Evaluation of an ET-based Drought Index Derived from Geostationary Satellite Data

The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle, and cannot readily capture non-precipitation based moisture inputs to the land-surface system (e.g., irrigation, shallow groundwater tables) that may temper drought impacts, or variable rates of water consumption across a landscape. This study assessed the value of a new drought index based on remote sensing of evapotranspiration (ET). The Evaporative Stress Index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET) mapped using signals of diurnal land-surface temperature change obtained from geostationary satellites. The study investigates the behavior and response timescales of the ESI through a retrospective comparison with standard precipitation-based drought indices, and with operational drought classifications recorded in the United States Drought Monitor (USDM). Drought indices based on anomalies in both ET and ET/PET are compared over the continental U.S. for the 2000-2009 growing seasons to standard drought indicators including the Standardized Precipitation Indices and the Palmer drought indices. The ET-based anomalies are also quantitatively compared with USDM drought classes, to assess potential utility in operational drought monitoring. Quantitative intercomparison of spatial and temporal correlation suggests that the performance of the ESI is similar to that of precipitation-based indices of comparable timescale, but with higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI where non-precipitation moisture inputs are likely to be important. Anomalies in ET/PET are better correlated with the precipitation indices and with the USDM than are the ET anomalies themselves, indicating that normalization by PET serves to isolate the ET signal component due to soil moisture variability from that of the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.