Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 8/17/2012
Publication Date: 10/22/2012
Citation: Anderson, M.C., Hain, C., Otkin, J., Cammalleri, C.N., Gao, F.N. 2012. Use of remotely sensed evapotranspiration maps for monitoring drought impacts at field to continental scales[abstract]. National Oceanic and Aeronautic Administration's 37th Climate Diagnostics and Prediction Workshop. 2012 CDROM. Interpretive Summary:
Technical Abstract: The Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET), highlighting areas with anomalously high or low rates of water use across the land surface. ET is retrieved via energy balance using remotely sensed land-surface temperature (LST) time-change signals. LST is a fast-response variable, providing proxy information regarding rapidly evolving surface soil moisture and crop stress conditions at relatively high spatial resolution. ESI values quantify standardized anomalies (sigma) in the ratio of clear-sky actual-to-potential ET (fPET), derived at continental scales using thermal infrared (TIR) satellite imagery from geostationary platforms at 3-10 km spatial resolution. In this talk, we will present results comparing spatiotemporal patterns in ESI with standard precipitation-based indices over the past decade. In 2012, ESI has captured early signals of the “flash drought” that has encompassed much of the central US, resulting from extended periods of hot, dry and windy conditions. We will also discuss methods for obtaining higher resolution assessments of surface moisture deficiencies, down to scales of individual fields, by spatially disaggregating the geostationary-derived ESI using LST data from polar orbiting platforms at 1-km resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) and 30-100 m resolution from Landsat. Stress information at these scales will be useful for improving yield forecasts and mitigating drought impacts at local scales. Time variability in fPET, as inferred from LST, may provide diagnostic signals of variable drought resilience across landscapes, revealing areas where plants have access to more stable moisture pools due to deeper rooting systems or shallower water table.