2011: Ocean–atmosphere influences on lowfrequency warm-season drought variability in the Gulf Coast and southeastern United States

• Main Authors: Jason T Ortegren, Paul A Knapp, AND Justin T Maxwell, William P Tyminski, Peter T Soulé
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: North Atlantic
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1073.6092; http://libres.uncg.edu/ir/uncg/f/P_Knapp_Ocean_2011.pdf

ABSTRACT From the 344 state climate divisions in the conterminous United States, nine distinct regions of warmseason drought variability are identified using principal component analysis. The drought metric used is the Palmer hydrological drought index for the period 1895-2008. The focus of this paper is multidecadal drought variability in the Southeast (SEUS) and eastern Gulf South (EGS) regions of the United States, areas in which the low-frequency forcing mechanisms of warm-season drought are still poorly understood. Low-frequency drought variability in the SEUS and EGS is associated with smoothed indexed time series of major oceanatmosphere circulation features, including two indices of spatiotemporal variability in the North Atlantic subtropical anticyclone (Bermuda high). Long-term warm-season drought conditions are significantly out of phase between the two regions. Multidecadal regimes of above-and below-average moisture in the SEUS and EGS are closely associated with slow variability in sea surface temperatures in the North Atlantic Ocean and with the summer mean position and mean strength of the Bermuda high. Multivariate linear regression indicates that 82%-92% of the low-frequency variability in warm-season moisture is explained by two of the three leading principal components of low-frequency variability in the climate indices. The findings are important for water resource managers and water-intensive industries in the SEUS and EGS. The associations identified in the paper are valuable for enhanced drought preparedness and forecasting in the study area and potentially for global models of coupled ocean-atmosphere variability.