Satellite-based Near-Real-Time Global Daily Terrestrial Evapotranspiration Estimates

Abstract. Accurate and timely information on global terrestrial actual evapotranspiration (ET) is crucial in agriculture, water resource management and drought forecasting in a changing climate. While numerous satellite-based ET products have been developed in recent decades, few provide near-real-time global terrestrial ET estimates. The MOD16 ET dataset, currently updating at the fastest rate, still experiences a delay of over two weeks. This is because most satellite-based ET algorithms rely on meteorological data from land surface models or in situ measurements, which cannot be obtained in near-real-time, resulting in delays of more than two weeks. To expedite global ET data access, we developed the Moderate Resolution Imaging Spectroradiometer (MODIS) based Variation of Standard Evapotranspiration Algorithm (VISEA) to provide global daily ET data within a week of the actual measurements at a spatial resolution of 0.05°. The VISEA model incorporates several key components: (1) A vegetation index (VI)-temperature (Ts) triangle method to simulate air temperature (Ta), serves as a basis for calculating other meteorological parameters (e.g., water vapor deficit and wind speed); (2) A daily evaporation fraction (EF) method based on the decoupling parameter, converts satellite-based instantaneous observations into daily ET estimates; (3) A net radiation calculation program takes into account cloud coverage in the atmosphere's downward longwave radiation. The VISEA model is driven by shortwave radiation from the European Centre for Medium-range Weather Forecasts (ERA5-Land) and MODIS land products, e.g., surface reflectance, land surface temperature/emissivity, land cover products), vegetation indices, and albedo as inputs. To assess its accuracy, we compared VISEA-with measurements from 149 flux towers, five other satellite-based global ET products, and precipitation data from the Global Precipitation Climatology Centre (GPCC). The evaluations show that the near-real-time ET using VISEA performs with similar accuracy to other existing data products and offers a significantly shorter time frame for daily data availability. Over 12 landcover types, the mean R is about 0.6 with an RMSE of 1.4 mm day^-1 at a daily scale. Furthermore, the consistent spatial patterns of multi-year average VISEA align closely with GPCC precipitation data, reaffirming the dataset's ability to accurately represent global terrestrial ET distribution. To emphasize the capabilities of the VISEA for drought monitoring, we analyzed the spatial and temporal variations of ET during a drought event and subsequent recovery with precipitation in the Yangtze River basin from August 28^th to September 1^st, 2022. The VISEA distinctly illustrated low ET levels (<0.2 mm day^-1) across most areas of the Yangtze River Basin on August 28th, indicating the severity of the drought. Conversely, a noticeable increase in ET (>0.9 mm day^-1) is observed on August 29^th, signifying the retreat of the drought due to precipitation. The near-real-time global daily terrestrial ET estimates could be valuable for meteorology and hydrology applications requiring real-time data, particularly in coordinating relief efforts during droughts. The VISEA code and dataset are available at https://doi.org/10.11888/Terre.tpdc.300782 (Huang et al., 2023a).