The Contribution of Mesoscale Convective Weather Systems to the Warm-Season Precipitation in the United States

1986 ◽  
Vol 25 (10) ◽  
pp. 1333-1345 ◽  
Author(s):  
J. M. Fritsch ◽  
R. J. Kane ◽  
C. R. Chelius
Keyword(s):  
United States ◽  
Warm Season ◽  
The United States ◽  
Mesoscale Convective ◽  
Convective Weather

scholarly journals A Radar-Based Climatology of Mesoscale Convective Systems in the United States

2019 ◽  
Vol 32 (5) ◽  
pp. 1591-1606 ◽  
Author(s):  
Alex M. Haberlie ◽  
Walker S. Ashley
Keyword(s):  
United States ◽  
Agricultural Land ◽  
Gulf Coast ◽  
Warm Season ◽  
The United States ◽  
Corn Belt ◽  
High Plains ◽  
Convective System ◽  
Aquifer Recharge ◽  
Mesoscale Convective

Abstract This research applies an automated mesoscale convective system (MCS) segmentation, classification, and tracking approach to composite radar reflectivity mosaic images that cover the contiguous United States (CONUS) and span a relatively long study period of 22 years (1996–2017). These data afford a novel assessment of the seasonal and interannual variability of MCSs. Additionally, hourly precipitation data from 16 of those years (2002–17) are used to systematically examine rainfall associated with radar-derived MCS events. The attributes and occurrence of MCSs that pass over portions of the CONUS east of the Continental Divide (ECONUS), as well as five author-defined subregions—North Plains, High Plains, Corn Belt, Northeast, and Mid-South—are also examined. The results illustrate two preferred regions for MCS activity in the ECONUS: 1) the Mid-South and Gulf Coast and 2) the Central Plains and Midwest. MCS occurrence and MCS rainfall display a marked seasonal cycle, with most of the regions experiencing these events primarily during the warm season (May–August). Additionally, MCS rainfall was responsible for over 50% of annual and seasonal rainfall for many locations in the ECONUS. Of particular importance, the majority of warm-season rainfall for regions with high agricultural land use (Corn Belt) and important aquifer recharge properties (High Plains) is attributable to MCSs. These results reaffirm that MCSs are a significant aspect of the ECONUS hydroclimate.

scholarly journals Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

2021 ◽  
pp. 1-52
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng
Keyword(s):  
United States ◽  
Great Plains ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Propagation Speed ◽  
Extreme Rainfall ◽  
The United States ◽  
Convective System ◽  
Large Variability ◽  
Mesoscale Convective

AbstractThis study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

scholarly journals Shifts in Precipitation Accumulation Extremes During the Warm Season Over the United States

2018 ◽  
Vol 45 (16) ◽  
pp. 8586-8595 ◽  
Author(s):  
Cristian Martinez‐Villalobos ◽  
J. David Neelin
Keyword(s):  
United States ◽  
Warm Season ◽  
The United States

Mesoscale Convective Complexes over the United States during 1983

1985 ◽  
Vol 113 (5) ◽  
pp. 888-901 ◽  
Author(s):  
D. M. Rodgers ◽  
M. J. Magnano ◽  
J. H. Arns
Keyword(s):  
United States ◽  
The United States ◽  
Mesoscale Convective

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.

Comparison of Ground-Based Radar and Geosynchronous Satellite Climatologies of Warm-Season Precipitation over the United States

2008 ◽  
Vol 47 (12) ◽  
pp. 3264-3270 ◽  
Author(s):  
John D. Tuttle ◽  
Richard E. Carbone ◽  
Phillip A. Arkin
Keyword(s):  
United States ◽  
Brightness Temperature ◽  
Satellite Data ◽  
Warm Season ◽  
Propagation Speed ◽  
Radar Data ◽  
The United States ◽  
Temperature Threshold ◽  
Brightness Temperatures ◽  
The Difference

Abstract Studies in the past several years have documented the climatology of warm-season precipitation-episode statistics (propagation speed, span, and duration) over the United States using a national composited radar dataset. These climatological studies have recently been extended to other continents, including Asia, Africa, and Australia. However, continental regions outside the United States have insufficient radar coverage, and the newer studies have had to rely on geostationary satellite data at infrared (IR) frequencies as a proxy for rainfall. It is well known that the use of IR brightness temperatures to infer rainfall is subject to large errors. In this study, the statistics of warm-season precipitation episodes derived from radar and satellite IR measurements over the United States are compared and biases introduced by the satellite data are evaluated. It is found that the satellite span and duration statistics are highly dependent upon the brightness temperature threshold used but with the appropriate choices of thresholds can be brought into good agreement with those based upon radar data. The propagation-speed statistics of satellite events are on average ∼4 m s−1 faster than radar events and are relatively insensitive to the brightness temperature threshold. A simple correction procedure based upon the difference between the steering winds for the precipitation core and the winds at the level of maximum anvil outflow is developed.

scholarly journals The Association of the Elevated Mixed Layer with Significant Severe Weather Events in the Northeastern United States*

2010 ◽  
Vol 25 (4) ◽  
pp. 1082-1102 ◽  
Author(s):  
Peter C. Banacos ◽  
Michael L. Ekster
Keyword(s):  
United States ◽  
Mixed Layer ◽  
Trajectory Analysis ◽  
Source Region ◽  
Warm Season ◽  
The United States ◽  
Severe Weather ◽  
Lapse Rate ◽  
Northeastern United States ◽  
Weather Events

Abstract The occurrence of rare but significant severe weather events associated with elevated mixed-layer (EML) air in the northeastern United States is investigated herein. A total of 447 convective event days with one or more significant severe weather report [where significant is defined as hail 2 in. (5.1 cm) in diameter or greater, a convective gust of 65 kt (33 m s−1) or greater, and/or a tornado of F2 or greater intensity] were identified from 1970 through 2006 during the warm season (1 May–30 September). Of these, 34 event days (7.6%) were associated with identifiable EML air in regional rawinsondes preceding the event. Taken with two other noteworthy events in 1953 and 1969, a total of 36 significant severe weather events associated with EML air were studied via composite and trajectory analysis. Though a small percentage of the total, these 36 events compose a noteworthy list of historically significant derechos and tornadic events to affect the northeastern United States. It is demonstrated that plumes of EML air emanating from the Intermountain West in subsiding, anticyclonically curved flows can reinforce the capping inversion and maintain the integrity of the EML across the central United States over a few days. The EML plume can ultimately become entrained into a moderately fast westerly to northwesterly midtropospheric flow allowing for the plume’s advection into the northeastern United States. Resultant thermodynamic conditions in the convective storm environment are similar to those more typically observed closer to the EML source region in the Great Plains of the United States. In addition to composite and trajectory analysis, two case studies are employed to demonstrate salient and evolutionary aspects of the EML in such events. A lapse rate tendency equation is explored to put EML advection in context with other processes affecting lapse rate.

scholarly journals Ensemble-Based Forecast Uncertainty Analysis of Diverse Heavy Rainfall Events

2010 ◽  
Vol 25 (4) ◽  
pp. 1103-1122 ◽  
Author(s):  
Russ S. Schumacher ◽  
Christopher A. Davis
Keyword(s):  
United States ◽  
Tropical Cyclones ◽  
Heavy Rainfall ◽  
Warm Season ◽  
The United States ◽  
Forecast Skill ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Cool Season ◽  
Ensemble Prediction System

Abstract This study examines widespread heavy rainfall over 5-day periods in the central and eastern United States. First, a climatology is presented that identifies events in which more than 100 mm of precipitation fell over more than 800 000 km2 in 5 days. This climatology shows that such events are most common in the cool season near the Gulf of Mexico coast and are rare in the warm season. Then, the focus turns to the years 2007 and 2008, when nine such events occurred in the United States, all of them leading to flooding. Three of these were associated with warm-season convection, three took place in the cool season, and three were caused by landfalling tropical cyclones. Global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System are used to assess forecast skill and uncertainty for these nine events, and to identify the types of weather systems associated with their relative levels of skill and uncertainty. Objective verification metrics and subjective examination are used to determine how far in advance the ensemble identified the threat of widespread heavy rains. Specific conclusions depend on the rainfall threshold and the metric chosen, but, in general, predictive skill was highest for rainfall associated with tropical cyclones and lowest for the warm-season cases. In almost all cases, the ensemble provides very skillful 5-day forecasts when initialized at the beginning of the event. In some of the events—particularly the tropical cyclones and strong baroclinic cyclones—the ensemble still shows considerable skill in 96–216-h precipitation forecasts. In other cases, however, the skill drops off much more rapidly as lead time increases. In particular, forecast skill at long lead times was the lowest and spread was the largest in the two cases associated with meso-α-scale to synoptic-scale vortices that were cut off from the primary upper-level jet. In these cases, it appears that when the vortex is present in the initial conditions, the resulting precipitation forecasts are quite accurate and certain, but at longer lead times when the model is required to both develop and correctly evolve the vortex, forecast quality is low and uncertainty is large. These results motivate further investigation of the events that were poorly predicted.

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