scholarly journals A 15 yr climatology of derecho-producing mesoscale convective systems over the central and eastern United States

2003 ◽  
Vol 24 ◽  
pp. 129-139 ◽  
Author(s):  
ML Bentley ML ◽  
JA Sparks
Keyword(s):  
United States ◽  
Mesoscale Convective Systems ◽  
Eastern United States ◽  
Convective Systems ◽  
Mesoscale Convective

scholarly journals Assessment of the High-Resolution Rapid Refresh Model’s Ability to Predict Mesoscale Convective Systems Using Object-Based Evaluation

2015 ◽  
Vol 30 (4) ◽  
pp. 892-913 ◽  
Author(s):  
James O. Pinto ◽  
Joseph A. Grim ◽  
Matthias Steiner
Keyword(s):  
United States ◽  
High Resolution ◽  
Size Distribution ◽  
Great Plains ◽  
Southeastern United States ◽  
Mesoscale Convective Systems ◽  
Eastern United States ◽  
Convective Systems ◽  
Object Based ◽  
Mesoscale Convective

Abstract An object-based verification technique that keys off the radar-retrieved vertically integrated liquid (VIL) is used to evaluate how well the High-Resolution Rapid Refresh (HRRR) predicted mesoscale convective systems (MCSs) in 2012 and 2013. It is found that the modeled radar VIL values are roughly 50% lower than observed. This mean bias is accounted for by reducing the radar VIL threshold used to identify MCSs in the HRRR. This allows for a more fair evaluation of the model’s skill at predicting MCSs. Using an optimized VIL threshold for each summer, it is found that the HRRR reproduces the first (i.e., counts) and second moments (i.e., size distribution) of the observed MCS size distribution averaged over the eastern United States, as well as their aspect ratio, orientation, and diurnal variations. Despite threshold optimization, the HRRR tended to predict too many (few) MCSs at lead times less (greater) than 4 h because of lead time–dependent biases in the modeled radar VIL. The HRRR predicted too many MCSs over the Great Plains and too few MCSs over the southeastern United States during the day. These biases are related to the model’s tendency to initiate too many MCSs over the Great Plains and too few MCSs over the southeastern United States. Additional low biases found over the Mississippi River valley region at night revealed a tendency for the HRRR to dissipate MCSs too quickly. The skill of the HRRR at predicting specific MCS events increased between 2012 and 2013, coinciding with changes in both the model physics and in the methods used to assimilate the three-dimensional radar reflectivity.

scholarly journals Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

2020 ◽  
Vol 21 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng ◽  
Jiwen Fan
Keyword(s):  
United States ◽  
False Alarm ◽  
Stage Iv ◽  
Cloud Base ◽  
Eastern United States ◽  
Convective Systems ◽  
Precipitation Measurement ◽  
Precipitation Characteristics ◽  
Mesoscale Convective ◽  
Global Precipitation

AbstractMesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

scholarly journals Forecasting the Maintenance of Mesoscale Convective Systems Crossing the Appalachian Mountains

2010 ◽  
Vol 25 (4) ◽  
pp. 1179-1195 ◽  
Author(s):  
Casey E. Letkewicz ◽  
Matthew D. Parker
Keyword(s):  
Appalachian Mountains ◽  
Severe Weather ◽  
Mesoscale Convective Systems ◽  
Radiosonde Data ◽  
Eastern United States ◽  
Unique Problem ◽  
Convective Systems ◽  
Barrier Analysis ◽  
Mesoscale Convective ◽  
The Mean

Abstract Forecasting the maintenance of mesoscale convective systems (MCSs) is a unique problem in the eastern United States due to the influence of the Appalachian Mountains. At times these systems are able to traverse the terrain and produce severe weather in the lee, while at other times they instead dissipate upon encountering the mountains. To differentiate between crossing and noncrossing MCS environments, 20 crossing and 20 noncrossing MCS cases were examined. The cases were largely similar in terms of their 500-hPa patterns, MCS archetypes, and orientations with respect to the barrier. Analysis of radiosonde data, however, revealed that the environment east of the mountains discriminated between case types very well. The thermodynamic and kinematic variables that had the most discriminatory power included those associated with instability, several different bulk shear vector magnitudes, and also the mean tropospheric wind. Crossing cases were characterized by higher instability, which was found to be partially attributable to the diurnal cycle. However, these cases also tended to occur in environments with weaker shear and a smaller mean wind. The potential reasons for these results, and their forecasting implications, are discussed.

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 Local and Regional Discriminators of Mesoscale Convective Vortex Development in Arizona

2003 ◽  
Vol 131 (8) ◽  
pp. 1939-1943
Author(s):  
David M. Brommer ◽  
Robert C. Balling ◽  
Randall S. Cerveny
Keyword(s):  
United States ◽  
Wind Shear ◽  
Summer Season ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective ◽  
Mesoscale Convective Vortex ◽  
Convective Vortices ◽  
Rawinsonde Data

Abstract In approximately half of Arizona's summer season (June–September) mesoscale convective systems evolve into mesoscale convective vortices (MCVs). Analysis of satellite imagery identified MCVs in Arizona over the period 1991–2000, and local and regional rawinsonde data discriminated conditions conducive for MCV development. These results indicate that MCVs are more likely to form from convective systems when the local and regional environments are characterized by relative stability in the 850–700-hPa layer and moderate wind shear in the 500–200-hPa layer. These characteristics are similar to results reported for MCV development in the central United States.

scholarly journals Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

2021 ◽  
Vol 118 (43) ◽  
pp. e2105260118
Author(s):  
Huancui Hu ◽  
L. Ruby Leung ◽  
Zhe Feng
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Land Surface ◽  
Warm Season ◽  
Summer Rainfall ◽  
Mesoscale Convective Systems ◽  
Rainfall Events ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective

Land–atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture–precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture–precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture–precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

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