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.

scholarly journals Near-Surface Thermodynamic Sensitivities in Simulated Extreme-Rain-Producing Mesoscale Convective Systems

2017 ◽  
Vol 145 (6) ◽  
pp. 2177-2200 ◽  
Author(s):  
Russ S. Schumacher ◽  
John M. Peters
Keyword(s):  
Water Vapor ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Mesoscale Convective Systems ◽  
Cold Pool ◽  
Near Surface ◽  
Low Level ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Outflow Boundary

Abstract This study investigates the influences of low-level atmospheric water vapor on the precipitation produced by simulated warm-season midlatitude mesoscale convective systems (MCSs). In a series of semi-idealized numerical model experiments using initial conditions gleaned from composite environments from observed cases, small increases in moisture were applied to the model initial conditions over a layer either 600 m or 1 km deep. The precipitation produced by the MCS increased with larger moisture perturbations as expected, but the rainfall changes were disproportionate to the magnitude of the moisture perturbations. The experiment with the largest perturbation had a water vapor mixing ratio increase of approximately 2 g kg−1 over the lowest 1 km, corresponding to a 3.4% increase in vertically integrated water vapor, and the area-integrated MCS precipitation in this experiment increased by nearly 60% over the control. The locations of the heaviest rainfall also changed in response to differences in the strength and depth of the convectively generated cold pool. The MCSs in environments with larger initial moisture perturbations developed stronger cold pools, and the convection remained close to the outflow boundary, whereas the convective line was displaced farther behind the outflow boundary in the control and the simulations with smaller moisture perturbations. The high sensitivity of both the amount and location of MCS rainfall to small changes in low-level moisture demonstrates how small moisture errors in numerical weather prediction models may lead to large errors in their forecasts of MCS placement and behavior.

scholarly journals Influence of Tropical Waves on the Lifecycle of Mesoscale Convective Systems over West Africa

2021 ◽  
Author(s):  
Marlon Maranan ◽  
Andreas Schlueter ◽  
Andreas H. Fink ◽  
Peter Knippertz
Keyword(s):  
West Africa ◽  
High Frequency ◽  
Rainfall Variability ◽  
Weather Prediction ◽  
Mesoscale Convective Systems ◽  
Convection Current ◽  
Maturity Stage ◽  
Convective Systems ◽  
Tropical Waves ◽  
Mesoscale Convective

<p>Rainfall variability over West Africa remains a major challenge for numerical weather prediction (NWP). Due to the largely stochastic and sub-grid nature of tropical convection, current NWP models still fail to provide reliable precipitation forecasts – even for a 1-day leadtime – and are barely more skillful than climatology-based forecasts. Thus, several recent studies have investigated the presumably more predictable influence of tropical waves on environmental conditions for convection and found distinct and coherent (thermo-)dynamical patterns depending on the type and phase of the wave. Of particular interest in this context is the interaction of the wave with the lifecycle of usually westward propagating mesoscale convective systems (MCSs), which are the major providers of rain in the region and can occasionally even lead to flooding. The exact mechanisms and strength of this interaction are still not entirely known.</p><p>This study combines two recent datasets in a novel way in order to systematically investigate the influence of tropical waves on MCS characteristics and lifecycle. First, MCSs are tracked within northern tropical Africa (20°W-30°E / 2°-15°N) over an 11-year period during the West African rainy season (April-October) using infrared brightness temperature fields provided by the Spinning enhanced visible and infrared imager (SEVIRI). Second, tropical waves are isolated by applying a filtering method in the wave-frequency domain to precipitation data of the Tropical Rainfall Measuring Mission (TRMM) within the 5°-15°N latitude band for the same target period. By combining the two datasets in space and time, the magnitude and phase of each wave is known at every timestep of the MCS tracks, which enables a systematic investigation of MCS characteristics as a function of wave properties.</p><p>Preliminary results suggest that long-lived MCSs (lifetime ≥ 12h) frequently couple with the “wet” phase of high-frequency tropical waves, in particular Kelvin, eastward inertia-gravity (EIG), and African easterly waves (AEW). Showing an enhanced occurrence frequency of MCS initiation, the wet phase of AEWs appears to have strong modulation capabilities during the genesis stage and further accompanies these long-lived MCSs during their entire lifetime. In the case of Kelvin waves and EIGs, the wet phase overlaps only with the intensification and maturity stage of these MCSs as a consequence of opposite directions of movement. Similar coupling patterns also exist for mixed Rossby gravity waves (MRGs), although to a weaker extent. Furthermore, no consistent coupling tendencies with long-lived MCSs are evident for low-frequency waves (Madden-Julian Oscillation (MJO), equatorial Rossby wave (ER)), arguably since they act on larger spatio-temporal scales. For short-lived MCSs (lifetime < 6h), the coupling with high-frequency waves is substantially weaker.</p><p>In the future we will also address potential influences of wave-wave interactions on MCSs as well as potential differences in coupling mechanisms between the Guinea Coast region and the Sahel farther north. With increasing efforts in the prediction of tropical waves, this study has the potential to aid the short-term forecasting of MCS development and its lifecycle. This can be of particular importance for the anticipation of extreme rainfall events and subsequent risk assessment in West Africa.</p>

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 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 On Contrasting Ensemble Simulations of Two Great Plains Bow Echoes

2016 ◽  
Vol 31 (3) ◽  
pp. 787-810 ◽  
Author(s):  
John Lawson ◽  
William A. Gallus
Keyword(s):  
Great Plains ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Model Error ◽  
Numerical Weather Prediction Model ◽  
Radius Of Curvature ◽  
Convective Systems ◽  
Bow Echo ◽  
Mesoscale Convective ◽  
Microphysical Parameterization

Abstract Bow echo structures, a subset of mesoscale convective systems (MCSs), are often poorly forecast within deterministic numerical weather prediction model simulations. Among other things, this may be due to the inherent low predictability associated with bow echoes, deficient initial conditions (ICs), and inadequate parameterization schemes. Four different ensemble configurations assessed the sensitivity of the MCSs’ simulated reflectivity and radius of curvature to the following: perturbations in initial and lateral boundary conditions using a global dataset, different microphysical schemes, a stochastic kinetic energy backscatter (SKEB) scheme, and a mix of the previous two. One case is poorly simulated no matter which IC dataset or microphysical parameterization is used. In the other case, almost all simulations reproduce a bow echo. When the IC dataset and microphysical parameterization is fixed within a SKEB ensemble, ensemble uncertainty is smaller. However, while differences in the location and timing of the MCS are reduced, variations in convective mode remain substantial. Results suggest the MCS’s positioning is influenced primarily by ICs, but its mode is most sensitive to the model error uncertainty. Hence, correct estimation of model error uncertainty on the storm scale is crucial for adequate spread and the probabilistic forecast of convective events.

scholarly journals Different Representation of Mesoscale Convective Systems in Convection-Permitting and Convection-Parameterizing NWP Models and Its Implications for Large-Scale Forecast Evolution

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 503 ◽  
Author(s):  
Karsten Peters ◽  
Cathy Hohenegger ◽  
Daniel Klocke
Keyword(s):  
Large Scale ◽  
Weather Prediction ◽  
Mesoscale Convective Systems ◽  
Limited Area ◽  
Synoptic Scale ◽  
Mean Flow ◽  
Convective Systems ◽  
Western Africa ◽  
Mesoscale Convective ◽  
The Difference

Representing mesoscale convective systems (MCSs) and their multi-scale interaction with the large-scale atmospheric dynamics is still a major challenge in state-of-the-art global numerical weather prediction (NWP) models. This results in potentially defective forecasts of synoptic-scale dynamics in regions of high MCS activity. Here, we quantify this error by comparing simulations performed with a very large-domain, convection-permitting NWP model to two operational global NWP models relying on parameterized convection. We use one month’s worth of daily forecasts over Western Africa and focus on land regions only. The convection-permitting model matches remarkably well the statistics of westward-propagating MCSs compared to observations, while the convection-parameterizing NWP models misrepresent them. The difference in the representation of MCSs in the different models leads to measurably different synoptic-scale forecast evolution as visible in the wind fields at both 850 and 650 hPa, resulting in forecast differences compared to the operational global NWP models. This is quantified by computing the correlation between the differences and the number of MCSs: the larger the number of MCSs, the larger the difference. This fits the expectation from theory on MCS–mean flow interaction. Here, we show that this effect is strong enough to affect daily limited-area forecasts on very large domains.

scholarly journals Spatiotemporal Characteristics and Large-Scale Environments of Mesoscale Convective Systems East of the Rocky Mountains

2019 ◽  
Vol 32 (21) ◽  
pp. 7303-7328 ◽  
Author(s):  
Zhe Feng ◽  
Robert A. Houze ◽  
L. Ruby Leung ◽  
Fengfei Song ◽  
Joseph C. Hardin ◽  
...  
Keyword(s):  
Great Plains ◽  
Rocky Mountains ◽  
Large Scale ◽  
Mesoscale Convective Systems ◽  
Rain Area ◽  
Stratiform Rain ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The U.S ◽  
Mcs Genesis

ABSTRACT The spatiotemporal variability and three-dimensional structures of mesoscale convective systems (MCSs) east of the U.S. Rocky Mountains and their large-scale environments are characterized across all seasons using 13 years of high-resolution radar and satellite observations. Long-lived and intense MCSs account for over 50% of warm season precipitation in the Great Plains and over 40% of cold season precipitation in the southeast. The Great Plains has the strongest MCS seasonal cycle peaking in May–June, whereas in the U.S. southeast MCSs occur year-round. Distinctly different large-scale environments across the seasons have significant impacts on the structure of MCSs. Spring and fall MCSs commonly initiate under strong baroclinic forcing and favorable thermodynamic environments. MCS genesis frequently occurs in the Great Plains near sunset, although convection is not always surface based. Spring MCSs feature both large and deep convection, with a large stratiform rain area and high volume of rainfall. In contrast, summer MCSs often initiate under weak baroclinic forcing, featuring a high pressure ridge with weak low-level convergence acting on the warm, humid air associated with the low-level jet. MCS genesis concentrates east of the Rocky Mountain Front Range and near the southeast coast in the afternoon. The strongest MCS diurnal cycle amplitude extends from the foothills of the Rocky Mountains to the Great Plains. Summer MCSs have the largest and deepest convective features, the smallest stratiform rain area, and the lowest rainfall volume. Last, winter MCSs are characterized by the strongest baroclinic forcing and the largest MCS precipitation features over the southeast. Implications of the findings for climate modeling are discussed.

scholarly journals Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

2020 ◽  
Vol 21 (2) ◽  
pp. 317-334
Author(s):  
Jingjing Tian ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng
Keyword(s):  
High Resolution ◽  
Spatial Variability ◽  
Great Plains ◽  
Mesoscale Convective Systems ◽  
Spatiotemporal Variability ◽  
Convective Systems ◽  
Ice Cloud ◽  
Convective Core ◽  
Mesoscale Convective ◽  
Ice Water

AbstractIn this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

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