Ocean-atmosphere influences on large-scale drought variability in the United States using SVDI

Extreme drought has a strong socio-economic impact. Especially where surface and ground water supplies are significantly reduced due to increased demands for agricultural and human consumption, which will likely increase in the future as climate change scenarios show significant drying over most of the U.S. by 2100. Understanding recent large-scale drought patterns and mechanisms producing extreme droughts is vital to understanding future risks. For this work, vapor pressure deficit (VPD) was used to calculate the Standardized VPD Drought Index (SVDI). The SVDI is presented as a simplified method of drought detection based on air temperature and relative humidity, rather than precipitation deficit. This work focuses on summer months from 1980 - 2021, and VPD was calculated with the North American Land Data Assimilation System data. Spatial drought characteristics are extracted from SVDI with EOF analysis, and a k-means cluster technique is applied to primary principal components, the multivariate ENSO index (MEI), and to sea surface temperature anomalies (SSTA) to identify large-scale extreme drought events. Individual clusters are investigated with atmospheric (e.g. wind, HGT, and MSLP) and oceanic components (e.g. SSTA, MEI, PDO, PNA, and NAO) contributing to drought to understand the mechanisms driving large-scale drought patterns. Results show mechanisms influencing summer drought patterns in the Western U.S. originate in the equatorial Pacific Ocean related to ENSO processes. However, large-scale drought in the central and southern US stem from mechanisms originating in the northern Pacific and northern Atlantic Oceans.