日本地球惑星科学連合2025年大会

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[E] 口頭発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG44] 静止軌道衛星による陸面観測

2025年5月28日(水) 09:00 〜 10:30 展示場特設会場 (5) (幕張メッセ国際展示場 7・8ホール)

コンビーナ:山本 雄平(千葉大学 環境リモートセンシング研究センター)、Miura Tomoaki(Univ Hawaii)、市井 和仁(千葉大学)、Chairperson:Tomoaki Miura(Univ Hawaii)

09:45 〜 10:00

[ACG44-03] A Hyper-temporal Monitoring of Terrestrial Evapotranspiration Using Himawari-8 Satellite

*張 北辰1市井 和仁1山本 雄平1李 偉1樋口 篤志1、Minseok Kang2、Youngryel Ryu3、Su-Jin Kim4村山 昌平5 (1.千葉大学、2.韓国国立農業気象センター、3.韓国ソウル大学校、4.韓国国立森林科学研究所、5.産業技術総合研究所)

キーワード:ひまわり8号、蒸発散量、日変化、PT-JPLモデル

Evapotranspiration (ET) is an important process whereby water loss from the Earth surface to the atmosphere, with energy transfer of the latent heat flux due to the water phase changes. The diurnal cycle of ET is affected by changes in stomatal conductance related to water or heat stress. The next-generation geostationary satellite can monitor surface changes with high-frequency observations every 10 minutes, supporting regional high-frequency ET estimation. In this study, we estimated diurnal ET over the Asia-Pacific region using the Japan’s geostationary satellite/sensor, Himawari-8/Advanced Himawari Imager (AHI). The Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model was used for ET estimation, with inputs including shortwave radiation, land surface temperature, and land surface reflectance from Himawari-8/AHI, as well as ancillary datasets from the European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) and the Moderate Resolution Imaging Spectroradiometer (MODIS). We validated the estimated ET using observations from 45 eddy covariance flux sites and compared the results with four available products. Hourly estimated ET accurately captured diurnal variation, with Kling-Gupta efficiency (KGE) values being positive at most of sites. Estimated ET showed comparable accuracy to other products and had an advantage in spatial resolution. Finally, a heatwave event in southeastern Australia in 2019 was used as a case study to preliminarily examine the capability of the estimated ET data in capturing environmental changes in regional and temporal distributions.