Winter Canola: A Potential Dual-Purpose Crop for the United States Southern Great Plains

2017 ◽  
Vol 109 (6) ◽  
pp. 2508-2520 ◽  
Author(s):  
S. Begna ◽  
S. Angadi ◽  
M. Stamm ◽  
A. Mesbah
Keyword(s):  
United States ◽  
Great Plains ◽  
The United States ◽  
Dual Purpose ◽  
Winter Canola ◽  
Southern Great Plains

scholarly journals Primary Atmospheric Drivers of Pluvial Years in the United States Great Plains

2018 ◽  
Vol 19 (4) ◽  
pp. 643-658 ◽  
Author(s):  
Paul X. Flanagan ◽  
Jeffrey B. Basara ◽  
Jason C. Furtado ◽  
Xiangming Xiao
Keyword(s):  
United States ◽  
Great Plains ◽  
Heavy Precipitation ◽  
The United States ◽  
Precipitation Variability ◽  
Northern Great Plains ◽  
Southern Great Plains ◽  
The Public ◽  
Moisture Fluxes ◽  
Precipitation Events

Abstract 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. The NGP pattern 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.

scholarly journals A comparison of multiscale variations of decade-long cloud fractions from six different platforms over the Southern Great Plains in the United States

2014 ◽  
Vol 119 (6) ◽  
pp. 3438-3459 ◽  
Author(s):  
Wei Wu ◽  
Yangang Liu ◽  
Michael P. Jensen ◽  
Tami Toto ◽  
Michael J. Foster ◽  
...  
Keyword(s):  
United States ◽  
Great Plains ◽  
The United States ◽  
Southern Great Plains

scholarly journals Drought and Pluvial Dipole Events within the Great Plains of the United States

2015 ◽  
Vol 54 (9) ◽  
pp. 1886-1898 ◽  
Author(s):  
Jordan Christian ◽  
Katarina Christian ◽  
Jeffrey B. Basara
Keyword(s):  
United States ◽  
Standard Deviation ◽  
Great Plains ◽  
Spatial Scales ◽  
The United States ◽  
Northern Great Plains ◽  
High Plains ◽  
Southern Great Plains ◽  
One Year ◽  
The U.S

AbstractThe 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.

The Temporal Evolution of Convective Indices in Storm-Producing Environments

2008 ◽  
Vol 23 (5) ◽  
pp. 786-794 ◽  
Author(s):  
Timothy J. Wagner ◽  
Wayne F. Feltz ◽  
Steven A. Ackerman
Keyword(s):  
United States ◽  
Temporal Resolution ◽  
Great Plains ◽  
Wind Shear ◽  
Temporal Evolution ◽  
The United States ◽  
Severe Weather ◽  
Wind Profiler ◽  
Southern Great Plains ◽  
Tornadic Storms

Abstract Temporal changes in stability and shear associated with the development of thunderstorms are quantified using the enhanced temporal resolution of combined Atmospheric Emitted Radiance Interferometer (AERI) thermodynamic profile retrievals and National Oceanic and Atmospheric Administration (NOAA) 404-MHz wind profiler observations. From 1999 to 2003, AERI systems were collocated with NOAA wind profilers at five sites in the southern Great Plains of the United States, creating a near-continuous dataset of atmospheric soundings in both the prestorm and poststorm environments with a temporal resolution of up to 10 min between observations. Median values for several standard severe weather indices were calculated for tornadic storms and nontornadic supercells. It was found that instability generally increases throughout the preconvective period, reaching a peak roughly 1 h before a tornado forms or a nontornadic supercell forms large hail. Wind shear for both tornadic and nontornadic storms starts to increase roughly 3 h before storm time. However, indices are highly variable between time and space and may not be representative of the environment at large.

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