Characteristics and Predictability of the December 2021 Extreme Winter Warm Spell in the Southern Great Plains of the United States

Extreme heat continues to impact numerous regions of the globe, yielding detrimental socioeconomic impacts on sectors including human health, agriculture, and water availability. Further, increasing temperatures due to climate change are not exclusive to boreal summer, with significant warming signals during boreal winter. Extreme warm temperatures during boreal winter are becoming more frequent (e.g., January 2023 in Europe; South America in July and August 2023). Winter season warm spells foster similar socioeconomic impacts, yet their characteristics and driving mechanisms are unknown compared to their summer heatwave counterparts. Therefore, this study examines the subseasonal-to-seasonal (S2S) characteristics of extreme warm boreal winter temperatures across the Southern Great Plains of the United States during December of 2021. Using a relative threshold heat wave definition for Southern Great Plains boreal winter warm spells between 1950 and 2022, we identify two winter warm spells during December 2021: (1) 29 November through 17 December 2021 and (2) 22 December through 31 December 2021. A time-lagged composite analysis identifies critical atmospheric, oceanic, and surface conditions during the December 2021 case study. Results show that the traditional blocking high was absent during the December 2021 winter warm spell. The first winter warm spell played a key role in initiating land-atmospheric feedbacks to aid the development of the second winter warm spell across the region. Furthermore, this study also investigates the ability of the ECMWF S2S real-time model in forecasting this extreme temperature event on subseasonal timescales. Diagnosing precursors of boreal winter warm spells events through reanalysis is valuable, but further investigating the forecast skill of an S2S model provides insight into how these precursors are represented within the S2S model. In order to increase predictability of these extreme warm temperatures during the boreal winter, not only is it crucial to understand key characteristics associated with these extreme events, but is just as important to understand the basis of the representation on these extreme events within S2S models currently.