JAXA Supercomputer System Annual Report February 2025-January 2026

Report Number: R25ER3500

Subject Category: Space Technology

PDF (to be added)

• Responsible Representative: Hiroshi Suto, Space Technology Directorate I Satellite Applications and Operations Center, Mission Manager
• Contact Information: Kei Shiomi, Shin ISHIDA, Rio KAJIURA(shiomi.kei@jaxa.jp;ishida.shin@jaxa.jp;kajiura.rio@jaxa.jp)
• Members: Makiko Hashimoto, Shin Ishida, Kenji Kowata, Fumie Kataoka, Yuki Kobayashi, Nobuhiro Kikuchi, Taro Makino, Tomoyuki Mabuchi, Kei Shiomi, Hiroshi Suto, Hideki Suetake, Yugi Yata, Yasufumi Saijoh, Tomoe Uchida, Rio Kajiura

Abstract

GOSAT‑2, the Greenhouse Gases Observing Satellite, has far exceeded its design lifetime and has continued observations for approximately eight years. As the characteristics of its onboard sensors (TANSO‑FTS‑2 and TANSO‑CAI‑2) change with prolonged operation, radiometric, geometric, and spectral properties are continuously evaluated through calibration and validation. Furthermore, by appropriately reflecting the obtained calibration results in the processing algorithms, the long‑term consistency of the dataset is ensured and the accuracy of greenhouse gas concentration estimates is improved.

Reference URL

Please refer to https://www.jaxa.jp/projects/sat/gosat2/index_j.html .

Reasons and benefits of using JAXA Supercomputer System

Processing the large volume of data accumulated through GOSAT-2's long-term operation requires greater computational resources, including more CPU cores, memory, and storage. To shorten the processing period and provide processed products to users more rapidly, the use of JSS3 is essential.

Achievements of the Year

(1)Processing for routine generation of TANSO-CAI-2 Level-1B products and the creation of browse images for public release

To enable early detection of operational issues or anomalies, we generated browse images for public release and processed GOSAT‑2/CAI‑2 data equivalent to Level-1B, which are used as inputs for higher‑level processing. In addition, we checked the Level‑1B processing status associated with missing satellite data.

Processing period are as follows.

2025/04/01-2026/03/31

(2) Development and validation of research products for TANSO‑FTS‑2

A research level retrieval algorithm is being developed that simultaneously utilizes short‑wavelength infrared (SWIR) and thermal infrared (TIR) spectra derived from Level‑1 data of TANSO‑FTS‑2 to retrieve carbon dioxide and methane concentrations in the troposphere in two vertical layers. In addition, by using the polarization information contained in the SWIR measurements, the algorithm aims to improve the accuracy of aerosol correction. The version released in 2023 revealed large discrepancies in CO₂ and CH₄ concentrations over oceanic regions, prompting an algorithm update. Using the improved algorithm, GOSAT‑2 data from 2019 to 2024 were processed. Figure 3 shows the 2.5‑degree grid monthly mean distributions of column averaged CO₂ and CH₄ concentrations derived from GOSAT and GOSAT‑2.

(3) Reprocessing associated with the TANSO‑FTS‑2 Level‑1 product version upgrade

Since the start of observations by TANSO‑FTS‑2 and TANSO‑CAI‑2, reprocessing of past Level‑1 products has been carried out on JSS3. In FY2025, analysis based on instrument function calibration and monthly calibration revealed that the sensitivity of the Band 1P/Band 1S bands previously degraded had begun to recover around 2023. Therefore, a parameter version update was implemented to revise the radiance degradation correction model for TANSO‑FTS‑2 (SWIR B1P/B1S only) for data acquired after November 15, 2022. A supercomputer was then used to generate the reprocessed products (V240240).

Fig.1: GOSAT-2 CAI-2 L1B processing on JSS-3

Fig.2: GOSAT-2 CAI-2 L1B brows image produced on JSS-3

Fig.3: The 2.5‑degree grid monthly mean values of column‑averaged greenhouse gas concentrations derived from GOSAT and GOSAT‑2 using the TANSO‑FTS‑2 research product algorithm. All data is for July 2022. (Top left) Column averaged concentration of carbon dioxide derived from GOSAT. (Top right) Column averaged concentration of methane derived from GOSAT. (Bottom left) Column averaged concentration of carbon dioxide derived from GOSAT-2. (Bottom right) Column averaged concentration of methane derived from GOSAT-2.

Publications

- Web

https://www.eorc.jaxa.jp/GOSAT/GOSAT-2/cai2.html

Usage of JSS

Computational Information

• Process Parallelization Methods: N/A
• Thread Parallelization Methods: Items (1) and (3) of this year's achievements are not applicable, while item (2) corresponds to OpenMP.
• Number of Processes: 1
• Elapsed Time per Case: 8 Hour(s)

JSS3 Resources Used

Fraction of Usage in Total Resources*1(%): 0.08

Details

Please refer to System Configuration of JSS3 for the system configuration and major specifications of JSS3.

*1: Fraction of Usage in Total Resources: Weighted average of three resource types (Computing, File System, and Archiver).

*2: Fraction of Usage：Percentage of usage relative to each resource used in one year.

ISV Software Licenses Used

*2: Fraction of Usage：Percentage of usage relative to each resource used in one year.

JAXA Supercomputer System Annual Report February 2025-January 2026