[A-CG44] Terrestrial monitoring using geostationary satellites

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

*Beichen Zhang¹, Kazuhito Ichii¹, Yuhei Yamamoto¹, Wei Li¹, Atsushi Higuchi¹, Minseok Kang², Youngryel Ryu³, Su-Jin Kim⁴, Shohei Murayama⁵ (1.Chiba University, 2.National Center for AgroMeteorology, 3.Seoul National University, 4.National Institute of Forest Science, 5.National Institute of Advanced Industrial Science and Technology)

Keywords:Himawari-8, evapotranspiration, diurnal cycle, PT-JPL model

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.