Minimize GOSAT-2

GOSAT-2 (Greenhouse gases Observing Satellite-2) / Ibuki-2

Spacecraft    Launch    Mission Status    Sensor Complement    References

GOSAT-2 is a follow-on Japanese mission in planning of GOSAT/Ibuki which was launched on January 23, 2009. The experiences gained from the operation of the GOSAT mission with regard to payload calibration and validation activities serve as input for the requirements of the GOSAT-2 mission. 1)

Although TANSO-FTS (on GOSAT) has some anomalies, GOSAT has accomplished certain results; in particular, the project recognized the availability of the GHG (Greenhouse Gas) observation from space and at the same time it has been pointed out that it's necessary to improve the concentration measurement precision to expand this mission to make it useful for humankind.

Hence, Japan's three parties, MOE (Ministry of the Environment), NIES (National Institute for Environmental Studies) and JAXA (Japan Aerospace Exploration Agency), which have led the GOSAT project, have investigated the requirements on the future greenhouse gases observation and defined the mission requirements for the GOSAT-2 mission. The overall mission goal is to give policy makers further observed and analyzed data on climate changes to contribute to decisions on emission reduction targets based on scientific facts. 2) 3)

Mission requirements

GOSAT

GOSAT-2

Uncertainty reduction of the future forecast

1. Concentration measurement precision

4 ppm (CO2)
34 ppb (CH4)
Observational period: 3 month
- 1,000 km mesh (terrestrial region)

0.5 ppm (CO2)
5 ppb (CH4)
Observational period: 1 month
- 500 km mesh (terrestrial region)
- 2,000 km mesh (ocean)

2. Estimation accuracy of flux

Reduce the estimation error on the sub-continental scale to half compared with the one estimated using only ground observation data

Estimate the monthly net fluxes with the accuracy of ±100%. Use of 1,000 km mesh (terrestrial region) and 4,000 km mesh (ocean)

Monitoring of greenhouse gas emissions

3. Expansion of the observation gases

-

Examine the feasibility of the calculation of the anthropogenic emission with the observation of the correlated material such as CO and NO2

4. Improvement of the natural emission estimation accuracy

(Chlorophyll Fluorescence observation as a result)

Investigate the correlation between the distribution of greenhouse gases and the vegetation activity

Table 1: Observational requirements for the GOSAT and GOSAT-2 missions

Some background: Experts say that greenhouse gases produced by human activity represent one of the biggest causes of global warming. The IPCC ( Intergovernmental Panel on Climate Change), an international organization of specialists that conducts scientific research on climate change and evaluates related climate policies, released its Fifth Assessment Report in 2013. In the document, the authors warned that "Warming of the climate system is unequivocal... It is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century... Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system." 4)

As the successor to the Ibuki mission, GOSAT-2 aims to gather observations of greenhouse gases with higher levels of accuracy via even higher-performance onboard observation sensors. The project will serve to provide observation data to environmental administrations and drive international anti-global warming efforts.

In December 2013, JAXA selected MELCO (Mitsubishi Electric Corporation) to build the GOSAT-2 spacecraft which is slated for launch in 2018. Mitsubishi Electric expects to be formally authorized to proceed with the development in April 2014, after completing an engineering contract with JAXA to finalize definitive performance requirements. 5) — In April 2014, JAXA awarded the GOSAT-2 contract to Mitsubishi Electric to officially begin developing the satellite system. 6)

GOSAT-2, like GOSAT/Ibuki, is a joint project of MOE, NIES and JAXA. Its high-performance sensor instrumentation will enable the collection of even more accurate data than was possible with Ibuki. 7)

In May 2014, ITT Exelis of Rochester, N.Y. (now Harris Corp. with HQ in Melbourne FL USA), has been awarded a contract to build TANSO-FTS (Thermal and Near-Infrared Sensor for carbon Observation-Fourier Transform Spectrometer), the primary payload for GOSAT-2. 8)

The goals for the GOSAT-2 are to measure carbon dioxide at 0.5 ppm and methane at 5 ppb at a 500 km mesh. Developers have also enhanced the satellite's focused, target-point observation capabilities (target-point observation functionality), enabling the device to gather accurate readings from a broader range of target points - an ability that will be especially beneficial in evaluations of industrial areas, densely populated areas, and other areas with large quantities of greenhouse gas emissions.

In another improvement over its predecessor, the GOSAT-2 is also capable of monitoring carbon monoxide concentrations. Whereas carbon dioxide not only comes from anthropogenic sources like industrial activity and fuel combustion but also has natural origins in forests and biological activity, carbon monoxide emissions are byproducts of human activity alone – not the natural world. Analyzing combined observations of carbon dioxide and carbon monoxide will give researchers an effective means of estimating carbon dioxide emissions from anthropogenic sources.

Item

GOSAT-2

GOSAT

Observed greenhouse gases

CO2, CH4, O3, H2O, CO, NO2

CO2, CH4, O3, H2O

Instruments

1. FTS (Fourier Transform Spectrometer)
2. Imager

1. FTS
2. Imager

LTAN (Local Time on Ascending Node)

13:00 ± 0:15 hr

13:00 ± 0:15 hr

Orbital altitude

613 km

666 km

Revisit time

3 days (may be increased)

3 days

TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer)

Coverage

Cross-track: ±35º, Along-track: ±40º

Cross-track: ±35º, Along-track: ±20º

Sampling

About 160 km interval, (5 points in the CT)

About 160 km interval

IFOV

10.5 km

10.5 km

Spectral ranges

1) 0.75-0.77 µm, 12,900-13,200 cm-1 (P/S) (O2A)
2) 1.59-1.67 µm, 6,000-6,300 cm-1 (P/S) (CO2,CH4)
3) 2.04-2.08 µm, 4,800-4,900 cm-1 (P/S) (CO2)
4) 2.33-2.38 µm, 4,200-4,300 cm-1 (CO)

5) 5.5-14.3 µm, 700-1,800 cm-1 (CO2,CH4,O3)

1) 0.75-0.77 µm, 12,900-13,200 cm-1 (O2A)
2) 1.59-1.67 µm, 5,800-6,400 cm-1 (CO2,CH4)
3) 2.04-2.08 µm, 4,800-5,200 cm-1 (CO2)
4) 2.33-2.38 µm, 700-1,800 cm-1 (CO2,CH4,O3)

Sampling duration

4 s

4 s

Function

Intelligent pointing

-

Spectral resolution

0.2 cm-1

0.2 cm-1

SNR

>400 (Band 1)
>300 (Band 2 to 5)
@SZA=30º, albedo=0.3)

>300

TANSO-CAI (Thermal And Near infrared Sensor for carbon Observation - Cloud and Aerosol Imager)

Spectroscopic System

Band pass filter and grating

Band pass filter

Spectral ranges

1) 322-450 nm (1 nm step)
2) 664-684 nm (eliminated ?)
3) 860-880 nm (eliminated ?)

4) to be eliminated

1) 370-390 nm
2) 664-684 nm
3) 860-880 nm
4) 1555-1645 nm

Spatial resolution, swath

1 km, 1000 km

Band 1-3: 500 m, 1000 km
Band 4: 1500 m, 750 km

Table 2: Tentative specifications of GOSAT-2 observations

GOSAT2_AutoB

Figure 1: GOSAT-2 and Climate Change Related Policies

 


 

Spacecraft:

The spacecraft is being manufactured by MELCO (Mitsubishi Electric Corporation), Kamakura Works, Japan as the prime contractor of GOSAT-2. JAXA awarded a preliminary contract to MELCO in December 2013 and a final contract in April 2014. In addition to building the GOSAT-2 spacecraft, a role MELCO performed for the first GOSAT, the company will manage development of the GOSAT-2 sensors and ground system as well as provide operation and maintenance services throughout the orbital design life of GOSAT-2, helping to ensure reliable, high-quality data.

The GOSAT-2 spacecraft is a medium-size satellite with two solar paddles. Its design is based on JAXA's ALOS-2 satellite launched in 2014. GOSAT-2 has a mass of about 1700 kg (dry mass), provides a power generation of 5 kW and has a design life of 5 years.

GOSAT2_AutoA

Figure 2: Artist's rendition of the deployed GOSAT-2 spacecraft (image credit: JAXA)

Parameter/Item

GOSAT-2

GOSAT

Orbit type

Sun synchronous

Sun synchronous

Local equator crossing time in a descending node

13:00 ± 0:15 hour

13:00 ± 0:15 hour

Altitude

613 km

666 km

Repeat cycle

6 days

3 days

Spacecraft size (main body)

5.3 x 2.0 x 2.8 m

3.7 x 1.8 x 2.0 m

Spacecraft mass

< 2,000 kg

1,750 kg

Spacecraft power

5.0 kW

3.8 kW

Table 3: Major requirements of GOSAT-2 spacecraft 9)

 

Development status:

• June 13, 2018: The Harris-built TANSO-FTS-2 instrument was delivered to Mitsubishi Electric Corporation for their GOSAT-2 Satellite, which is building the satellite for JAXA (Japanese Aerospace Exploration Agency). 10)

- This represents the third instrument Harris has delivered to Japan in recent years, including two advanced imagers for the Himawari-8 and -9 weather satellites, which launched in 2014 and 2016, respectively.

 

Launch: The GOSAT-2/Ibuki-2 satellite was launched on 29 October 2018 (04:08:00 UTC, 13:08:00 JST) on the H-IIA vehicle. The launch site was TNSC (Tanegashima Space Center), Kagoshima, Japan. — The launch and flight of H-IIA F40 proceeded as planned. The separations of GOSAT-2 and KhalifaSat were confirmed respectively at approximately 16 minutes and 09 seconds and 24 minutes and 15 seconds after liftoff. 11) 12)

Orbit: Sun-synchronous orbit, altitude = 613 km, inclination = 97.8º, revisit cycle of 6 days, LTAN (Local Time at Ascending Node) at 13:00 ± 0.15 hours.

Secondary payloads on this mission:

• KhalifaSat, an Earth Observation minisatellite of MBRSC (Mohammed Bin Rashid Space Center), Dubai.

• Diwata-2b, a Philippine EO microsatellite, developed at the Philippine DOST (Department of Science and Technology) in cooperation with the Tohoku University and Hokkaido University, Japan.

• PROITERES-2 (Project of Osaka Institute of Technology Electric-Rocket-Engine onboard Small Space Ship-2), a technology demonstration microsatellite (50 kg) of OIT (Osaka Institute of Technology), Japan.

• AUTcube-2, a CubeSat technology demonstration of Aichi University of Technology, Japan.

• Stars-O, a CubeSat technology demonstration of Shizuoka University, Japan.

• Ten-Koh is a technology demonstration minisatellite (220 kg) of the Kyushu Institute of Technology, Japan. The satellite is to observe LEO environments (magnetosphere observation) and the primary purpose is to provide valuable data for future development of satellites or operation.

 

Mission status

• October 30, 2018: JAXA received telemetry data from Ibuki-2 (GOSAT-2), confirming that the satellite attitude control system had transitioned to a steady state. The current status of the Ibuki-2 satellite is stable. 13)

- Subsequently, the following procedure occurred : power generation that supports the satellites' operation by the deployed solar array wings, ground communications and sound attitude control that maintains those operations. Combined by the completion of the series of other operations, such as powering up of the bus and mission equipment, Ibuki-2 has been able to sustain itself in orbit. This concludes the critical operations phase.

- Ibuki-2 will move on to the next operations phase, where the functions of the satellite's onboard apparatus will be examined approximately in the next 2.5-month period.

 


 

Sensor complement: (TANSO-FTS-2, TANSO-CAI-2)

TANSO-FTS-2 (Thermal and Near-infrared Sensor for Carbon Observation-Fourier Transform Spectrometer-2)

In May 2014, MELCO awarded a subcontract to ITT Exelis of Rochester, N.Y. (now Harris Corp. of Melbourne FL, USA) to build TANSO-FTS-2, the primary instrument for GOSAT-2 (Ref. 8). The objective of TANSO-FTS-2 is to measure the density of greenhouse gases in the atmosphere.

Applying its expertise in weather and imaging sciences, Harris is developing the primary payload for the GOSAT-2 (Greenhouse Gases Observing Satellite-2), which is planned for launch in 2018. The Harris built TANSO-FTS-2) will measure the density of greenhouse gases in the atmosphere. 14)

The Harris TANSO-FTS-2 provides very high SNR (Signal-to-Noise Ratio) levels, very accurate onboard calibration, an agile pointing system, and an intelligent pointing system that increases useful data collections in the presence of clouds. The instrument is able to detect the precise locations of greenhouse gas emissions with extremely high accuracy over the entire globe, and with rapid uptake rates. This information is critical to climate planning decision makers and climate scientists around the world.

GOSAT2_Auto9

Figure 3: Illustration of the TANSO-FTS-2 instrument (image credit: Harris Corp.)

The Harris TANSO-FTS-2 features an IP (Intelligent Pointing) system that increases useful data collections in the presence of clouds. IP uses a high-resolution RGB infrared camera to identify cloud-free regions near the commanded LOS (Line of Site) position.

As shown in the color image of Figure 4, onboard processing uses the raw camera image to create a cloud mask and then determines, via a convolution, the least cloudy area of the FOV (Field of View). The instrument LOS is then shifted to the cloud-free region before the interferogram is collected.

In the example in Figure 5, the percentage of usable cloud-free data collects increases from 20% (green locations) to 46% (green plus blue locations), which is a 2.3 times improvement. Globally, IP is expected to provide a substantial improvement in the cloud-free data yield.

GOSAT2_Auto8

Figure 4: TANSO-FTS-2 cloud-free region identification (image credit: Harris Corp.)

GOSAT2_Auto7

Figure 5: Derived cloud mask data comparison (image credit: Harris Corp.)

GOSAT-2 design feature

Mission benefits

CrIS-based passive detector cooler

Inherently reliable, achieves temperatures needed for IR detectors

New intelligent pointing function

Detects cloud-free areas and repoints scanner in real time to maximize the number of cloud-free measurements

Highly accurate and stable scanner

Minimizes scene-induced interferogram fluctuations during data collects

Very linear signal outputs

Minimizes radiance errors due to nonlinearity effects

Interferometer improvements

More stable laser outputs and more stable zero path difference position

Target for ILS characterization

Accurate on orbit ILS characterization in two spectral bands

Multiple spectralon surfaces in solar calibration target

Excellent knowledge of solar calibration target radiances over life

Flight-proven high-emissivity infrared calibration target

CrIS-based target provides emissivity >995% and temperature errors <100 mK for precise calibration accuracy

Stabilized optical temperatures

Most of instrument is actively temperature controlled to provide enhanced calibration accuracy

Stable scanner performance over life

Significant motor torque margin, full outgas of components, robust EMI shielding, reprogrammable servo coefficients

Improved solar calibration accuracy

Glint shield prevents Earth radiance of spacecraft glints from impacting solar calibration accuracy

ILS target uniformity

Integrating sphere ensures very good uniformity for best ILS calibration

Minimized scanner disturbances to interferometer

Scanner peak torques avoid zero-velocity points of interferometer turnaround, which is most sensitive for zero path difference shifts

Negligible stray light during calibration

Baffles to ensure no stray light impact to calibration

Improved telemetry for IR calibration

Large number of accurate temperature sensors provide improved calibration corrections

Fixed-rate sampling

Simplifies onboard processing while ensuring low-noise performance

Table 4: Design features enable improved mission performance for GOSAT-2

TANSO-FTS-2 measures high-resolution spectra of upwelling Earth radiance in 5 spectral bands (left) to extract concentrations of greenhouse gases (CO2, CH4) and artificial emission sources (CO). The development of TANSO-FTS-2 is being performed under a subcontract by Mitsubishi Electric Corporation, the GOSAT-2 prime contractor of the JAXA GOSAT-2 Project. 15)

Band

Spectral range (µm)

Wave numbers

Resolution

Mission purpose

1

0.755 - 0.772

12,950 - 13,250

0.2 cm-1

Total column oxygen; used to derive total column mass

2

1.563 - 1.695

5900 - 6400

0.2 cm-1

Total column carbon dioxide and methane

3

1.923 - 2.381

4200 - 5200

0.2 cm-1

Total column carbon dioxide, moisture and carbon monoxide

4

5.56 - 8.45

1183 - 1800

0.2 cm-1

Methane and moisture

5

8.45 - 14.29

700 - 1183

0.2 cm-1

Temperature profile, carbon dioxide

Table 5: Specification of the TANSO-FTS-2 spectral bands

GOSAT2_Auto6

Figure 6: Block diagram if TANSO-FTS-2 (image credit: Harris Corp.)

GOSAT2_Auto5

Figure 7: Illustration of the TANSO-FTS-2 elements (image credit: Harris Corp.)

GOSAT2_Auto4

Figure 8: Key components of the FTS-2 instrument have been completed. Top row (left to right): FOV Monitor Camera, Integrated Optics Assembly Structure, Scene Selection Assembly Structure, Telescope. Bottom row (left to right): Spectralon for solar calibration target, Chassis for command and control electronics unit, Scanner optical encoder, Circuit card assemblies (image credit: Harris Corp.)

The TANSO-FTS-2 instrument has a mass of 225 kg and an average power consumption of 270 W.

 

TANSO-CAI-2 (Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager-2)

TANSO-CAI-2 is a push-broom imaging sensor that has forward- and backward-looking bands (±20º) for observing the optical properties of aerosols and clouds, and for monitoring the status of urban air pollution and trans-boundary air pollution over oceans. An important role of CAI-2 is to perform cloud discrimination in each direction. 16) 17)

GOSAT-2 has three instruments which can be used for cloud discrimination. (1) On-board camera (CAM) is a RGB camera. It points in the direction of TANSO-FTS-2 viewing and it has higher spatial resolution than TANSO-CAI-2. TANSO-FTS-2 has an intelligent pointing system. This system judges the presence or absence of clouds in IFOV of the TANSO-FTS-2 using the CAM in on-board processing, and automatically changes the pointing angle of the TANSO-FTS-2 if there are clouds. By this system, an increase in the probability of obtaining cloud-free TANSO-FTS-2 is expected. (2) CAI-2 has a near infrared (NIR, 0.87 µm) band and shortwave infrared (SWIR, 1.60 µm) band, which are effective in cloud detection. The CLAUDIA (Cloud and Aerosol Unbiased Decision Intellectual Algorithm) is employed by GOSAT for cloud discrimination.

The derivation of aerosol optical properties needs CAI-2 cloud discrimination. Under this situation, the CAM is used for the intelligent pointing system, the CAI-2 for cloud discrimination except thin cirrus, and the 2.0 µm of the FTS-2 for thin cirrus. CLAUDIA-CAI only uses the radiances of three (center wavelengths of 0.67, 0.87 and 1.60 µm) of the four bands (Table 6).

GOSAT2_Auto3

Figure 9: Observation direction angles of GOSAT-2 TANSO-CAI-2 and Terra MISR. (a) TANSO-CAI-2 has forward- (+20º) and backward-looking (-20º) bands. (b) MISR has nine cameras (nadir, ±26.1º, ±45.6º, ±60.0° and ±70.5º forward and backward of the local vertical), image credit: GOSAT-2 Team)

Items

GOSAT-2

GOSAT

Spectral ranges (nm)

Forward viewing (+20º)

b1: 333-353
b2: 433-453
b3: 664-684
b4: 859-879
b5: 1585-1675

Backward viewing (-20º)

b6: 370-390
b7: 540-560
b8: 664-684
b9: 859-879
b10: 1585-1675

Nadir viewing

b1: 370-390

b2: 664-684
b3: 860-880
b4: 1555-1645

Spatial resolution (nadir)

except band 5, 10
460 m (700 µrad)

band 5, 10
920 m (1400 µrad)

band 1-3 band 4
500 m(750 µrad) 1500 m(2250 µrad)

Swath/FOV

every point on Earth to be observed at least twice, a recurrent cycle

band 1-3 band 4
1002 km (72º) 786 km (60º)

SNR
(@ spectral- radiance/albedo)
(W/m2/sr/µm)

b1: >200 (45/0.158)
b2: >200 (79/0.144)
b3: >200 (46/0.106)
b4: >200 (30/0.112)
b5: >200 (7/0.101)

b6: >200 (48/0.152)
b7: >200 (65/0.125)
b8: >200 (46/0.106)
b9: >200 (30/0.112)
b10: >200 (7/0.101)

b1: >200 (47/0.149)

b2: >200 (45/0.104)
b3: >200 (29/0.108)
b4: >200 (7/0.101)

Table 6: Specifications of GOSAT-2 TANSO-CAI-2 and GOSAT TANSO-CAI 18)

GOSAT2_Auto2

Figure 10: External appearance and inside of the TANSO-CAI-2 optical unit (image credit: JAXA)

GOSAT2_Auto1

Figure 11: Illustration of the lens assembly of TANSO-CAI-2 (image credit: JAXA)

Meanwhile the ABO2 (A-band oxygen cloud screeningalgorithm) was developed. Although ABO2 can judge the presence or absence of clouds in IFOV of the FTS-2 without CAI-2, the processing time of cloud discrimination using the O2A-band is longer than using CAI-2. Furthermore, there is a possibility to take advantage of the aerosol optical properties derived using CAI-2 to reduce greenhouse gas retrieval uncertainty. The derivation of aerosol optical properties needs CAI-2 cloud discrimination. Under this situation, the CAM is used for the intelligent pointing system, the CAI-2 for cloud discrimination except thin cirrus, and the 2.0 µm of the FTS-2 for thin cirrus. CLAUDIA-CAI only uses the radiances of three (center wavelengths of 0.67, 0.87 and 1.60 µm) of the four bands (Table 6). The 1.60 µm band is used to discriminate clouds in bright desert areas (Figure 12).

GOSAT2_Auto0

Figure 12: Cloud discrimination results for desert with and without the 1.60 µm band. (a) Input GOSAT CAI L1B image (GOSAT path 22 frame 26 in Algeria on 3 October 2012). R: CAI band 2, G: CAI band 3, B: CAI band 1. (b) Cloud discrimination by CLAUDIA-CAI using the 1.60 µm band. White pixels were assigned as cloud and black pixels were assigned as clear. (c) Cloud discrimination result not using the 1.60 µm band. The bright surface is misidentified as clouds (image credit: GOSAT-2 Team)

Although cloud discrimination will be performed in each direction, the use of the forward and backward cloud discrimination in the processing for the calculation of the greenhouse gases concentration was discussed. 19) Summarizing what is described in the article, it is necessary to make an addition of margins to the IFOV of the FTS-2 in a cloud discrimination result image depending on cloud moving by wind for the time difference between CAI-2 observation time and FTS-2 observation time. Thus, the difference between forward and backward cloud discrimination by CLAUDIA must be considered. Meanwhile, MISR (Multi-angle Imaging SpectroRadiometer) aboard Terra provides radiometrically and geometrically calibrated images for spectral bands at nine widely spaced angles (nadir, ±26.1°, ±45.6°, ±60.0° and ±70.5° forward and backward of the local vertical, Figure 9 (b). The center wavelengths of each of these bands are 0.45, 0.56, 0.67 and 0.87 µm. Therefore, it is possible to examine the difference in forward and backward CAI-2 cloud discrimination using the MISR 0.67 and 0.87 µm bands (CLAUDIA-MISR) at ±26.1° excluding bright desert areas.

The TANSO-CAI-2 instrument has a mass of 137 kg and a power consumption of 350 W (average in daytime;operation mode), 220 W (average in night time; stand-by mode). TANSO-CAI-2 will observe only during day time except for lunar calibration and electrical calibration.

 


1) Masakatsu Nakajima, Hiroshi Suto, Kazuhiko Yotsumoto, Masashi Abe, Akihiko Kuze, Kei Shiomi, Tomoaki Tanaka, Hiroshi Ohyama, Yumiko Tateshita, "Overview of the GOSAT-2 Mission," Proceedings of the 29th ISTS (International Symposium on Space Technology and Science), Nagoya-Aichi, Japan, June 2-8, 2013, paper: 2013-n-60

2) Masakatsu Nakajim, Akihiko Kuze, Hiroshi Suto, "GOSAT-2 - Mission Requirements and Specifications," Proceedings of the 63rd IAC (International Astronautical Congress), Naples, Italy, Oct. 1-5, 2012, paper: IAC-12, B1.2. 3

3) "Greenhouse gases Observing SATellite-2 (GOSAT-2)," JAXA, URL: http://global.jaxa.jp/projects/sat/gosat2/

4) "About Greenhouse gases Observing SATellite-2 (GOSAT-2)," JAXA, URL: http://global.jaxa.jp/projects/sat/gosat2/index.html

5) "Mitsubishi Electric Awarded Contract for GOSAT-2 Satellite System," Mitsubishi Electric, Release No 2807, Dec. 12, 2013, URL: http://www.mitsubishielectric.com/news/2013/pdf/1212.pdf

6) "Mitsubishi Electric Begins Developing GOSAT-2 Satellite System," Mitsubishi Electric, Release No 2837, April 9, 2014, URL: http://www.mitsubishielectric.com/news/2014/pdf/0409.pdf

7) Tsuneo Matsunaga, Isamu Morino, Yukio Yoshida, Makoto Saito and the NIES GOSAT-2 Project Team, "The Status of NIES GOSAT-2 Project," Proceedings of the IWGGMS-10 (10th International Workshop on Greenhouse Gas Measurements from Space) ESA/ESTEC, The Netherlands, May 5-7, 2014, URL: http://www.congrexprojects.com/2014-events/14c02/programme

8) "Exelis wins multimillion-dollar contract for climate-monitoring satellite payload," Exelis, May 20, 2014, URL: http://www.exelisinc.com/News/
PressReleases/Pages/Exelis-wins-GoSat-Contract.aspx

9) http://www.gosat-2.nies.go.jp/about/spacecraft_and_instruments/

10) "Advanced Sensor Built by Harris is Delivered to Mitsubishi Electric Corporation for their GOSAT-2 Satellite," Satnews Daily, 13 June 2018, URL: http://www.satnews.com/story.php?number=1553571907

11) "Launch Results of the H-IIA F40 Encapsulating GOSAT-2 and KhalifaSat," JAXA Press Release, 29 October 2018, URL: http://global.jaxa.jp/press/2018/10/20181029_h2af40.html

12) Stephen Clark, "GOSAT-2 and KhalifaSat," Spaceflight Now, 16 May 2018, URL: https://spaceflightnow.com/launch-schedule/

13) "Ibuki-2 (GOSAT-2) completion of critical operations phase," JAXA Press Release, 30 October 2018, URL: http://global.jaxa.jp/press/2018/10/20181030_gosat2.html

14) "TANSO-FTS-2 Instrument for the GOSAT-2 Payload," Harris, URL: https://www.harris.com/sites/default/files/downloads/
solutions/tanso-fts-2_gosat-2_datasheet_d0801.pdf

15) Ronald Glumb, Peter Mantica, Alan Bell, Christopher Ellsworth, Lawrence Suwinski, and Jeremy Dobler, "Update on the TANSO-FTS-2 instrument for GOSAT-2," URL: http://www.nies.go.jp/soc/events/iwggms12
/pdf/post/Poster_55_Ronald_Glumb.pdf

16) Yu Oishi, Takashi Y. Nakajima, Tsuneo Matsunaga, "Difference between forward- and backward-looking bands of GOSAT-2 CAI-2 cloud discrimination used with Terra MISR data," International Journal of Remote Sensing, Vol. 37 , Issue 5,pp: 1115-1126, 2016, http://www.tandfonline.com/doi/full/
10.1080/2150704X.2016.1145822
, URL: http://www.tandfonline.com/doi/pdf/10.
1080/2150704X.2016.1145822?needAccess=true

17) Yu Oishi, Haruma Ishida, Takashi Y. Nakajima, Ryosuke Nakamura, Tsuneo Matsunaga, "The Impact of Different Support Vectors on GOSAT-2 CAI-2 L2 Cloud Discrimination," Remote Sensing. 2017, 9, 1236; doi:10.3390/rs9121236, URL: https://res.mdpi.com/remotesensing/remotesensing-09-
01236/article_deploy/remotesensing-09-01236.pdf?filename=&attachment=1

18) Information provided by Dr. Masakatsu Nakajima, the mission manager of GOSAT-2 of JAXA.

19) Y. Oishi, T. M. Nagao,H. Ishida, T. Y. Nakajima, T. Matsunaga. 2015b. "Preliminary Study of a Method Using the GOSAT-2 CAI-2 Cloud Discrimination for Screening of Cloud-Contaminated FTS-2 Data." [In Japanese with English abstract.] Journal of Remote Sensing Society of Japan 35 (5): pp: 299–306
 


The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: "Observation of the Earth and Its Environment: Survey of Missions and Sensors" (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates (herb.kramer@gmx.net).

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