Wednesday, 25 January 2017
4E (Washington State Convention Center )
As our world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Prognostic land-surface models require accurate a priori information about global precipitation patterns, soil moisture storage capacity, groundwater tables, and artificial controls on water supply (e.g., irrigation, dams and diversions, inter-basin water transfers, etc.) to reliably link rainfall to evaporative fluxes. In contrast, diagnostic estimates of ET can be generated, with no prior knowledge of the surface moisture state, by energy balance models using thermal-infrared (TIR) remote sensing of land-surface temperature (LST) as a boundary condition. The LST inputs carry valuable proxy information regarding soil moisture and its effect on soil surface evaporation and canopy stresses limiting transpiration. Our team is developing a high spatial (375-m) and temporal (daily clear-sky) resolution evapotranspiration monitoring system over the MENA region, generated with the TIR-based Atmosphere-Land-Exchange Inverse (ALEXI) model. ALEXI is based on the Two-Source Energy Balance (TSEB) land surface representation, which partitions fluxes and surface temperature between nominal soil and canopy components within the modeling scene. The dataset will be generated with a recently developed technique, which exploits day-night observations of LST from polar orbiting sensors, in this case VIIRS, to estimate the morning rise in LST needed as a crucial forcing to the ALEXI system. This method has been evaluated against geostationary observations of LST and has been shown to reasonably match high temporal resolutions of mid-morning rise in LST, with errors generally in the 5 to 10% range. The VIIRS MENA 375-m ET system will also be used to generate ET estimates initially from 2015 through 2016, with an expectation of near-realtime generation of ET data products by 2017.
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