Satellite-based near-real-time global daily terrestrial evapotranspiration estimates
Abstract. Accurate and timely global evapotranspiration (ET) data are crucial for agriculture, water resource management, and drought forecasting. Although numerous satellite-based ET products are available, few offer near-real-time data. For instance, products like NASA's ECOsystem Spaceborne Thermal Radiometer Experiment mounted on the International Space Station (ECOSTRESS) and MOD16 face challenges such as uneven coverage and delays exceeding 1 week in data availability. In this study, we refined the Variation of the Standard Evapotranspiration Algorithm (VISEA) by fully integrating satellite-based data, e.g., European Centre for Medium-Range Weather Forecasts ERA5-Land shortwave radiation (which includes satellite remote sensing data within its assimilation system) and MODIS land surface data (which include surface reflectance, temperature and/or emissivity, land cover, vegetation indices, and albedo as inputs). This enables VISEA to provide near-real-time global daily ET estimates with a maximum delay of 1 week at a resolution of 0.05°. Its accuracy was assessed globally using observation data from 149 flux towers across 12 land cover types and comparing them with five other satellite-based ET products and Global Precipitation Climatology Centre (GPCC) data. The results indicate that VISEA provides accurate ET estimates that are comparable to existing products, achieving a mean correlation coefficient (R) of about 0.6 and an RMSE of 1.4 mm d−1. Furthermore, we demonstrated VISEA's utility in drought monitoring during a drought event in the Yangtze River basin in 2022 in which ET changes correlated with precipitation. The near-real-time capability of VISEA is, thus, especially valuable in meteorological and hydrological applications for coordinating drought relief efforts. The VISEA ET dataset is available at https://doi.org/10.11888/Terre.tpdc.300782 (Huang, 2023a).
Authors
- Jing M. Chen (ORCID: https://orcid.org/0000-0002-8682-1293)
- Qiuhong Tang (ORCID: https://orcid.org/0000-0002-0886-6699)
- Yong Luo (ORCID: https://orcid.org/0000-0002-7721-3974)
- Tammo S. Steenhuis (ORCID: https://orcid.org/0000-0003-0508-9350)
- Wei Cheng (ORCID: https://orcid.org/0000-0002-6499-0213)
- Lei Huang (ORCID: https://orcid.org/0000-0002-2943-4342)
- Wen Shi
Institutions
- Fujian Normal University (CN)
- China Meteorological Administration (CN)
- University of Toronto (CA)
- Chinese Academy of Sciences (CN)
- Cornell University (US)
- Beijing Meteorological Bureau (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Earth system science data
- Published
- 2024-09-12
- DOI
- https://doi.org/10.5194/essd-16-3993-2024
- Citations
- 7
- Primary Topic
- Plant Water Relations and Carbon Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 1.98
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China