scholarly journals Analysis of mesoscale convective system initiations in the United States Corn Belt in the warm season of the years 1979 to 2013

2016 ◽  
Author(s):  
Elisabeth Callen
2019 ◽  
Vol 32 (5) ◽  
pp. 1591-1606 ◽  
Author(s):  
Alex M. Haberlie ◽  
Walker S. Ashley

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.


2021 ◽  
pp. 1-52
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng

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.


2006 ◽  
Vol 21 (1) ◽  
pp. 69-85 ◽  
Author(s):  
Russ S. Schumacher ◽  
Richard H. Johnson

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.


2017 ◽  
Vol 32 (2) ◽  
pp. 511-531 ◽  
Author(s):  
Luke E. Madaus ◽  
Clifford F. Mass

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.


Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 384
Author(s):  
John R. Lawson ◽  
William A. Gallus ◽  
Corey K. Potvin

The bow echo, a mesoscale convective system (MCS) responsible for much hail and wind damage across the United States, is associated with poor skill in convection-allowing numerical model forecasts. Given the decrease in convection-allowing grid spacings within many operational forecasting systems, we investigate the effect of finer resolution on the character of bowing-MCS development in a real-data numerical simulation. Two ensembles were generated: one with a single domain of 3-km horizontal grid spacing, and another nesting a 1-km domain with two-way feedback. Ensemble members were generated from their control member with a stochastic kinetic-energy backscatter scheme, with identical initial and lateral-boundary conditions. Results suggest that resolution reduces hindcast skill of this MCS, as measured with an adaptation of the object-based Structure–Amplitude–Location method. The nested 1-km ensemble produces a faster system than in both the 3-km ensemble and observations. The nested 1-km simulation also produced stronger cold pools, which could be enhanced by the increased (fractal) cloud surface area with higher resolution, allowing more entrainment of dry air and hence increased evaporative cooling.


2014 ◽  
Vol 142 (3) ◽  
pp. 1053-1073 ◽  
Author(s):  
Aaron Johnson ◽  
Xuguang Wang ◽  
Ming Xue ◽  
Fanyou Kong ◽  
Gang Zhao ◽  
...  

Abstract Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 forecasts out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods are compared to the larger-scale IC and physics perturbations in an experimental convection-allowing ensemble. For a precipitation forecast driven primarily by a synoptic-scale baroclinic disturbance, small-scale IC perturbations resulted in little precipitation forecast perturbation energy on medium and large scales, compared to larger-scale IC and physics (LGPH) perturbations after the first few forecast hours. However, for a case where forecast convection at the initial time grew upscale into a mesoscale convective system (MCS), small-scale IC and LGPH perturbations resulted in similar forecast perturbation energy on all scales after about 12 h. Small-scale IC perturbations added to LGPH increased total forecast perturbation energy for this case. Averaged over 34 forecasts, the small-scale IC perturbations had little impact on large forecast scales while LGPH accounted for about half of the error energy on such scales. The impact of small-scale IC perturbations was also less than, but comparable to, the impact of LGPH perturbations on medium scales. On small scales, the impact of small-scale IC perturbations was at least as large as the LGPH perturbations. The spatial structure of small-scale IC perturbations affected the evolution of forecast perturbations, especially at medium scales. There was little systematic impact of the small-scale IC perturbations when added to LGPH. These results motivate further studies on properly sampling multiscale IC errors.


2015 ◽  
Vol 28 (12) ◽  
pp. 4890-4907 ◽  
Author(s):  
Xiangrong Yang ◽  
Jianfang Fei ◽  
Xiaogang Huang ◽  
Xiaoping Cheng ◽  
Leila M. V. Carvalho ◽  
...  

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.


10.1175/820.1 ◽  
2004 ◽  
Vol 19 (6) ◽  
pp. 1127-1135 ◽  
Author(s):  
William A. Gallus ◽  
Moti Segal

Abstract The likelihood of simulated rainfall above a specified threshold being observed is evaluated as a function of the amounts predicted by two mesoscale models. Evaluations are performed for 20 warm-season mesoscale convective system events over the upper Midwest of the United States. Simulations were performed using 10-km versions of the National Centers for Environmental Prediction Eta Model and the Weather Research and Forecasting (WRF) model, with two different convective parameterizations tested in both models. It was found that, despite large differences in the biases of these different models and configurations, a robust relationship was present whereby a substantial increase in the likelihood of observed rainfall exceeding a specified threshold occurred in areas where the model runs forecast higher rainfall amounts. Rainfall was found to be less likely to occur in those areas where the models indicated no rainfall than it was elsewhere in the domain; it was more likely to occur in those regions where rainfall was predicted, especially where the predicted rainfall amounts were largest. The probability of rainfall relative-operating-characteristic and relative-operating-level curves showed that probabilistic forecasts determined from quantitative precipitation forecast values had skill comparable to the skill obtained using more traditional methods in which probabilities are based on the fraction of ensemble members experiencing rainfall. When the entire sample of cases was broken into training and test sets, the probability forecasts of the test sets evidenced good reliability. The relationship noted should provide some additional guidelines to operational forecasters. The results imply that the tested models are better able to indicate the regions where atmospheric processes are most favorable for convective rainfall (where the models generate enhanced amounts) than they are able to predict accurately the rainfall amounts that will be observed.


2008 ◽  
Vol 136 (8) ◽  
pp. 3087-3105 ◽  
Author(s):  
Vagner Anabor ◽  
David J. Stensrud ◽  
Osvaldo L. L. de Moraes

Abstract Serial mesoscale convective system (MCS) events with lifetimes over 18 h and up to nearly 70 h are routinely observed over southeastern South America from infrared satellite imagery during the spring and summer. These events begin over the southern La Plata River basin, with individual convective systems generally moving eastward with the cloud-layer-mean wind. However, an important and common subset of these serial MCS events shows individual MCSs moving to the east or southeast, yet the region of convective development as a whole shifts upstream to the north or northwest. Analyses of the composite mean environments from 10 of these upstream-propagating serial MCS events using NCEP–NCAR reanalysis data events indicates that the synoptic conditions resemble those found in mesoscale convective complex environments over the United States. The serial MCS events form within an environment of strong low-level warm advection and strong moisture advection between the surface and 700 hPa from the Amazon region southward. One feature that appears to particularly influence the low-level flow pattern at early times is a strong surface anticyclone located just off the coast of Brazil. At upper levels, the MCSs develop on the anticyclonic side of the entrance region to an upper-level jet. Mean soundings show that the atmosphere is moist from the surface to near 500 hPa, with values of convective available potential energy above 1200 J kg−1 at the time of system initiation. System dissipation and continued upstream propagation to the north and northwest occurs in tandem with a surface high pressure system that crosses the Andes Mountains from the west.


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