Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

TLDR

Thermal infrared remote sensing of land‑surface temperature provides key information on subsurface moisture needed to estimate evapotranspiration and monitor drought, but empirical indices based on LST and NDVI can be ambiguous when other factors influence plant function. The study presents a physically based surface energy balance model driven by TIR remote sensing to interpret LST and NDVI in relation to subsurface moisture and to fuse multi‑satellite data for daily evapotranspiration mapping at ~10 m resolution. The ALEXI model, a multi‑sensor TIR approach coupling a two‑source land‑surface model with an atmospheric boundary layer model, and its DisALEXI extension, spatially disaggregate fluxes using moderate‑resolution TIR imagery, together provide a framework for daily ET mapping at continental scales and sub‑kilometer resolution by integrating data from geostationary and polar orbiting satellites. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US GOES, European Meteosat, Chinese Fengyun 2B, and Japanese GMS satellites. Abstract.

Abstract

Abstract. Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection) are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI) spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa and other continents with geostationary satellite coverage.