scholarly journals Warm Season Variations in the Low-Level Circulation and Precipitation over the Central United States in Observations, AMIP Simulations, and Idealized SST Experiments

2009 ◽  
Vol 22 (20) ◽  
pp. 5401-5420 ◽  
Author(s):  
Scott J. Weaver ◽  
Siegfried Schubert ◽  
Hailan Wang
Keyword(s):  
Great Plains ◽  
Large Scale ◽  
Climate Model ◽  
Warm Season ◽  
Atmospheric Model ◽  
Warm Pool ◽  
Precipitation Variability ◽  
Western Hemisphere ◽  
Low Level ◽  
Sst Variability

Abstract Sea surface temperature (SST) linkages to central U.S. low-level circulation and precipitation variability are investigated from the perspective of the Great Plains low-level jet (GPLLJ) and recurring modes of SST variability. The observed and simulated links are first examined via GPLLJ index regressions to precipitation, SST, and large-scale circulation fields in the NCEP–NCAR and North American Regional Reanalysis (NARR) reanalyses, and NASA’s Seasonal-to-Interannual Prediction Project (NSIPP1) and Community Climate Model, version 3 (CCM3) ensemble mean Atmospheric Model Intercomparison Project (AMIP) simulations for the 1949–2002 (1979–2002 for NARR) period. Characteristics of the low-level circulation and its related precipitation are further examined in the U.S. Climate Variability and Predictability (CLIVAR) Drought Working Group idealized climate model simulations (NSIPP1 and CCM3) forced with varying polarities of recurring modes of SST variability. It is found that the observed and simulated correlations of the GPLLJ index to Atlantic and Pacific SST, large-scale atmospheric circulation, and Great Plains precipitation variability for 1949–2002 are robust during the July–September (JAS) season and show connections to a distinct global-scale SST variability pattern, one similar to that used in forcing the NSIPP1 and CCM3 idealized simulations, and a subtropical Atlantic-based sea level pressure (SLP) anomaly with a maximum over the Gulf of Mexico. The idealized simulations demonstrate that a warm Pacific and/or a cold Atlantic are influential over regional hydroclimate features including the monthly preference for maximum GPLLJ and precipitation in the seasonal cycle. Furthermore, it appears that the regional expression of globally derived SST variability is important for generating an anomalous atmospheric low-level response of consequence to the GPLLJ, especially when the SST anomaly is positioned over a regional maximum in climatological SST, and in this case the Western Hemisphere warm pool.

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.

Teleconnections Governing the Interannual Variability of Great Plains Low-Level Jets in May

2021 ◽  
pp. 1-60
Author(s):  
Shubhi Agrawal ◽  
Craig R. Ferguson ◽  
Lance Bosart ◽  
D. Alex Burrows
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
Large Scale ◽  
Warm Season ◽  
Near Surface ◽  
Low Level ◽  
South Central ◽  
Decadal Scale ◽  
Low Level Jets ◽  
Upper Level

AbstractA 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.

scholarly journals Explicit Convection over the Western Pacific Warm Pool in the Community Atmospheric Model

2005 ◽  
Vol 18 (10) ◽  
pp. 1482-1502 ◽  
Author(s):  
MichałZ. Ziemiański ◽  
Wojciech W. Grabowski ◽  
Mitchell W. Moncrieff
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Atmospheric Model ◽  
Warm Pool ◽  
Western Pacific ◽  
Boreal Winter ◽  
Western Pacific Warm Pool ◽  
Climate System Model ◽  
Pacific Warm Pool ◽  
Standard Configuration

Abstract This paper reports on the application of the cloud-resolving convection parameterization (CRCP) to the Community Atmospheric Model (CAM), the atmospheric component of the Community Climate System Model (CCSM). The cornerstone of CRCP is the use of a two-dimensional zonally oriented cloud-system-resolving model to represent processes on mesoscales at the subgrid scale of a climate model. Herein, CRCP is applied at each climate model column over the tropical western Pacific warm pool, in a domain spanning 10°S–10°N, 150°–170°E. Results from the CRCP simulation are compared with CAM in its standard configuration. The CRCP simulation shows significant improvements of the warm pool climate. The cloud condensate distribution is much improved as well as the bias of the tropopause height. More realistic structure of the intertropical convergence zone (ITCZ) during the boreal winter and better representation of the variability of convection are evident. In particular, the diurnal cycle of precipitation has phase and amplitude in good agreement with observations. Also improved is the large-scale organization of the tropical convection, especially superclusters associated with Madden–Julian oscillation (MJO)-like systems. Location and propagation characteristics, as well as lower-tropospheric cyclonic and upper-tropospheric anticyclonic gyres, are more realistic than in the standard CAM. Finally, the simulations support an analytic theory of dynamical coupling between organized convection and equatorial beta-plane vorticity dynamics associated with MJO-like systems.

scholarly journals Warm Season Rainfall Variability over the U.S. Great Plains in Observations, NCEP and ERA-40 Reanalyses, and NCAR and NASA Atmospheric Model Simulations

2005 ◽  
Vol 18 (11) ◽  
pp. 1808-1830 ◽  
Author(s):  
Alfredo Ruiz-Barradas ◽  
Sumant Nigam
Keyword(s):  
Great Plains ◽  
Rainfall Variability ◽  
Warm Season ◽  
Moisture Flux ◽  
Atmospheric Model ◽  
Precipitation Variability ◽  
Reanalysis Data ◽  
Ncep Reanalysis ◽  
Model Simulations ◽  
Precipitation Estimates

Abstract Interannual variability of Great Plains precipitation in the warm season months is analyzed using gridded observations, satellite-based precipitation estimates, NCEP reanalysis data and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data, and the half-century-long NCAR Community Atmosphere Model (CAM3.0, version 3.0) and the National Aeronautics and Space Administration (NASA) Seasonal-to-Intraseasonal Prediction Project (NSIPP) atmospheric model simulations. Regional hydroclimate is the focus because of its immense societal impact and because the involved variability mechanisms are not well understood. The Great Plains precipitation variability is represented rather differently, and only quasi realistically, in the reanalyses. NCEP has larger amplitude but less traction with observations in comparison with ERA-40. Model simulations exhibit more realistic amplitudes, which are between those of NCEP and ERA-40. The simulated variability is however uncorrelated with observations in both models, with monthly correlations smaller than 0.10 in all cases. An assessment of the regional atmosphere water balance is revealing: Stationary moisture flux convergence accounts for most of the Great Plains variability in ERA-40, but not in the NCEP reanalysis and model simulations; convergent fluxes generate less than half of the precipitation in the latter, while local evaporation does the rest in models. Phenomenal evaporation in the models—up to 4 times larger than the highest observationally constrained estimate (NCEP’s)—provides the bulk of the moisture for Great Plains precipitation variability; thus, precipitation recycling is very efficient in both models, perhaps too efficient. Remote water sources contribute substantially to Great Plains hydroclimate variability in nature via fluxes. Getting the interaction pathways right is presently challenging for the models.

scholarly journals A Mechanistically Credible, Poleward Shift in Warm-Season Precipitation Projected for the U.S. Southern Great Plains?

2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Dry Season ◽  
Wet Season ◽  
Southern Great Plains ◽  
Poleward Shift

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

scholarly journals Investigation of Atmospheric Rivers Impacting the Pigeon River Basin of the Southern Appalachian Mountains

2018 ◽  
Vol 33 (1) ◽  
pp. 283-299 ◽  
Author(s):  
Douglas K. Miller ◽  
David Hotz ◽  
Jessica Winton ◽  
Lukas Stewart
Keyword(s):  
North Carolina ◽  
River Basin ◽  
Large Scale ◽  
Large Fraction ◽  
Appalachian Mountains ◽  
Warm Season ◽  
Atmospheric Rivers ◽  
Southern Appalachian Mountains ◽  
Low Level ◽  
Southern Appalachian

Abstract Rainfall observations in the Pigeon River basin of the southern Appalachian Mountains over a 5-yr period (2009–14) are examined to investigate the synoptic patterns responsible for downstream flooding events as observed near Knoxville, Tennessee, and Asheville, North Carolina. The study is designed to address the hypothesis that atmospheric rivers (ARs) are primarily responsible for the highest accumulation periods observed by the gauge network and that these periods correspond to events having a societal hazard (flooding). The upper 2.5% (extreme) and middle 33% (normal) rainfall events flagged using the gauge network observations showed that half of the heaviest rainfall cases were associated with an AR. Of those extreme events having an AR influence, over 73% had a societal hazard defined as minor-to-major flooding at the USGS river gauge located in Newport, Tennessee, or flooding observations for locations near the Tennessee and North Carolina border reported in the Storm Data publication. Composites of extreme AR-influenced events revealed a synoptic pattern consisting of a highly amplified slow-moving positively tilted trough, suggestive of the anticyclonic Rossby wave breaking scenario that sometimes precedes hydrological events of high impact. Composites of extreme non-AR events indicated a large-scale weather pattern typical of a warm season scenario in which an anomalous low-level cyclone, cut off far from the primary upper-tropospheric jet, was located in the southeastern United States. AR events without a societal hazard represented a large fraction (75%–88%) of all ARs detected during the study period. Synoptic-scale weather patterns of these events were fast moving and had weak low-level atmospheric dynamics.

scholarly journals Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

2020 ◽  
Vol 33 (19) ◽  
pp. 8339-8365 ◽  
Author(s):  
Funing Li ◽  
Daniel R. Chavas ◽  
Kevin A. Reed ◽  
Daniel T. Dawson II
Keyword(s):  
United States ◽  
North America ◽  
Great Plains ◽  
Large Scale ◽  
Extreme Values ◽  
Convective Available Potential Energy ◽  
The United States ◽  
Synoptic Scale ◽  
Low Level ◽  
High Bias

AbstractSevere local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features—including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones—that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both extreme values of SLS environmental parameters and synoptic-scale features in the ERA5 reanalysis and in the Community Atmosphere Model, version 6 (CAM6), historical simulation during 1980–2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in convective available potential energy over the eastern United States primarily due to a high bias in surface moisture and, to a lesser extent, storm-relative helicity due to enhanced low-level winds. Composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, our results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.

scholarly journals Convection Initiation Caused by Heterogeneous Low-Level Jets over the Great Plains

2018 ◽  
Vol 146 (8) ◽  
pp. 2615-2637 ◽  
Author(s):  
Joshua G. Gebauer ◽  
Alan Shapiro ◽  
Evgeni Fedorovich ◽  
Petra Klein
Keyword(s):  
Great Plains ◽  
Three Dimensional ◽  
Warm Season ◽  
The United States ◽  
Dimensional Structure ◽  
Nonuniform Heating ◽  
Low Level ◽  
Low Level Jets ◽  
Convection Initiation ◽  
Capping Inversion

AbstractObservations from three nights of the Plains Elevated Convection at Night (PECAN) field campaign were used in conjunction with Rapid Refresh model forecasts to find the cause of north–south lines of convection, which initiated away from obvious surface boundaries. Such pristine convection initiation (CI) is relatively common during the warm season over the Great Plains of the United States. The observations and model forecasts revealed that all three nights had horizontally heterogeneous and veering-with-height low-level jets (LLJs) of nonuniform depth. The veering and heterogeneity were associated with convergence at the top-eastern edge of the LLJ, where moisture advection was also occurring. As time progressed, this upper region became saturated and, due to its placement above the capping inversion, formed moist absolutely unstable layers, from which the convergence helped initiate elevated convection. The structure of the LLJs on the CI nights was likely influenced by nonuniform heating across the sloped terrain, which led to the uneven LLJ depth and contributed toward the wind veering with height through the creation of horizontal buoyancy gradients. These three CI events highlight the importance of assessing the full three-dimensional structure of the LLJ when forecasting nocturnal convection over the Great Plains.

scholarly journals An evaluation of clouds and radiation in a large-scale atmospheric model using a cloud vertical structure classification

2020 ◽  
Vol 13 (2) ◽  
pp. 673-684
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho
Keyword(s):  
Large Scale ◽  
Vertical Structure ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atmospheric Model ◽  
Radiative Effects ◽  
Surface Cooling ◽  
Vertical Location ◽  
High Clouds

Abstract. We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a subcolumn cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50 % more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ∼20 % in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.

Sign in / Sign up

Export Citation Format

Share Document