GC13J-0813:
Modeling and Satellite Remote Sensing of the Meteorological Effects of Irrigation during the 2012 Central Plains Drought

Monday, 15 December 2014
Clint Aegerter1, Jun Wang1, Cui Ge1, Amy L Kessner1, Ambrish Sharma1, Laura Judd1,2, Brian Wardlow1, Jinsheng You1, Martha Shulski1, Suat Irmak1 and Ayse Kilic1, (1)University of Nebraska Lincoln, Lincoln, NE, United States, (2)University of Houston, Houston, TX, United States
Abstract:
In the summer of 2012, the Central Plains of the United States experienced one of its most severe droughts on record. This study uses satellite data from Moderate-resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) to document several geophysical parameters including land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), cloud fraction, and total rainfall associated with the drought and human response to the drought (irrigation). Non-irrigated areas often showed 5 K LST increases and negative NDVI anomalies (compared to summer 2002-2011 averages) while irrigated areas showed < 2 K LST anomalies and NDVI anomalies near zero. As expected, the cloud fraction anomaly is negative nearly everywhere in the domain. However, the largest reduction in cloud fraction is found over the heavily-irrigated area, which conflicts with several previous modeling studies showing an increase in cloud fraction over irrigated areas. This could be explained by a hypothesis that the temperature gradient between irrigated and non-irrigated areas is strong enough during severe drought to produce a local circulation (similar to land/sea breezes) that results in an atmospheric downdraft over the irrigated area. To test this hypothesis, reanalysis data, including ERA-Interim data from the European Center for Medium-Range Weather Forecasts (ECMWF) and North American Regional Reanalysis (NARR) data from the National Centers for Environmental Prediction (NCEP), are examined and WRF simulations are conducted to interpret the observational data and evaluate the hypothesis previously discussed.