Abstract
AbstractThe ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the National Aeronautics and Space Administration (NASA). The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level‐3 (L3) latent heat flux (LE) data products. These data are generated from the Level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized root‐mean‐square error, RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are overrepresented. The 70‐m‐high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1‐km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data.
Highlights
Remote sensing of evapotranspiration (ET) has advanced substantially over the past few decades (Fisher et al, 2017)
The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level‐3 (L3) latent heat flux (LE) data products
This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data
Summary
Remote sensing of evapotranspiration (ET) has advanced substantially over the past few decades (Fisher et al, 2017). ET data are produced from a wide range of airborne and spaceborne sensors, instruments, and missions from high spatial resolution to global coverage (Allen et al, 2007; Anderson et al, 2011; Fisher et al, 2008; Miralles et al, 2011; Mu et al, 2011; Su, 2002). These data are used in, for example, biodiversity assessments (Fisher et al, 2011; Gaston, 2000), regional water balance closures Geostationary satellites such as GOES capture the diurnal cycle, but lack cohesive global coverage, and suffer from even worse spatial resolution (>3 km) (Fisher et al, 2017)
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