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M. Hoerling, J. Eischeid, A. Kumar, R. Leung, A. Mariotti, K. Mo, S. Schubert, and R. Seager

Central Great Plains precipitation deficits during May–August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in the summer owing to large-scale subsidence and atmospheric stabilization.

Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in sum mertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability of the severe summer Great Plains drought occurring may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. The implications of this study's findings for U.S. seasonal drought forecasting are discussed.

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Paul A. Dirmeyer, Jiangfeng Wei, Michael G. Bosilovich, and David M. Mocko

Abstract

A quasi-isentropic, back-trajectory scheme is applied to output from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979–2005. The evaporative source patterns for any location and time period are effectively two-dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50%–400% larger than at monthly time scales. Significant differences suggest that moisture transport may be a key factor in precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events.

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Richard Seager, Lisa Goddard, Jennifer Nakamura, Naomi Henderson, and Dong Eun Lee

Abstract

The causes of the Texas–northern Mexico drought during 2010–11 are shown, using observations, reanalyses, and model simulations, to arise from a combination of ocean forcing and internal atmospheric variability. The drought began in fall 2010 and winter 2010/11 as a La Niña event developed in the tropical Pacific Ocean. Climate models forced by observed sea surface temperatures (SSTs) produced dry conditions in fall 2010 through spring 2011 associated with transient eddy moisture flux divergence related to a northward shift of the Pacific–North American storm track, typical of La Niña events. In contrast the observed drought was not associated with such a clear shift of the transient eddy fields and instead was significantly influenced by internal atmospheric variability including the negative North Atlantic Oscillation of winter 2010/11, which created mean flow moisture divergence and drying over the southern Plains and southeast United States. The models suggest that drought continuation into summer 2011 was not strongly SST forced. Mean flow circulation and moisture divergence anomalies were responsible for the summer 2011 drought, arising from either internal atmospheric variability or a response to dry summer soils not captured by the models. The summer of 2011 was one of the two driest and hottest summers over recent decades but it does not represent a clear outlier to the strong inverse relation between summer precipitation and temperature in the region. Seasonal forecasts at 3.5-month lead time did predict onset of the drought in fall and winter 2010/11 but not intensification into summer 2011, demonstrating the current, and likely inherent, inability to predict important aspects of North American droughts.

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Zengchao Hao and Amir AghaKouchak

Abstract

Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, drought monitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDM and provides additional information and insights into drought monitoring.

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