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Hurricane Harvey produced unprecedented widespread rainfall amounts over 1000 mm in portions of southeast Texas, including Houston, from 26 to 31 August 2017. The highly efficient and prolonged warm rain processes associated with Harvey played a key role in the catastrophic flooding that occurred throughout the region. Precipitation efficiency (PE) is widely referred to in the scientific literature when discussing excessive precipitation events that lead to catastrophic flash flooding, but has yet to be explored or quantified in tropical cyclones coincident with polarimetric radar observations. With the introduction of dual-polarization radar to the NEXRAD WSR-88D network, polarimetric radar variables such as ZH, ZDR, and KDP can be used to gain insight into the precipitation processes that contribute to enhanced PE. It was found that 6-h mean values of ZH between 35 and 45 dBZ, ZDR between 1 and 1.5 dB, and KDP greater than 1° km−1 were collocated with the regions of PE greater than 100% between 27 and 29 August. Additionally, supercell thunderstorms embedded in the outer bands of Harvey were identified via 3–6 km Multi-Radar Multi-Senor (MRMS) rotation tracks and were collocated with swaths of enhanced positive ZH, ZDR, and KDP. A polarimetric rainfall relationship estimates that 1-h mean rainfall rates in these supercells were as high as 85 mm h−1 and made a significant contribution to the excessive precipitation event that occurred over the 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: The purpose of this study was to investigate the seasonal to interannual variability of the temporal and spatial distributions of land–atmosphere coupling (LAC) at the mesoscale within the Southern Great Plains (SGP) of the United States. The North American Regional Reanalysis data set from 1979 to 2014 was used to complete this study. To further expand the relationship between soil moisture and precipitation, LAC was examined for the effects of soil moisture variability on latent heat flux (SM‐E) and the impact of latent heat flux variability on precipitation (E‐P). Results revealed that within the SGP there is a temporal and spatial seasonal evolution of the SM‐E relationship and dry boreal summer month (June, July and August, JJA) periods exhibit a stronger E‐P relationship relative to pluvial boreal summer month periods. Further, the variability of coupling was large both within‐season (i.e. JJA) as well as at the interannual scale while the interannual spatial and temporal coherence was such that no specific locations showed consistent coupling within the domain. Thus, the results indicate that while the SGP domain is sensitive to coupling, the location of preferred coupling is likely due to non‐local factors at the mesoscale embedded within synoptic conditions as well as the regional climate. [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]

The purpose of this study was to quantify dipole events (a drought year followed by a pluvial year) for various spatial scales including the nine Oklahoma climate divisions and the author-defined regions of the U.S. Southern Great Plains (SGP), High Plains (HP), and Northern Great Plains (NGP). Analyses revealed that, on average, over twice as many standard deviation (STDEV) dipoles existed in the latter half of the dataset (1955-2013) relative to the first half (1896-1954), suggesting that dramatic increases in precipitation from one year to the next within the Oklahoma climate divisions are increasing with time. For the larger regions within the Great Plains of the United States, the percent chance of a significant pluvial year following a significant drought year was approximately 25% of the time for the SGP and NGP and approximately 16% of the time for the HP. The STDEV dipole analyses further revealed that the frequency of dipoles was consistent between the first and second half of the dataset for the NGP and HP but was increasing with time in the SGP. The temporal periods of anomalous precipitation during relative pluvial years within the STDEV dipole events were unique for each region whereby October occurred most frequently (70%) within the SGP, September occurred most frequently (60%) within the HP, and May occurred most frequently (62%) within the NGP. [ABSTRACT FROM AUTHOR]

Severe droughts in the Southern Great Plains (SGP: Kansas, Oklahoma, and Texas) in recent years have reduced the productivity of tallgrass prairie and resulted in substantial economic losses to the beef cattle industry in this region. Understanding spatial and temporal patterns of agricultural drought in the SGP can help ranchers to develop and implement drought mitigation strategies. In this study, the Land Surface Water Index (LSWI), calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) near infrared and shortwave infrared bands, was used to assess agricultural drought in the tallgrass prairie region of the SGP during 2000–2013. The number of consecutive days with LSWI < 0 (DNLSWI) during the growing season was defined as the drought duration, which, was then used to identify and analyze frequency of summer drought and whole growing season drought (WGSD). The spatial pattern of DNLSWI was consistent with the east-to-west decreasing precipitation gradient across the SGP region. Summer drought duration as depicted by the DNLSWI in the western portion of the study area was around one and a half month. The occurrence of WGSD increased from one year in the east to up to six years in the west, demonstrating the susceptibility of the tallgrass prairie region to drought. In addition to the total amount of precipitation, its intra-annual distribution also played an important role in drought development. A comparison with other widely used national drought products, namely the Evaporative Stress Index (ESI), the Vegetation Drought Response Index (VegDRI), and the United States Drought Monitor (USDM), shows that LSWI-based drought has good agreement with ESI and USDM. Quantitative analyses indicate that LSWI-based drought agreed better with ESI in severe drought conditions than in moderate or pre-drought conditions. Severe drought periods characterized by the USDM also had low LSWI values. The areas affected by drought derived from the LSWI-based drought index were significantly correlated with hay production. As an indicator of vegetation water stress at moderate spatial resolution (∼500 m), the LSWI has the potential to show drought conditions for an individual ranch and offer guidance for drought mitigation activities and livestock production. [ABSTRACT FROM AUTHOR]

This study analyzed the top 1% 24-hour rainfall events from 1994 to 2013 at eight climatological sites that represent the east to west precipitation gradient across the Arkansas-Red River Basin in North America. A total of 131 cases were identified and subsequently classified on the synoptic-scale, mesoscale, and local-scale to compile a climatological analysis of these extreme, heavy rainfall events based on atmospheric forcings. For each location, the prominent midtropospheric pattern, mesoscale feature, and predetermined thermodynamic variables were used to classify each 1% rainfall event. Individual events were then compared with other cases throughout the basin. The most profound results were that the magnitudes of the thermodynamic variables such as convective available potential energy and precipitable water values were poor predictors of the amount of rainfall produced in these extreme events. Further, the mesoscale forcings had more of an impact during the warm season and for the westernmost locations, whereas synoptic forcings were extremely prevalent during the cold season at the easternmost locations in the basin. The implications of this research are aimed at improving the forecasting of heavy precipitation at individual weather forecasts offices within the basin through the identified patterns at various scales. [ABSTRACT FROM AUTHOR]