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Short-term drought forecasting can be aided with an understanding of the likelihood of dry periods persisting from one season to the next. This research examines drought persistence in the Southeastern United States by identifying spatial patterns of seasonal drought frequency and persistence, using logistic regression to calculate the odds and probability of drought persisting from one season to the next, and examining the effects of El Niño-Southern Oscillation (ENSO) drought persistence in the Southeast. The 3-month climate division-scale Standardized Precipitation Index (SPI) data from 1895 to 2011 is used to examine meteorological drought. Logistic regression is well-suited to examining a binary independent variable (drought or no drought) and also circumvents many of the assumptions that limit linear regression. Results show generally weak seasonal drought persistence throughout the region. However, we do find that some areas in the Southeast United States, like North-Central Alabama are more prone to drought and drought persistence than others. Logistic regression model outcome shows that the probability of spring drought varies as a strong function of winter SPI in the central Southeast United States region. While areas in the western portion of the study region, including Texas and Oklahoma are more prone to summer-to-fall drought persistence, as the probability of fall drought is strongly related to summer SPI. Overall we conclude that seasonal drought forecasts are difficult in the Southeast United States because of infrequent drought persistence. However, the logistic regression model does provide an accurate method for probabilistic seasonal drought forecasts in the region.

We provide an overview of the hydroclimatology of the Southeastern USA, and review the primary factors that influence hydroclimatic variability on seasonal to interannual timescales. The Southeastern USA is characterized by high mean annual precipitation, but with significant variability. Precipitation variability is on the rise in this region, with more frequent, longer duration dry periods and infrequent, short duration, but heavy precipitation events. Hydroclimatic extremes are a relatively common occurrence in the region. Seasonal to interannual hydroclimatic variability in the Southeast is primarily controlled by El Niño/Southern Oscillation (ENSO), the Pacific North American (PNA) pattern, the Bermuda High, and tropical cyclones. Future research should focus on providing a better understanding of current and future drivers of hydroclimatic variability, including interactions between human-dominated components, such as urban areas, and the hydroclimatic system. Additional research is also needed on hydroclimatic extremes (droughts and floods).

Limited research has been performed examining the relationships between southeast US wildfire and weather type patterns using modern techniques and data sets. The purpose of this article is to examine the relationship between wildfire ignitions in the central Gulf Coast, United States and weather type occurrences in an effort to identify regional patterns associated with wildfire ignitions. Wildfire occurrence data are obtained for nine national forests in the central Gulf Coast for the period 1970 to 2011. The Spatial Synoptic Classification scheme (SSC) is used to classify daily weather type variations for each national forest. Years with high numbers of ignitions experience statistically higher numbers of dry tropical (DT) weather types than years with low numbers of ignitions in five of nine national forests. These differences range from 17 to 160% more DT days during periods of high ignitions. Statistically significant positive Spearman rank correlations exist between annual number of ignitions and annual number of DT days in a given forest. While understanding such relationships on an annual scale is useful, it says nothing about the actual timing of weather types leading up to an ignition. An analysis of weather type activity 30, 90, and 180 days prior to ignitions reveals that the median ratio of DT days to moist moderate (MM) and moist tropical (MT) days is statistically higher for periods leading up to a fire. Positive phases of the North Atlantic Oscillation (NAO) result in an increased number of DT days. This confirms previous studies that have suggested the strength of the westerlies increases during the positive phase of the NAO, driving DT weather types eastward from their southwest US/Mexico source region. We can therefore also conclude that the positive phase of the NAO is linked with increased wildfire activity in the central Gulf Coast, United States.

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