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Wintertime cold air outbreaks (CAOs) in the Great Plains of the United States have significant socioeconomic, environmental, and infrastructural impacts; the events of December 1983 and February 2021 are key examples of this. Previous studies have investigated CAOs in other parts of North America, particularly the eastern United States, but the development of CAOs in the Great Plains and their potential subseasonal-to-seasonal (S2S) predictability have yet to be assessed. This study first identifies 37 large-scale CAOs in the Great Plains between 1950 and 2021, before examining their characteristics, evolution, and driving mechanisms. These events occur under two dominant weather regimes at event onset: one set associated with anomalous ridging over Alaska and the other set associated with anomalous pan-Arctic ridging. Alaskan ridge CAOs evolve quickly (i.e., on synoptic time scales) and involve stratospheric wave reflection. Conversely, Arctic high CAOs are preceded by weak stratospheric polar vortex conditions several weeks prior to the event. Both categories of CAOs feature anomalous upward wave activity flux from Siberia, with downward wave activity flux over Canada seen only in the Alaskan ridge CAOs. The rapid development of the Alaskan ridge CAOs, also linked with a North Pacific wave train and anomalous wave activity flux from the central Pacific, suggests that these events could be forced by tropical modes of variability. These findings present evidence that different forcing mechanisms, with contrasting time scales, may produce distinct sources of predictability for these CAOs on the S2S time scale. [ABSTRACT FROM AUTHOR]

In the U.S. Great Plains (GP), diagnosing precipitation variability is key in developing an understanding of the present and future availability of water in the region. Building on previous work investigating U.S. GP pluvial years, this study uses ERA twentieth century (ERA-20C) reanalysis data to investigate key circulation anomalies driving GP precipitation anomalies during a subset of GP pluvial years (called in this paper Pattern pluvial years). With previous research showing links between tropical Pacific sea surface temperature (SST) anomalies and GP climate variability, this study diagnoses the key circulation anomalies through an analysis of SSTs and their influence on the atmosphere. Results show that during Pattern southern Great Plains (SGP) pluvial years, central tropical Pacific SST anomalies are coincident with key atmospheric anomalies across the Pacific basin and North America. During northern Great Plains (NGP) Pattern pluvial years, no specific pattern of oceanic anomalies emerges that forces the circulation anomaly feature inherent in specific NGP pluvial years. Utilizing the results for SGP pluvial years, a conceptual model is developed detailing the identified pathway for the occurrence of circulation patterns that are favorable for pluvial years over the SGP. Overall, results from this study show the importance of the identified SGP atmospheric anomaly signal and the potential for predictability of such events. [ABSTRACT FROM AUTHOR]

Global "hot spots" for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation. [ABSTRACT FROM AUTHOR]

With the increasing use of the term "flash drought" within the scientific community, Otkin et al. provide a general definition that identifies flash droughts based on their unusually rapid rate of intensification. This study presents an objective percentile-based methodology that builds upon that work by identifying flash droughts using standardized evaporative stress ratio (SESR) values and changes in SESR over some period of time. Four criteria are specified to identify flash droughts: two that emphasize the vegetative impacts of flash drought and two that focus on the rapid rate of intensification. The methodology was applied to the North American Regional Reanalysis (NARR) to develop a 38-yr flash drought climatology (1979–2016) across the United States. It was found that SESR derived from NARR data compared well with the satellite-based evaporative stress index for four previously identified flash drought events. Furthermore, four additional flash drought cases were compared with the U.S. Drought Monitor (USDM), and SESR rapidly declined 1–2 weeks before a response was evident with the USDM. From the climatological analysis, a hot spot of flash drought occurrence was revealed over the Great Plains, the Corn Belt, and the western Great Lakes region. Relatively few flash drought events occurred over mountainous and arid regions. Flash droughts were categorized based on their rate of intensification, and it was found that the most intense flash droughts occurred over the central Great Plains, Corn Belt, and western Great Lakes region. [ABSTRACT FROM AUTHOR]

Precipitation variability has increased in recent decades across the Great Plains (GP) of the United States. Drought and its associated drivers have been studied in the GP region; however, periods of excessive precipitation (pluvials) at seasonal to interannual scales have received less attention. This study narrows this knowledge gap with the overall goal of understanding GP precipitation variability during pluvial periods. Through composites of relevant atmospheric variables from the ECMWF twentieth-century reanalysis (ERA-20C), key differences between southern Great Plains (SGP) and northern Great Plains (NGP) pluvial periods are highlighted. The SGP pluvial pattern shows an area of negative height anomalies over the southwestern United States with wind anomalies consistent with frequent synoptic wave passages along a southward-shifted North Pacific jet. TheNGPpattern during pluvial periods, by contrast, depicts anomalously low heights in the northwestern United States and an anomalously extended Pacific jet. Analysis of daily heavy precipitation events reveals the key drivers for these pluvial events, namely, an east-west height gradient and associated stronger poleward moisture fluxes. Therefore, the results show that pluvial years over the GP are likely driven by synoptic-scale processes rather than by anomalous seasonal precipitation driven by longer time-scale features. Overall, the results present a possible pathway to predicting the occurrence of pluvial years over the GP and understanding the causes of GP precipitation variability, potentially mitigating the threats of water scarcity and excesses for the public and agricultural sectors. [ABSTRACT FROM AUTHOR]

ABSTRACT Agriculture is a critical industry to the economy of the Great Plains ( GP) region of North America and sensitive to change in weather and climate. Thus, improved knowledge of meteorological and climatological conditions during the growing season and associated variability across spatial and temporal scales is important. A distinct climate feature in the GP is the asynchronicity (AS) between the timing of temperature and precipitation maxima. This study investigated a long-term observational data set to quantify the AS and to address the impacts of climate variability and change. Global Historical Climate Network Daily ( GHCN-Daily) data were utilized for this study; 352 GHCN-Daily stations were identified based on specific criteria and the dates of the precipitation and temperature maxima for each year were identified at daily and weekly intervals. An asynchronous difference index ( ADI) was computed by determining the difference between these dates averaged over each decade. Analysis of daily and weekly ADI revealed two physically distinct regimes of ADI (positive and negative), with comparable shifts in the timing of both the maximum of precipitation and temperature over all six states within the GP examined when comparing the two different regimes. Time series analysis of decadal average ADI yielded moderate shifts (∼5 to 10 days from linear regression analysis) in ADI in several states with increased variability occurring over much of the study region. [ABSTRACT FROM AUTHOR]