Dryness over the U.S. Southwest, a Springboard for Cold Season Pacific SST to Influence Warm Season Drought over the U.S. Great Plains

2021 ◽  
Vol 22 (1) ◽  
pp. 63-76
Author(s):  
Yizhou Zhuang ◽  
Amir Erfanian ◽  
Rong Fu
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Rainfall Variability ◽  
Warm Season ◽  
Summer Precipitation ◽  
Cold Season ◽  
Early Summer ◽  
Moisture Condition ◽  
Moisture Advection ◽  
The U.S

AbstractAlthough the influence of sea surface temperature (SST) forcing and large-scale teleconnection on summer droughts over the U.S. Great Plains has been suggested for decades, the underlying mechanisms are still not fully understood. Here we show a significant correlation between low-level moisture condition over the U.S. Southwest in spring and rainfall variability over the Great Plains in summer. Such a connection is due to the strong influence of the Southwest dryness on the zonal moisture advection to the Great Plains from spring to summer. This advection is an important contributor for the moisture deficit during spring to early summer, and so can initiate warm season drought over the Great Plains. In other words, the well-documented influence of cold season Pacific SST on the Southwest rainfall in spring, and the influence of the latter on the zonal moisture advection to the Great Plains from spring to summer, allows the Pacific climate variability in winter and spring to explain over 35% of the variance of the summer precipitation over the Great Plains, more than that can be explained by the previous documented west Pacific–North America (WPNA) teleconnection forced by tropical Pacific SST in early summer. Thus, this remote land surface feedback due to the Southwest dryness can potentially improve the predictability of summer precipitation and drought onsets over the Great Plains.

scholarly journals On the Link between Summer Dry Bias over the U.S. Great Plains and Seasonal Temperature Prediction Skill in a Dynamical Forecast System

2019 ◽  
Vol 34 (4) ◽  
pp. 1161-1172 ◽  
Author(s):  
Constantin Ardilouze ◽  
Lauriane Batté ◽  
Bertrand Decharme ◽  
Michel Déqué
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Climate Models ◽  
Warm Season ◽  
Seasonal Temperature ◽  
Forecast System ◽  
Temperature And Precipitation ◽  
The Impact ◽  
The U.S ◽  
Dry Bias

Abstract Soil moisture anomalies are expected to be a driver of summer predictability for the U.S. Great Plains since this region is prone to intense and year-to-year varying water and energy exchange between the land and the atmosphere. However, dynamical seasonal forecast systems struggle to deliver skillful summer temperature forecasts over that region, otherwise subject to a consistent warm-season dry bias in many climate models. This study proposes two techniques to mitigate the impact of this precipitation deficit on the modeled soil water content in a forecast system based on the CNRM-CM6-1 model. Both techniques lead to increased evapotranspiration during summer and reduced temperature and precipitation bias. However, only the technique based on a correction of the precipitation feeding the land surface throughout the forecast integration enables skillful summer prediction. Although this result cannot be generalized for other parts of the globe, it confirms the link between bias and skill over the U.S. Great Plains and pleads for continued efforts of the modeling community to tackle the summer bias affecting that region.

scholarly journals Evaluation of Precipitation Simulated by Seven SCMs against the ARM Observations at the SGP Site*

2013 ◽  
Vol 26 (15) ◽  
pp. 5467-5492 ◽  
Author(s):  
Hua Song ◽  
Wuyin Lin ◽  
Yanluan Lin ◽  
Audrey B. Wolf ◽  
Roel Neggers ◽  
...  
Keyword(s):  
Great Plains ◽  
Warm Season ◽  
Cold Season ◽  
Surface Precipitation ◽  
Low Level ◽  
Moisture Advection ◽  
Simulated Surface ◽  
Atmospheric Radiation Measurement ◽  
Rain Events ◽  
Heat And Moisture

Abstract This study evaluates the performances of seven single-column models (SCMs) by comparing simulated surface precipitation with observations at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site from January 1999 to December 2001. Results show that although most SCMs can reproduce the observed precipitation reasonably well, there are significant and interesting differences in their details. In the cold season, the model–observation differences in the frequency and mean intensity of rain events tend to compensate each other for most SCMs. In the warm season, most SCMs produce more rain events in daytime than in nighttime, whereas the observations have more rain events in nighttime. The mean intensities of rain events in these SCMs are much stronger in daytime, but weaker in nighttime, than the observations. The higher frequency of rain events during warm-season daytime in most SCMs is related to the fact that most SCMs produce a spurious precipitation peak around the regime of weak vertical motions but rich in moisture content. The models also show distinct biases between nighttime and daytime in simulating significant rain events. In nighttime, all the SCMs have a lower frequency of moderate-to-strong rain events than the observations for both seasons. In daytime, most SCMs have a higher frequency of moderate-to-strong rain events than the observations, especially in the warm season. Further analysis reveals distinct meteorological backgrounds for large underestimation and overestimation events. The former occur in the strong ascending regimes with negative low-level horizontal heat and moisture advection, whereas the latter occur in the weak or moderate ascending regimes with positive low-level horizontal heat and moisture advection.

Land surface phenology along urban to rural gradients in the U.S. Great Plains

2015 ◽  
Vol 165 ◽  
pp. 42-52 ◽  
Author(s):  
J.J. Walker ◽  
K.M. de Beurs ◽  
G.M. Henebry
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Land Surface Phenology ◽  
The U.S

scholarly journals Spring warming drives past and future shifts in Great Plains storm intensity

2020 ◽  
Author(s):  
Chijun Sun ◽  
Timothy Shanahan ◽  
Pedro DiNezio ◽  
Nicholas McKay ◽  
Priyadarsi Roy
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Climate Model ◽  
Warm Season ◽  
Extreme Weather ◽  
Dynamical Response ◽  
Storm Activity ◽  
Convective Systems ◽  
Past Behavior ◽  
Climate Model Simulations

Abstract The climate of the Great Plains is dominated by mesoscale convective systems (MCS), which supply a significant portion of warm season rainfall and are responsible for severe weather and flooding across the region. However, little is known about past behavior and long-term drivers of these systems, limiting our ability to predict future changes in hydroclimate and extreme weather for much of the central US. Here, we generate a new record of past MCS activity and hydroclimate variability from central Texas and compare it against the results of transient climate model simulations to understand the underlying causes of past changes in extreme weather and climate in the central US. We find that changes in storm activity and hydroclimate in the southern Great Plains over the last the 20,000 years were dominated by changes in the strength of the Great Plains Low Level Jet, driven by springtime land surface temperature changes. These results suggest that a similar dynamical response to future warming will lead to enhanced MCS activity and an increase in extreme weather and flooding across the southern and central Great Plains in the future.

Soil Moisture Influence on the Incidence of Summer Mesoscale Convective Systems in the U.S. Great Plains

2021 ◽  
Author(s):  
Rachel Gaal ◽  
James L. Kinter
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Large Scale ◽  
Mesoscale Convective Systems ◽  
Antecedent Soil Moisture ◽  
Initiation Point ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The U.S

AbstractMesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004-2016. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e. only non-squall line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ~100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located northeast (southwest) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

scholarly journals The Physics of Drought in the U.S. Central Great Plains

2016 ◽  
Vol 29 (18) ◽  
pp. 6783-6804 ◽  
Author(s):  
Ben Livneh ◽  
Martin P. Hoerling
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Growing Season ◽  
Surface Model ◽  
Moisture Conditions ◽  
Soil Moisture Variability ◽  
The U.S ◽  
Rainfall Deficits ◽  
Moisture Variability

Abstract The semiarid U.S. Great Plains is prone to severe droughts having major consequences for agricultural production, livestock health, and river navigation. The recent 2012 event was accompanied by record deficits in precipitation and high temperatures during the May–August growing season. Here the physics of Great Plains drought are explored by addressing how meteorological drivers induce soil moisture deficits during the growing season. Land surface model (LSM) simulations driven by daily observed meteorological forcing from 1950 to 2013 compare favorably with satellite-derived terrestrial water anomalies and reproduce key features found in the U.S. Drought Monitor. Results from simulations by two LSMs reveal that precipitation was directly responsible for between 72% and 80% of the soil moisture depletion during 2012, and likewise has accounted for the majority of Great Plains soil moisture variability since 1950. Energy balance considerations indicate that a large fraction of the growing season temperature variability is itself driven by precipitation, pointing toward an even larger net contribution of precipitation to soil moisture variability. To assess robustness across a larger sample of drought events, daily meteorological output from 1050 years of climate simulations, representative of conditions in 1979–2013, are used to drive two LSMs. Growing season droughts, and low soil moisture conditions especially, are confirmed to result principally from rainfall deficits. Antecedent meteorological and soil moisture conditions are shown to affect growing season soil moisture, but their effects are secondary to forcing by contemporaneous rainfall deficits. This understanding of the physics of growing season droughts is used to comment on plausible Great Plains soil moisture changes in a warmer world.

scholarly journals Predictability of Midsummer Great Plains Low-Level Jet and Associated Precipitation

2020 ◽  
Vol 35 (1) ◽  
pp. 215-235 ◽  
Author(s):  
Kelsey M. Malloy ◽  
Ben P. Kirtman
Keyword(s):  
Great Plains ◽  
North American ◽  
Large Scale ◽  
Linear Regression Analysis ◽  
Intraseasonal Variability ◽  
Warm Season ◽  
Summer Precipitation ◽  
Climate System Model ◽  
Low Level ◽  
Low Level Jet

Abstract Warm-season precipitation in the U.S. “Corn Belt,” the Great Plains, and the Midwest greatly influences agricultural production and is subject to high interannual and intraseasonal variability. Unfortunately, current seasonal and subseasonal forecasts for summer precipitation have relatively low skill. Therefore, there are ongoing efforts to understand hydroclimate variability targeted at improving predictions, particularly through its primary transporter of moisture: the Great Plains low-level jet (LLJ). This study uses the Community Climate System Model, version 4 (CCSM4), July forecasts, made as part of the North American Multi-Model Ensemble (NMME), to assess skill in reproducing the monthly Great Plains LLJ and associated precipitation. Generally, the CCSM4 forecasts capture the climatological jet but have problems representing the observed variability beyond two weeks. In addition, there are predictors associated with the large-scale variability identified through linear regression analysis, shifts in kernel density estimators, and case study analysis that suggest potential for improving confidence in forecasts. In this study, a strengthened Caribbean LLJ, negative Pacific–North American (PNA) teleconnection, El Niño, and a negative Atlantic multidecadal oscillation each have a relatively strong and consistent relationship with a strengthened Great Plains LLJ. The circulation predictors, the Caribbean LLJ and PNA, present the greatest “forecast of opportunity” for considering and assigning confidence in monthly forecasts.

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