Supercell Storm Research Articles

Characteristics of environmental factors associated with typhoon Kongrey (1825) over the Eastern Coastal Region of Korea

In this study, the characteristics of environmental factors associated with typhoon Kongrey were examined using radiosonde, wind-profiler, radar, and Automated Surface Observing System (ASOS) data in Uljin, which is located the eastern coast of Korea. The radiosonde data were obtained from intensive observation between 1500 LST 5 to 0000 LST 7 October 2018. Environmental factors such as Total Precipitable Water (TPW) and Strom Relative Environmental Helicity (SREH) were selected to examine their relations to typhoon-accompanied precipitation. The TPW peak with 60.54 mm appeared at 1200 LST 6 October, which is 6 h after the peak of typhoon precipitation. It was found that the TPW variation is largely associated with the effect of water vapor supply from the typhoon with nearest proximity to Uljin at 1500 LST 6 October. Mean SREH, which indicates mechanical instability, was 761 m2 s⁻2 during the period in which typhoon precipitation occurred. These environments would provide a good condition for the development of super-cell storms, causing heavy precipitation associated with typhoon. In addition, it was found that the correlation coefficient between SREH and typhoon rainfall is 0.8 (p-value = 0.02).

Impact of the Hierarchical Ensemble Filter Covariance Localization Method on EnKF Radar Data Assimilation: Observing system simulation experiments

An adaptive localization method using the hierarchical ensemble filter (HEF) technique was first applied to the ensemble Kalman filter (EnKF) radar data assimilation (DA) though observing system simulation experiments (OSSEs) for an idealized supercell storm. The HEF method calculates localization by minimizing the sampling error without defining the physical distance between observation and state variables. Four experiments using regular Gaspari and Cohn (GC) and HEF localization methods with different group sizes (group numbers of ensembles) were performed. The HEF localization experiments perform better than GC experiment, producing smaller analysis errors and larger ensemble spreads for most model state variables, and stronger wind, vertical vorticity, and cold pools. The best results are obtained when the largest group size is used in the HEF experiment. With this improved analysis, the forecast error is reduced for most variables and levels. The dynamical and thermal distributions of HEF experiments are found to better promote the development of the supercell storm which helps to improve the forecast reflectivity in terms of location, intensity, and area coverage. This suggests the potential of HEF localization for an EnKF radar DA. A larger group size for this method is expected to lead to improved analysis and forecast results compared with the regular GC localization method.

Advances in Severe Convection Research and Operation in China

This article reviews the advances in severe convection research and operation in China during the past several decades. The favorable synoptic situations for severe convective weather (SCW), the major organization modes of severe convective storms (SCSs), the favorable environmental conditions and characteristics of weather radar echoes and satellite images of SCW and SCSs, and the forecasting and nowcasting techniques of SCW, are emphasized. As a whole, Chinese scientists have achieved a profound understanding of the synoptic patterns, organization, and evolution characteristics of SCW from radar and satellite observations, and the mechanisms of different types of convective weather in China. Specifically, in-depth understanding of the multiple types of convection triggers, along with the environmental conditions, structures and organization modes, and maintenance mechanisms of supercell storms and squall lines, has been obtained. The organization modes and climatological distributions of mesoscale convective systems and different types of SCW, and the multiscale characteristics and formation mechanisms of large hail, tornadoes, downbursts, and damaging convective wind gusts based on radar, satellite, and lightning observations, as well as the related features from damage surveys, are elucidated. In terms of operational applications, different types of identification and mesoanalysis techniques, and various forecasting and nowcasting techniques using methods such as the “ingredients-based” and deep learning algorithms, have been developed. As a result, the performance of operational SCW forecasts in China has been significantly improved.

A Preliminary Polarimetric Radar Comparison of Pretornadic and Nontornadic Supercell Storms

Abstract Supercell thunderstorms produce a variety of hazards, including tornadoes. A supercell will often exist for some time prior to producing a tornado, while other supercells never become tornadic. In this study, a series of hypotheses is tested regarding the ability of S-band polarimetric radar fields to distinguish pretornadic from nontornadic supercell storms. Several quantified polarimetric radar metrics are examined that are related to storm inflow, updraft, and hailfall characteristics in samples of 19–30 pretornadic and 18–31 nontornadic supercells. The results indicate that pretornadic supercells are characterized by smaller hail extent and echo appendages with larger mean drop size. Additionally, differential reflectivity ZDR column size is larger and less variable in the pretornadic storms in the 25–30 min prior to initial tornadogenesis. Many of the results indicate relatively small polarimetric differences that will likely be difficult to translate to operational use. Hail extent and ZDR column size, however, may exhibit operationally useful differences between pretornadic and nontornadic supercells.

Assimilating polarimetric radar data with an ensemble Kalman filter: OSSEs with a tornadic supercell storm simulated with a two‐moment microphysics scheme

AbstractThe impact of assimilating differential reflectivity ZDR in addition to reflectivity (ZH) and radial velocity (Vr) from a polarimetric radar on the analysis of a tornadic supercell storm using an ensemble Kalman filter (EnKF) is studied in an observing system simulation experiment (OSSE) framework assuming a perfect forecast model. A double‐moment microphysics scheme is used to allow for proper simulation of polarimetric signatures. Root‐mean‐square errors of analysed state variables are calculated and the structure and intensity of analysed fields and derived quantities are examined. Compared to the baseline experiment assimilating radial velocity and reflectivity only, the assimilation of additional ZDR further reduces the errors of all state variables. The analysed hydrometeor fields are improved in both pattern and intensity distributions. Polarimetric signatures including ZDR and KDP columns, and ZDR arc in the supercell, are much better reproduced. Sensitivity experiments are performed that exclude the updating of hydrometeor number concentrations by ZDR or of state variables not directly linked to ZDR via observation operators. The results show that if number concentrations are not updated together with the mixing ratios, most of the benefit of assimilating ZDR is lost. Among other state variables, the updating of water vapour mixing ratio qv has the largest positive impact while the impact of updating vertical wind w comes in second. The updating of horizontal wind components or temperature has a much smaller but still noticeable impact. Reliable flow‐dependent cross‐covariances among the state variables and observation prior as derived from the forecast ensemble and used in EnKF are clearly very beneficial.

Analysis of Hail Processes Caused by a Supercell Storm

Analysis of Hail Processes Caused by a Supercell Storm

2020年贵阳机场一次超级单体风暴天气诊断分析

2020年贵阳机场一次超级单体风暴天气诊断分析

Microphysical and Dynamical Effects of Mixed-Phase Hydrometeors in Convective Storms Using a Bin Microphysics Model: Melting

AbstractThe dynamics of convective systems are inherently linked to microphysical processes through phase changes that result in warming or cooling. This is especially true of near-surface cooling via evaporation and melting of falling hydrometeors. In most numerical simulations, the melting of frozen hydrometeors (e.g., hail, graupel, snow) is computed within parameterized bulk microphysics schemes, many of which lack the ability to accurately represent mixed-phase hydrometeors (i.e., partially melted ice), which can affect hydrometeor sedimentation, melting, and evaporation of shed drops. To better understand the microphysical and dynamical effects of melting in convective storms, a bin microphysics scheme was used in the Weather Research and Forecasting Model for two idealized cases: a supercell storm and a squall line. Physically based predicted liquid fraction, instantaneous melting, and instantaneous shedding schemes were used to examine the role and importance of melting hydrometeors for these two storm modes. The results suggest that the amount of precipitation is dependent on the representation of melting. Moreover, the dynamic and thermodynamic characteristics of the simulated storms are found to differ substantially between the melting scenarios, resulting in varied storm system evolution; these differences are found to be dependent on the ambient aerosol concentration, although the differences induced by changing the representation of melting generally outweigh those of changing the aerosol loading. The results highlight the large role of melting in convective storm characteristics and suggest that further model improvements are needed in the near future.

The College Park, Maryland, Tornado of 24 September 2001

The 24 September 2001 College Park, Maryland, tornado was a long-track and strong tornado that passed within a close range of two Doppler radars. It was the third in a series of three tornadoes associated with a supercell storm that developed in Stafford County, Virginia, and initiated 3–4 km southwest of College Park and dissipated near Columbia, Howard County. The supercell tracked approximately 120 km and lasted for about 126 min. This study presents a synoptic and mesoscale overview of favorable conditions and forcing mechanisms that resulted in the severe convective outbreak associated with the College Park tornado. The results show many critical elements of the tornadic event, including a negative-tilted upper-level trough over the Ohio Valley, a jet stream with moderate vertical shear, a low-level warm, moist tongue of the air associated with strong southerly flow over south-central Maryland and Virginia, and significantly increased convective available potential energy (CAPE) during the late afternoon hours. A possible role of the urban heat island effects from Washington, DC, in increasing CAPE for the development of the supercell is discussed. Satellite imagery reveals the banded convective morphology with high cloud tops associated with the supercell that produced the College Park tornado. Operational WSR-88D data exhibit a high reflectivity “debris ball” or tornadic debris signature (TDS) within the hook echo, the evolution of the parent storm from a supercell structure to a bow echo, and a tornado cyclone signature (TCS). Many of the mesoscale features could be captured by contemporary numerical model analyses. This study concludes with a discussion of the effectiveness of the coordinated use of satellite and radar observations in the operational environment of nowcasting severe convection.

Lower-Tropospheric Influences on the Timing and Intensity of Afternoon Severe Convection over Modest Terrain in a Convection-Allowing Ensemble

AbstractA 50-member convection-allowing ensemble is used to examine effects of daytime PBL evolution and ambient flow interacting with modest terrain features on convection initiation (CI) in the lee of the Rocky Mountains. The examined case (4 June 2015) has isolated supercell storms that initiate during mid- to late afternoon along the northern portion of the Palmer Lake Divide, which is a ~0.5-km-deep zonally oriented terrain feature in east-central Colorado that extends eastward from the Rocky Mountains. To diagnose factors most crucial to storm development, two 10-member subensembles are constructed from the full 50-member ensemble. One subensemble (STRONG) has storm locations with mature storm intensities, and average timing of CI similar to that observed. The other subensemble (WEAK) has fewer storms, with generally weaker intensity, and delayed CI. Environmental composites constructed from these subensembles reveal a stronger surface horizontal convergence zone and moisture gradient in STRONG, resulting from 2–3.5 m s−1 stronger southerly winds on the south flank of the convergence zone. The stronger southerlies result from accelerated PBL growth and momentum mixing in the presence of strong low-to-midtropospheric vertical shear, which is facilitated by reduced above-PBL static stability in the composite STRONG initial condition. Stronger time-averaged low-to-midtropospheric upward motion coincides with the surface convergence zone in STRONG, and individual CI locations occur at the northeastern edge of the composite vertical motion maximum. Trajectory analysis with STRONG members confirms that the CI locations are consistent with large vertical displacements, and corresponding relative humidity increases leading to decreases in convective inhibition, as the southerly airstream ascends across the convergence zone.

Impact of Ground-Based Remote Sensing Boundary Layer Observations on Short-Term Probabilistic Forecasts of a Tornadic Supercell Event

Abstract Due to lack of high spatial and temporal resolution boundary layer (BL) observations, the rapid changes in the near-storm environment are not well represented in current convective-scale numerical models. Better representation of the near-storm environment in model initial conditions will likely further improve the forecasts of severe convective weather. This study investigates the impact of assimilating high temporal resolution BL retrievals from two ground-based remote sensing instruments for short-term forecasts of a tornadic supercell event on 13 July 2015 during the Plains Elevated Convection At Night field campaign. The instruments are the Atmospheric Emitted Radiance Interferometer (AERI) that retrieves thermodynamic profiles and the Doppler lidar (DL) that measures horizontal wind profiles. Six sets of convective-scale ensemble data assimilation (DA) experiments are performed: two control experiments that assimilate conventional and WSR-88D radar observations using either relaxation-to-prior-spread (RTPS) or the adaptive inflation (AI) technique and four experiments similar to the control but that assimilate either DL or AERI or both observations in addition to all other observations that are in the control experiments. Results indicate a positive impact of AERI and DL observations in forecasting convective initiation (CI) and early evolution of the supercell storm. The experiment that employs the AI technique to assimilate BL observations in DA enhances the humidity in the near-storm environment and low-level convergence, which in turn helps forecasting CI. The forecast improvement is most pronounced during the first ~3 h. Results also indicate that the AERI observations have a larger impact compared to DL in predicting CI.

A rapid identification and warning method for severe weather via Doppler radar based on an improved TITAN algorithm

An adaptive fast-recognition warning algorithm for severe weather using ground-based Doppler radar and Tropical Rainfall Measuring Mission (TRMM) sensor data is proposed for different seasons, regions and topography conditions in the East and South China Seas. An improved regional segmentation method and the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm were applied to identify three-dimensional strong storm cells and their physical features. Multiple logistic linear regression was used to establish a probabilistic warning model for strong convective weather, such as hail and lightning. Doppler radar identification and warning experiments were carried out for a strong squall line near the East China Sea and a supercell storm near the South China Sea. The experimental results showed that the proposed method has higher identification accuracy based on the azimuth and distance than the traditional algorithm. Moreover, the false negative and false report rates of the proposed method are low, which helps to quickly identify and warn against severe weather and protect lives and property.

Mesoscale characteristics of a rare severe hailstorm event

This study analyzed the environmental field, physical quantify fields, convection parameters and radar echo characteristics of a severe hailstorm that occurred on June 18, 2013, due to a mesoscale convective system. The analysis was performed using ground meteorological data, sounding data and GFS-ANL (gfs 0.5° × 0.5°) reanalysis data in combination with satellite cloud imagery and Doppler radar observations. The results showed that this rare hailstorm event was generated under the influence of a weakening and eastwardly moving low vortex over Lake Balkhash; and a distinct shear line in the middle and lower troposphere over the western South Xinjiang. Strong vertical wind shears, deep conditionally unstable stratification, ample water vapor in the lower troposphere and suitable wet-bulb zero heights are important contributors to the formation of severe hailstorms. An increase in convective available potential energy (CAPE) and a decrease in the lifting index are strong indicators of a severe hailstorm. For the studied hailstorm event, the time corresponding to the maximum value of the normalized CAPE was close to the timing of the actual hailstorm. The severe hailstorm, consisting of multiple supercells, exhibited notable characteristics of hail clouds and supercells. The formation, disappearance and replacement of strong convection cells occurred while the supercells were sustained. The tracking and forecasting results obtained using the Thunderstorm Identification, Tracking, Analysis and Nowcasting system are found to be, to a certain extent, able to indicate of the direction of the supercell storms during this severe hailstorm event.

Ensemble Kalman Filter Assimilation of Polarimetric Radar Observations for the 20 May 2013 Oklahoma Tornadic Supercell Case

AbstractReal polarimetric radar observations are directly assimilated for the first time using the ensemble Kalman filter (EnKF) for a supercell case from 20 May 2013 in Oklahoma. A double-moment microphysics scheme and advanced polarimetric radar observation operators are used together to estimate the model states. Lookup tables for the observation operators are developed based on T-matrix scattering amplitudes for all hydrometeor categories, which improve upon previous curved-fitted approximations of T-matrix scattering amplitudes or the Rayleigh approximation. Two experiments are conducted: one assimilates reflectivity (Z) and radial velocity (Vr) (EXPZ), and one assimilates in addition differential reflectivity (ZDR) below the observed melting level at ~2-km height (EXPZZDR). In the EnKF analyses, EXPZZDR exhibits a ZDR arc that better matches observations than EXPZ. EXPZZDR also has higher ZDR above 2 km, consistent with the observed ZDR column. Additionally, EXPZZDR has an improved estimate of the model microphysical states. Specifically, the rain mean mass diameter (Dnr) in EXPZZDR is higher in the ZDR arc region and the total rain number concentration (Ntr) is lower downshear in the forward flank than EXPZ when compared to values retrieved from the polarimetric observations. Finally, a negative gradient of hail mean mass diameter (Dnh) is found in the right-forward flank of the EXPZZDR analysis, which supports previous findings indicating that size sorting of hail, as opposed to rain, has a more significant impact on low-level polarimetric signatures. This paper represents a proof-of-concept study demonstrating the value of assimilating polarimetric radar data in improving the analysis of features and states related to microphysics in supercell storms.

Prediction of an EF4 supercell tornado in Funing, China: Resolution dependency of simulated tornadoes and their structures

An EF4 supercell tornado that occurred on 23 June 2016 in Funing, China is simulated using the WRF model. Five nested forecast experiments are run, with the horizontal grid spacing of the inner-most nest being 4000, 1333, 444, 148, and 49 m, respectively. All experiments reproduce the general characteristics of the observed supercell storm, but tornado-like vortex does not develop until the grid spacing is 444 m or less. The tornadoes on the 444, 148 and 49 m grids reach EF1, EF2 and EF3 intensities, respectively. The tornado vortex simulated on the 444 m grid tends to maintain a one-cell structure, while a ring of high-vorticity develops during the mature stage of the tornado vortex on the 148 m grid leading to a two-cell structure. On the 49 m grid, microscale vortices along the outflow boundary merge into and help organize the main tornado vortex while multiple ‘suction vortices’ develop later along the high-vorticity ring leading to a multi-vortex tornado. These sub-vortices create localized regions of intense winds due to the super-positioning of the sub-vortex and main vortex circulations and the system translation speed. Sub-vortices also create irregular strong surface wind patterns with localized ‘damage cores’, broadening the tornadic wind swath; these are consistent with the Funing tornado damage survey. Based on the results, we recommend a horizontal grid spacing of at least 500 m for real-time warn-on-forecast applications in order to capture tornado-like vortices while for tornado dynamics, prediction and predictability studies 50 m or less is recommended.

Mesoscale Convective Vortex that Causes Tornado-Like Vortices over the Sea: A Potential Risk to Maritime Traffic

AbstractStrong gusty winds in a weak maritime extratropical cyclone (EC) over the Tsushima Strait in the southwestern Sea of Japan capsized several fishing boats on 1 September 2015. A C-band Doppler radar recorded a spiral-shaped reflectivity pattern associated with a convective system and a Doppler velocity pattern of a vortex with a diameter of 30 km [meso-β-scale vortex (MBV)] near the location of the wreck. A high-resolution numerical simulation with horizontal grid interval of 50 m successfully reproduced the spiral-shaped precipitation pattern associated with the MBV and tornado-like strong vortices that had a maximum wind speed exceeding 50 m s−1 and repeatedly developed in the MBV. The simulated MBV had a strong cyclonic circulation comparable to a mesocyclone in a supercell storm. Unlike mesocyclones associated with a supercell storm, however, its vorticity was largest near the surface and decreased monotonically with increasing height. The strong vorticity of the MBV near the surface originated from a horizontal shear line in the EC. The tornado-like vortices developed in a region of strong horizontal shear in the western part of the MBV, suggesting that they were caused by a shear instability.

Ray Curvature on a Flat Earth for Computing Virtual WSR-88D Signatures of Simulated Supercell Storms

Abstract Two accepted postulates for applications of ground-based weather radars are that Earth’s surface is a perfect sphere and that all the rays launched at low-elevation angles have the same constant small curvature. To accommodate a straight vertically launched ray, we amend the second postulate by making the ray curvature dependent on the cosine of the launch angle. A standard atmospheric stratification determines the ray-curvature value at zero launch angle. Granted this amended postulate, we develop exact formulas for ray height, ground range, and ray slope angle as functions of slant range and launch angle on the real Earth. Standard practice assumes a hypothetical equivalent magnified earth, for which the rays become straight while ray height above radar level remains virtually the same function of the radar coordinates. The real-Earth and equivalent-earth formulas for height agree to within 1 m. Our ultimate goal is to place a virtual Doppler radar within a numerical or analytical model of a supercell and compute virtual signatures of simulated storms for development and testing of new warning algorithms. Since supercell models have a flat lower boundary, we must first compute the ray curvature that preserves the height function as the earth curvature tends to zero. Using an approximate height formula, we find that keeping planetary curvature minus the ray curvature at zero launch angle constant preserves ray height to within 5 m. For standard refraction the resulting ray curvature is negative, indicating that rays bend concavely upward relative to a flat earth.

Evaluation of Supercell Storm Triggering Factors Based on a Cloud Resolving Model Simulation

An attempt has been made in this study to examine the conditional instability parameters in the selected area and to determine the main ingredients responsible for initiation and evolution of supercell storm over Skopje, Macedonia on 6 August 2016. WRF model forecasts provide the basic meteorological parameters for cloud model initialization and the detail information about atmospheric instability potential as triggering factor for severe convection. The cloud model simulation has been performed with very fine spatial and temporal resolution capable to resolve the detail aspects of convection. The results utilizing this novel method suggest that, upper level lifting, moisture advection, large CAPE, near surface convergence and increased potential vortices in the selected area play substantial role in early assessment of the atmospheric status, convective instability and storm potential. In addition the directional wind shear (veering) at the near surface layer, high storm helicity index, differential heating induced by the strong local forcing environment serve as triggering factors for initiation of supercell storm with rotational updrafts-mesocyclone. The cloud model simulation with fine resolution allows more detail insight into the storm dynamics and the mechanism of generation of rotational updrafts and mesocyclone, a hook echo signature and the presence of bounded weak echo region as ingredients for supercellular structure and evolution. The overshooting top of 15 km, peak updraft speed of 40 m/s, wind gust of 35 m/s and reflectivity which exceeds 70 dBZ indicates to the occurrence of a very severe storm. A longer live cycle of storm and the intense water production, with extreme rainfall rate of 38 mm/5 min, contribute to formation of excessive torrential rainfall and local catastrophic flooding.

Direct Assimilation of Radar Reflectivity Data Using 3DVAR: Treatment of Hydrometeor Background Errors and OSSE Tests

Despite the well-known importance of background error covariance in data assimilation, not much study has been focused on its impact on the assimilation of radar reflectivity within a three-dimensional variational (3DVar) framework. In this study, it is shown that unphysical analysis increments of hydrometeors are produced when using vertically homogeneous background error variance. This issue cannot be fully solved by using the so-called hydrometeor classification in the reflectivity observation operator. Alternatively, temperature-dependent background error profiles for hydrometeor control variables are proposed. With such a treatment, the vertical background error profiles are specified to be temperature dependent, allowing for more physical partitioning of radar-observed precipitation information among the liquid and ice hydrometeors. The 3DVar analyses using our treatment are compared with those using constant background error or “hydrometeor classification” through observing system simulation experiments with a simulated supercell storm. Results show that 1) 3DVar with constant hydrometeor background errors produces unphysical rainwater at the high levels and unphysical snow at the low levels; 2) the hydrometeor classification approach reduces unphysical rainwater and snow at those levels, but the analysis increments are still unphysically spread in the vertical by the background error covariance when the vertically invariant background errors are used; and 3) the temperature-dependent background error profiles enable physically more reasonable analyses of liquid and ice hydrometeors from reflectivity assimilation.

A beautiful scene of rainbows and hailcores from a supercell storm

WeatherVolume 73, Issue 7 p. E2-E2 Inside Cover Photograph A beautiful scene of rainbows and hailcores from a supercell storm First published: 03 July 2018 https://doi.org/10.1002/wea.3298Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume73, Issue7July 2018Pages E2-E2 RelatedInformation