Basic
Observation Plan of the TANSO Sensor”. The cal-mode data are acquired in accordance withthe operation policies provided thereof and used for L1 processing, trend evaluation, etc.
B-1.4.1 Calibration of the TANSO-FTS (short wavelength infrared (SWIR) bands)
The in-flight calibration of TANSO-FTS will be carried out in three aspects: radiance, geometry
and spectral characteristics. The following items will be evaluated with respect to each of P
and S polarization bands in short wavelength infrared (SWIR) bands (Bands 1-3).
(1) Radiance evaluation(a) Calibration of the sensitivity
In-orbit calibration of SWIR bands will be performed through solar irradiation
calibration using the diffuser plate for every orbit, and deep-space calibration in parallelwith TIR band is performed. In L1 processing, it is planned to convert the observed
values into radiance values using the sensitivity calibration coefficients obtained fromground tests. The coefficients will be revised based on an analysis of the results fromthe solar irradiance calibrations, lunar calibrations (to be discussed in more details later),and vicarious calibrations.
B-2

(b) Lunar calibration
The purpose of lunar calibration is to calibrate the efficiency of the overall opticalsystem for SWIR bands by using the reflected solar radiation from the moon surface as
the calibration source. The lunar calibration will be performed on the orbit when the
average of lunar surface radiance becomes the largest (at lunar age of 14.8±0.1). In
this calibration, the satellite will be oriented to the moon so that FTS’s FOV catches themoon on the full scale, and FTS will keep pointing at the moon with its pointing
mechanism for at least two minutes.
The moon is an extremely stable reflector with a radiance variance of 10-7/year. The
stability has been reported so high that the fluctuation is less than 1%, based on the
results from the sensitivity trend evaluations for those sensors observing ultra violet toshort wavelength infrared bands, such as MODIS, ASTER, etc., that have been
conducted as part of lunar calibrations (USGS, 2006). The evaluation methods
adopted in these past evaluations are as follows:
・ The sensitivity trend was evaluated at each time of calibration using a stable lightsource.
・ The absolute sensitivity was evaluated based on ROLO data—ROLO (RObotic Lunar
Observatory) is USGS’s reflectance database for lunar calibration.
(c) Linearity
The linearity for the response of the optical system, including temperature dependence,
will be checked based on the data observed while uniform light with different radiancelevels is introduced into the FTS optical system. Listed below are candidate targets
that have uniform radiances.
・ Offset:
Deep-space calibration
・ Low radiance:
Ocean, snow and ice (B2-3)
・ Medium radiance: Forestry
・ High radiance:
Solar irradiation calibration, snow and ice (for B1 only), dry saltlakes (for B1 only), desert, playa(d) Absolute radiance
The radiance observed by FTS is compared with the radiance of ground surface
radiation obtained from the experiments in vicarious calibrations or synchronous
observations with a well-calibrated sensor on board other spacecraft or aircraft. In
order to match the radiances of the reference instrument and FTS, the sensor radiancemodel, and calibration coefficients are adjusted and absolute radiometric accuracies areevaluated.
There are two major approaches to this evaluation method:・ To use in-situ data
・ To use global data(i) Using in-situ data
Specific physical parameters, such as the ground-surface reflectance, as to a
B-3

specific location on the earth are obtained accurately and synchronously in avicarious calibration experiment. The GOSAT-observed radiance is evaluated incomparison with the radiance at the top of atmosphere computed by using theabove mentioned parameters. Since the observation bands contain absorption
bands of CO2, CH4 and other species, it is desirable to synchronize the validation
experiments with this evaluation.
(ii) Using global data
The synchronized data are extracted from the data acquired by a well-calibrated
sensor on board other spacecraft for radiance comparison. Since the radiance isinfluenced by the observation timing or geometry, the FTS data and the reference
data may not easily fit when directly compared. In such a case, the radiance isevaluated by comparing the GOSAT-observed radiance with the radiance at the
top of atmosphere computed based on the physical parameters, such as
ground-surface reflectance.
Currently, Aqua/MODIS and OCO (Orbiting Carbon Observatory) are listed as
candidates for reference satellites in this comparative evaluation.
(e) Relative radiance between the sensors
FTS and CAI both observe the 1.6μm band in Bands 2 and 4, respectively. The relative
radiance accuracy between the two sensors is evaluated by assessing the temporalvariation and temperature dependence per gain.
(2) Geometric evaluation(a) Pointing accuracy
The alignment of the CAM, attached in the FTS sensor for checking its FOV, and FTS is
assumed to be known and the CAM has an FOV of approximately 30 km and a spatial
resolution of approximately 100 m in the VGA mode. FTS’s geometric accuracy isevaluated using imagery taken by the CAM over GCPs with known coordinates as well
as clear radiance boundaries between bright and dark. The following scenes are to be
used in this evaluation:
・ Land/sea boundaries (scenes containing coastal lines also covering projections from theland, such as peninsulas and capes)
・ Islands (scenes containing the whole land of an island within the FTS’s FOV of 10 km)(b) Pointing stability
The pointing accuracy of the pointing mirror during an interferogram measurement(typically for four seconds) is evaluated by acquiring data by the CAM in the movie
mode. The following scenes are to be used in this evaluation:
・ Land/sea boundaries (scenes containing coastal lines also covering projections from theland, such as peninsulas and capes)(c) Geometric accuracy between the sensors
B-4

The geometric accuracy between FTS and CAI is evaluated by assessing thedisplacements of common GCPs on CAM and CAI images. Further, since the sensors
observe the same wavelength region, the geometric accuracy of FTS can becomparatively assessed against CAI by searching the position of FTS Band 2 (10-km
resolution) on a CAI Band 4 (1.5-km resolution) image with the radiance matching
function.
(3) Evaluation of spectral characteristics(a) Instrument function
The instrument function of Band 2 is evaluated by irradiating 1.55μm semiconductor
laser light onto the diffuser plate and observing the diffused light.
(b) Wavelength accuracy
The wavelength shift is evaluated by referring to the wavelength position of a known
atmospheric absorption band.
(c) Polarization sensitivity
The radiance ratio between the P and S polarization bands of the target with known
polarization characteristics is evaluated using the following data.
・Solar irradiation calibration data (natural light of the sun is unpolarized.)(d) SNR
Targeting a uniform high-radiance range, the SNR is evaluated as to each band detector
and gain. The following data will be accumulated and used for the evaluation.
・ Solar irradiation calibration data
・ Desert, snow and ice (for B1 only)
B-1.4.2 Calibration of TANSO-FTS (TIR band)(1) Radiance evaluation(a) Calibration of the sensitivity
In-orbit calibration of TIR band will be performed using deep-space radiation(equivalent to a radiance temperature of 3 K) and the blackbody on board the satellite(equivalent to a radiance temperature of app. 290 K). The L1 processing algorithm forthis calibration is currently assumed to employ the following methods:
・ The blackbody and deep-space radiances are assigned to the highest level and the lowest
level, respectively, for fitting based on a high-order regression curve. The values
obtained in the ground tests are used as the factors in the high-order terms.
・ Since the sensitivity is subject to the influence of background radiances inside theinstrument, phase correction should be taken into consideration, while at the same time
directing attention to the combination of data to be used in the calibration, the monitored
temperature of the sensor, etc.

B-5

(b) Linearity
The offset and linearity of the response of the optical system, including temperaturedependence, will be checked based on the observation data taken while uniform lightwith different radiance levels is introduced into the FTS optical system. The following
lists up candidate data to be used for this evaluation.
・ Offset: Deep-space calibration
・ Low radiance: Snow and ice
・ Medium radiance: Forestry, oceanography
・ High radiance: Blackbody calibration, deserts, playa(c)Absolute radiance
Similarly to SWIR bands, the absolute radiance of TIR band will be evaluated by thefollowing two approaches:・ To use in-situ data
・ To use global data(i) Using in-situ data
A high-accuracy calibration will be performed by acquiring the atmospheric profile,including temperature of air, water vapor, etc., while targeting the locations where thesea surface temperature is measured with buoys.
(ii) Using global data
The synchronized data are extracted from the data (equivalent to Level 1) acquired bya well-calibrated sensor on board other spacecraft for radiance comparison.
Furthermore, the accuracy of calibration is evaluated over a wide area of the ocean byusing sea-surface temperature and meteorological data on the global scale with a high,consistent accuracy.
Currently, Aura/TES and Aqua/AIRS are listed as candidates for reference satellites inthis comparative evaluation, and NOAA’s sea-surface temperature (SST) analysis of
Reynolds, etc. are planned for the reference database.

(2) Geometric evaluation
Since the same optical system is used for acquiring FTS SWIR and TIR band data, the geometricevaluation of TIR band is conducted following that of SWIR bands.
(3) Evaluation of spectral characteristics(a) Wavelength calibration
The wavelength shift is evaluated by observing known atmospheric absorption bands.
(b) SNR
Targeting a uniform high-radiance range, the SNR is evaluated as to each gain.
following data will be accumulated and used for the evaluation.
・ Blackbody calibration
・ Desert
B-6

TheB-1.5 Calibration of TANSO-CAI(1) Radiance evaluation(a) Calibration of the sensitivity
CAI does not carry any special functions associated with the sensitivity calibration inorbit. Thus, the calibration is performed only with the sensitivity calibration
expression to be obtained in the ground tests. However, the following data will beacquired as solely for the offset (dark signal output).
・ Nighttime observation
・ Optical black element(b) Lunar calibration
The lunar calibration for CAI will be performed on the same orbit as that of FTS. It is
intended to calibrate the sensitivity of the devices of the linear array detectors where
lunar calibration light enters. In this calibration, CAI imagery will be acquired while
scanning an area of ±2.55deg or greater covering the entire moon surface twice in bothways (four scans) continuously at an angular velocity of 0.1 deg/sec or less in the Y-axis
direction.
(c)

・
・
・
・

Linearity
The linearity of the response of the optical system, including temperature dependence, isevaluated based on the observation data taken while uniform light with different
radiance levels is introduced to the CAI optical system. Listed below are candidate
targets that have uniform radiances.
Offset: Nighttime observation, optical black element
Low radiance: Ocean, snow and ice (for B4 only)
Medium radiance: Forestry
High radiance: Snow and ice (B1-3), dry salt lakes (B1-3), desert, playa(d) Absolute radiance
Similarly to FTS, the absolute radiance of CAI will be evaluated by the following two
approaches:・ To use in-situ data
・ To use global data(i) Using in-situ data
The calibration coefficients are determined through optimization based on aerosol datameasured at as many locations as possible by the AERONET (NASA, 2006) and
SKYNET (Chiba Univ., 2006), both of which are deployed worldwide.
(ii) Using global data
The synchronized data are extracted from the data (equivalent to Level 1) acquired by awell-calibrated sensor on board other spacecraft for radiance comparison. Furthermore,
the accuracy of calibration is evaluated by using the ground surface reflectance, aerosolparameters, climatological values, and other physical values (equivalent to Level 2) or
B-7

databases providing these values, acquired by other spacecraft on the global scale with ahigh, consistent accuracy.
Currently, Aqua/MODIS and Aura/OMI are listed as candidates for reference satellites
in this comparative evaluation, and the ground surface reflectance datasets of GOME
(Global Ozone Monitoring Experiment) and TOMS (Total Ozone Mapping
Spectrometer), etc. are planned for the reference database.
(2) Geometric evaluation(a) Pointing accuracy
The geometric accuracy of CAI imagery is evaluated using imagery taken over GCPs
with known coordinates as well as clear radiance boundaries between bright and dark.
The GCP database to be used for GOSAT should be chosen beforehand from coastline
database GSHHS.
The following scenes are to be used in this evaluation:
・ Land/sea boundaries (scenes containing coastal lines also covering projections from theland, such as peninsulas and capes)(b) Band-to-band registration
The offset between bands is determined relatively by evaluating the pointing accuracy
as to each band, as described in (a) above.
(3) Image quality evaluation(a) Calibration of the pixel-to-pixel sensitivity
The coefficients for correcting the pixel-to-pixel sensitivity are calculated byaccumulating data in each pixel direction, deriving the average values, and comparing
the averages in the line direction, using data taken over wide-area targets with uniform,high radiances. Since GOSAT’s swath stretches for 750-1,000 km, it is infeasible toperform the calibration at once. Thus, more than one site must be selected for thecalibration. The following lists up the candidate target sites.
・ Snow and ice (B1-B3), desert(b) MTF
In order to extract edge and point spectra, the MTF is calculated using
geometrically-corrected observation data covering edges, such as coastal lines, andpoint sources, such as islands. Based on the derived MTF, the spatial resolution
dependent on the optical characteristics is evaluated. The following scenes are to be
used in this evaluation:
・ Coastal lines
・ Islands(c)

SNR
Targeting a uniform high radiance range, the SNR is evaluated as to each band detector
B-8and gain. The following data will be accumulated and used for the evaluation.
・ Snow and ice (B1-3), dry salt lakes (B1-3), desert, playa
B-1.6 Preparation for Calibration(1) Examination of the calibration approach with the use of in-situ data
In vicarious calibrations using TANSO observation data and ground observation data, it isimportant to select test sites in view of the uniformity (across the FTS’s FOV of 10 km),
temporal stability, probability of clear sky, and accessibility. The following candidate sites
have been found as satisfactory for the calibration purpose.
・Railroad Valley Playa, Nevada, U.S.A.
・Strzelecki Desert (Tinga Tingana), South Australia, Australia
These sites have been scrutinized in terms of appropriateness as the calibration sites. Railroad
Valley has constantly been used as a vicarious calibration site for Landsat, MODIS, ASTER, etc.
by the University of Arizona for a long time. The OCO project likewise is considering the useof the valley as its calibration test site. Tinga Tingana in Strzelecki Desert is a highly uniform
site where the CSIRO (Commonwealth Scientific and Industrial Research Organisation) of
Australia has set up a part of the AERONET.
Figure B-1-1 below shows MODIS images over Railroad Valley and Tinga Tingana. The redcircles indicate the FTS’s FOV of 10 km when it is pointing at the sites. Each image stretchesfor 30 km×30 km. While the uniform area in Railroad Valley just barely covers the 10-km
FOV of FTS, Tinga Tingana is covered with uniform land that amply extends over the FOV.
Figure B-1-2 plots the probability of clear sky throughout 2004 at these sites, and the graphapparently suggests that the probability drops during wintertime at both sites. Thus, it isdesirable to secure calibration sites in both north and south hemispheres in consideration of thelaunch schedule. It is still under examination whether these sites are selected for GOSAT’s
calibration sites or not.

B-9Railroad Valley

Tinga Tingana

Figure B-1-1 MODIS band 7 (2.1μm) images over the candidate calibration sites(2) Examination of the calibration approach with the use of global data
In order to select most appropriate sites for cross-calibration with data taken by other missions,the spatial uniformity, temporal stability, etc. at the candidate sites are evaluated based on theexisting global data observing these sites.

Figure B-1-2 Clear-sky rate at the candidate calibration sites(Aqua/MODIS data in 2004)

B-10

Figure B-1-3 indicates an average reflectance distribution on the 5 x 5 pixel basis (app. 25
square kilometers) of MODIS band 7 (2.1μm) data and the standard deviation among 25 samples.
The samples were retrieved from the global reflectance data (average of 16 days) of MODIS on
board Aqua and Terra. There are several spots with uniform reflectance in the Sahara Desert
and the Rub’ al khali Desert. In addition, as the reflectance in this band is susceptible to soil
moist and decreases with it, a high reflectance is obtained only in deserts or bare lands.

Figure B-1-3 Survey on the spatial uniformity using the ground surface reflectancedata acquired by MODIS band 7 (2.1μm)
Upper: Average reflectance of 5×5 pixels (app. 25km)
Lower: Standard deviation of 25 samples
Figure B-1-4 shows an annual average of the ground surface reflectance in the Sahara Desert (ofapp. 22 samples), and the standard deviation for the year. POLDER (POLarization and
Directionality of the Earth's Reflectances) targeted the sites marked with x, namely Egypt 1(N27.12, E26.10) and Algeria 3 (N30.32, E7.66), in its vicarious calibration. (Hagolle, 1999)
Figure B-1-5 plots the reflectance at Egypt 1 and Algeria 3 during the year in the time series. It
reveals that those sites selected by POLDER have a high temporal stability and, as shown in
Figure B-1-3, a high spatial uniformity.
Based on the analyses of these existing data, the GOSAT Project will select the most appropriate
sites for its calibration activities in light of the resolutions and swaths of TANSO-FTS and CAI,
and collect data accordingly.
B-11

Figure B-1-4 Investigation on the temporal stability based on the ground-surface
reflectance data of MODIS band 7 (2.1μm)
Upper: Annual average (app. 22 samples)
Lower: Standard deviation

Figure B-1-5 Chronological plotting of the ground-surface reflectanceat the specific observation points for one year
Left: Egypt 1 site
Right: Algeria 3 site

B-12

B-2 GOSAT/TANSO Validation Plan
B-2.1 Basic philosophy for the validation“Validation” of GOSAT products means an evaluation of uncertainties of GOSAT L2, L3 and L4
products, as provided in Table 1 of the Research Announcement document*, compared with otherdata with less uncertainties that were acquired independently of GOSAT. “Comparison”, on theother hand, means an evaluation of uncertainties of GOSAT products against observation data withequivalent uncertainties or data estimated by simulation models; thus it should be distinguished from“validation” above. Both evaluation methods, however, are intended to assess the data quality of
GOSAT products (data quality assurance), and at the same time play a significant role in evaluating
the appropriateness of the data processing algorithms. Therefore, any findings from the evaluations
will be reflected in revising the algorithms, as necessary.
Additionally, the “calibration” is an evaluation of L1 product data to be performed mainly by JAXA
and focuses on calibration of radiance spectra (e.g., absolute radiance, linearity, offset, wavelength,
instrument function, SNR, etc.) However, it excludes an evaluation of spectral parameters and the
Fraunhofer lines, which are necessary for retrieval of the CO2 and CH4 column abundances based on
the radiance spectra obtained from TANSO-FTS observation data, since these values have been
evaluated at the algorithm development stage.
In formulating a validation plan for GOSAT TANSO, it is important first to assign priority orders to
the validation items because the manpower and budget for observation and analysis activities inconnection with the validation are not unlimited.
The appropriateness of the processing algorithms must be verified prior to the launch of the satellite.
This evaluation is called “algorithm validation”. The algorithm validation has been conducted
through observational experiments by the FTS sensor installed at a high elevation and on an aircraft.
These observational experiments must continually be performed in the future to improve thealgorithms.
After launch, another important evaluation, in addition to product validation, is to verify theappropriateness of parameters, such as optical characteristics of aerosols, which are relevant to errors.
This post-launch evaluation is called “parameter validation”. Although GOSAT makes greatersocial contribution with its higher-level products than lower-level products (L2), validation of thelatter is of primary importance as it provides the foundation for generating the former. Thus, it ispreferred to perform validation of lower-level products first followed by that of higher-levelproducts.
The priorities of GOSAT product validation and comparison have been set as follows:(1) L2 SWIR CO2 and L2 SWIR CH4 column abundances(2) L2 TIR CO2 and L2 TIR CH4 vertical profile of concentration(3) Global distributions of L3 SWIR CO2 and CH4 column abundances(4) Global distribution of L4A CO2 flux(5) Global distribution of L4B CO2 concentration
B-13

uncertainty = (accuracy) 2 + (precision) 2 accuracy = bias
The basic policy on collection of validation data is to prioritize the use of diverse observation data
being acquired routinely in all parts of the world, considering that the GOSAT itself observes theentire earth on varied conditions in terms of ground surface, meteorology, and atmosphere. To thisend, certain specific observation points will be set as “super sites” for focused and continued
observation for the validation purposes of products and algorithm, and necessary observing
equipment are installed at these sites. Furthermore, campaign observations will be planned andcarried out, which include air-borne observation on various meteorological conditions.
The data to be validated are those that have been taken on the following geographical andmeteorological conditions:a. Land area with clear sky
b. Sea area with clear sky (sunglint observation)c. Land area with thin cirrus clouds and aerosols
d. Sea area with thin cirrus clouds and aerosols (sunglint observation)*Excluding areas covered with thick clouds.
In addition, the validation must be conducted in light of certain standards for match-up conditions interms of space and time.
Of all the analytical work in the validation, NIES will be responsible for the basic validations
analysis and incorporation of the results into the revision of algorithms, as part of the GOSAT
Project. In the meantime, it is expected that more research activities concerning the validation
analysis of the GOSAT data products will be carried out by the GOSAT Science Team members,scientists participating in the RA, and other users at large.
B-2.2 Experimental observation for the algorithm validation
The processing algorithm to derive the CO2 column abundance must be verified prior to the launchthrough experiments simulating the satellite observation geometry, more specifically, by observing
solar light reflections from the earth surface with an FTS, a similar sensor to the one on board thesatellite, installed at a high-elevation ground point or on board an airplane.
(1) Observation at a high elevation
NIES carried out two observational experiments using an FTS sensor, similar to TANSO-FTS,
installed near the summit of Mt. Tsukuba Japan at an elevation of 800 m in 2005 and 2006. In
these experiments, the CO2 concentration calculated from the data acquired by FTS was comparedwith the measurement made by a light airplane, which took off from near the farmland close to thefoot of the mountain and flew up to an altitude of 3,000 m carrying the CO2 in-situ instrument. The
results demonstrated an accuracy of about 1% of the FTS’s observation with respect to the CO2column abundance in the atmospheric layers at an altitude of 3 km and lower. It is vital to continue
observational experiment in this manner on various meteorological conditions in the future, pursuing
B-14

an improved accuracy.
(2) Air-borne observation
An algorithm validation is made by the spectroscopic observation using the FTS mounted on theaircraft at a very high altitude, simultaneously with the in-situ CO2 concentration measurement
onboard an aircraft. This method more directly simulates the behaviors of the FTS on board thesatellite in nadir looking observation from a very high altitude than the observation at ahigh-elevation ground point, although the vibration of the aircraft remains as a problem.
B-2.3 SWIR/TIR Product Validation(1) Validation of CO2 and CH4 column abundances by SWIR observation
The observing instrument to be used for validating the CO2 and CH4 column abundances must be
based on fully-established technology with no bias, assuring data quality as well as achieving an
excellent observation accuracy of about 1 %. An observation method which uses absorption of
direct solar light is the best technique for observing the column abundance directly. Thus, ahigh-resolution FTS installed on the ground proves to be the most appropriate method among all
available measuring instruments. FTS can observe spectrum anytime as long as there is direct solar
irradiance for approximately 10 minutes.
The footprint of TANSO-FTS extends for as long as 10.5 km. In order to reduce observation errors,
observation points where the surface cover is flat and uniform within this size are ideal for the
purpose of the validation. Some of FTS’s observation points are situated in mountainous areas;thus it is essential to collect surrounding information of the observation points and select flat areasthat will least contribute to observation errors.
If there is an obvious bias in the TANSO-FTS retrieval results or if the measurement accuracy falls
below a certain level, it is necessary to identify the cause of the error and improve the dataprocessing algorithm. Of the various parameters that affect the retrieval of column abundances,namely cirrus cloud, aerosol, surface albedo, air pressure, air temperature, water vapor, andconcentrations of other gases, the effects of cirrus cloud and aerosols are the most dominant. The
surface albedo can be obtained fairly accurately from the TANSO-FTS observation data by means ofa retrieval analysis and it does not substantially affect the derived column abundance value.
Therefore, the priority of the surface albedo is set low. Furthermore, the priority of meteorologicalparameters, such as air pressure, air temperature, and water vapor, is also low since they are usuallytaken from meteorgical reanalysis data.
Measuring cirrus cloud and aerosol requires i) a sky radiometer that can estimate the optical
thickness, the grain size distribution and the complex refraction index averaged in the nadir direction
and ii) a polarized lidar that can identify the vertical distribution of cirrus clouds and aerosols anddistinguish between sphericity and non-sphericity. Thus, it is important, in terms of validation
strategy, to set up these instruments at the ground based FTS observation sites to enable
simultaneous observation.
The vertical distribution data directly measured (sampled and analyzed) by a taking-off and landing
B-15

regular passenger airplane provide an effective reference for the derived CO2 column abundance.
However, this measurement can gather data for the vertical profile of CO2 concentration between the
ground level and an altitude of approximately 11 km. As about 22 % of CO2 exists above the
11-km altitude, other methods to either correctly estimate or measure the CO2 level above thisaltitude are needed for calculating the column abundance. If the fluctuation of CO2 abundance inthe higher altitudes remains within 4 %, the model climatological values derived from the past actual
measurements can be used. Furthermore, CO2 concentration on the ground surface needs to bemeasured in order to ascertain the concentration between the ground level and the minimum altitude
where aircraft can measure. Moreover, it is desirable to use the sky radiometer and lidar in thevicinity of the validation sites for measuring cirrus cloud and aerosol. At some airports, however,
the air is significantly contaminated. Therefore, meteorological conditions of the sites must be
carefully examined when selecting validation sites.
As for CH4, there is a possibility that air-borne observation (bottle sampling) data is effective.
Moreover, it can be effective in validation as there are most recent data up to an altitude of about 35
km based on balloon observation.
Sunglint observation basically takes place on the ocean. However, validation of product bysunglint observation may be replaced by data acquired by a high-resolution FTS installed nearcoastal lines and/or data obtained by aircraft flying above the vicinity of coastal lines.
WDCGG provides ground-based CO2 and CH4 measurements. This dataset may well serve as
collateral evidence if used with consideration given to seasonal variation and spatial
representativeness. Among others, in the south hemisphere, where the seasonal variation ofconcentration is very small, this dataset is highly effective and may even serve as validation data.
One of possible scientific validation methods is to synthesize (or assimilate) the CO2 distribution in
the surrounding of the observation point based on the concentration profile measured by air-borne
using regional atmospheric transport models, calculate the concentration profile up in the sky overthe flat place with uniform albedo, which corresponds to the GOSAT observation point, and compare
the findings with GOSAT product. However, the appropriateness of the method itself needs to beverified, first of all, and there are several other problems that remain to be addressed with thismethod.
The following sets forth policies concerning validation data collection.
・Install a number of observation instruments (high-resolution FTS, lidar and sky radiometer)at several specific observation points and perform observation with priority at these “focal
observation points”.
・Effectively utilize “campaign observation with aircraft if necessary” for observation data onsuch meteorological and ground surface conditions that are not covered by the “focal
observation points”.
・Utilize the observation data routinely acquired, such as those taken by the existinghigh-resolution FTS installed on the ground, air-borne observation data, and WMO
WDCGG ground observation data, as the GOSAT observation coverage is the entire globe.
・The column abundances in sea areas are derived based on sunglint observation. As theconcentration variation is smaller in sea areas than land areas, data covering the validation
B-16

sites on the ground that are located near the sea can be used with consideration given to thewind direction. Moreover, observation data acquired in islands and by vessels can also be
used for indirect evaluation.
Based on the above policies, data at typical observation points are acquired; the specific criteria for
selecting such observation points can be summarized as follows:・Latitude: low , middle , high・Amount of water vapor: high, low
・Albedo: uniform, nonuniform
・Aerosols: variant, invariant
At present, if 10 validation points for ground-based FTS observation and another 10 for aircraft
observation can be acquired, minimum requirements in the validation can be satisfied. The total 20
are expected as sufficient to minimally cover the above conditions. However, if a handy validation
observation instrument which satisfies the validation requirements is developed, more points may be
selected and the validation can more largely be deployed.
Data measured at each observation point will be evaluated in light of both temporal and spatial
variations to identify the uncertainties in the products. However, the evaluation of biases requires
roughly three months at the sites where seasonal variation is small and six months in general. The
evaluation results will be sorted according to the above criteria and quality will be assured by data
category. In case that this approach is difficult, alternative effective methods include a trajectory
analysis with consideration given to temporal and spatial variations and a validation analysis basedon regional CO2 transport models.
The following describes specific plans of observation and data acquisition for the validation purpose.
a) Validation by FTS observation(i) Observation by ground-based high-resolution FTS
Observation by ground-based high-resolution FTS will be performed at several observation
points in Japan, on the regular basis.
In conducting the validation, it is additionally useful that the observation data acquired by
the ground-based high-resolution FTSs are analyzed and evaluated using the same dataprocessing algorithm (radiative transport equation) as the one used for the analysis of
TANSO-FTS.
(ii) Utilization of data acquired by ground-based high-resolution FTS networks etc.
Data from the ground-based high-resolution FTS observation networks will be used.
The Project will also arrange the use of data at other observation points through direct
negotiation with the pertinent data providers, RA-based joint researches, and so forth.
When selecting ground observational sites for the GOSAT validation, the most ideal sites at
the initial validation stage should preferably have flat and uniform surface and extend for awide range commensurate with the 10.5-km footprint of TANSO-FTS, whereby error
factors can maximally be avoided.
B-17

Thus, the validation sites will be selected based on the following criteria.
・Seasonal variation: small (south hemisphere)→ large (north hemisphere)
・Air pollution: minor → major・Land surface: simple → complex
The options are:・Sunglint
・Snow and ice(iii) Observation by small FTSs
If moving observation is necessitated, these small-sized FTS can be used, after
evaluating the measurement accuracy, data quality and operational stability.
b) Validation by air-borne/balloon-borne observation(i) Utilization of data from the air-borne observation
The continuous CO2 measurement equipment on board aircraft acquires the spatial(horizontal) distribution of CO2 concentration at very high altitudes and the vertical profiles
CO2 concentration around the airports, since it can acquire data while not only flying
horizontally but also taking off (ascending) and landing (descending).
Additionally, as aircraft travels in the horizontal direction for approximately 100 km while
ascending up to an altitude of about 10 km where it flies horizontally, and 200 to 300 km
while descending from the stable altitude, spatial representativeness of the concentration
should be taken into consideration at the time of analysis. To this end, transport models
can be used for this evaluation. Furthermore, since the concentration in the lower
atmosphere near the airport grows due to effects from the urban air in many cases, it isnecessary to judge effectiveness of data in view of the wind direction. Moreover, thefluctuation of the CO2 concentration in the layers above the highest altitude that the aircraft
can reach must also be evaluated. So far, the findings from balloon-borne observation forthe stratosphere have revealed that the fluctuation of the column abundance is around 0.5％,
very roughly. More details will be investigated in continued studies to follow.
(ii) Data acquisition by balloons
Balloon-borne observation data, including the past data, must be obtained in order toascertain the characteristics of the variation of the CO2 column abundance in the layers
above the upper limit of air-borne observation.
c) Others(i) Observation by small balloons
The CO2 sonde to be installed on board a small-sized balloon, which is being developed,
may be used for the validation after evaluating the measurement accuracy, data quality andoperational stability and ensuring that it is practical in terms of cost, etc.
(ii) Observation by compact spectrometer
Fabry-Perot Etalons based spectrometer, currently being developed, may be used for thevalidation after evaluating the measurement accuracy, data quality and operational stability
and ensuring that it is practical in terms of cost, etc.
B-18

(2) Validation of CO2 and CH4 products by TIR observation
The data acquired for validating L2 SWIR CO2 and CH4 will also be used for validating L2 TIR CO2
and CH4 products. Additionally, the validation will be more effective if combined with airtemperature, air pressure, humidity profile, and ground emissivity data. As for nighttime
observation, the data already acquired will be utilized as far as possible. The validation plan will
be further detailed in consultation with the parties responsible for TIR.
In addition, since air temperature and H2O and O3 concentration profile by TIR are products to begenerated internally by JAXA for the research purpose, JAXA will carry out necessary evaluations
on data quality.
(3) Comparison in the global distribution of CO2 and CH4 column abundances based on SWIR
observation
L3 products do not require special evaluation since they are derived by temporal and spatial
averaging of the validated L2 products.
(4) Comparison of CO2 flux
The global distribution of L4A CO2 flux and L4B CO2 concentration are positioned as subject tocomparison due to the following reasons, and it is preferred that these are evaluated as part ofresearch activities, including RA, instead of validating in the Project.
・L4A and L4B are both calculated by models.
・The reliability of the transport models to be used is not firmly established and is still underdiscussion among scientists. Ensemble averaging among multiple models will enable a
comparative evaluation.
・Flux observation is intended for the research purpose, and it requires substantial efforts to obtainthe necessary data.
・The comparison of the flux observation with models requires scaling-up, which is a process stillat the research level.
・The sea flux varies with the exchange coefficient.
L4A products provide an estimation of the monthly average of CO2 flux in each of the 64 regions
into which the globe has been divided.
As for comparison of L4A products with other observation data, data acquired by vessels are
effective since the flux in sea area (latitude 5° × longitude 5°) is regarded as almost uniform.
On the contrary, the flux in land area is calculated based on the mesh size of latitude 1°× longitude
1° in the calculation process, in assumption of the flux distribution patterns within the regions. On
the other hand, the ground-based observation of CO2 flux is made on the “point” basis, with asignificant regional difference and the smallness in number and spatial unevenness of theobservation points, and thus it is difficult to use these points directly for the validation of L4A
products. In order to solve this problem, a scaling-up method using land-area ecosystem models
plays a vital role. Many countries, including Japan, have been engaged in research on such
scaling-up methods and further progress in this effort is expected to be seen in the near future.

B-19

As for research on CO2, the following comparisons can be conducted.
a) Use of data on the CO2 flux between the air and the ocean
The CO2 flux between the air and the ocean is calculated by measuring the partial pressuresof CO2 in the surface sea water and in the air and applying the exchange coefficient. The
exchange coefficient depends on the wind velocity, temperature of water at the sea surface andsalinity.
b) Use of the observation data acquired at flux monitoring sites
There are several flux monitoring sites in Hokkaido, and although there is a problem in theunevenness in topography and vegetation, the data obtained there by utilizing the land-area
ecosystem model may possibly be used in comparison with the flux (L4A) in GOSAT global
carbon balance estimation model.
(5) Comparison of the global distribution of CO2 concentration
L4B products to be offered are a monthly average of 3D concentration distribution obtained asmesh data of latitude 1°× longitude 1°. The comparison of the L4B products with otherobservation data is made on the one-hour value or monthly average value of the latitude1°×
longitude1° grid, which is the base data of the L4B products. As for the reference data, thedata used as the reference in the L2 validation (column abundances acquired by theground-based FTSs and concentration profile acquired by air-borne observation) and dataacquired by several other kinds of ground and marine observations can be generally andcomprehensively utilized.
(6) Comparison with other satellite data
Comparison with CO2 and CH4 column abundance data acquired by other satellites, such as the OCO,
is instrumental for evaluation of the data quality of GOSAT products.
a) OCOOCO is scheduled to be launched in December 2008 by NASA/JPL (Jet Propulsion
Laboratory). It will observe the CO2 column abundance in short wavelength-infrared bands,
as with GOSAT. The satellite will fly at the forefront of the so-called A-train constellation of
the U.S. EOS program and it can obtain necessary physical quantities, such as aerosols, fromthe other member satellites. Therefore, it focuses only on observation of the CO2 (and O2)
column abundance.
OCO’s spectrometer is a grating type and the observation bands are 1.61, 2.06 and 0.76 μm,
which almost coincide with those of GOSAT’s.
In the future, it is necessary to scrutinize the possibility of concluding a cooperative agreement
or framework between the two missions and examine detailed methods of data acquisition andother procedures.
b) SCIAMACHYSCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY)
B-20

is an on-board sensor of the ENVISAT of the ESA. Its primary purpose is to observe theatmospheric trace components necessary for chemistry in the troposphere and the stratosphere.
The spectrometer is a grating type with eight channels sensitive to ultraviolet, visible, andshort wavelength infrared bands. The observation modes range from nadir, solar/lunar
occultation, and limb scattering. It observes both the concentration profiles and column
abundances of O3, CO, CH4, etc.
In addition, as the derivation of CO2 is also being attempted, it may serve as effective
reference for comparison with the GOSAT data.
Even other satellites that are not originally intended to measure greenhouse gases, such as
AIRS and IASI, can also be used as referential data sources.
B-2.4 Validation of parameters related to error factors in SWIR observation(1) Aerosol, thin cirrus cloud
In order to evaluate the appropriateness of the L2 processing algorithm for TANSO-FTS (SWIR)
data, the parameters related to error factors, namely the optical characteristics of aerosols, such as
optical thickness, wavelength index, and single scattering albedo, and the vertical distribution, areextracted via the networks referred to hereunder or otherwise, in addition to the validation of data
quality. It must be noted, however, that it takes a certain lead time for the latest data to be uploadedon the Website, and hence in case that it is urgent to obtain the data, a request for data acquisition
must be made directly to the observer.
Furthermore, it is necessary to install sky radiometers and lidars at those locations where
ground-based FTS or air-borne observation is carried out. The lidar can measure the vertical
distribution of aerosols and thin cirrus clouds with an accuracy of approximately 15 m, anddistinguish between sphericity and non-sphericity based on the extinction of polarization, thereby
identifying whether the substance is rain cloud, cirrus cloud, or sand dust. The sky radiometermeasures the direct solar irradiance and forward scattering in the sky. The measurements can also
be used for estimating not only the optical thickness, particle size distribution, and complex
refractive index, but also the single scattering albedo and phase function. These data are useful tothe validation of TANSO-CAI products.
(2) Ground surface reflectance
The accuracy of the ground surface reflectance retrieved from SWIR data will be confirmed with theuse of the following data. The observation points for this purpose must be selected where the land
surface is homogeneous.
a) MODISMODIS (Moderate Resolution Imaging Spectroradiometer) is an optical sensor on board Terra
and Aqua, NASA’s earth observing satellites. It observes a wavelength range of 0.4 to 14 μm
in 36 bands with a 2,330 km swath and spatial resolutions of 250 to 1,000 m. The Science
Team at NASA developed the processing algorithms and each data center is generating
various products including the ground surface reflectance.

B-21b) ASTER
ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) is an opticalsensor on board Terra, NASA’s earth observing satellite. It consists of the Visible
Near-Infrared Radiometer (VNIR), Short-Wave Infrared Radiometer (SWIR) and Thermal
Infrared Radiometer (TIR). It observes a wavelength range of 0.52 to 11.65 μm in 14 bands
with a 60-km swath and spatial resolutions of 15 to 90 m. The standard products generated
by the Japan side include the ground surface reflectance, land surface temperature, land
surface emittance and DEM.
(3) Oxygen column abundance
The oxyten column abundance, obtained in Band 1(O2 A band in 0.76 μm), will be validated.
a) Ground air pressure and rawinsonde data
The validation will be performed using the data routinely taken at observation points for theupper atmosphere together with new observation data to be acquired as necessary. The
rawinsonde data will also be used for addional other validations.
b) Meteorogical data reanalysis
Since the observation points for thte upper atmosphere are not evenly distributed among theoceans, developing countries and polar areas, meteorogical reanalysis results are also used in
the validation.

B-2.5 Validation of CAI Products
TANSO-CAI is a supplementary sensor to TANSO-FTS. In other words, the CAI products(concerning parameters related to error factors) that relates to the validation of TANSO-FTS L2
products should be validated with a priority because these CAI data are necessary for generating
TANSO-FTS L2 products. On the other hand, the validation of the other CAI products is rated at alower priority, while, in the meantime, the validation of cloud mask products is quite essential.
CAI L1B products are generated by NIES, and the evaluation of the position, band-to-bandregistration, radiance, etc. is extremely important.
Since the CAI products and validation data of parameters related to error factors in short wavelength
infrared are common in part, the detailed validation plan will be determined in coordination with theparties in charge of CAI.
B-2.6 Campaign Observation
Air-borne observation by the direct observation instrument is important to be performed
simultaneously with observation by the remote sensing instruments, such as FTS, lidar or otherwise,in order to confirm the accuracy of TANSO-FTS measurements.
The evaluation will be performed as to whether temporal variation of the accuracy of each
instrument is ascertained, by acquiring high-accuracy CO2 concentration profile data by the aircraft
which will ascend to a high altitude in synchronization with the satellite and calculating the column
B-22

abundance obtained therefrom. The CO2 concentration above the highest altitude where the aircraft
can reach varies with the altitude of the tropopause. Therefore, it is crucial to calculate the altitudeof the tropopause correctly. To this end, interpolation of simultaneous observation data taken by
the rawinsonde or meteorological reanalysis data is performed. It is also needed to measure theCO2 concentration at the ground level, because the aircraft cannot measure the concentration
between the land surface and the lowest altitude which the aircraft can observe.
Moreover, it is considered as effective to simultaneously carry out direct observation by aircraft on
aerosols, which act as error factors.

Figure B-2-1 Concept of the validation observation for CO2 & CH4 column abundancesB-23

B-2.7 Validation Schedule
Table B-2-1 lists the validation schedule based on the assumption that GOSAT will be launched
January 2009.
This schedule is a plan for preparing the validation activities and securing the necessary data, as of
the issuance of this document.
Table B-2-1 Validation Schedule

First half of2007
4Second half ofFirst half ofSecond half ofFirst half of
2007
2008
2008
2009
9 10
34
9 10
34
9

Survey and plan for validation
Calibration of ground‐based high‐resolution FTS
Evaluation of the validation data and acquisition
Planning of validation analysis methods
Evaluation of ＪＡＬ project data
Construction of validation data processing and acquisition system
Examination of validation data processing and acquisition system
Preparation of observation for validation
LaunchExamination of validation processing
system using GOSAT data（3 months）
Initial validation（ 3 months）
Substantial validation
Field observation for algorithm
verification before the launch

B-24

Field campaign observation

B-3 Overview of Processing Algorithms
This document describes processing flow and basic concepts of processing algorithms for
GOSAT/TANSO data
B-3.1 Overview of the overall processing system
Figure B-3-1 shows an overview of the overall data processing flow together with the data level ofthe product produced at each step. More details of the processing levels (L1, L1A to L4B) of the
GOSAT/TANSO data products are given in Table 1 of the RA Document.

L1A

L1B

L1→L2

L4B

L4A
L2
↓
L3

Figure B-3-1 Data processing flow and data product levels
The data measured with the TANSO-FTS and TANSO-CAI sensors are processed to several kinds ofproducts according to the flow given in Fig. B-3-1. Interferograms (FTS L1A), observed values by
FTS, are converted into spectra (FTS L1B), while the CAI L1 data are processed to cloud andaerosol properties (CAI L2). These data, at observation points under almost clear sky conditions,are combined to estimate the column abundances of CO2 and CH4 (FTS L2), and further to draw a
global concentration map (FTS L3), and still further to estimate global carbon flux (emission andabsorption ) distribution (L4A) and three dimensional (3D) distribution of CO2 (L4B) after analyses
utilizing the atmospheric transport model.
The following sections of this Appendix outline the data processing steps and algorithms for the FTS
and CAI data, focusing on L1 and L2 processing.
B-3.2 Level 1 processing of the TANSO-FTS data
(1) L1A data (interferogram)
B-25

L1A data consist of the interferograms of both observation data (the scattered light byearth-atmosphere system) and calibration data (the solar irradiation from outer space using thestandard solar diffuser of the TANSO sensor), time data, mission telemetry data (temperatureinside the instrument, pointing angle of the tracking mechanism, etc.), scale-conversion-relateddata, and so on. The L1A data, however, are regarded as “internal products”, and will not bereleased to general users, but a part of them will be provided for the RA Investigators who
research on themes in the field of calibration/validation or development of algorithms.
(2) L1B data (spectrum)L1B data consist of basic data (number of datasets, gain value, scanning direction, etc.), spectraof observation data (voltage value per wave number [V/cm-1]) for the short wavelength infrared“SWIR” bands, and spectral radiance [W/cm2/cm-1/str] for the thermal-infrared (“TIR”) band),calibration data, instrument function, time data, mission telemetry data, scale-conversion
coefficients, quality data, geometric information data (the latitude/longitude of the center of theobservation point), and so on. Further, the calibration data on SWIR sensitivity will be
provided.
(3) Overview of L1A to L1B processing
The data of the SWIR bands (Bands 1, 2, 3) are processed in the following steps.
・Engineering value conversion. (Conversion from discrete-valued digital numbers to voltage
values)・Spiky noises are detected and corrected. Basically, no non-linear correction is performed on the
SWIR band data, though the correction function itself is equipped.
・The zero path difference (ZPD) position in the above interferogram is detected.
・Fourier-transformed.
・A flag is generated by confirming the low-frequency components in the spectrum. (A flag is set
when the spectrum contains large values around the low-frequency region, to indicate that the
FOV fluctuated and/or small vibration occurred during the scanning.)
・(In case that a flag is set) the interferogram is corrected by removing the low-frequency
components of spectrum.
・By applying a given window function to decrease spectral resolution, the data are complex
Fast-Fourier transformed (FFT) every 0.2 cm-1. The phase angle is calculated from the ratio
between real and imaginary parts after the transformation, while the phase information isderived from the transformed values.
・The interferogram is now zero-filled to yield 76,545 (= 37×5×7) data points (after correction of
the low-frequency components), complex Fourier-transformed without phase correction, androtated by the phase angle derived from the above to produce the phase-corrected spectra(spectra of the real part). Note that the L1B data to be distributed will contain both real andimaginary parts.
The data of the TIR band (Band 4) are processed in the following steps. However, these steps
represent just a method, and are subject to change in the future.
・Engineering value conversion. (Conversion from discrete-valued digital numbers to voltage
B-26

values)・Spiky noises are detected and corrected, followed by non-linear correction after subtracting
direct current (DC) components.
・The zero path difference (ZPD) position in the above interferogram is detected, FFT shifted.
・(Similarly to the SWIR data) the necessity for correction for the low-frequency components
due to FOV fluctuation is checked from their spectrum without phase correction, and thecorrection is made if necessary.
・After the phase correction, the number of data points in the interferogram is adjusted to 38,400(= 2９ ×3×52) through zero-filling, and the data are Fourier-transformed. Furthermore, byusing the deep-space and blackbody observation data in the TIR band, observation spectral
data (the real part data after Fourier-transformation) are converted into spectral radiance(W/cm2/cm-1/str).
As for Bands 1, 2, 3, if the interferogram exhibits a DN value of 65,400 or larger at the ZPD position,
the data are regarded as saturated and a quality flag is set. As for Band 4, if the digital DN at the
ZPD position is 65,400 or larger or 136 or smaller, the interferogram is regarded as saturated and aquality flag is set.
Moreover, the wavelength calibration is performed for the TANSO-FTS, due consideration to (i) the
oscillation wavelength (1310 nm (nominal)) of the semiconductor laser varies with the temperature,and (ii) the alignment may be affected by the temperature variation in orbit.
B-3.3 Level 1 processing of the TANSO-CAI data
TANSO-CAI has four observation bands: Bands 1-3 have a wavelength width of 20 nm, spatial
resolution of 0.5 km, and 2,000 elements, and Band 4 (the center wavelength is 1.60μm) has awavelength width of 90 nm, spatial resolution of 1.5 km, and 500 elements.
L1A data are provided with information necessary for radiometric correction and geometriccorrection.
L1A data ,however, are classified as internal products of the Project, and will not be released togeneral users. However, some of them will be provided for the RA Investigators who carry out
research on calibration/validation or development of algorithms.
(1) Radiometric correction
L1A digital data are converted into radiance values (W/m2/μm/str), using scale conversion
coefficients. Since the detectors are of diode type, it is, in principle, not necessary to perform
non-linear correction of the output values. In addition, the gain setting for the CAI observation
bands will be adjusted, based on the gain switch table to be generated on the monthly basis, so
as to avoid saturation of output signals.
(2) Geometric correction
Information on the relative scales (expansion, compression and rotation) for datasets of different
B-27

bands makes it possible to determine the band-to-band registration. By making Band 3 thereference, other bands’ data are expressed relatively as the displacement from the reference.
The number of center pixels for Bands 1-3 is 1,024, and that for Band 4, 256, and the
band-to-band registration error after correction is targeted at 0.2 pixel or lower. In addition, L1
data are supplemented with the latitude and longitude information of the representative
elements.
(3) L1B data
TANSO-CAI L1 data are supplemented with the above-mentioned information necessary forcorrection before release. L1B data are generated as standard products with the observation
positions corrected, after scale conversion based on the information, band-to-band registration,and ortho-rectification per pixel based on the elevation information (Digital Elevation Model:
DEM).
(4) L1B+ data
CAI L1B data are then projected on a map, on a certain scene scale, and their stored radiancedata per pixel/band are resampled to generate L1B+ image data (standard products) for release.
B-3.4 Level 2 processing of the TANSO-CAI data
The CAI data are processed to standard products which provide cloud flag information.
Research products, which provide parameters of cloud and aerosol characteristics, are derived
from these products.
First of all, optically thick clouds on the sea surface and on relatively dark land surfaces are
discriminated by using two visible bands of the CAI sensor. If they are found to be clouds,
specifically water clouds, cloud characteristics are analyzed. The cloud characteristics to be
estimated are the cloud optical thickness (at a wavelength of 0.5µm) τc, which is a non-dimensional
value that represents the optical thickness of clouds, and the effective radius of a cloud particle τe.
Table B-3.4-1 lists up the cloud products to be derived from the CAI data.

B-28

Table B-3.4-1 Cloud products derived from the CAI sensor
Estimated parameter
Cloud flag

Unit

Band
No.

Remarks-

2, 3, 4*2, 4

Optically thick clouds on the sea
surface and relatively dark land
surface
Water clouds and ice clouds

2, 4Water clouds and ice clouds

Cloud optical
thickness (@0.5µm)
Effective radius ofµm
cloud particles
Vertically integrated
g/m2
total amount of cloudwater* Band 4 will be used for studies.

2, 4Secondly, aerosol characteristics are analyzed by combining data from all CAI observation bands
with ancillary data, including meteorological data. There are various types of aerosols existing on
the globe; the primary aerosols include anthropogenic aerosols, such as sulfates, black carbons, andorganic carbons, and dust aerosols and sea salt aerosols. In estimating the aerosol characteristics, it
is assumed that anthropogenic aerosols are composed of internal mixing of sulfates and black
carbons, and the three types of aerosols, i.e. anthropogenic, dust, and sea salt aerosols, are mixed
externally to constitute a particle system. Based on these assumptions, the optical thickness of eachtype of aerosol (at a wavelength of 550nm), τa, and the component ratio (volumetric ratio) of black
carbon to anthropogenic aerosols, γsoot will be estimated. These are summarized in Table B-3, 4-2.

Table B-3.4-2 Aerosol parameters estimated from the CAI data
Estimated parameters
Anthropogenic aerosol mode
Aerosol optical thickness
Dust aerosol mode
(Wavelength: 550nm)
Sea-salt aerosol mode(over the sea only)*
Volumetric ratio of black carbons in the anthropogenic aerosol mode

τacm
τdst
τslt
vsoot
*Except sunglint region

The following provides an outline of individual processing algorithms.
(1) Cloud flag algorithm
Multi-wavelength imagers, such as MODIS and GLI, have water vapor channels and infrared split
windows to discriminate altostratus and cirrus, in addition to many visible channels, and thus canaccurately discriminate clouds as a single sensor. In contrast, the CAI sensor has only four bands
with a wavelength range of near-ultraviolet to short wavelength infrared, making its discrimination
accuracy potentially inferior to MODIS or GLI. For this reason, users of cloud flags arerecommended to appropriately select and employ the several types of cloud discrimination test
B-29

results provided by CAI and the cloud flags provided separately by FTS observations and others.
Of the CAI observation bands, Band 2 (0.670µm) and Band 3 (0.865µm) are the primary bands fordiscriminating clouds. Although it is possible to use the short wavelength infrared 1.6µm band
(Band 4) to discriminate between ice clouds and water clouds in the presence of optically thickclouds, this is currently at the examination stage. Two types of threshold-value tests are currently
planned using the cloud flag algorithm: tests to examine the reflectances in visible bands 2 and 3 anda color test for the ratio of the reflectances between these two bands. The former is adiscrimination method that utilizes the fact that the reflectance on clouds is higher than that on thesea surface or on relatively dark land surfaces, while the latter stands on the fact that the reflectanceson clouds in Bands 2 and 3 are almost equal.
The CAI cloud flag algorithm will be used to conduct the four tests listed in Table B-3.4-3 below,
and the test results will be stored as data.

Test No.
Test 1
Test 2
Test 3
Test 4

Table B-3.4-3 CAI cloud flag tests (Draft)Contents to be implemented
R[B2] > (R2+A[B2])R[B3] > (R3+A[B3])0.9 < (R[B2]/R[B3]) < 1.1
If “true” on Test 1 and Test 3, examine R[B4]/R[B2].

Here, R[B2], R[B3], and R[B4] represent the reflectance in CAI Bands 2, 3, and 4Note 1), respectively;
A[B2] and A[B3] represent the ground-surface albedo in Bands 2 and 3; and R2 and R3 are themargin values of the ground-surface albedo. Tests 1 to 3 diagnose the possibility that object pixels
are clouds. The results of Test 4 provide information conducive to discriminating between ice
clouds and water clouds, on an examination basis. The accuracy of cloud flag achieved by the CAI
sensor alone may be subject to the following limitations: Optically thin clouds, particularly cirrus,
cannot be completely identified by this method; and discrimination of clouds by CAI is limited onbright ground surfaces, such as surfaces covered with snow and ice or desert, and in regions where
the ground surface state changes rapidly with time.
Note 1) The reflectance is defined as πL /(F0 cos θ 0 ) here. L is observed radiance, F0 is solar irradiance basedon the instrument function, and θ 0 is the solar zenith angle.

(2) Cloud characteristics algorithm
The principle for obtaining optical thickness of the cloud and effective radius of cloud particles are
as follows. Light is scarcely absorbed in CAI Band 2 (0.670µm) even if multiple scattering by
cloud particles occurs since the imaginary part of the complex index of refraction of water droplets isvery small and is approx. 10-8. Therefore, the light injected into the cloud layer repeats scattering
due to cloud particles and ultimately the light that scatters toward the satellite from the top of thecloud is observed. A greater amount of light is observed in CAI Band 2 as the cloud optical
thickness increases, augmenting the light scattered upward from the top of the cloud. The
probability of upward scattering as a result of multiple scattering will reach the upper limit when the
optical thickness increases to around 70, and the observed radiance will be saturated in the meantime.
B-30

On the other hand, CAI Band 4 (1.6µm) is used to estimate the effective radius of cloud particles.
The imaginary part of the complex index of refraction of water droplets in this wavelength range isover 10-5, which is one thousand times greater than that in visible light. Therefore, the shortwavelength infrared light that enters the cloud layer is absorbed during the multiple scattering due tocloud particles. The light observed by the CAI Band 4 gets weaker, when cloud particles becomelarger and therefore absorb light more strongly. The absorption in the cloud layer becomes
gradually saturated when the effective radii of cloud particles increase to around 30µm, which is theupper limit.
In remote sensing of cloud characteristics, the optical thickness and effective radius of particles
of clouds are calculated from observed radiances in visible and infrared bands. The radiances
directly observed include radiative components that are essentially unnecessary for estimation ofclouds characteristics, such as the ground surface reflection components and thermal radiation
components from the cloud layer. These components are therefore removed in calculation byusing the transmittance of the atmosphere and cloud, satellite zenith angle, solar zenith angle,
relative azimuth angle, etc. Estimations of the physical values using satellite observations areaccomplished by comparing the simulated radiance obtained by using the radiative transfer code
(Nakajima and Tanaka, 1986, 1988) and the observed radiances by CAI. A database (lookup table,
LUT) table of angle dependent radiance, transmittance of atmosphere and cloud, and sphericalalbedo has been prepared in advance for various optical thickness of cloud and the effective radius ofcloud particles, and it is used in this algorithm which performs iterative calculations using the
Newtonian method.
(3) Aerosol characteristics algorithm
CAI has observation bands at 670 nm and 870 nm, which are sensitive to aerosol scattering and often
utilized for remote sensing of aerosols, as well as the band at 380 nm, which is insensitive toreflection from the ground surface and sensitive to absorptive aerosol, and the band at 1.6 μm, which
is sensitive to large-particle aerosols. The aerosol characteristic parameters will be estimated by the
maximum a posteriori (MAP) method, calculating the satellite signals of these four bands
theoretically.
In addition, as the estimation of aerosol parameters based on the CAI data is tightly restricted,
aerosol information on the locations which are not covered by CAI estimation will be obtained fromthe estimation results based on the aerosol transport model being developed by the GOSAT Project.
This model is a 3D dynamic simulator for aerosols developed for the GOSAT Project, having
Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) as its core.
B-3.5 Level 2 processing of the TANSO-FTS-SWIR data
In the three FTS SWIR bands, the sensor observes signals on the two polarization planes, which areperpendicular to each other, in each band. That is, it acquires data (interferogram) for six bands, intotal. The FTS SWIR data, combined with various ancillary data, are used to calculate the column
abundances of CO2 and CH4 within target accuracies (i.e. relative errors of 1% for CO2 and 2% forB-31

CH4 in a certain period). The retrieved column abundance [molecules/cm2] is converted to XCO2
[v/v] (volumetric mixing ratio), which represents the ratio of CO2 in the atmosphere with no water
vapor, or a relative humidity of 0%, (dry atmosphere). In many cases it is this converted quantitythat is used for application. This conversion requires ground-surface pressure information, thus thecolumn abundance of oxygen (or ground-surface pressure) derived from FTS Band 1 data and theground-surface pressure obtained from objective analysis data at the observation time and location
are used.
Figure B-3-2 on the next page depicts the data processing flow for generating L2 column abundance
products from L1B (spectra) data of FTS SWIR observation.

B-32

FTS SWIR data
(L1B)
DEM
(GTOPO30)
CAI data (L1A)

Pre-processing

Pre-processing of
meteorological data
CAI L1B processing

CAI L1B
Intermediate file

Pre-processing of thecalculation results from theatmospheric transport modelCalculation results

Calculation by theatmospheric transport
model

CAI L2 cloud
discrimination

CAI L2cloud flag

Meteorological data
(GPV)

FilteringCalculation results

CAI L2 processing

Calculation by theaerosol transport model(SPRINTARS)(Aerosol characteristics)

CAI L2aerosolparameters

Setting of initial and a priori
values

MODIS
Ground-surface
reflectance data

Calculation of gaseousconcentrations

Product generation

FTS SWIR data
(L2)

Figure B-3-2 Data processing flow from TNASO-FTS-SWIR L1B to L2 products
B-33

(1) Use of polarization information
The FTS SWIR observation can measure polarization signals on two perpendicular axes, which
are called the P (parallel) axis and the S (senkrecht—a German word for “perpendicular”) axis.
The P and S observation data are planned to be applied in the data processing flow, by means of
the following three approaches. “Approach 1” will be adopted in the initial version of theprocessing algorithm. A series of simulations have found that the degree of polarization is low
in observation of reflection from the earth surface, whereas it is high in sunglint observation
over the sea surface.
【Approach 1】 The two polarization components of the observed light are compounded toprovide total intensities. In this approach, the scalar radiative transfer code, which does
not take the polarization state into consideration, will be used in the theoretical calculation.
【Approach 2】 The radiance spectra of the two polarization components of the observed
light are used independently. In this approach, the vector radiative transfer model (Pstar2bcode), developed by the GOSAT Project, will be used in the theoretical calculation. The
Pstar2b code runs at a speed a few times slower than conventional scalar radiative transfer
codes, however, it is a code which runs much faster than any other polarization calculation
code, after being improved for fast running.
【Approach 3】 The radiance spectra of the two polarization components of the observed
light are approximated by total intensities. In this approach, it is assumed thatpolarization-related parameters, such as ground-surface albedo, scattering phase matrix,
etc., are different between the two polarization components, whereas the other parameters,
including the optical thickness and gaseous concentration, are identical. Based on theseassumptions, the radiative transfer is calculated in an approximate manner, using a scalarradiative transfer code per polarization axis.
(2) Retrieval algorithm
In the processing algorithm to estimate column abundances from L1B to L2, the first calculation
is for the vertical distribution of the volumetric mixing ratio of the gas of interest as anintermediate parameter, in preparation for achieving the column abundances of CO2 and CH4 asfinal outputs. The information necessary for this retrieval will be supplied by objective
analysis data for the meteorological parameters, such as the vertical distributions of air
temperature and pressure, measured at the same location at the same time as the GOSAT
observation. In addition, absorption bands in the FTS SWIR bands do not have such radiancespectral signals that have a weighting function structure which is steep enough in the altitude
direction to require vertical distribution. Therefore, the intermediate product, the vertical
distribution of the volumetric mixing ratio, may have an extremely unstable structure.
Nevertheless, the column abundance can be stably obtained. The reason is, though the
explanation is not rigorous as it disregards the impact of multiple scattering or path radiances,that the size of the area obtained by integrating the absorption depth of the absorption line
structure within the radiance spectrum observed is deeply linked with the amount of column
abundance.
The L1B to L2 retrieval algorithm is based on a constrained Gauss-Newton method of a
B-34

non-linear least squares method to the observed radiance spectra. In other words, the solutions
are obtained stably from the observation information together with a priori information. The
solutions to be derived consecutively are expressed as the following equation.

x i+1 = xi + (K iT Sε−1K i + S a−1 ) [K iT Sε−1 (y − F ( xi )) − S a−1 ( xi − x a )]−1

B-3-(1)

Where xi is the vector of the parameter to be estimated at the ith time, xa is its a priori
information (the a priori value which can be used as the initial guess at the beginning of
estimation), S ε is the error variance-covariance matrix (no. of wavenumber points × no. ofwavenumber points) of the observed spectra, S a is the variance-covariance matrix (no. ofparameters to be estimated × no. of parameters to be estimated) of the a priori information, y is
the vector of observed spectrum (no. of wavenumber points), F ( xi ) is the simulated spectrum
theoretically calculated using a radiative transfer code when the variable is xi , and K i is theJacobian matrix (no. of wavenumber points × no. of parameters to be estimated), which
expresses the divergence of spectra against the unit change of the target parameter. Note also thatK = ∂y ∂x here.
Furthermore, Equation B-3-(1) above corresponds to an adoption of such a solution that gives
the minimum value for the cost function given as below (Equation B-3-(2)). It is called theMaximum A Posteriori (MAP) estimation method.

J(x ) = [y − F ( x)] Sε−1 [y − F (x)] + ( x − x a ) S a−1 (x − x a ) → min.
T

T

B-3-(2)The values of elements of S ε will be determined based on the characteristics of the sensor (e.g.
SNR). The values of the diagonal elements of S a are given by a priori information regarding
how freely the target parameters can vary with altitudes, while those of the non-diagonal
elements are given by the information regarding the inter-constraints of variation among thetarget parameters (e.g., correlation between vertical distributions of each gaseous species).
Basically, the molecular spectroscopic parameters provided by the HITRAN 2004 database will
be used for calculating theoretical spectra in B-3-(2), except CO2 of Bands 2 and 3 and partly
CH4 of the 1.67-μm band, for which the 2008 version of line parameters and data generated in
the GOSAT Project will be used, respectively. Moreover, when performing spectral-fitting in
B-3-(2), channel selection will be performed in order to eliminate the impact of Fraunhofer lines
in the solar atmosphere and of water vapor in the earth atmosphere. The information on solar
Fraunhofer lines in the 1.6-μm and 2.0-μm bands will be supplied by the data generated by Dr. R.
L. Kurucz, Harvard-Smithonian Observatory in the U.S., in response to the request from the
GOSAT Project.
Research and development of this algorithm have been promoted using the radiative transfer
code improved based on HSTAR code, an extended RSTAR code developed by Professor
Teruyuki Nakajima and his research group at Center for Climate System Research, University ofTokyo, which can calculate the effects of (multiple) scattering and attenuation by atmospheric
B-35

molecules, aerosol, and clouds particles present on the optical paths. With the help of this code,
the column abundance can be estimated at an expected precision even in the presence of
optically-thin clouds and aerosols, as demonstrated in numerical simulations. Consequently,
the “filtering” process in the processing flow provided in Figure B-3-2 is the process carried out by
the program to determine whether or not the observation data under processing is a clear-sky
scene or a scene with optically-thin clouds or aerosols. The data processed in this way thenundergo L2 processing.
In addition, the ground-surface albedo is also added as a target parameter and retrieved
simultaneously by means of Equation B-3-(1). With this processing, it is possible to flexibly
estimate the column abundances of CO2 and CH4 for any spectrum structure of theground-surface albedo.
(3) Fast retrieval algorithm
In order to realize the above-mentioned estimation algorithm, a new data processing system which
combines the discrete ordinate method as a radiative transfer and the MAP method, is being
developed. Additionally, the Project is promoting the research and development on a fast andhigh-accuracy technique called the Photon Path-length Probability Density Function (PPDF) method,which is based on a simple radiation model by combining the Monte Carlo method and theEquivalence theorem and retrieves PPDF parameters simultaneously with other unknown quantities,
such as CO2, from the observed spectra, as a future version of GOSAT operational processing
algorithm.
B-3.6 Level 2 processing of the TANSO-FTS (thermal-infrared band) data
Data from thermal-infrared sensors on board spacecraft platforms have been used mainly for
analyzing CO2 concentrations. With this technique, however, it is difficult to detect significant
change in the CO2 concentration in the boundary layer, such as decrease due to absorption byvegetation or increase due to artificial CO2 sources, although the changes in concentration in the
middle and upper layers of the troposphere can be analyzed with a high accuracy. This is because
the difference between the atmospheric temperature at the altitude where concentration changes
occur and the equivalent radiance temperature of the background radiation is smaller in the lower
layers of the atmosphere, making it more difficult to detect.
For FTS thermal-infrared observation (referred to as “TANSO-FTS-TIR” hereafter), it is expectedthat the vertical profile of CO2 concentrations down to altitudes of 700 to 750 hPa from the upper
atmosphere can be obtained under clear-sky conditions, though it depends on the vertical profile ofatmospheric temperatures. Figure B-3-3 plots a typical vertical resolution function (Averaging
Kernel) in medium latitudes.
(1) Vertical profile of CO2 concentrations
Independent temperature information is required for deriving the concentrations of CO2 from thethermal-infrared band data. The TANSO-FTS TIR observation uses objective analysis data because
there are no simultaneously-operated microwave sensors.
B-36

Figure B-3-3 Averaging kernel of CO2 analysis based on the TANSO-FTS-TIR data -Typicalexample in mid- latitudes (Saitoh et al., 2006)
For retrieval analysis of CO2 concentrations, a physical analysis technique, more precisely the
Maximum A Posteriori (MAP) method as in Eq.B-3-(2), will be employed, similarly to FTS SWIR
observation.
The results obtained by statistically processing the output of the CO2 transport model will be used as
the initial guess values and covariance values of the CO2 concentration. Since the Jacobian matrix
is a function of vertical profiles of atmospheric temperatures and CO2 concentrations, the optimal
Jacobian matrix is calculated for each region, season, and local time from the vertical profiles ofatmospheric temperature and CO2 concentration from the objective analysis and theabove-mentioned initial guess value, respectively.
(2) CO2 column abundance
The radiance spectrum of the CO2 hot band close to 10 μm is utilized for this analysis; namely, thefact is used that the decrease in radiance depends on the column abundance of CO2 with thebackground of a warm ground surface or sea surface as in Solar Occultation.
First, the Jacobian matrix in the 10 μm band of CO2 is calculated based on the vertical profiles ofatmospheric temperatures and volumes of water vapor in each FTS FOV that was analyzed using theobjective analysis value as the initial guess value. To reduce errors in estimating the volume ofwater vapor, baseline compensation is performed such that the systemic gap between the simulated
spectrum and the observed spectrum is compensated using a wavelength range with a small volumeof absorption by gases. The column abundance of CO2 is derived by applying the Jacobian matrix
B-37

to the difference between the simulated spectrum and the observed spectrum after this baseline
compensation. The wavelength dependence of the ground-surface emissivity is required tosimulate the radiance spectrum; the results estimated from database for the ground-surface
emissivity and the meteorological data obtained before and after the observation are utilized for suchdata. For the concentration of ozone, which influences this wavelength band, data of other satellite
sensors such as OMI, are utilized.
(3) Cloud screening
The fractional cloud coverage in the FTS FOV is estimated based on the analysis results of the CAI
sensor during the daytime. However, the analysis results of the FTS TIR data are also usedconcurrently because thermal infrared radiation spectra are superior in detecting thin ice clouds suchas cirrus clouds. During the nighttime, however, clouds are discriminated solely by the FTS TIRband because the CAI sensor is not operated.
There are three methods for analyzing clouds using the FTS thermal-infrared data.
1. Slicing method
2. Threshold value method
3. Split window method
The slicing method estimates the altitude at the top of cumulus clouds by applying the method ofMenzel et al. (1983), which uses the 15 μm band of CO2. The threshold value method, the second
item above, discriminates clouds based on the difference between the value provided by thesea-surface temperature database, storing the analyzed results of data from the AVHRR on NOAA
satellite and/or MODIS, and the sea-surface temperature estimated from the FTS TIR data with theassumption of no cloud. Although this method is superior over the sea, these data will be used only
as references for land areas due to a large error in the ground-surface temperature of objective
analysis data. The split window method, listed last, performs an analysis using the combination ofdata of two wavelength bands, 8 to 10 μm and 11 to 13 μm, which enables to judge cloud altitudes
and distinguish between ice and water particles in the areas that are identified as cloudy.
B-3.7 Level 3 processing and more advanced (higher-level) processing
L3 product is generated as a global map, by using the column abundances of CO2 and CH4 (L2)
calculated from the TANSO-FTS-SWIR data after applying temporal/spatial interpolation andappropriate statistical processes to the GOSAT observation data for fixed sections (e.g. 2.5° meshes(TBD)) during a given period of time, to calculate the value for each section. Similarly, TIR L3
product is planned as a global map, but the details are yet to be determined.
L3 processing of the CAI data is also planned, though very roughly, to provide standard products on
global radiance maps (with cloud cover), global radiance maps (without cloud cover), and vegetationindex maps (for a certain observation period), and research products on aerosol characteristics maps
and cloud characteristics maps (for a certain observation period) . Details will be fixed hereafter.
More advanced-level products are also planned, targeting the release just after one year, at the
shortest, after the satellite launch. These include global flux maps (L4A) in 64 divided regions,B-38

which will be generated through inverse calculation, based on atmospheric transport models ,of
GOSAT L2 or L3 data and CO2 and CH4 concentration data acquired at monitoring stations on the
ground , and 3D distribution maps of CO2 and CH4 concentrations (L4B) calculated from L4A datausing atmospheric transport models. The details of processing algorithms for these products havenot been finalized yet, and hence are excluded from this Appendix.

B-39

Thermal And Near infrared Sensor for carbon Observation (TANSO)
on board
the Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

Appendix C
Operation Policies of GOSAT and Basic Observation Plan of the TANSO Sensor

Operation Policies of GOSAT and Basic Observation Plan of the TANSO Sensor
This document describes the policies for the operation of GOSAT and the basic plan for theobservation by the TANSO sensor.

The contents of this document should be carefully confirmed orreferred to in preparing research proposals to be submitted in response to the RA. RA Investigators,
if they find any matter to be confirmed in more detail in the course of preparing proposals, arerequested to contact the RA Office for clarification, at the contact address provided in Chapter 14 of
the RA Document.

C-1 Operation of GOSAT
C-1.1 Orbital Parameters of GOSAT
Table C-1.1-1 specifies the nominal orbit of GOSAT.
Table C-1.1-1 Nominal orbit of GOSATParameters
Orbit type
Altitude against the earth at Equator
Inclination angle
Orbital period
No. of days per recurrence
Orbits per day
Orbits per recurrence
Descending node time
Recurrence accuracy

Description
Sun-synchronous, quasi-recurrent
666 km
98.06 degapp. 98.2 minutes
3 days14 + 2/3 revolutions
44 revolutions
13 hours ±15 minutes (12:48)±2.5kmSee technical information for more detail.

C-1.2 Control and Maintenance of the Orbit
GOSAT will be maneuvered every three to six days (TBD) for orbit control to maintain thesun-synchronous quasi-recurrent orbit (as to the descending node time, altitude/recurrence, etc.), in
order to secure a recurrence accuracy of ±2.5 km for the operation of the sensor observation.

C-1

C-2 Operation of TANSO-FTS/CAI
C-2.1 Functions of TANSO-FTS/CAI(1)

Functions of TANSO-FTS

 Observes the atmosphere in visible-, short wavelength-infrared and thermal-infrared bands
looking toward the earth center.
 Carries out observation over the land in lattice points in general Observes the same footprint during one interferogram measurement while the satellite ismoving.
 Observes the interferogram multiple times for the same footprint to improve the SNR in somelattice point observation.
 Observes at a fixed angle (or fixed distance) interval in cross-track direction during the latticeobservations.
 Returns to the same footprint after three days in lattice point observation.
 Observes sea area where sunglint is expected, using the two-axis (AT/CT) mechanism.
 Performs solar irradiance calibration in the visible band and the short wavelength infrared
bands and blackbody calibration in the thermal-infrared band in orbit.
 Performs deep-space calibration in the visible-, short wavelength- and thermal-infrared bands.
 Performs annual lunar calibration on the sensitivity by pointing the satellite and the two
sensors to the moon.
(2)

Functions of TANSO-CAI Observes cloud and aerosol with spatial resolutions of 0.5 to 1.5 km.
 Performs annual calibration on the sensitivity by pointing the +Z axis of the satellite to themoon.

C-2.2 Operation Mode
Tables C-2.2-1 and C-2.2-2 show the basic operation modes of TANSO-FTS and TANSO-CAI.

C-2

Table C-2.2-1 Basic operation modes of TANSO-FTS
Operation mode
Description
Observation mode Daytime
Observation in the short wavelength infrared bands andI
observation
thermal-infrared band.
Nighttime
Observation in the thermal-infrared band.
observation
Performs blackbody calibration and deep-space calibration.
Observation mode II(In case of a failure of one of the solar paddles or othersimilar event) the operation of thermal-infrared observation issuspended and the pointing mechanism is locked to cope withthe situation that the power supply level of the satellite
becomes lower.
*The observation time is set as ten minutes per orbit, and thesensor is set to the Standby II mode for the rest of the time.
*TANSO-CAI is assumed as set to the All-Off mode.
Specific
Sunglint observation Observes sunglint points according to the uplinked
observationcommands.
mode
Specificpoint Observes specified points according to the uplinked
observationcommands.
“Specific points” include lakes, validation sites, ground-based
CO2 observation points, etc.
Calibration Lunar calibration
Performs observation in the short wavelength infrared bands
mode
once a year, as necessary. This calibration is performed byrotating GOSAT to point to the moon at around the time when
the average radiance from the moon surface marks thehighest, and orienting the sensor’s FOV toward the moonusing the pointing mechanism.
Solar
irradiance Performs solar irradiance calibration for every orbit when thecalibration
satellite is in sunlight and the ground surface is in shade.
Thus, this calibration takes place at rise of the sun.
Instrument function Performs calibration on the instrument function by irradiating
calibration
a 1.55-μｍ-long semiconductor laser light.
Electrical
Performs calibration of signal processing in the analoguecalibration
signal processing system and beyond, by inputting a reference
voltage signal.
Table C-2.2-2 Basic operation modes of TANSO-CAI
Operation mode
Description
Observation mode
Performs observation by CAI.
Calibration Lunar calibration
Performs lunar calibration once a year, as necessary. Thismode
calibration will be performed by rotating GOSAT to point to
the moon at around the time when the average radiance fromthe moon surface marks the highest. It is performed
concurrently with the lunar calibration of FTS.
Electrical
Performs calibration concerning signal processing in thecalibration
analogue-signal processing system and beyond, by inputting areference voltage signal.
Nighttime
Calibrates the offset level at nighttime.
calibration

C-3

C-2.3 In-orbit Operation
Figure C-2.3-1 illustrates the operation of TANSO-FTS and TANSO-CAI orbiting the earth for theobservation over lattice points, whereas Figure C-2.3.2 below provides images of data acquisition in
the observation mode I and the specific observation mode (sunglint observation).

Sunglint

observation is performed above the ocean, where sunglint occurs, at low or middle latitude.

TANSO-FTS (short wavelength infrared) solar irradiance cal.

TANSO-FTS, CAI lunar calibration

Extent of TANSO-FTS (shortwavelength infrared) observation
Extent of TANSO-CAI (visible andshort wavelength infrared) observation

Sunlight
TANSO-CAI nighttime calibration
Extent of TANSO-FTS (thermal-infrared)
observation

Figure C-2.3-1 In-orbit operation

Figure C-2.3-2 Images of data acquisition for the observation over lattice points and specificobservation modes

C-4

C-2.4 Nominal Operation

C-2.4.1 Nominal Operation of TANSO-FTS(1) Observation over lattice points
TANSO-FTS performs observation in the short wavelength infrared bands when the target groundsurface is in daylight, while, it can perform observation in the thermal-infrared band regardless ofwhether it is daytime or nighttime.

However, the FTS operation in the light-load mode (LLM) or

super-light load mode (S-LLM) is different, in both the short wavelength- and thermal-infrared
bands.

There are five modes for the FTS observation over lattice points, depending on the numberof scans in cross-track direction, namely 1, 3, 5, 7, and 9.

The sensor receives the ascending nodetime information from the satellite, based on which it performs the time adjustment (correction of
the scanning cycle).

It returns to the same footprint for every pointing mode observation, for every

recurrence in three days, with a target accuracy of 4 km.

The start and end times of FTS’s daytime

observation in the short wavelength infrared bands are specified by the stored commands uplinked
from the ground.
Table C-2.4-1 and Figure C-2.3-1 on the next page show a sample scanning pattern for observation
over lattice points and an overview of the scanning pattern in cross-track direction, respectively. In
addition, the ratios of the distance between observation points along-track (AT) and cross-track (CT)directions are given in Table C-2.4-2.
Table C-2.4-1 Data acquisition cycle and cross-track scanning pattern
No. of observation points in
Observation time at a time
No. of times for observing thecross-track direction(sec)same footprint
1
4.0
3
3
4.0
3
5
4.0
1
7
2.0
1
9
1.1
１
*: For adjusting to the observation timing, it must be feasible to lock the pointing mechanism
before the start time of a specific observation.

C-5

Table C-2.4-2 Time and location distances between observation points in AT and CT directions
No. of
VerticalObservation
Horizontal
observation
space attime at one
CT settling AT settling
AT angularspace atAT interval
points inlatitudeobservation
time
time
range
latitude
timecross-track
30 deg
point
(sec)
(sec)
(deg(+/-))
30 deg (km)direction
(km)
(sec)
1
788.8
90.3
12.8
N/A
0.4
13.2
3.7
3
262.9
283.1
13.2
0.6
0.6
41.4
12.1
5
157.8
152.2
4.0
0.45
0.45
22.2
6.5
7
112.7
114.9
2.0
0.4
0.4
16.8
4.9
9
87.6
86.2
1.1
0.4
0.4
12.6
3.7
* Observation time at one observation point: In the observation modes with the number of observation points in CT
direction being one and three, the observation time includes twice the turnaround time (=CT settling time = AT
settling time), as the interferogram is measured over the same footprint in these modes.
*AT interval time = observation time at an observation point × No. of CT observation points + CT settling time × (No.
of CT observation points - 1) ＋AT settling time = (observation time at one observation point＋turnaround time) ×
No. of CT observation points

Figure C-2.4-1 Scanning pattern in cross-track direction(2) Specific point observation
In the specific point observation mode, FTS makes observation over a specific ground point(one-point observation) for observing a relatively small coverage, such as calibration/validation sites.
When observing a large coverage, such as natural-gas pipeline, it observes multiple specific points
consecutively (consecutive observation).

The same observation mode, however, is selected toperform both specific point observations (one-point and consecutive).

The observation time andthe AT and CT angles will be specified by the commands uplinked from the ground.
(3) Sunglint observation
In the sunglint mode, TANSO-FTS makes observation over the ocean.

C-6

In this observation, thesunglint point is computed on the ground and the angle of the pointing mirror is set to observe thatpoint. The sensor then observes the sunglint point in strips.

Sunglint observation is performed at

low or middle latitudes, but the detailed latitude ranges for the FTS observation are still being
examined.

Incidentally, the latitude range varies with the seasons.

C-2.4.2 Nominal Operation of CAITANSO-CAI observes the target while the observation ground point is in daylight.
is different for LLM and S-LLM modes.

The operation

The start and end times of TANSO-CAI daytime

observation is specified by the stored commands uplinked from the ground.

C-2.4.3 Operation in Calibration Modes(1) Blackbody, deep-space calibration mode
In FTS’s deep-space calibration (in the short wavelength- and thermal-infrared bands) andblackbody calibration (in the thermal-infrared band), the data are acquired during the lattice or
specific point observation mode operation, by designating arbitrary points (by specifying the elapsed
time from the ascending node time, up to 16 points per orbit) using the commands to be uplinked
from the ground.

These points can be specified individually and do not have to be equally spaced.

When acquiring data over the same calibration point as previous calibrations, it is not necessary to
specify the point every time.

In addition, in blackbody/deep-space observation, the observation

time of the previous observation mode (1.1, 2, or 4 seconds) is applied, and it requires a total of four
observation points, consisting of one for pointing to the blackbody, another for observing theblackbody, another for pointing to deep space and the other for observing deep space.

Since thedetectors continuously output data while changing the pointing direction, the data rate remains
constant.

(In order to distinguish these data from effective data, the pointing “completion” flag will

be indicated as “uncompleted”).
(2) Solar irradiance calibration mode
Solar irradiance calibration (using the diffuser plate) for FTS will be performed immediately before
the target observation point on the ground comes into daylight, by selecting the diffuser plate for use
and switching to the solar irradiance calibration mode with the stored commands (designating time
as parameters).
(3) Lunar calibration mode
The sensitivity calibration of both FTS and CAI is performed using the reflection of sunlight fromthe moon surface as the light source.

The integrated value of the reflection from the entire moon

surface serves as the calibration light.

Of the linear array detectors of CAI, the sensitivity of theC-7devices is calibrated where lunar calibration light enters.

That of the other devices, which do

not receive the calibration light, is calibrated by means of relative calibration based on the
ground observation data over deserts, etc.

In case that a device placed near the center of CAI fails

down, another nominal device takes over the job by offsetting in the satellite’s pointing direction.

C-2.5 Gain Setting(1) Gain setting of FTS
Three levels (Low/Medium/High) of gain setting are available for Bands 1, 2, and 3 of FTS.
However, only one level can be selected for all bands.

In addition, the following settings are thebasic preconditions in FTS observation.
Observation over lattice points, specific point observation:

High gain

Note, however, that medium gain should be chosen for observing desert areas at low latitudes,
as necessary.
Sunglint observation:

High gain

Note, however, that medium gain may be chosen, as necessary.
Solar irradiance calibration:



Low gain will not be used, in principle.

Medium gain (fixed)

The gain setting can be changed, as necessary, in the following scenarios, based on the pass orargument of latitude being the parameter.
When passing over the zone at the designated argument of latitude.

When observing sunglint points.

When observing specific ground points(2) Gain setting of CAI
Three levels (Low/Medium/High) of gain setting are available for Bands 1, 2, and 3 of CAI.
the gain is adjusted by the integral time.
of latitude being the parameter.

In fact,

The gain value can be set based on the pass or argument

However, only one level can be selected for all bands. The gain

setting value is maintained as a static parameter and is assumed to be readjusted about once a month.

C-8

Thermal And Near infrared Sensor for carbon Observation (TANSO)
onboardthe Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

Appendix D
Contents of Research Proposal and Application Forms

1. Cover sheet
1.1.

Profile of investigators (Form 1a)
Fill in the following information in its entirety.
・ Information about the Principal Investigator (PI): Name, title, department, affiliation,
address, nationality, phone number, fax number, e-mail address
・ Information about the RA Investigators other than the PI (Co-Is): Name, affiliation, ande-mail address of each RA Investigator
・ The PI’s background, experience in the selected research field, research papers, etc.
・ Signature of the PI

1.2.

Summary of the research proposal (Form 1b)
Fill in the following information in accordance with the instructions given in parentheses.
・ Research field (Select one from the four given fields: Scientific research/ Calibration andvalidation/ Processing algorithms/ Data application.)・ Research theme (Describe the contents of your proposed research in the most simple andadequate way.)・ Main sensor to be used (Select from FTS/ CAI/ None.)・ Sensors to be used in combination (Select from FTS+CAI / None, just in case.
・ New data acquisition request, if necessary. Detailed requirement will be specified later
・ Data distribution request (If necessary, select the product name(s) from Table 1 “List of
GOSAT/TANSO Products” in the RA Document.)
・ Abstract of your research proposal (no more than 200 words) (Include the purposes,
significance of the research in the selected research field, methods, time schedule, andexpected benefits of the proposed research)

2. Main proposal (no more than five (5) pages)
Describe in detail the background, purposes, and technological level of the proposed research,
the importance of the research compared with related researches carried out in the other fields,
and the details of research activities, in the main body of the proposal. In addition, the details of
research activities must include a rough plan of the work and experiments to be performed andan outline of the methods and procedures to be employed in the research. Having covered these
items, describe the following items where necessary.
・ Table of contents
・ Purpose(s) of the proposed research・ Significance and importance of the proposed research in the selected research field・ Methodology
・ Algorithms to be used
・ Expected outcomes
D-1

・ Distribution requests and acquisition plan for the GOSAT/TANSO data (area of interest,
processing level, product name, acquisition window, etc.)
・ Requests for the satellite data owned by JAXA (area of interest, processing level,acquisition window, etc.)

3. Work plan (Research schedule) (Form 2)
Submit the time schedule for your research activities on Form 2, with an explanation on thefocus of research work and any associated schedules. Incidentally, this work plan should start inand after February 2011.

4. Data distribution request
Request for JAXA’s satellite data (other than the GOSAT data) (Form 3)
In order to request a provision of datasets of any of the satellites listed below, fill out andsubmit Form 3. JAXA has the rights to distribute the observation data of the following
satellites.
・ Japanese Earth Resources Satellite (JERS) (global)
・ Advanced Earth Observing Satellite (ADEOS) (global)
・ Tropical Rainfall Measuring Mission (TRMM) (global)
・ LANDSAT (around Japan)
・ SPOT (around Japan)
In addition, the satellite data acquired in the past are archived and retrievable on the following
Website. Investigators who are willing to request for the satellite data are recommended to
first check on the Website if the data requested are available, before submitting a data request
form.
・ Search site for observation data of JERS, ADEOS, TRMM, SPOT**, LANDSAT*/**.
https://www.eoc.jaxa.jp/iss/jsp/indexEn.html*The LANDSAT archive (up to Landsat-5) includes data received up to March 31, 2001
(TBD).
**SPOT and LANDSAT-7 archives include data received up to March 31, 2002 (TBD).

5. Information about the Investigators
State the background, research papers or publications, and special skills and qualifications of
the PI, as supporting information for the selection of research proposals. Likewise, present thesame information about the other RA Investigators (Co-Is).

D-2

6. Data processing and analysis facility
List up major facilities and equipment available for carrying out the proposed research andadditional facilities and equipment that the Investigators may procure. Also, describe theassistance from their organizations/affiliations, if any, for which the RA Investigators are
qualified for the purpose of carrying out the proposed research.

D-3

Form 1aProposal No.
(For JAXA/NIES/MOE’s use)

<Cover sheet>
Profile of Investigators
Principal Investigator (PI)Name:
Title:
Department:
Affiliation:
Address:
Nationality:

E-mail address:

Phone:Fax:

RA Investigators (Co Investigators: Co-I)
Name

Affiliation

E-mail address

Background, experience in the pertinent research field, theses, etc. of the PI:

Signature (PI):D-4

Form 1b

Proposal No.
(For JAXA/NIES/MOE’s use)
Name of PI:

Summary of Research Proposal(Place a circle (○) in the parentheses by the pertinent response.)
1． Research field (Choose one only.) *[] Calibration / Validation #[] Data processing algorithms[] Carbon balance estimation, atmospheric transport models# In case of Calibration / Validation, specify ［[] Data application］Calibration ［］Validation*Your choice of research field will not affect the selection of research proposals.
2． Main sensor to be used［ ］FTS ［］CAI [］None

3． Sensors to be used in combination［］FTS ［ ］CAI [］None

4． New data acquisition request
［

］Yes

［ ］No

If yes, detailed requirement will be specified later.

5． Request for data distribution［ ］Yes［ ］NoIf yes, select the product name(s) from “Table 1 List of GOSAT/TANSO Products” in the RA
Document.
6． Research theme
7． Abstract of the research proposal (no more than 200 words)

D-5

Form 2
Proposal No.

Work Plan for the Joint Research (Research Schedule)
Name of PI:

20010
6

8

10

2011
12

2

4

6

8

10

2012
12

2

4

Plan

Interim
Evaluation

Description
2013
6

8

10

2014
12

2

4

6

8

10

Plan
Description

D-6

12

2

6

8

10

12

2

Form 3
Proposal No.
Requests for JAXA’s satellite data (other than the GOSAT data)(For JERS, ADEOS, TRMM, ADEOS-II, SPOT, or LANDSAT)Name of PI:

Area of Interest
Sensor(pass/row orlat./lon.)

Observation
window

No. of scenes
Processing level
Min.

Max.

The distribution media for providing the requested data will be determined according to the data
size.

D-7

Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

General Contractual Conditions for the Joint Research on the GOSAT data
(Third RA)
The Japan Aerospace Exploration Agency (JAXA), The National Institute for Environmental Studies(NIES), and the Ministry of the Environment (MOE) of Japan (hereinafter referred to as the “Three
Parties” collectively) made the third research announcement on greenhouse gases observing sensor
onboard the satellite (hereinafter referred to as the “RA”), in August 2010 following the last year’s
second RA, with regard to the use of data acquired by Greenhouse gases Observing SATellite(“GOSAT”) (hereinafter referred to as the “GOSAT data”), to solicit research proposals from publicwhich will further enhance and exploit the outcomes of the GOSAT Project. The Three Parties
selected and approved research proposals submitted in response to the RA, which were deemed as
appropriate by the RA Selection and Evaluation Committee (hereinafter referred to as the“Committee”). The Three Parties and the research organization (hereinafter “RO”) of the principal
investigator (hereinafter “PI”) whose research proposal was accepted hereby agree to and execute
accordingly the contract (hereinafter “Contract”) to carry out a joint research (hereinafter “Joint
Research”) as provided for hereunder. If the PI does not belong to any organization, the “RO”
referred to hereunder shall be read as the “PI”.

Article 1 (Definitions)
1.1 For the purpose of the Contract, the following terms shall have the meanings as provided below.
1.1.1 The “Research Result” is the output acquired as a result of executing the Contract and itmeans the technical outcomes and scientific findings, including but not limited toinvention, device, design, copyrighted literary work, and know-how, which are stated as
Research Results in connection with the purpose of the Joint Research in documents
including, but not limited to, research reports prepared in accordance with the provisionsof Article 6 hereof.
1.1.2 The “Intellectual Property Right” means the rights stipulated by Article 2.2 of the JapaneseIntellectual Property Basic Law.
1.1.3 The “Interim Evaluation” means an evaluation by the Three Parties on the Research
Results and the progress reports submitted. The first Interim Evaluation is currently
scheduled for the second quarter of 2012 (April through June) and will evaluate theinterim report compiled and submitted by the RO in accordance with Article 6.2 hereof.
1.2 For the purpose of the Contract, the “Invention(s)” specifically includes inventions subject topatent right, device subject to utility model right, creation subject to design right, trademark right,
circuit layout access right, and copyrighted literary work (including programs), and idea subject tothe know-how to be defined in Article 7 hereof.

E-1

Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

1.3 For the purpose of the Contract, the “Implementation” of the Intellectual Property Rights means
the deeds as stipulated by Article 2.3 of the Patent Law, Article 2.3 of the New Utility Model Law,
Article 2.3 of the Design Law, Article 2.3 of the Trademark Law, and Article 2.3 of the Law
Concerning Semiconductor Integrated Circuit Layouts, the creation of derivative works as
stipulated by Article 2.1.11 of the Copyright Law, the deeds as stipulated by Articles 2.1.15 and2.1.19 of the same law and the implementation of the know-how.
1.4 For the purpose of the Contract, the “PI” is the representative researcher who submitted his/herresearch proposal in response to the third RA and investigates on the research theme proposed andselected and approved in the RA. On the other hand, the “RA Investigators” indicates
investigators who cooperate and participate in the research activities of the PI on said research
theme and are approved by the RO and registered by the Three Parties.

Article 2 (Roles and Responsibilities in the Joint Research)
2.1 The Three Parties shall undertake the tasks defined in the following provisions in conjunction
with the Joint Research.
2.1.1 Acceptance of data processing requests submitted by the RO to the extent approved by theThree Parties and provision of the requested GOSAT data to the RO.
2.1.2 Provision of information on mission control data, etc. necessary for the RO to carry out its
research activities under the RA scheme, to the extent possible.
2.1.3 Evaluation of the Research Results and the progress reports in the Interim Evaluation andnotification of the evaluation results to the RO.
2.1.4 Organization of research report meetings and other necessary gatherings.
2.2 The RO shall undertake the tasks defined in the following provisions in conjunction with the
Joint Research.
2.2.1 Implementation of the research in accordance with the work plan for the Joint Research.
2.2.2 Submitting interim reports on the research progress to the Three Parties (basically once ayear).
2.2.3 Participation in the research report meetings and other necessary gatherings organized by
the Three Parties.

Article 3 (Term of the Joint Research)
The Contract for the Joint Research shall enter into force when the Three Parties acknowledges theapplication of the RO based on the application form, and the term of the Joint Research under theContract shall commence on the day of the signing of the Contract and continues for the operational
period of GOSAT/TANSO plus the operational period of its ground system—five years after thelaunch, in principle (until January 22, 2014). However, in case that the Joint Research is evaluated asE-2

Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

disapproved for extension by the Interim Evaluation, it may be possible that the Joint Research beterminated. On the other hand, in case that the RO wants to extend the term of the Joint Research,
the RO can apply the extension for the three Parties, and if approved, the Joint Research will be
extended with the same conditions for one (1) more year.

Article 4 (Investigators to be Engaged in the Joint Research)
4.1 The RO shall ensure that the PI, designated in the research proposal, and the RA Investigators,
listed in the RA Investigator list submitted by the PI to the Three Parties, participate in the Joint
Research.
4.2 The Three Parties may consult and coordinate with the RO so as to make their researchers, listed
in the Three Parties’ researcher list to be prepared separately, participate in the Joint Research.
4.3 The RA Investigators are mutatis mutandis bound by the articles governing the RO in theContract, and the RO shall be responsible for taking every possible measure to ensure that the RA
Investigators observe the stipulations provided in the Contract.
4.4 In case that the RO is willing to add an investigator to the RA Investigator list, the RO shallnotify the Three Parties of such situation in writing and take necessary measures to ensure that the
new RA Investigator observes the stipulations provided in the Contract.

Article 5 (Research Expenses)
The Three Parties and the RO shall individually bear necessary expenses incurred in the course of
performing the respective tasks in association with the Joint Research.

Article 6 (Preparation of Research Result Report)
6.1 The RO shall pull together and organize the Research Results attained during the term of the
Joint Research in a written report (“Research Report”) and submit it to the Three Parties at thecompletion of the Joint Research.
6.2 The RO shall submit a progress report and an interim report by March 1, 2012 , to the Three
Parties, for the purpose of the Interim Evaluation of the Research Results slated for the second
quarter of 2012 (April through June). Notwithstanding the foregoing, if the research term shall becompleted by the end of March 2012, the submission is not necessary.

Article 7 (Specification of Know-How)
7.1 The Three Parties and the RO shall promptly specify the items, which are deemed as theknow-how arising out of the Joint Research (hereinafter referred to as the “Know-How”), from theitems stated as the Research Results in the Research Report provided for in the previous provision,in mutual discussion.

E-3

Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

7.2 When specifying the Know-How, the parties hereto shall clearly indicate the confidentiality
period during which the specified Know-How shall be classified (hereinafter referred to as the“Confidentiality Period”).
7.3 The Confidentiality Period as set forth hereinabove shall be determined in consultation between
the Three Parties and the RO, whereas it is set, in principle, at five (5) years from the following
day of the completion of the Joint Research, provided, however, that the Three Parties and the RO
may extend or shorten the Confidentiality Period in mutual discussion.

Article 8 (Carrying-in of Equipment, etc.)
8.1 The Three Parties and the RO may carry in equipment or commodities necessary for
implementing the Joint Research into the facility space of the other party, provided that suchcarrying-in is approved by the other party in advance. When carrying the equipment, etc. in, thecarrying party shall abide by the rules and regulations of the other party.
8.2 The Three Parties and the RO shall not use the equipment or commodities having carried in by
the other party (hereinafter referred to as the “Carried-in Commodities”) for any other purpose
than the implementation of the Joint Research.
8.3 In case that the Carried-in Commodities are lost or damaged, the Three Parties and the RO,
regardless of the cause of such loss or damage, shall promptly notify the other party.

Article 9 (Exchange of Information)
9.1 The Three Parties and the RO shall mutually provide its own technical documents andproprietary objects, including but are not limited to, programs, other than the GOSAT data
(hereinafter the same applies), necessary for the implementation of the Joint Research (hereinafterreferred to as the “Technical Documents”) free of charge to the other party and allow the otherparty to use the Technical Documents, and may request advice from the other party as necessary.
9.2 The Three Parties and the RO may not use the Technical Documents as set forth hereinabove
provided by the other party for any other purpose than the implementation of the Joint Researchnor disclose them to any third party not involved in the Joint Research.
9.3 The Three Parties and the RO shall return or appropriately discard the Technical Documents
provided by the other party, after the expiration of the Contract, according to the instructions
given by the other party.

Article 10 (Provision of and Rights to the GOSAT Data)
10.1 The Three Parties shall provide the RO with the GOSAT data free of charge, based on Article
2.1.2 hereof, conforming to the stipulations hereunder.
10.1.1 The RO shall be provided with the GOSAT data free of charge, to the extent approved

E-4Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

for submitting data distribution requests per research theme by the Committee.
10.1.2 The Three Parties shall not be liable for guaranteeing the quality or timely delivery of the
GOSAT data
10.1.3. The Three Parties shall not be liable for any situation where the RO is unable to obtain
the GOSAT data due to an anomaly of GOSAT, operational constraint, or othercontingency.
10.2 The RO shall abide by the following provisions with regard to the acquisition and handling of
the GOSAT data to be provided by the Three Parties.
10.2.1 The RO shall be entitled to submit data acquisition requests to the extent predetermined
per research theme by the Committee.
10.2.2 The RO may use the GOSAT data solely for the purpose of the implementation of the
Joint Research.
10.2.3 The RO shall not duplicate all or any portion of the GOSAT data for any other purpose
than data backup, except for duplication of the data to distribute it to the RA
Investigators solely for the purpose of the implementation of the Joint Research.
10.2.4 The RO shall handle the GOSAT data such that the original data are recoverable inaccordance with the provisions of Article 16 “Confidentiality” hereof, and shall notprovide or disclose all or any portion of it to any third party who is not involved in the
Joint Research.
10.2.5 When the Contract is expired, the RO shall return to the Three Parties or appropriately
store the GOSAT data provided by the Three Parties, in accordance with the instructions
given by the Three Parties.
10.3 The ownership of the GOSAT data provided by the Three Parties to the RO shall be managed inaccordance with the following provisions.
10.3.1 The “Intellectual Property Rights” whatsoever concerning the GOSAT data provided to
the RO shall belong to the Three Parties
10.3.2 Notwithstanding the previous provision, in case that the RO modifies the GOSAT dataand creates higher-level value-added data such that the original data is unrecoverable,
by means of advanced data processing, in the process of implementing the Joint
Research, the ownership of the “Intellectual Property Rights” of such data shall be
determined in light of the proportions of intellectual contribution of the Three Parties
and the RO to the data and other factors, in mutual consultation.

Article 11 (Ownership of and Application for the Intellectual Property Rights)
11.1 In case that the Invention(s) are derived from the implementation of the Joint Research, theThree Parties and the RO shall promptly notify the other party, and discuss the ownership of andE-5

Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

the necessity of application for the Intellectual Property Rights concerning said Invention(s).
11.2 In case that the Three Parties or the RO invents singly and independently in consequence of the
Joint Research, the Intellectual Property Rights concerning the Invention(s) shall belong solely tothe inventing party, and said party may proceed with the application process at its own discretion,
provided, however, that said party obtains approval of the other party prior to such application.
In such a case, the cost and expenses arising out of the application procedure and the preservationof the rights shall be borne by said party.
11.3 In case that the Three Parties and the RO invent jointly in consequence of the Joint Research,both parties shall co-own the Intellectual Property Rights concerning such Invention(s), in
proportion to the share of the Intellectual Property Rights mutually discussed and agreed. The twoparties shall jointly take such action as application for the Intellectual Property Rights inaccordance with the separate agreement regarding joint application to be executed between theparties hereto. In such a case, the cost and expenses arising out of the application procedure andthe preservation of the rights shall be borne by both parties in proportion to the respective portionsof such Intellectual Property Rights.

Article 12 (Overseas Application)
12.1 The provisions of the previous Article shall apply also to the application procedure and thepreservation of the Intellectual Property Rights in overseas countries.
12.2 In case that the Three Parties and the RO jointly apply for the Intellectual Property Rights
commonly owned by both parties, in accordance with the third paragraph of the previous Article,
in an overseas country, the two parties shall sufficiently confer in advance.

Article 13 (Exploitation of the Research Results)
13.1 In case that the Three Parties or the RO is willing to exploit the Research Results, the party inneed of such exploitation may do so (or make a third party do so to serve the party’s purpose) freeof charge without consent of the other party, only for the purpose of its internal research anddevelopment, which is nonprofit-making and peaceful.
13.2 In case that the Three Parties or the RO is willing to exploit the Intellectual Property Rights
commonly owned, the party shall obtain consensus of the other party in advance and pay the
exploitation fee determined in the separate agreement regarding exploitation of the Intellectual
Property Rights to be executed between the parties hereto, except for such cases as provided for in
the previous provision.
13.3 The Three Parties may exploit, edit, duplicate and distribute freely the progress reports, interim
reports and the Research Report submitted by the RO. In such a case, the PI and RA Investigators
shall not execute the moral rights.

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

Article 14 (Licensing of the Intellectual Property Rights to the Third Party)
14.1 In case that the Three Parties or the RO is willing to license the co-owned Intellectual Property
Rights resulting from the Joint Research to a third party, the party shall obtain consensus of theother party in advance in writing and both parties shall discuss and determine the details of
licensing conditions.
14.2 In case that the Intellectual Property Rights commonly owned by the parties hereto are licensed
to the third party in accordance with the previous provision, the Three Parties or the RO shallcollect the license fee determined in the separate agreement regarding licensing of the Intellectual
Property Rights to be executed between the parties hereto, from the licensed third party. The
collected license fee shall be distributed between the Three Parties and the RO in proportion to therespective portions of such Intellectual Property Rights.

Article 15 (Transfer of the Portion of the Intellectual Property Rights)
15.1 The Three Parties and the RO may transfer portion of the Intellectual Property Rights resulting
from the Joint Research solely to a designated party, in consultation with the other party. Suchtransfer shall be executed in accordance with the separate agreement regarding transfer of theIntellectual Property Rights to be executed between the parties hereto. In case that either party
transfers its own portion of the Intellectual Property Rights, the transferring party shall ensure totransfer all the rights and obligations associated with said Intellectual Property Rights to thedesignated party.
15.2 In case that the Three Parties or the RO is willing to abandon its portion of the Intellectual
Property Rights commonly owned, the abandoning party shall notify the other party first inadvance and transfer it to the other party if the other party so requests.

Article 16 (Confidentiality)
16.1 For the purpose of the Joint Research, the “Confidential Information” shall include all
information to which any of the following provisions applies.
16.1.1 Documents and tangible products, such as samples, out of the outcomes obtained inconsequence of the implementation of the Joint Research, which are indicated asconfidential, or any tangible and intangible items that are confirmed as confidential
between the Three Parties and the RO in writing.
16.1.2 Any tangible and intangible information disclosed or provided as classified informationby the other party
16.2 The Three Parties and the RO shall manage the Confidential Information in an appropriatemanner and shall not leak or disclose it to any other party than the investigators and researchersE-7

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

who are engaged in the Joint Research, except for the following.
16.2.1 Information already in the public domain at the time of disclosure or coming to theknowledge of the party.
16.2.2 Information that became publicly known due to reasons not attributable to the party after
the time of disclosure or coming to its knowledge.
16.2.3 Information that can be proven to be already known to the party at the time of disclosure
or coming to its knowledge.
16.2.4 Contents that can be proven to be learned by legal means from the third party withappropriate right without an obligation to secrecy.
16.2.5 Information or materials that can be proven to be obtained by the party independently of
the information disclosed by the other party
16.2.6 Information approved for disclosure in writing by the other party
16.2.7 Any information, the disclosure of which is required by a court order or legal authority;
if required, the required party shall promptly notify the other party of such requirement.
16.3 The obligation to maintain the confidentiality based on the previous paragraph shall remain
effective for five (5) years from the expiration (including termination) of the Contract, provided,
however, that the Three Parties and the RO may extend or shorten the Confidentiality Period
based on mutual discussion and agreement.

Article 17 (Disclosure of the Research Result)17.1 The Three Parties and the RO may release or disclose the Research Results obtained inconsequence of the Joint Research (hereinafter referred to as the “Disclosure of the Research
Results”), provided that the obligations set forth in Article 16 above are strictly observed.
17.2 In case of the previous provision, the Three Parties or RO who is willing to disclose the
Research Result (hereinafter referred to as the “Disclosing Party”) shall notify the other party inwriting of such Disclosure of the Research Results in advance and obtain prior written consent of
the other party, provided that the notified party shall not reject such request for approval without
justifiable reason.
17.3 If the notified party recognizes that the contents to be disclosed have a possibility of infringing
its interests anticipated for the future, the party shall send a written request to the Disclosing Party
for correcting the contents to be disclosed, and the Disclosing Party shall sufficiently consult withthe other party. The Disclosing Party shall not disclose the contents mentioned in the noticereceived from the other party in accordance with this provision because of the possibility of
infringing the other party’s potential interests in the future, without approval of the other party.
17.4 The Disclosing Party may make said Disclosure of the Research Results, provided that the party
explicates that the disclosed Research Results have been obtained in the process of the Joint

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Research and indicates the source of the GOSAT data.
17.5 The Three Parties and the RO shall be required to notify each other in accordance with theprovision of the second paragraph above during the effective term of the Joint Research and also
an additional one year from the following day of the completion of the Joint Research, provided,
however, that the Three Parties and the RO may extend or shorten this period by mutual
discussion and agreement.

Article 18 (Mutual Liability for Damage)
The Three Parties or the RO shall not claim for indemnification for any impediment or death that
occurs to its staff or damage to or loss of its asset, caused by the other party in the process of
implementing the Joint Research, unless otherwise such impediment or death that occurs to its staff
or damage to or loss of its asset has resulted from the intentional malpractice or gross negligence ofthe other party.
Article 19 (Temporary suspension and restart of the Joint Research)
For the following reasons listed below, which are considered to interrupt the Joint
Research beyond the PI’s or the RO’s control, the RO shall be allowed to temporarilysuspend the Joint Research upon consultation with the Three Parties. Its duration andthe timing of restart will be also decided upon consultation between the Three Parties
and the RO. In such a case, neither of the parties hereto shall claim for compensation
whatsoever.
In case if the duration of suspension becomes longer than the effective term of theContract, or in case if the timing of restart cannot be anticipated, the RO shall request
the Three Parties for the termination of the Contract and the Three Parties shall agreewith the request according to the Article 20.1.
(1) Devastating natural disasters such as earthquakes, fires, windstorm, flood, etc.
(2) Retirement of the PI(3) Long-term hospitalization or medical treatment due to sickness or an accident(4) Parturition, maternity leave, and nursing leave(5) Long-term business transfer or trip to the other organization(6) Difficulty to sustain the research system and its environment due to the budgetarysituations, etc.
(7) Difficulty to sustain the research team due to the RO’s organizational changes
And other unavoidable reasons that the Committee judges as hindering of the Joint
Research.

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

Article 20 (Termination of the Contract)20.1 The Three Parties or the RO may terminate the Contract if any of the following cases occurs:
20.1.1 The Three Parties and the RO mutually agree to termination of the Contract;
20.1.2 The other party conducts improper or unrightful deeds in the process of executing theContract and fails to remedy such deeds within seven (7) days from receipt of notice
requesting for cure of such breach by the party; and20.1.3 The other party breaches the Contract and fails to remedy such breach within seven (7)days from receipt of notice requesting for cure of such breach by the party.
20.2 Even in such a case that the Contract is terminated in accordance with this Article, the RO shallstill be required to compile all outcomes from the Joint Research performed thus far and submit inform of a report to the Three Parties.

Article 21 (Effective Term of the Contract)21.1 The Contract shall be valid for the period provided in Article 1, 2, 3, and 6 hereof.
That is, the time of commencement is the latest signing date among the authorized
signers among the Three Parties and the RO. Whereas, the time of expiration is thedate when the Committee confirms and accepts the Research Report submitted by the
PI at the completion of his/her Joint Research in accordance with Article 6, within 1
year from the most current Interim Evaluation that the Three Parties approved thecontinuation of the Joint Research.
21.2 The provisions of Articles 9, 10.2-3, and 11-15 shall survive after the effective term of theContract stipulated by the previous paragraph for the effective period for the Intellectual Property
Rights stipulated by the respective provisions, and Articles 16 and 17 shall remain valid for theperiod stipulated by the respective provisions.

Article 22 (Consultation)
The matters not provided in the Contract, if any, shall be stipulated in consultation between theThree Parties and the RO.
Article 23 (Change of RO)
23.1 The Contract between the RO and the Three Parties will be automaticallyterminated when the PI leaves the RO due to his/her transfer to the otherorganization etc.
23.2 For continuation of the RA research, new RO of the PI (or the PI him-/herself if
he/she does not belong to any organization) and the Three Parties must agree anew to
the Contract to carry out the Joint Research.

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

23.3 During the anew contracting process mentioned in the previous section, in case if
the new RO itself or its belonging country is deemed as not complying with the
purpose of the RA or as concerned to use the GOSAT data for non-peaceful purposes,
the Three Parties have a right to reject an execution of the Contract with the new RO.

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Appendix E

General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

Terms for Clarification in the General Contractual Conditions for the Joint
Research on the GOSAT data
The following “Terms for Clarification” are attached in order to give the RO clear idea of
the Contract and to enhance the smooth contracting process by disclosing its
interpretations, which were agreed between the Three Parties and certain ROs of thefirst and the second RA in the past. This clarification does not alter the contents of theContract of the first and the second RA themselves, but it is used to clarify their termsof the general contractual conditions.
Article 1 (Definitions)
The “Research Result(s)” as defined in Article 1.1.1, does explicitly not include Know-How of
the RO. The “Research Result” defined hereof is limited to modified, higher-level, value-added
outcomes and data derived from GOSAT data, in relation to the research proposed by the PI in
the RA. The “Research Results” are those confirmed in the research reports prepared inaccordance with the provisions of Article 6 hereof and are the technical outcomes and scientificfindings in consistent with the Joint Research.

Article 4 (Investigators to be Engaged in the Joint Research)
RA Investigators including PI and Co-Is may share the GOSAT data with theirlaboratories, including students, research assistants, and postdoctoral fellows
without having to obtain permission from the Three Parties for each such person.
However, in such case, it is on the premise that the RO shall have provided theThree Parties with a list of RA Investigators for access and registration to the
GOSAT data delivery site. The students, assistants, and postdoctoral fellows
working for the PI or Co-Is may access the data under the control of the PI or Co-Is
strictly for tasks of fulfilling the purposes as defined in the research proposal.
Article 7 (Specification of Know-How)
The Three Parties’ Know-How shall be considered confidential and treated as suchfor the Confidentiality Period of 5 years or until publicly released by the Three
Parties, whichever comes sooner. The Three Parties’ Know-How will be identified to
the RO before delivery by the Three Parties so that the RO can treat such Know-How
accordingly. The Know-How is limited to the technical outcomes and scientific findings
specified as the Research Results. Because the Know-How is Confidential Information describedin Article 16, each party (the Three Parties and the RO) shall treat the Know-How as Confidential

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

Information. However, the Three Parties acknowledge that the RO is not obligated to treat its
own RO Know-How as Confidential Information in conformity of the provision of Article 16.2.3;“Information that can be proven to be already known to the party at the time of disclosure or
coming to its knowledge.” Therefore, the Three Parties acknowledge that the RO decides how theRO treats its own Know-How.
The Three Parties acknowledge the RO’s position that the RO does not wish to receive
information or data from the Three Parties that places any sort of confidentiality obligation on the
RO that inhibits the RO from publishing its own Research Results, its own Know-How, or any
RO-generated higher-level, value-added GOSAT data. And that is, the Three Parties understandthat certain ROs wish to act under a principle of free publication of their own Research Results,
which is, except the Three Parties’ Know-How, these ROs may freely publish their own Research
Results, Know-How, or any RO-generated higher-level, value-added GOSAT data without amoratorium or prior approval from any other party.
However, in order to preserve scientific integrity and to allow all parties involved to coordinate
fair opportunities in prospective publications, the RO shall submit proposed publications to theThree Parties 30 days prior to submission of said publication to journals or conferences in writing,in order to allow the Three Parties to review and coordinate said publication and to identify Three
Parties’ confidential or proprietary information.
Article 9 (exchange of Information)
Article 9 is for the purpose of granting an offer or an exchange of technical documents,
programs, and advices between the Three Parties and the RO when the both parties
agree. This is absolutely not to intend the RO for submitting program code or
algorithms to the Three Parties or any third parties (other research institutes).
Regardless of Article 9, validation methods or algorithms are the subjects to be
published in scientific journals or magazines.
Article 11 (Ownership and Application of the Intellectual Property Rights)
For purposes of the work carried out under this Contract, the RO will provide noticeto the Three Parties when the RO intends on pursuing protection regarding its
intellectual property. The Three Parties agree that approval for the RO to proceedwith protecting its intellectual property will not be unreasonably withheld. The Three
Parties understand that the RO does not usually accept a requirement to get approval
from another party to proceed with protecting our own intellectual property.
Article 13 (Exploitation of the Research Results)

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General Contractual Conditions for the Joint Researchon the GOSAT data (Third RA)

The RO can exploit the Research Results generated by itself for any purpose, but theymust be non-profit-making and peaceful purpose. The Three parties understand that
this provision is meant to grant a license to the Three Parties to use the Research
Results in a particular way and not meant to restrict the RO’s use of its own Research
Results.
Article 16 (Confidentiality)
The Three Parties and the RO shall manage the Confidential Information defined in
Article 16.1 in an appropriate manner and shall not leak or disclose it to any otherparty than the investigators who are engaged in the Joint Research during theConfidentiality Period of Article 13.3. (The Confidential Information includes theKnow-How of other organizations, but for the RO’s own Know-How, its own Research
Results, or any RO-generated higher-level, value-added GOSAT data that the original
data is unrecoverable, they might not be considered as the Confidential Information if
the RO decides them not to be defined so.)
Article 17 (Disclosure of the Research Result)
As defined in Article 16 hereof, the Confidential Information is the Know-How andother information that are agreed as confidential between the Three Parties and the RO in
writing. Therefore, for the RO’s own Know-How, its own Research Results, or any
RO-generated higher-level, value-added GOSAT data that the original data is
unrecoverable, if they are not confirmed as the Confidential Information between theThree Parties and the RO, they are not the Confidential Information and the RO canfreely publish them. However, again, in order to preserve scientific integrity and to allow allparties involved to coordinate fair opportunities in prospective publications, the RO shall notify
the Three Parties about the prospective publication in writing and submit proposed publications to
the Three Parties 30 days prior to submission of said publication to journals or conferences inorder to allow the Three Parties to review and coordinate said publication and to identify Three
Parties’ confidential or proprietary information.
Article 18 (Mutual Liability for Damage)
Each party (the Three Parties and the RO) shall be responsible for any claims anddemands arising under the Joint Research in proportion to its fault in the events
giving rise to such claims and demands, as determined by the law and judicial
precedent and as limited by any law applicable to one or the other of the Parties.

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Article 22 (Consultation)
In case of conflict between these Terms for Clarification and the “General Contractual Conditions
for the Joint Research on the GOSAT data”, the Three Parties and the RO shall agree to further
discuss the clarification.

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Appendix E
Thermal And Near infrared Sensor for carbon Observation(TANSO) onboard
the Greenhouse gases Observing SATellite (GOSAT)The Third Research Announcement
Joint Research Agreement
The Japan Aerospace Exploration Agency (JAXA), the National Institute forEnvironmental Studies (NIES) and the Ministry of the Environment (MOE) (hereinafterreferred to as the “Three Parties” collectively) made the Third Research Announcement
on GOSAT (hereinafter referred to as the “3rd RA”) in August 2010 following the lastyear’s Second Research Announcement, in order to solicit research proposals from publicwith regard to the use of data acquired by GOSAT, aiming to further exploit the outcomesand effectiveness of the GOSAT Project. A following research proposal was selected by
the RA Selection and Evaluation Committee and adopted by the Three Parties.
Title of Research Proposal:(Principal Investigator (hereinafter “PI”):)

The Three Parties and the Research Organization (hereinafter referred to as the “RO”)
of the PI or PI himself/herself, who submitted the adopted research proposal, hereby
enter into and execute this Joint Research Agreement pursuant to the terms andconditions of the “General Contractual Conditions for the Joint Research on the GOSAT
data (3rd RA)” (Attachment A).
The PI will be delivered the GOSAT data based on the “Provision of and Rights to the GOSAT
Data” defined in Article 10 of the General Contractual Conditions mentioned above and the“GOSAT/TANSO Data Policies” described in Chapter 4 of the RA main text. (For the“JAXA’s satellite data other than the GOSAT data”, please refer to Attachment B.) As referredin Chapter 8.1 “Rights” of the PI in the RA main text, the number of observation requests
and deliverable standard/research products will be determined in terms of thecompliance with the purpose of the research. Also note that the technical information
about sensors etc. is subject to change. When any change occurred, it will be informed to
the PI by the GOSAT RA office.
The Contract shall be valid for the period provided in Article 1, 2, 3, and 6 of theGeneral Contractual Conditions, which is for the operational period of GOSAT/TANSO plus theoperational period of its ground system—five years after the launch, in principle (until January 22,2014). The time of commencement is the latest signing date among the authorized signersof the Three Parties and the RO. Whereas, the time of expiration is the date when theCommittee confirms and accepts the Research Report submitted by the PI at thecompletion of his/her Joint Research in accordance with Article 6 within 1 year from themost current Interim Evaluation that the Three Parties approved the continuation of the
Joint Research.
IN WITNESS WHEREOF, the parties hereto have executed in duplicate by placing
signatures of the representatives of the Three Parties and the Organization (or PI), andAppendix E
the RA office and the representative(s) of the Organization shall keep one copy of theoriginals.
(Signatures)
1. Representative(s) of the Organization of the PI (or the PI himself/herself in case he/she
does not belong to any organization):
Name of Organization:
Contact Address:
Name of Representative(s):Date:Signature

2. Representative of the Three Parties:
Space Applications Mission Directorate
Japan Aerospace Exploration Agency
Director: Takashi Hamazaki
Date:
Signature
Takashi Hamazaki
Center for Global Environmental Research
National Institute for Environmental Studies
NIES GOSAT Project Leader: Tatsuya Yokota
Date:
Signature
Tatsuya Yokota
Research and Information Office, Policy and
Coordination Division, Global Environment Bureau
Ministry of the Environment, Japan
Section Chief: Taro Kawasato
Date:
Signature
Taro Kawasato

Thermal And Near infrared Sensor for carbon Observation (TANSO)
on board
the Greenhouse gases Observing SATellite (GOSAT)

Research Announcement

Appendix F

User Category, Glossary and Abbreviation List

F.1

User Category

Users of GOSAT products are categorized as follows.

F.1-1 Categories of GOSAT product users
User category

Description

Project staff (PS)

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

RA Investigator (RA)A cooperative investigator who works with the PI to carry out the research
activities represented by the PI and is registered by the Three Parties.

RA* Investigator

An RA Investigator who researches on a theme in the algorithm orcalibration/validation fields.

(RA*)
RA+ Investigator(RA+)
Science Team
member (ST)Science Team
member* (ST*)
General user (GU)F.2

An RA Investigator who researches on a theme in the models or dataapplication fields.
Member of the GOSAT Science Team (excluding those members who
research on themes in the calibration/validation field.)
A Science Team member who researches on a theme in the algorithm orcalibration/validation fields.
A general GOSAT data user who does not fall under any of the above
categories.

Glossary and Abbreviations List

The following tables list up and explain the terms and abbreviations used in the RA.

Table F.2-1 Glossary
Term
RA Investigator

Description
An investigator who carries out the research on a theme selected in the RA.
He or she works with the PI to carry out the research activities represented
by the PI, and is registered by the Three Parties.

F-1

Term
RA Selection and
Evaluation
Committee(TheCommittee)
Apodization

Description
A committee which selects research proposals submitted in response to the
RA and provides the Three Parties with advice in the process of selecting
research themes. The committee also evaluates the progress and results of
the research by the selected RA Investigators and provides the Three Parties
with necessary advice.
It represents a convolution procedure using a pseudo weighting function(apodizing function) as a function of the optical path difference when theinterferogram is Fourier-transformed into the spectrum. The interferogram ismultiplied by the apodizing function before the Fourier transform.

In thecase of no apodization, the instrumental line shape function is the sincfunction. Generally, the apodization makes the full width at half maximumof a instrumental line shape function larger, although unphysical oscillationof the sinc function is suppressed.
Along-track direction

Flight direction of the satellite on the spacecraft fixed coordinates.

Interferogram

Patterns of interferometric light obtained as a result of the following steps: i)split incident light into two beams using the beam splitter, ii) change one ofthe path lengths of the two split beams, and iii) let the two beams of lightinterfere with each other again.

Inverse modelA method (model) to estimate the sources and sinks and the emission andabsorption of atmospheric constituents of interest, such as CO2, using
observation data such as the GOSAT data, with the combined use of
atmospheric transport models and statistical techniques.

Aerosol

A microscopic liquid or solid particle floating in the atmosphere.

Original data

Products provided by JAXA or NIES. This should be distinguished fromthe data obtained as a result of the research carried out by RA Investigators.

Observation request

A request for specific data acquisition for a specific purpose, such as anobservation over a calibration/validation site, which is not covered by
GOSAT’s routine observation (in lattice point).

Geometric correction

A process of correcting the positional information in observation data, suchas band-to-band registration, correction of the latitude and longitudes ofobservation points based on elevation information, etc.

Gaseous column

The total amount of gas present in the vertical air column per unit area.

amount(Number of molecules per unit area).

(column abundance)
Gaseous

Vertical distribution of gaseous concentrations (Number of molecules perconcentration profile

unit area or volumetric ratio of the target species per unit area)

F-2

Term

Description

Cross-track direction

The direction perpendicular to the flight direction of the satellite on thesatellite fixed coordinates.

Gain

The signal amplification factor used for amplifying signals to an appropriate
signal processing level (voltage), set up by using commands for every
brightness (light intensity) of observation targets. For GOSAT, there arethree gain setting levels each for FTS and CAI: L (Low), M (Middle), and H(High).

Validation stage

GOSAT L2 and L3 products will undergo the following three validation
stages before released and distributed to users.
(i) Initial check
Visual check on the result of processing of certain observation data, inorder to confirm the validity of calibration of the sensor characteristics
and data processing algorithms.
(ii) Validation analysis:
Comparison of GOSAT observation data with validation data, in order toevaluate the reliability of the products.
(iii) Confirmation after the release:
Check to be performed after releasing the products to limited users, tosee if any problem with the products is reported after a certain period oftime.
The products are categorized into four stages in the process of thesevalidation steps, namely U (Unchecked), P (Preliminarily checked), V(Validated), and C (Confirmed). These stages are called the “validation
stages”.

Corner cube

A trihedral made up of three planer reflectors which are perpendicular toeach other. The light injected into the trihedral bounces on each of thethree planes and will always return to the incident direction.

Science TeamAn organization established for the purpose of providing the GOSAT Projectwith scientific advice.

Sunglint

Specular reflection of the sunlight on the water surface, in general. In thisphenomenon, the specular reflection point is on the same plane as the sun
and the sensor, and the reflection angle is the same as the incidence angle.
However, as the intensity of the reflected light reaching the sensor is thestrongest in the vicinity of such a reflection point, FTS observes the vicinityof specular reflection points for its water-surface observation.

Scan

The unit of acquisition of one interferogram by FTS.

F-3

Term
Instrument

Descriptionfunction Calibration performed with consideration given to the wavelength

calibration

dependence of the sensitivity .

Atmospheric transport A numerical model to estimate the distribution of an atmospheric constituent
model

of interest (e.g., CO2, CH4) and its variation under certain condition.

Incase of CO2 (or CH4), the model simulates the variation of its concentration
based on the existing flux data, with meteorological data (air temperature,
wind parameters, etc.) and chemical reactions in the atmosphere taken into
consideration.
Dichroic filter

An optical filter which passes only light with specific wave number bandand reflects the other.

Sun-synchronous
sub-recurrent orbit

An orbit combining a sun-synchronous orbit and a sub-recurrent orbit,
having the characteristics of the two. In the former orbit, the orbital planeof the satellite rotates once while the earth revolves the sun once (onerevolution). In the latter orbit, the satellite returns to almost the same orbit
at a certain interval (recurrence).

GOSAT returns to almost the same

footprint after 44 orbits in three days.

The descending node time (local

solar time) is adjusted to around 13 o’clock, and the local time at the nadir
point of the satellite is almost the same time at medium and low latitudes.
Carbon flux
estimation model

A model to estimate the emission and absorption of carbons for a region (acertain scale which the entire globe is divided into), based on the
distributions of CO2, etc. in the atmosphere obtained by GOSAT orotherwise together with meteorological data.

Observation in lattice
point

Regular observation of FTS on the fixed ground points (lattice points).

In

all the five pointing modes (depending on the number of points per scan, 1,
3, 5, 7, or 9), the sensor observes the same footprint every recurrence after
three days.

Specific point

Observation over specific ground points other than the lattice points

observation

observed in the routine observation, such as calibration/validation sites,
observation points along a natural gas pipeline, etc.

Source inventory

Information concerning the location and volume of sources of carbon orother species.

Band pass filter

An optical filter which passes only light with wave numbers in a certain
range, and rejects (attenuates) light with wave numbers outside that range.

F-4

Term
Full-widthatDescription
half An indicator of the spread (width) of a chevron-shaped function, such as

maximum (FWHM)

instrument function.

It is defined as the difference in the wavelengths orwave numbers at the two points where the value of the function marks a halfof the maximum.
Radiance calibration

Correction process of converting integer values (digital numbers) ofobservation data to the radiance unit, using various observation data.
The abbreviation of the Principal Investigator, who represents the group of

PI (Principal

investigators who engage in the research activities on the research theme

Investigator)

adopted in the RA and serves as the contact person to the Three Parties on
all matters relating to the joint research agreement.

Beam splitter

Fourier

An optical device which splits a light flux into two. A part of the light
injected into the beam splitter reflects back and the other part penetrates. A
beam splitter which splits polarization components is called a polarized
beam splitter.

Transform An observing instrument which observes the interferometric light

Spectrometer (FTS)(interferogram) acquired with the interferometer, and Fourier-transforms it
into radiance spectra.

In the GOSAT Project, the spectrometer is applied tomeasure the absorption spectra of CO2, CH4, etc.
Product

An electronic file, containing the processed results of GOSAT’s observation
data, prepared in the predetermined format for distribution to users.

Product

distribution A request made by an RA investigator for provision of data products

requestnecessary for implementing the research on the selected theme.

Spectral resolution

The minimum difference in wavelength, in case of the wavelength
resolution, or wave number, in case of the wave number resolution, that the
spectrometer can determine.

Polarization

Light of which the electric or magnetic field oscillates in a specificdirection.

ManeuverAn activity to control the attitude, speed, etc. , consequently orbit, of thespacecraft, by thrusting its control engine, etc.

It is performed in order tomaintain or change the spacecraft to the expected attitude or orbit.
Land

ecosystem A model which expresses the exchange processes of heat, water, carbon, etc.

model

(e.g., photosynthesis, respiration) between the land ecosystem, comprised offorest, pasture, etc., and the atmosphere.

F-5

Table F.2-2 Abbreviation List
Abbreviation

Description

ADEOS

ADvanced Earth Observation Satellite

ADEOS-II/GLI

ADvanced Earth Observation Satellite-II/GLobal Imager

AERONET

AErosol RObotic NETwork

AIRS

Atmospheric InfraRed Sounder

ALOS

Advanced Land Observing Satellite

ASE

Association of Space Explorers

ASTER

Advanced Spaceborne Thermal Emission and Reflection Radiometer

AT

Along Track

CALIPSO

Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation

CAM

monitor CAMera

CME

Continuous CO2 Measuring Equipment

CNES

Centre National d'Etudes Spatiales (in French) : National Center of SpaceStudies (in English)

CSIRO

Commonwealth Scientific and Industrial Research Organization

CT

Cross Track

DB

Diode Box

DEM

Digital Elevation Model

ENVISATENVIronmental SATellite

EOS

Earth Observing System (NASA Project)

FFT

Fast Fourier Transform

GAW

Global Atmosphere Watch (WMO Project)

GCP

Ground Control Point

GOME

Global Ozone Monitoring Experiment

GOSAT

Greenhouse gases Observing SATellite

GSFC

Goddard Space Flight Center(NASA)

GSHHS

Global Self-consistent Hierarchical High-resolution Shorelines

HDF

Hierarchical Data Format

HITRAN

HIgh-resolution TRANsmission molecular absorption database

HSTAR

High-resolution System for Transfer of Atmospheric Radiation

IASI

Infared Atmospheric Sounding Interferometer

IGM

InterferoGraM

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Abbreviation

Description

IIR

Imaging Infrared Radiometer

ILAS

Improved Limb Atmospheric Spectrometer

IMG

Interferometric Monitor for Greenhouse Gas

IRS

Indian Remote Sensing satellite

JAXA

Japan Aerospace Exploration Agency

JERS

Japanese Earth Resources Satellite

JPL

Jet Propulsion Laboratory

LLM

Light Load Mode

LUT

Look Up Table

MAP

Maximum A Posteriori

MDP

Mission Data Processor

MODIS

MODerate resolution Imaging Spectroradiometer

MOE

Ministry Of the Environment of Japan

MOS

Marine Observation Satellite

MTF

Modulation Transfer Function

NDACC

Network for the Detection of Atmospheric Composition Change

NDVI

Normalized Difference Vegetation Index

NetCDF

Network Common Data Form

NIES

National Institute for Environmental Studies (Japan)

NIR

Near InfraRedNOAANational Oceanic and Atmospheric Administration

OCO

Orbiting Carbon Observatory (NASA Spacecraft)

OMI

Ozone Monitoring Instrument

POLDER

POLarization and Directionality of the Earth's Reflectances

PPDF

Photon Pathlength Distribution Function

PRISM

Panchromatic Remote sensing Instrument for Stereo Mapping

U,P,V,C

Unchecked,Preliminary checked,Validated,Confirmed (Stages of Validation)

RA

Research Announcement

RAMCES

Reseau Atmospherique de Mesure des Composes a Effet de Serre (inFrench) : Near Real Time CO2 Concentration (in English)

ROLO

RObotic Lunar Observatory

RSTAR

Remote sensing System for Transfer of Atmospheric Radiation

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Abbreviation

Description

SAR

Synthetic Aperture Radar

SCIAMACHY

SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY

S-LLM

Super-Light Load Mode

SNR

Signal to Noise Ratio

SPOT

Satellite Pour l'Observation de la TerreSPRINTARS

Spectral Radiation-Transport Model for Aerosol Species

ST

Science TeamSWIR

Short Wavelength InfraRed / Short Wave Infrared Radiometer

TANSO

Thermal And Near infrared Sensor for carbon Observation

TANSO-CAITANSO－Cloud and Aerosol Imager

TANSO-FTS

TANSO－Fourier Transform Spectrometer

TCCON

Total Carbon Column Observing Network

TES

Tropospheric Emission Spectrometer

TIR

Thermal Infrared Radiometer

TOMS

Total Ozone Mapping Spectrometer

TRANSCOM

atmospheric tracer TRANSport model interCOMparison project

TRMM

Tropical Rainfall Measuring Mission

USGS

U.S. Geological Survey

VGA

Video Graphics Array

WDCGG

World Data Centre for Greenhouse Gases

WFC

high-resolution Wide Field Camera

WMO

World Meteorological Organization

WWW

World Wide Web

ZPD

Zero Path Difference

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