Wednesday, 13 January 2016
New Orleans Ernest N. Morial Convention Center
Extremes in the water cycle, such as drought, cause significant impacts on society that can be reduced through preparations made possible by monitoring and prediction. Improvements in drought monitoring and prediction require a better understanding of the mechanisms that lead to intensification and recovery of drought. Feedbacks between the land and the atmosphere play a role in drought intensification, persistence and recovery, however due to the complexity of the feedbacks it can be difficult to tease out the driving mechanisms. Recent work has developed a classification of land-atmosphere interactions that summarizes these complex interactions into coupling regimes. One of these regimes is dry coupling, which is connected with drought initialization, persistence and intensification through feedbacks between the land and the atmosphere. The temporal persistence of this coupling regime and its impact on the water cycle is summarized through the Coupling Drought Index (CDI).
Until now, the CDI has primarily been applied to reanalysis and modeling data. In this work the NASA AQUA satellite, which provides measurements of the atmosphere from AIRS and soil moisture from AMSR-E, are used in the coupling classification framework. The resulting CDI from satellite is compared with other drought monitoring variables to assess its utility for monitoring drought and is shown to provided an early warning of the onset of the 2012 Midwest U.S. drought compared to other drought indices. The dry coupling regime is the primary driver of the CDI and is important to understanding drought characteristics. As such a method for attributing the initiation and duration of the dry coupling regime is presented and compared with results from reanalysis and satellite remote sensing. The trend in the frequency and duration of dry coupling events is also explored for the U.S. and across the globe. The ability to utilize these observations of land-atmosphere interactions from satellite remote sensing to better model drought initialization and persistence is discussed.
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