Biases in the Prediction of Convective Storm Characteristics with a Convection Allowing Ensemble

2021 ◽  
Author(s):  
Joseph A. Grim ◽  
James O. Pinto ◽  
Thomas Blitz ◽  
Kenneth Stone ◽  
David C. Dowell
Keyword(s):  
Warm Season ◽  
Storm Events ◽  
Convective Storm ◽  
Convective Storms ◽  
Convective Systems ◽  
Object Based ◽  
Mesoscale Convective ◽  
Macrophysical Properties ◽  
Storm Characteristics ◽  
Convective Mode

AbstractThe severity, duration, and spatial extent of thunderstorm impacts is related to convective storm mode. This study assesses the skill of the High Resolution Rapid Refresh Ensemble (HRRR-E) and its deterministic counterpart (HRRRv4) at predicting convective mode and storm macrophysical properties using 35 convective events observed during the 2020 warm season across the eastern U.S. Seven cases were selected from each of five subjectively-determined convective organization modes: tropical cyclones, mesoscale convective systems (MCSs), quasi-linear convective systems, clusters, and cellular convection. These storm events were assessed using an object-based approach to identify convective storms and determine their individual size. Averaged across all 35 cases, both the HRRR-E and HRRRv4 predicted storm areas were generally larger than observed, with this bias being a function of storm lifetime and convective mode. Both modeling systems also under-predicted the rapid increase in storm counts during the initiation period, particularly for the smaller-scale storm modes. Interestingly, performance of the HRRRv4 differed from that of the HRRR-E, with the HRRRv4 generally having a larger bias in total storm area than the HRRR-E due to HRRRv4 predicting up to 66% more storm objects than the HRRR-E. The HRRR-E accurately predicted the convective mode 65% of the time, with complete misses being very rare (<5% of the time overall). However, an evaluation of rank histograms across all 35 cases revealed that the HRRR-E tended to be under-dispersive when predicting storm size for all but the MCS mode.

scholarly journals Toward 1-km Ensemble Forecasts over Large Domains

2017 ◽  
Vol 145 (8) ◽  
pp. 2943-2969 ◽  
Author(s):  
Craig S. Schwartz ◽  
Glen S. Romine ◽  
Kathryn R. Fossell ◽  
Ryan A. Sobash ◽  
Morris L. Weisman
Keyword(s):  
The United States ◽  
Grid Spacing ◽  
Ensemble Forecasts ◽  
Convective Systems ◽  
Object Based ◽  
Probabilistic Forecasts ◽  
Mesoscale Convective ◽  
Computational Resources ◽  
Horizontal Grid ◽  
Better Than

Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member, 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually were best, especially over the first 12 h and at rainfall rates ≥ 5.0 mm h−1 at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.

scholarly journals Radar Z–RRelationship for Summer Monsoon Storms in Arizona

2005 ◽  
Vol 20 (4) ◽  
pp. 672-679 ◽  
Author(s):  
Efrat Morin ◽  
Robert A. Maddox ◽  
David C. Goodrich ◽  
Soroosh Sorooshian
Keyword(s):  
Hydrologic Model ◽  
Storm Events ◽  
Convective Storm ◽  
Convective Storms ◽  
Discharge Rates ◽  
Wide Range ◽  
Gauge Data ◽  
R Relation ◽  
Initial Results ◽  
Good Agreement

Abstract Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by the National Weather Service (NWS) to identify areas of extreme precipitation that could lead to flooding. Radar-based rainfall estimates have been compared to gauge observations for 13 convective storm events over a densely instrumented, experimental watershed to derive an accurate reflectivity–rainfall rate (i.e., Z–R) relationship for these events. The resultant Z–R relationship, which is much different than the NWS operational Z–R, has been examined for a separate, independent event that occurred over a different location. For all events studied, the NWS operational Z–R significantly overestimates rainfall compared to gauge measurements. The gauge data from the experimental network, the NWS operational rain estimates, and the improved estimates resulting from this study have been input into a hydrologic model to “predict” watershed runoff for an intense event. Rainfall data from the gauges and from the derived Z–R relation produce predictions in relatively good agreement with observed streamflows. The NWS Z–R estimates lead to predicted peak discharge rates that are more than twice as large as the observed discharges. These results were consistent over a relatively wide range of subwatershed areas (4–148 km2). The experimentally derived Z–R relationship may provide more accurate radar estimates for convective storms over the southwest United States than does the operational convective Z–R used by the NWS. These initial results suggest that the generic NWS Z–R relation, used nationally for convective storms, might be substantially improved for regional application.

scholarly journals Observations of Hail–Wind Ratios from Convective Storm Reports across the Continental United States

2020 ◽  
Vol 35 (2) ◽  
pp. 635-656 ◽  
Author(s):  
Matthew J. Bunkers ◽  
Steven R. Fleegel ◽  
Thomas Grafenauer ◽  
Chauncy J. Schultz ◽  
Philip N. Schumacher
Keyword(s):  
United States ◽  
Late Summer ◽  
Weather Forecast ◽  
Eastern United States ◽  
Convective Storm ◽  
Convective Storms ◽  
Warm Summer ◽  
Central United States ◽  
Spatiotemporal Analyses ◽  
Convective Mode

Abstract The objective of this study is to provide guidance on when hail and/or wind is climatologically most likely (temporally and spatially) based on the ratio of severe hail reports to severe wind reports, which can be used by National Weather Forecast (NWS) forecasters when issuing severe convective warnings. Accordingly, a climatology of reported hail-to-wind ratios (i.e., number of hail reports divided by the number of wind reports) for observed severe convective storms was derived using U.S. storm reports from 1955 to 2017. Owing to several temporal changes in reporting and warning procedures, the 1996–2017 period was chosen for spatiotemporal analyses, yielding 265 691 hail and 294 449 wind reports. The most notable changes in hail–wind ratios occurred around 1996 as the NWS modernized and deployed new radars (leading to more hail reports relative to wind) and in 2010 when the severe hail criterion increased nationwide (leading to more wind reports relative to hail). One key finding is that hail–wind ratios are maximized (i.e., relatively more hail than wind) during the late morning through midafternoon and in the spring (March–May), with geographical maxima over the central United States and complex/elevated terrain. Otherwise, minimum ratios occur overnight, during the late summer (July–August) as well as November–December, and over the eastern United States. While the results reflect reporting biases (e.g., fewer wind than hail reports in low-population areas but more wind reports where mesonets are available), meteorological factors such as convective mode and cool spring versus warm summer environments also appear associated with the hail–wind ratio climatology.

scholarly journals Elucidating the Life Cycle of Warm-Season Mesoscale Convective Systems in Eastern China from the Himawari-8 Geostationary Satellite

2020 ◽  
Vol 12 (14) ◽  
pp. 2307
Author(s):  
Dandan Chen ◽  
Jianping Guo ◽  
Dan Yao ◽  
Zhe Feng ◽  
Yanluan Lin
Keyword(s):  
Life Cycle ◽  
Large Scale ◽  
Eastern China ◽  
Warm Season ◽  
Northern China ◽  
Early Morning ◽  
Geostationary Satellite ◽  
Mesoscale Convective Systems ◽  
Convective Systems ◽  
Mesoscale Convective

The life cycle of mesoscale convective systems (MCSs) in eastern China is yet to be fully understood, mainly due to the lack of observations of high spatio-temporal resolution and objective methods. Here, we quantitatively analyze the properties of warm-season (from April to September of 2016) MCSs during their lifetimes using the Himawari-8 geostationary satellite, combined with ground-based radars and gauge measurements. Generally, the occurrence of satellite derived MCSs has a noon peak over the land and an early morning peak over the ocean, which is several hours earlier than the precipitation peak. The developing and dissipative stages are significantly longer as total durations of MCSs increase. Aided by three-dimensional radar mosaics, we find the fraction of convective cores over northern China is much lower when compared with those in central United States, indicating that the precipitation produced by broad stratiform clouds may be more important for northern China. When there exists a large amount of stratiform precipitation, it releases a large amount of latent heat and promotes the large-scale circulations, which favors the maintenance of MCSs. These findings provide quantitative results about the life cycle of warm-season MCSs in eastern China based on multiple data sources and large numbers of samples.

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 The 2015 Plains Elevated Convection at Night Field Project

2017 ◽  
Vol 98 (4) ◽  
pp. 767-786 ◽  
Author(s):  
Bart Geerts ◽  
David Parsons ◽  
Conrad L. Ziegler ◽  
Tammy M. Weckwerth ◽  
Michael I. Biggerstaff ◽  
...  
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Convective Available Potential Energy ◽  
Warm Season ◽  
Lower Troposphere ◽  
Convective Systems ◽  
Predictive Skill ◽  
Mesoscale Convective ◽  
The Rich ◽  
Convection Initiation

Abstract The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

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.

Aboveground Thermodynamic Observations in Convective Storms from Balloonborne Probes Acting as Pseudo-Lagrangian Drifters

2018 ◽  
Vol 99 (4) ◽  
pp. 711-724 ◽  
Author(s):  
Paul M. Markowski ◽  
Yvette P. Richardson ◽  
Scott J. Richardson ◽  
Anders Petersson
Keyword(s):  
Mesoscale Meteorology ◽  
Severe Storms ◽  
Convective Storms ◽  
Convective Systems ◽  
Lagrangian Drifters ◽  
Straight Line ◽  
Mesoscale Convective ◽  
Supercell Storms ◽  
Lagrangian Drifter

AbstractThe severe storms research community lacks reliable, aboveground, thermodynamic observations (e.g., temperature, humidity, and pressure) in convective storms. These missing observations are crucial to understanding the behavior of both supercell storms (e.g., the generation, reorientation, and amplification of vorticity necessary for tornado formation) and larger-scale (mesoscale) convective systems (e.g., storm maintenance and the generation of damaging straight-line winds). This paper describes a novel way to use balloonborne probes to obtain aboveground thermodynamic observations. Each probe is carried by a pair of balloons until one of the balloons is jettisoned; the remaining balloon and probe act as a pseudo-Lagrangian drifter that is drawn through the storm. Preliminary data are presented from a pair of deployments in supercell storms in Oklahoma and Kansas during May 2017. The versatility of the observing system extends beyond severe storms applications into any area of mesoscale meteorology in which a large array of aboveground, in situ thermodynamic observations are needed.

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