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.

Characteristics of U.S. Extreme Rain Events during 1999–2003

2006 ◽  
Vol 21 (1) ◽  
pp. 69-85 ◽  
Author(s):  
Russ S. Schumacher ◽  
Richard H. Johnson
Keyword(s):  
United States ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Organizational Structures ◽  
The United States ◽  
Convective System ◽  
Precipitation Total ◽  
Extreme Rain ◽  
Rain Events ◽  
Reflectivity Data

Abstract This study examines the characteristics of a large number of extreme rain events over the eastern two-thirds of the United States. Over a 5-yr period, 184 events are identified where the 24-h precipitation total at one or more stations exceeds the 50-yr recurrence amount for that location. Over the entire region of study, these events are most common in July. In the northern United States, extreme rain events are confined almost exclusively to the warm season; in the southern part of the country, these events are distributed more evenly throughout the year. National composite radar reflectivity data are used to classify each event as a mesoscale convective system (MCS), a synoptic system, or a tropical system, and then to classify the MCS and synoptic events into subclassifications based on their organizational structures. This analysis shows that 66% of all the events and 74% of the warm-season events are associated with MCSs; nearly all of the cool-season events are caused by storms with strong synoptic forcing. Similarly, nearly all of the extreme rain events in the northern part of the country are caused by MCSs; synoptic and tropical systems play a larger role in the South and East. MCS-related events are found to most commonly begin at around 1800 local standard time (LST), produce their peak rainfall between 2100 and 2300 LST, and dissipate or move out of the affected area by 0300 LST.

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 Tropopause-Penetrating Convection from Three-Dimensional Gridded NEXRAD Data

2016 ◽  
Vol 55 (2) ◽  
pp. 465-478 ◽  
Author(s):  
David L. Solomon ◽  
Kenneth P. Bowman ◽  
Cameron R. Homeyer
Keyword(s):  
United States ◽  
Three Dimensional ◽  
Warm Season ◽  
The United States ◽  
Lapse Rate ◽  
High Plains ◽  
Annual Cycles ◽  
Weather Radars ◽  
The North ◽  
The Stability

AbstractA new method that combines radar reflectivities from individual Next Generation Weather Radars (NEXRAD) into a three-dimensional composite with high horizontal and vertical resolution is used to estimate storm-top altitudes for the continental United States east of the Rocky Mountains. Echo-top altitudes are compared with the altitude of the lapse-rate tropopause calculated from the ERA-Interim reanalysis and radiosondes. To sample the diurnal and annual cycles, tropopause-penetrating convection is analyzed at 3-h intervals throughout 2004. Overshooting convection is most common in the north-central part of the United States (the high plains). There is a pronounced seasonal cycle; the majority of overshooting systems occur during the warm season (March–August). There is also a strong diurnal cycle, with maximum overshooting occurring near 0000 UTC. The overshooting volume decreases rapidly with height above the tropopause. Radiosonde observations are used to evaluate the quality of the reanalysis tropopause altitudes and the dependence of overshooting depth on environmental characteristics. The radar–radiosonde comparison reveals that overshooting is deeper in double-tropopause environments and increases as the stability of the lower stratosphere decreases.

scholarly journals Evaluating Smartphone Pressure Observations for Mesoscale Analyses and Forecasts

2017 ◽  
Vol 32 (2) ◽  
pp. 511-531 ◽  
Author(s):  
Luke E. Madaus ◽  
Clifford F. Mass
Keyword(s):  
United States ◽  
Rural Areas ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Active Period ◽  
Eastern United States ◽  
Short Term ◽  
Mesoscale Convective ◽  
Dynamic Structures ◽  
Further Development

Abstract Smartphone pressure observations have the potential to greatly increase surface observation density on convection-resolving scales. Currently available smartphone pressure observations are tested through assimilation in a mesoscale ensemble for a 3-day, convectively active period in the eastern United States. Both raw pressure (altimeter) observations and 1-h pressure (altimeter) tendency observations are considered. The available observation density closely follows population density, but observations are also available in rural areas. The smartphone observations are found to contain significant noise, which can limit their effectiveness. The assimilated smartphone observations contribute to small improvements in 1-h forecasts of surface pressure and 10-m wind, but produce larger errors in 2-m temperature forecasts. Short-term (0–4 h) precipitation forecasts are improved when smartphone pressure and pressure tendency observations are assimilated as compared with an ensemble that assimilates no observations. However, these improvements are limited to broad, mesoscale features with minimal skill provided at convective scales using the current smartphone observation density. A specific mesoscale convective system (MCS) is examined in detail, and smartphone pressure observations captured the expected dynamic structures associated with this feature. Possibilities for further development of smartphone observations are discussed.

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