scholarly journals Evaluation of Ensemble Configurations for the Analysis and Prediction of Heavy-Rain-Producing Mesoscale Convective Systems*

2014 ◽  
Vol 142 (11) ◽  
pp. 4108-4138 ◽  
Author(s):  
Russ S. Schumacher ◽  
Adam J. Clark
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Great Plains ◽  
Heavy Rain ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Probabilistic Forecasts ◽  
Mesoscale Convective ◽  
Physical Parameterizations

Abstract This study investigates probabilistic forecasts made using different convection-allowing ensemble configurations for a three-day period in June 2010 when numerous heavy-rain-producing mesoscale convective systems (MCSs) occurred in the United States. These MCSs developed both along a baroclinic zone in the Great Plains, and in association with a long-lived mesoscale convective vortex (MCV) in Texas and Arkansas. Four different ensemble configurations were developed using an ensemble-based data assimilation system. Two configurations used continuously cycled data assimilation, and two started the assimilation 24 h prior to the initialization of each forecast. Each configuration was run with both a single set of physical parameterizations and a mixture of physical parameterizations. These four ensemble forecasts were also compared with an ensemble run in real time by the Center for the Analysis and Prediction of Storms (CAPS). All five of these ensemble systems produced skillful probabilistic forecasts of the heavy-rain-producing MCSs, with the ensembles using mixed physics providing forecasts with greater skill and less overall bias compared to the single-physics ensembles. The forecasts using ensemble-based assimilation systems generally outperformed the real-time CAPS ensemble at lead times of 6–18 h, whereas the CAPS ensemble was the most skillful at forecast hours 24–30, though it also exhibited a wet bias. The differences between the ensemble precipitation forecasts were found to be related in part to differences in the analysis of the MCV and its environment, which in turn affected the evolution of errors in the forecasts of the MCSs. These results underscore the importance of representing model error in convection-allowing ensemble analysis and prediction systems.

scholarly journals The Evolution of Morning Convective Systems over the U.S. Great Plains during the Warm Season. Part II: A Climatology and the Influence of Environmental Factors

2008 ◽  
Vol 136 (3) ◽  
pp. 929-944 ◽  
Author(s):  
Carl E. Hane ◽  
John A. Haynes ◽  
David L. Andra ◽  
Frederick H. Carr
Keyword(s):  
Great Plains ◽  
Warm Season ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Limited Area ◽  
Southern Plains ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Synoptic Features ◽  
Discriminant Analyses

Abstract Mesoscale convective systems that affect a limited area within the southern plains of the United States during late morning hours during the warm season are investigated. A climatological study over a 5-yr period documents the initiation locations and times, tracks, associated severe weather, and relation to synoptic features over the lifetimes of 145 systems. An assessment is also made of system evolution in each case during the late morning. For a subset of 48 systems, vertical profiles of basic variables from Rapid Update Cycle (RUC) model analyses are used to characterize the environment of each system. Scatter diagrams and discriminant analyses are used to assess which environmental variables are most promising in helping to determine which of two classes of evolutionary character each system will follow.

scholarly journals Assimilation of Satellite-Derived Soil Moisture for Improved Forecasts of the Great Plains Low-Level Jet

2020 ◽  
Vol 148 (11) ◽  
pp. 4607-4627
Author(s):  
Craig R. Ferguson ◽  
Shubhi Agrawal ◽  
Mark C. Beauharnois ◽  
Geng Xia ◽  
D. Alex Burrows ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Wind Speed ◽  
Data Assimilation ◽  
Great Plains ◽  
Wrf Model ◽  
Added Value ◽  
Low Level ◽  
Convective Systems ◽  
South Central ◽  
Mesoscale Convective

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.

scholarly journals Toward 1-km Ensemble Forecasts over Large Domains

2017 ◽  
Vol 145 (8) ◽  
pp. 2943-2969 ◽  
Author(s):  
Craig S. Schwartz ◽  
Glen S. Romine ◽  
Kathryn R. Fossell ◽  
Ryan A. Sobash ◽  
Morris L. Weisman
Keyword(s):  
The United States ◽  
Grid Spacing ◽  
Ensemble Forecasts ◽  
Convective Systems ◽  
Object Based ◽  
Probabilistic Forecasts ◽  
Mesoscale Convective ◽  
Computational Resources ◽  
Horizontal Grid ◽  
Better Than

Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member, 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually were best, especially over the first 12 h and at rainfall rates ≥ 5.0 mm h−1 at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.

scholarly journals Observational Analysis of the Predictability of Mesoscale Convective Systems

2007 ◽  
Vol 22 (4) ◽  
pp. 813-838 ◽  
Author(s):  
Israel L. Jirak ◽  
William R. Cotton
Keyword(s):  
United States ◽  
Wind Shear ◽  
Vertical Wind Shear ◽  
The United States ◽  
Vertical Wind ◽  
Mesoscale Convective Systems ◽  
Convective Initiation ◽  
Low Level ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.

scholarly journals The Role of Continental Mesoscale Convective Systems in Forecast Busts within Global Weather Prediction Systems

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 681 ◽  
Author(s):  
Parsons ◽  
Lillo ◽  
Rattray ◽  
Bechtold ◽  
Rodwell ◽  
...  
Keyword(s):  
Great Plains ◽  
Numerical Models ◽  
Weather Prediction ◽  
Mesoscale Convective Systems ◽  
The Arctic ◽  
Convective Systems ◽  
Middle Latitudes ◽  
Medium Range ◽  
Mesoscale Convective ◽  
Prediction Systems

Despite significant, steady improvements in the skill of medium-range weather predictionsystems over the past several decades, the accuracy of these forecasts are occasionally very poor.These forecast failures are referred to as “busts” or “dropouts”. The lack of a clear explanationfor bust events limits the development and implementation of strategies designed to reduce theiroccurrence. This study seeks to explore a flow regime where forecast busts occur over Europe inassociation with mesoscale convective systems over North America east of the Rocky Mountains.Our investigation focuses on error growth in the European Centre for Medium-Range WeatherForecasting’s (ECMWF’s) global model during the summer 2015 PECAN (Plains Elevated Convectionat Night) experiment. Observations suggest that a close, but varied interrelationship can occurbetween long-lived, propagating, mesoscale convection systems over the Great Plains and Rossbywave packets. Aloft, the initial error occurs in the ridge of the wave and then propagates downstreamas an amplifying Rossby wave packet producing poor forecasts in middle latitudes and, in somecases, the Arctic. Our results suggest the importance of improving the representation of organizeddeep convection in numerical models, particularly for long-lived mesoscale convective systems thatproduce severe weather and propagate near the jet stream.

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 Characteristics of Mesoscale Convective Systems over China and Its Vicinity Using Geostationary Satellite FY2

2015 ◽  
Vol 28 (12) ◽  
pp. 4890-4907 ◽  
Author(s):  
Xiangrong Yang ◽  
Jianfang Fei ◽  
Xiaogang Huang ◽  
Xiaoping Cheng ◽  
Leila M. V. Carvalho ◽  
...  
Keyword(s):  
Warm Season ◽  
The United States ◽  
Geostationary Satellite ◽  
Mesoscale Convective Systems ◽  
Convective System ◽  
Convective Systems ◽  
Diurnal Cycles ◽  
Mesoscale Convective ◽  
Positive Correlations ◽  
Monthly Variations

Abstract This study investigates mesoscale convective systems (MCSs) over China and its vicinity during the boreal warm season (May–August) from 2005 to 2012 based on data from the geostationary satellite Fengyun 2 (FY2) series. The authors classified and analyzed the quasi-circular and elongated MCSs on both large and small scales, including mesoscale convective complexes (MCCs), persistent elongated convective systems (PECSs), meso-β circular convective systems (MβCCSs), meso-β elongated convective system (MβECSs), and two additional types named small meso-β circular convective systems (SMβCCSs) and small meso-β elongated convective systems (SMβECSs). Results show that nearly 80% of the 8696 MCSs identified in this study fall into the elongated categories. Overall, MCSs occur mainly at three zonal bands with average latitudes around 20°, 30°, and 50°N. The frequency of MCSs occurrences is maximized at the zonal band around 20°N and decreases with increase in latitude. During the eight warm seasons, the period of peak systems occurrences is in July, followed decreasingly by June, August, and May. Meanwhile, from May to August three kinds of monthly variations are observed, which are clear northward migration, rapid increase, and persistent high frequency of MCS occurrences. Compared to MCSs in the United States, the four types of MCSs (MCCs, PECSs, MβCCSs, and MβECSs) are relatively smaller both in size and eccentricity but exhibit nearly equal life spans. Moreover, MCSs in both countries share similar positive correlations between their duration and maximum extent. Additionally, the diurnal cycles of MCSs in both countries are similar (local time) regarding the three stages of initiation, maturation, and termination.

scholarly journals A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017

2021 ◽  
Vol 13 (2) ◽  
pp. 827-856
Author(s):  
Jianfeng Li ◽  
Zhe Feng ◽  
Yun Qian ◽  
L. Ruby Leung
Keyword(s):  
United States ◽  
High Resolution ◽  
Atmospheric Chemistry ◽  
Rocky Mountains ◽  
Deep Convection ◽  
The United States ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Data Product ◽  
Mesoscale Convective

Abstract. Deep convection possesses markedly distinct properties at different spatiotemporal scales. We present an original high-resolution (4 km, hourly) unified data product of mesoscale convective systems (MCSs) and isolated deep convection (IDC) in the United States east of the Rocky Mountains and examine their climatological characteristics from 2004 to 2017. The data product is produced by applying an updated Flexible Object Tracker algorithm to hourly satellite brightness temperature, radar reflectivity, and precipitation datasets. Analysis of the data product shows that MCSs are much larger and longer-lasting than IDC, but IDC occurs about 100 times more frequently than MCSs, with a mean convective intensity comparable to that of MCSs. Hence both MCS and IDC are essential contributors to precipitation east of the Rocky Mountains, although their precipitation shows significantly different spatiotemporal characteristics. IDC precipitation concentrates in summer in the Southeast with a peak in the late afternoon, while MCS precipitation is significant in all seasons, especially for spring and summer in the Great Plains. The spatial distribution of MCS precipitation amounts varies by season, while diurnally, MCS precipitation generally peaks during nighttime except in the Southeast. Potential uncertainties and limitations of the data product are also discussed. The data product is useful for investigating the atmospheric environments and physical processes associated with different types of convective systems; quantifying the impacts of convection on hydrology, atmospheric chemistry, and severe weather events; and evaluating and improving the representation of convective processes in weather and climate models. The data product is available at https://doi.org/10.25584/1632005 (Li et al., 2020).

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