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We present a comparative analysis of atmospheric rivers (ARs) and Great Plains low-level jets (GPLLJs) in the central United States during April–September 1901–2010 using ECMWF’s Coupled Reanalysis of the Twentieth Century (CERA-20C). The analysis is motivated by a perceived need to highlight overlap and synergistic opportunities between traditionally disconnected AR and GPLLJ research. First, using the Guan–Walliser integrated vapor transport (IVT)-based AR classification and Bonner–Whiteman-based GPLLJ classification, we identify days with either an AR and/or GPLLJ spanning 15% of the central United States. These days are grouped into five event samples: 1) all GPLLJ, 2) AR GPLLJ, 3) non-AR GPLLJ, 4) AR non-GPLLJ, and 5) all AR. Then, we quantify differences in the frequency, seasonality, synoptic environment, and extreme weather impacts corresponding to each event sample. Over the twentieth century, April–September AR frequency remained constant whereas GPLLJ frequency significantly decreased. Of GPLLJ days, 36% are associated with a coincident AR. Relative to ARs that are equally probable from April–September, GPLLJs exhibit distinct seasonality, with peak occurrence in July. A 500-hPa geopotential height comparison shows a persistent ridge over the central United States for non-AR GPLLJ days, whereas on AR GPLLJ days, a trough-and-ridge pattern is present over western to eastern CONUS. AR GPLLJ days have 34% greater 850-hPa windspeeds, 53% greater IVT, and 72% greater 24-h precipitation accumulation than non-AR GPLLJ days. In terms of 95th-percentile 850-hPa wind speed, IVT, and 24-h precipitation, that of AR GPLLJs is 25%, 45%, and 23% greater than non-AR GPLLJs, respectively.

 

Abstract A spectral analysis of Great Plains 850-hPa meridional winds (V850) from ECMWF’s coupled climate reanalysis of 1901-2010 (CERA-20C) reveals that their warm season (April-September) interannual variability peaks in May with 2-6 year periodicity, suggestive of an underlying teleconnection influence on low-level jets (LLJs). Using an objective, dynamical jet classification framework based on 500-hPa wave activity, we pursue a large scale teleconnection hypothesis separately for LLJs that are uncoupled (LLJUC) and coupled (LLJC) to the upper-level jet stream. Differentiating between jet types enables isolation of their respective sources of variability. In the South Central Plains (SCP), May LLJCs account for nearly 1.6 times more precipitation and 1.5 times greater V850 compared to LLJUCs. Composite analyses of May 250-hPa geopotential height (Z250) conditioned on LLJC and LLJUC frequencies highlight a distinct planetary-scale Rossby wave pattern with wavenumber-five, indicative of an underlying Circumglobal Teleconnection (CGT). An index of May CGT is found to be significantly correlated with both LLJC ( r = 0.62) and LLJUC ( r = −0.48) frequencies. Additionally, a significant correlation is found between May LLJUC frequency and NAO ( r = 0.33). Further analyses expose decadal scale variations in the CGT-LLJC(LLJUC) teleconnection that are linked to the PDO. Dynamically, these large scale teleconnections impact LLJ class frequency and intensity via upper-level geopotential anomalies over the western U.S. that modulate near-surface geopotential and temperature gradients across the SCP. 

The U.S. Great Plains warm season climate is inextricably linked to the frequency and structure of the region's southerly low‐level jet. In the present‐day climate (1977–2009), low‐level jets are shown to occur on 26%, 46%, and 62% of May–September days in the northern (NGP), central (CGP) and southern (SGP) Great Plains, respectively, and account for at least 26%, 25%, and 36% of those region's precipitation during the same period. A shortcoming of previous research has been a failure to treat upper‐level dynamically coupled, or cyclone‐induced jets, separately from jets that are relatively uncoupled from synoptic flow. Differentiating between jet types is essential to proper mechanistic diagnosis and attribution of jet‐related wind, precipitation, and temperature changes to their local land or remote oceanic forcing. Using a new CERA‐20C objective dynamical jet classification dataset, this study achieves the first quantitative assessment of changes in coupled and uncoupled jets between 1901 and 2010 for NGP, CGP, and SGP. Declines in warm season jet frequency are pinpointed to July–September jets. In the NGP and CGP, both jet types have undergone significant increases in speed and height with concomitant decreases in CAPE and precipitation. NGP uncoupled jet and CGP coupled jet precipitation has decreased by 0.5 and 0.8 mm day⁻¹, respectively, which accounts for 41%–44% of total May–September precipitation decreases between 1905–1937 and 1977–2009. A dynamic situation in which synoptic and local soil moisture changes drive opposite jet responses is discussed.

 

Abstract The Great Plains (GP) southerly nocturnal low-level jet (GPLLJ) is a dominant contributor to the region’s warm-season (May–September) mean and extreme precipitation, wind energy generation, and severe weather outbreaks—including mesoscale convective systems. The spatiotemporal structure, variability, and impact of individual GPLLJ events are closely related to their degree of upper-level synoptic coupling, which varies from strong coupling in synoptic trough–ridge environments to weak coupling in quiescent, synoptic ridge environments. Here, we apply an objective dynamic classification of GPLLJ upper-level coupling and fully characterize strongly coupled (C) and relatively uncoupled (UC) GPLLJs from the perspective of the ground-based observer. Through composite analyses of C and UC GPLLJ event samples taken from the European Centre for Medium-Range Weather Forecasts’ Coupled Earth Reanalysis of the twentieth century (CERA-20C), we address how the frequency of these jet types, as well as their inherent weather- and climate-relevant characteristics—including wind speed, direction, and shear; atmospheric stability; and precipitation—vary on diurnal and monthly time scales across the southern, central, and northern subregions of the GP. It is shown that C and UC GPLLJ events have similar diurnal phasing, but the diurnal amplitude is much greater for UC GPLLJs. C GPLLJs tend to have a faster and more elevated jet nose, less low-level wind shear, and enhanced CAPE and precipitation. UC GPLLJs undergo a larger inertial oscillation (Blackadar mechanism) for all subregions, and C GPLLJs have greater geostrophic forcing (Holton mechanism) in the southern and northern GP. The results underscore the need to differentiate between C and UC GPLLJs in future seasonal forecast and climate prediction activities. 

Abstract In the context of forecasting societally impactful Great Plains low-level jets (GPLLJs), the potential added value of satellite soil moisture (SM) data assimilation (DA) is high. GPLLJs are both sensitive to regional soil moisture gradients and frequent drivers of severe weather, including mesoscale convective systems. An untested hypothesis is that SM DA is more effective in forecasts of weakly synoptically forced, or uncoupled GPLLJs, than in forecasts of cyclone-induced coupled GPLLJs. Using the NASA Unified Weather Research and Forecasting (NU-WRF) Model, 75 GPLLJs are simulated at 9-km resolution both with and without NASA Soil Moisture Active Passive SM DA. Differences in modeled SM, surface sensible (SH) and latent heat (LH) fluxes, 2-m temperature (T2), 2-m humidity (Q2), PBL height (PBLH), and 850-hPa wind speed (W850) are quantified for individual jets and jet-type event subsets over the south-central Great Plains, as well as separately for each GPLLJ sector (entrance, core, and exit). At the GPLLJ core, DA-related changes of up to 5.4 kg m −2 in SM can result in T2, Q2, LH, SH, PBLH, and W850 differences of 0.68°C, 0.71 g kg −2 , 59.9 W m −2 , 52.4 W m −2 , 240 m, and 4 m s −1 , respectively. W850 differences focus along the jet axis and tend to increase from south to north. Jet-type differences are most evident at the GPLLJ exit where DA increases and decreases W850 in uncoupled and coupled GPLLJs, respectively. Data assimilation marginally reduces negative wind speed bias for all jets, but the correction is greater for uncoupled GPLLJs, as hypothesized. 

The Great Plains (GP) low-level jet (GPLLJ) contributes to GP warm season water resources (precipitation), wind resources, and severe weather outbreaks. Past research has shown that synoptic and local mesoscale physical mechanisms (Holton and Blackadar mechanisms) are required to explain GPLLJ variability. Although soil moisture–PBL interactions are central to local mechanistic theories, the diurnal effect of regional soil moisture anomalies on GPLLJ speed, northward penetration, and propensity for severe weather is not well known. In this study, two 31-member WRF-ARW stochastic kinetic energy backscatter scheme ensembles simulate a typical warm season GPLLJ case under CONUS-wide wet and dry soil moisture scenarios. In the GP (24°–48°N, 103°–90°W), ensemble mean differences in sensible heating and PBL height of 25–150 W m −2 and 100–700 m, respectively, at 2100 UTC (afternoon) culminate in GPLLJ 850-hPa wind speed differences of 1–4 m s −1 12 hours later (0900 UTC; early morning). Greater heat accumulation in the daytime PBL over dry soil impacts the east–west geopotential height gradient in the GP (synoptic conditions and Holton mechanism) resulting in a deeper thermal low in the northern GP, causing increases in the geostrophic wind. Enhanced daytime turbulent mixing over dry soil impacts the PBL structure (Blackadar mechanism), leading to increased ageostrophic wind. Overnight geostrophic and ageostrophic winds constructively interact, leading to a faster nocturnal GPLLJ over dry soil. Ensemble differences in CIN (~50–150 J kg −1 ) and CAPE (~500–1000 J kg −1 ) have implications for severe weather predictability. 

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. Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges(GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiativecalled “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature(LST)/subsurface temperature (SUBT) anomalies over high mountain areas as acrucial factor that can lead to significant improvement in precipitationprediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is differentfrom, and complements, other international projects that focus on theoperational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regionalclimate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect ofthe Tibetan Plateau, discusses the LST/SUBT initialization, and presents thepreliminary results. Multi-model ensemble experiments and analyses ofobservational data have revealed that the hydroclimatic effect of the springLST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond EastAsia and its S2S prediction. Preliminary studies and analysis have alsoshown that LS4P models are unable to preserve the initialized LST anomaliesin producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are tooshallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state andanomalies of LST over the Tibetan Plateau. Innovative approaches have beendeveloped to largely overcome these problems. 

Low-level jets (LLJ) around the world critically support the food, water, and energy security in regions that they traverse. For the purposes of development planning and weather and climate prediction, it is important to improve understanding of how LLJs interact with the land surface and upper-atmospheric flow, and collectively, how LLJs have and may change over time. This study details the development and application of a new automated, dynamical objective classification of upper-atmospheric jet stream coupling based on a merging of the Bonner–Whiteman vertical wind shear classification and the finite-amplitude local wave activity diagnostic. The classification approach is transferable globally, but applied here only for the Great Plains (GP) LLJ (GPLLJ). The analysis spans the period from 1901 to 2010, enabled by the ECMWF climate-quality, coupled Earth reanalysis of the twentieth century. Overall, statistically significant declines in total GPLLJ event frequency over the twentieth century are detected across the entire GP corridor and attributed to declines in uncoupled GPLLJ frequency. Composites of lower- and upper-atmospheric flow are shown to capture major differences in the climatological, coupled GPLLJ, and uncoupled GPLLJ synoptic environments. Detailed analyses for southern, central, and northern GP subregions further highlight synoptic differences between weak and strong GPLLJs and provide quantification of correlations between total, coupled, and uncoupled GPLLJ frequencies and relevant atmospheric anomalies. Because uncoupled GPLLJs tend to be associated with decreased precipitation and low-level wind speed and enhanced U.S. ridge strength, this finding may suggest that support for drought over the twentieth century has waned.