scholarly journals Dynamical connection between Great Plains low-level winds and variability of central Gulf States precipitation

2016 ◽  
Vol 121 (7) ◽  
pp. 3421-3434 ◽  
Author(s):  
Bing Pu ◽  
Robert E. Dickinson ◽  
Rong Fu
2008 ◽  
Vol 21 (7) ◽  
pp. 1532-1551 ◽  
Author(s):  
Scott J. Weaver ◽  
Sumant Nigam

Abstract Variability of the Great Plains low-level jet (GPLLJ) is analyzed from the perspective of larger-scale, lower-frequency influences and regional hydroclimate impacts as opposed to the usual analysis of its frequency, diurnal variability, and mesoscale structure. The circulation-centric core analysis is conducted with monthly data from the high spatiotemporal resolution, precipitation-assimilating North American Regional Reanalysis, and the 40-yr ECMWF Re-Analysis (ERA-40) (as necessary) to identify the recurrent patterns of GPLLJ variability and their large-scale circulation links. The links are first investigated from regressions of an index representing meridional wind speed in the climatological jet-core region; the core region itself is defined from analysis of seasonal and diurnal variability of the jet structure and moisture fluxes. The analysis reveals that GPLLJ variability is, indeed, linked to coherent, large-scale, upper-level height patterns over the Pacific and North Atlantic Oscillation (NAO) variability in the Atlantic. A Rossby wave source analysis shows the Pacific height pattern to be potentially linked to tropical diabatic heating anomalies in the west-central basin and in the eastern Pacific sector. EOF analysis of GPLLJ variability shows it to be composed of three modes that, together, account for ∼75% of the variance. The modes represent the strengthening/expansion of the jet core (38%), with a strong precipitation impact on the northern Great Plains, and linked to post-peak-phase ENSO variability; meridional shift of the GPLLJ (23%), with a Gulf states precipitation focus, and linked to pre-peak-phase ENSO variability; and in-place strengthening of the GPLLJ (12%), with dipolar influence on Great Plains and Gulf states precipitation, and linked to summer NAO variability.


2017 ◽  
Vol 51 (4) ◽  
pp. 1537-1558 ◽  
Author(s):  
James F. Danco ◽  
Elinor R. Martin

2020 ◽  
Vol 33 (19) ◽  
pp. 8339-8365 ◽  
Author(s):  
Funing Li ◽  
Daniel R. Chavas ◽  
Kevin A. Reed ◽  
Daniel T. Dawson II

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.


2020 ◽  
pp. 1-55
Author(s):  
Mateusz Taszarek ◽  
Natalia Pilguj ◽  
John T. Allen ◽  
Victor Gensini ◽  
Harold E. Brooks ◽  
...  

AbstractIn this study we compared 3.7 mln rawinsonde observations from 232 stations over Europe and North America with proximal vertical profiles from ERA5 and MERRA2 to examine how well reanalysis depicts observed convective parameters. Larger differences between soundings and reanalysis are found for thermodynamic theoretical parcel parameters, low-level lapse rates and low-level wind shear. In contrast, reanalysis best represents temperature and moisture variables, mid-tropospheric lapse rates, and mean wind. Both reanalyses underestimate CAPE, low-level moisture and wind shear, particularly when considering extreme values. Overestimation is observed for low-level lapse rates, mid-tropospheric moisture and the level of free convection. Mixed-layer parcels have overall better accuracy when compared to most-unstable, especially considering convective inhibition and lifted condensation level. Mean absolute error for both reanalyses has been steadily decreasing over the last 39 years for almost every analyzed variable. Compared to MERRA2, ERA5 has higher correlations and lower mean absolute errors. MERRA2 is typically drier and less unstable over central Europe and the Balkans, with the opposite pattern over western Russia. Both reanalyses underestimate CAPE and CIN over the Great Plains. Reanalyses are more reliable for lower elevations stations and struggle along boundaries such as coastal zones and mountains. Based on the results from this and prior studies we suggest that ERA5 is likely one of the most reliable available reanalysis for exploration of convective environments, mainly due to its improved resolution. For future studies we also recommend that computation of convective variables should use model levels that provide more accurate sampling of the boundary-layer conditions compared to less numerous pressure levels.


2020 ◽  
Vol 148 (11) ◽  
pp. 4607-4627
Author(s):  
Craig R. Ferguson ◽  
Shubhi Agrawal ◽  
Mark C. Beauharnois ◽  
Geng Xia ◽  
D. Alex Burrows ◽  
...  

AbstractIn 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.


2018 ◽  
Author(s):  
Iago Algarra ◽  
Jorge Eiras-Barca ◽  
Gonzalo Miguez-Macho ◽  
Raquel Nieto ◽  
Luis Gimeno

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Ying Tang ◽  
Julie Winkler ◽  
Shiyuan Zhong ◽  
Xindi Bian ◽  
Dana Doubler ◽  
...  

2018 ◽  
Vol 33 (5) ◽  
pp. 1109-1120 ◽  
Author(s):  
David E. Jahn ◽  
William A. Gallus

Abstract The Great Plains low-level jet (LLJ) is influential in the initiation and evolution of nocturnal convection through the northward advection of heat and moisture, as well as convergence in the region of the LLJ nose. However, accurate numerical model forecasts of LLJs remain a challenge, related to the performance of the planetary boundary layer (PBL) scheme in the stable boundary layer. Evaluated here using a series of LLJ cases from the Plains Elevated Convection at Night (PECAN) program are modifications to a commonly used local PBL scheme, Mellor–Yamada–Nakanishi–Niino (MYNN), available in the Weather Research and Forecasting (WRF) Model. WRF forecast mean absolute error (MAE) and bias are calculated relative to PECAN rawinsonde observations. The first MYNN modification invokes a new set of constants for the scheme closure equations that, in the vicinity of the LLJ, decreases forecast MAEs of wind speed, potential temperature, and specific humidity more than 19%. For comparison, the Yonsei University (YSU) scheme results in wind speed MAEs 22% lower but specific humidity MAEs 17% greater than in the original MYNN scheme. The second MYNN modification, which incorporates the effects of potential kinetic energy and uses a nonzero mixing length in stable conditions as dependent on bulk shear, reduces wind speed MAEs 66% for levels below the LLJ, but increases MAEs at higher levels. Finally, Rapid Refresh analyses, which are often used for forecast verification, are evaluated here and found to exhibit a relatively large average wind speed bias of 3 m s−1 in the region below the LLJ, but with relatively small potential temperature and specific humidity biases.


2018 ◽  
Vol 146 (8) ◽  
pp. 2615-2637 ◽  
Author(s):  
Joshua G. Gebauer ◽  
Alan Shapiro ◽  
Evgeni Fedorovich ◽  
Petra Klein

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.


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