Colorado Plowable Hailstorms: Synoptic Weather, Radar, and Lightning Characteristics

Abstract Synoptic weather, S-band dual-polarization radar, and total lightning observations are analyzed from four thunderstorms that produced “plowable” hail accumulations of 15–60 cm in localized areas of the Colorado Front Range. Results indicate that moist, relatively slow (5–15 m s−1) southwesterly-to-westerly flow at 500 hPa and postfrontal low-level upslope flow, with 2-m dewpoint temperatures of 11°–19°C at 1200 LST, were present on each plowable hail day. This pattern resulted in column-integrated precipitable water values that were 132%–184% of the monthly means and freezing-level heights that were 100–700 m higher than average. Radar data indicate that between one and three maxima in reflectivity Z (68–75 dBZ) and 50-dBZ echo-top height (11–15 km MSL) occurred over the lifetime of each hailstorm. These maxima, which imply an enhancement in updraft strength, resulted in increased graupel and hail production and accumulating hail at the surface within 30 min of the highest echo tops. The hail core had Z ~ 70 dBZ, differential reflectivity ZDR from 0 to −4 dB, and correlation coefficient ρHV of 0.80–0.95. Time–height plots reveal that these minima in ZDR and ρHV gradually descended to the surface after originating at heights of 6–10 km MSL ~15–60 min prior to accumulating hailfall. Hail accumulations estimated from the radar data pinpoint the times and locations of plowable hail, with depths greater than 5 cm collocated with the plowable hail reports. Three of the four hail events were accompanied by lightning flash rates near the maximum observed thus far within the thunderstorm.

Download Full-text

Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector–Derived Flow

Monthly Weather Review ◽

10.1175/mwr-d-18-0119.1 ◽

2018 ◽

Vol 146 (10) ◽

pp. 3461-3480 ◽

Cited By ~ 10

Author(s):

Jason M. Apke ◽

John R. Mecikalski ◽

Kristopher Bedka ◽

Eugene W. McCaul ◽

Cameron R. Homeyer ◽

...

Keyword(s):

Doppler Radar ◽

Deep Convection ◽

Motion Vector ◽

Three Dimensional ◽

Radar Data ◽

Severe Weather ◽

Lightning Flash ◽

Rapid Scan ◽

Total Lightning ◽

The Relationship

Abstract Rapid acceleration of cloud-top outflow near vigorous storm updrafts can be readily observed in Geostationary Operational Environmental Satellite-14 (GOES-14) super rapid scan (SRS; 60 s) mode data. Conventional wisdom implies that this outflow is related to the intensity of updrafts and the formation of severe weather. However, from an SRS satellite perspective, the pairing of observed expansion and updraft intensity has not been objectively derived and documented. The goal of this study is to relate GOES-14 SRS-derived cloud-top horizontal divergence (CTD) over deep convection to internal updraft characteristics, and document evolution for severe and nonsevere thunderstorms. A new SRS flow derivation system is presented here to estimate storm-scale (<20 km) CTD. This CTD field is coupled with other proxies for storm updraft location and intensity such as overshooting tops (OTs), total lightning flash rates, and three-dimensional flow fields derived from dual-Doppler radar data. Objectively identified OTs with (without) matching CTD maxima were more (less) likely to be associated with radar-observed deep convection and severe weather reports at the ground, suggesting that some OTs were incorrectly identified. The correlation between CTD magnitude, maximum updraft speed, and total lightning was strongly positive for a nonsupercell pulse storm, and weakly positive for a supercell with multiple updraft pulses present. The relationship for the supercell was nonlinear, though larger flash rates are found during periods of larger CTD. Analysis here suggests that combining CTD with OTs and total lightning could have severe weather nowcasting value.

Download Full-text

Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings

Weather and Forecasting ◽

10.1175/waf-d-13-00075.1 ◽

2014 ◽

Vol 29 (3) ◽

pp. 623-638 ◽

Cited By ~ 5

Author(s):

Patrick C. Kennedy ◽

Steven A. Rutledge ◽

Brenda Dolan ◽

Eric Thaler

Keyword(s):

Radar Data ◽

Front Range ◽

Dual Polarization ◽

Remotely Sensed Data ◽

Colorado State University ◽

Freezing Level ◽

Severe Thunderstorms ◽

Fort Collins ◽

Single Polarization ◽

Real Time Identification

Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.

Download Full-text

Random Forest Model to Assess Predictor Importance and Nowcast Severe Storms using High-Resolution Radar–GOES Satellite–Lightning Observations

Monthly Weather Review ◽

10.1175/mwr-d-19-0274.1 ◽

2021 ◽

Author(s):

John R. Mecikalski ◽

Thea N. Sandmæl ◽

Elisa M. Murillo ◽

Cameron R. Homeyer ◽

Kristopher M. Bedka ◽

...

Keyword(s):

Great Plains ◽

Random Forests ◽

Motion Vector ◽

Radar Data ◽

Lightning Flash ◽

Severe Storms ◽

Tornado Warnings ◽

Predictor Importance ◽

Scan Data ◽

Total Lightning

AbstractFew studies have assessed combined satellite, lightning, and radar databases to diagnose severe storm potential. The research goal here is to evaluate next-generation, 60-second update frequency geostationary satellite and lightning information with ground-based radar to isolate which variables, when used in concert, provide skillful discriminatory information for identifying severe (hail ≥2.5 cm in diameter, winds ≥25 m s–1, tornadoes) versus non-severe storms. The focus of this study is predicting severe thunderstorm and tornado warnings. A total of 2,004 storms in 2014–2015 were objectively tracked with 49 potential predictor fields related to May, daytime Great Plains convective storms. All storms occurred when 1-min Geostationary Operational Environmental Satellite (GOES)–14 “super rapid scan” data were available. The study used three importance methods to assess predictor importance related to severe warnings, and random forests to provide a model and skill evaluation measuring the ability to predict severe storms. Three predictor importance methods show that GOES mesoscale atmospheric motion vector derived cloud-top divergence and above anvil cirrus plume presence provide the most satellite-based discriminatory power for diagnosing severe warnings. Other important fields include Earth Networks Total Lightning flash density, GOES estimated cloud-top vorticity, and overshooting-top presence. Severe warning predictions are significantly improved at the 95% confidence level when a few important satellite and lightning fields are combined with radar fields, versus when only radar data are used in the random forests model. This study provides a basis for including satellite and lightning fields within machine-learning models to help forecast severe weather.

Download Full-text

Evaluation of Different Storm Parameters as the Proxies for Gridded Total Lightning Flash Rates: A Convection-Allowing Model Study

Atmosphere ◽

10.3390/atmos12010095 ◽

2021 ◽

Vol 12 (1) ◽

pp. 95

Author(s):

Xinyao Qian ◽

Haoliang Wang

Keyword(s):

Data Assimilation ◽

Mesoscale Convective System ◽

Radar Data ◽

Skill Score ◽

Convective System ◽

Test Case ◽

Lightning Flash ◽

Simulation Accuracy ◽

Mesoscale Convective ◽

Total Lightning

Lightning simulation is important for a variety of applications, including lightning forecast, atmospheric chemical simulation, and lightning data assimilation. In this study, the potential of five storm parameters (graupel volume, precipitation ice mass, radar echo volume, maximum updraft, and updraft volume) to be used as the proxy for the diagnosis of gridded total lightning flash rates has been investigated in a convection-allowing model. A mesoscale convective system occurred in the Guangdong province of China was selected as the test case. Radar data assimilation was used to improve the simulation accuracy of the convective clouds, hence providing strong instantaneous correlations between observed and simulated storm signatures. The areal coverage and magnitude of the simulated lightning flash rates were evaluated by comparing to those of the total lightning observations. Subjective and the Fractions Skill Score (FSS) evaluations suggest that all the five proxies tested in this study are useful to indicate general tendencies for the occurrence, region, and time of lightning at convection-allowing scale (FSS statistics for the threshold of 1 flash per 9 km2 per hour were around 0.7 for each scheme). The FSS values were decreasing as the lightning flash rate thresholds used for FSS computation increased for all the lightning diagnostic schemes with different proxies. For thresholds from 1 to 3 and 16 to 20 flashes per 9 km2 per hour, the graupel contents related schemes achieved higher FSS values compared to the other three schemes. For thresholds from 5 to 15 flashes per 9 km2 per hour, the updraft volume related scheme yielded the largest FSS. When the thresholds of lightning flash rates were greater than 13 flashes per 9 km2 per hour, the FSS values were below 0.5 for all the lightning diagnostic schemes with different proxies.

Download Full-text

Lightning Data Assimilation Scheme in a 4DVAR System and its Impact on Very-Short-Term Convective Forecasting

Monthly Weather Review ◽

10.1175/mwr-d-19-0396.1 ◽

2020 ◽

Author(s):

Xian Xiao ◽

Juanzhen Sun ◽

Xiushu Qie ◽

Zhuming Ying ◽

Lei Ji ◽

...

Keyword(s):

Vertical Velocity ◽

Doppler Radar ◽

Analysis Data ◽

Radar Data ◽

Lightning Flash ◽

Short Term ◽

Distance Weighted ◽

Dynamical Consistency ◽

Analysis System ◽

Total Lightning

AbstractA proof-of-concept method for the assimilation of total lightning observations in the 4DVAR framework is proposed and implemented into the Variational Doppler Radar Analysis System (VDRAS). Its performance is evaluated for the very-short-term precipitation forecasts of a localized convective event over northeastern China. The lightning DA scheme assimilated pseudo observations for vertical velocity fields derived from observed total lightning rates and statistically computed vertical velocity profile from VDRAS analysis data. To reduce representative errors of the derived vertical velocity, a distance-weighted horizontal interpolation is applied to the input data prior to the DA. The case study reveals that although 0–2 hour precipitation nowcasts are improved by assimilating lightning data alone compared to CTRL (no radar or lightning) and RAD (radar only), better results are obtained when the lightning data are assimilated with radar data simultaneously. The assimilation of both data sources results in improved dynamical consistency with enhanced updraft and latent heat as well as improved moisture distributions. Additional experiments are conducted to evaluate the sensitivity of the combined DA scheme to varied vertical velocity profiles, radii of horizontal interpolation, binning time intervals, and relationships used to estimate the maximum vertical velocity from lightning flash rates. It is shown that the scheme is robust to these variations with both radar and lightning assimilated data.

Download Full-text

Numerical Simulations of Lightning and Storm Charge of the 29–30 May 2004 Geary, Oklahoma, Supercell Thunderstorm Using EnKF Mobile Radar Data Assimilation

Monthly Weather Review ◽

10.1175/mwr-d-13-00403.1 ◽

2014 ◽

Vol 142 (11) ◽

pp. 3977-3997 ◽

Cited By ~ 19

Author(s):

Kristin M. Calhoun ◽

Edward R. Mansell ◽

Donald R. MacGorman ◽

David C. Dowell

Keyword(s):

Data Assimilation ◽

Radar Data ◽

Main Body ◽

Lightning Flash ◽

Wind Fields ◽

Propagation Length ◽

Kinematic Evolution ◽

Supercell Storm ◽

Total Lightning ◽

Radar Data Assimilation

Abstract Results from simulations are compared with dual-Doppler and total lightning observations of the 29–30 May 2004 high-precipitation supercell storm from the Thunderstorm Electrification and Lightning Experiment (TELEX). The simulations use two-moment microphysics with six hydrometeor categories and parameterizations for electrification and lightning while employing an ensemble Kalman filter for mobile radar data assimilation. Data assimilation was utilized specifically to produce a storm similar to the observed for ancillary analysis of the electrification and lightning associated with the supercell storm. The simulated reflectivity and wind fields well approximated that of the observed storm. Additionally, the simulated lightning flash rates were very large, as was observed. The simulation reveals details of the charge distribution and dependence of lightning on storm kinematics, characteristics that could not be observed directly. Storm electrification was predominately confined to the updraft core, but the persistence of both positive and negative charging of graupel in this region, combined with the kinematic evolution, limited the extent of charged areas of the same polarity. Thus, the propagation length of lightning flashes in this region was also limited. Away from the updraft core, regions of charge had greater areal extent, allowing flashes to travel farther without termination due to unfavorable charge potential. Finally, while the simulation produced the observed lightning holes and high-altitude lightning seen in the observations, it failed to produce the observed lightning initiations (or even lightning channels) in the distant downstream anvil as seen in the observed storm. Instead, the simulated lightning was confined to the main body of the storm.

Download Full-text

Convection during the North American Monsoon across Central and Southern Arizona: Applications to Operational Meteorology

Weather and Forecasting ◽

10.1175/waf-d-15-0097.1 ◽

2017 ◽

Vol 32 (2) ◽

pp. 377-390 ◽

Cited By ~ 2

Author(s):

Jaret W. Rogers ◽

Ariel E. Cohen ◽

Lee B. Carlaw

Keyword(s):

North American ◽

Precipitable Water ◽

North American Monsoon ◽

Lightning Flash ◽

Severe Thunderstorm ◽

Independent Dataset ◽

The North ◽

Forecast Models ◽

Total Lightning ◽

The Relationship

Abstract This comprehensive analysis of convective environments associated with thunderstorms affecting portions of central and southern Arizona during the North American monsoon focuses on both observed soundings and mesoanalysis parameters relative to lightning flash counts and severe-thunderstorm reports. Analysis of observed sounding data from Phoenix and Tucson, Arizona, highlights several moisture and instability parameters exhibiting moderate correlations with 24-h, domain-total lightning and severe thunderstorm counts, with accompanying plots of the precipitable water, surface-based lifted index, and 0–3-km layer mixing ratio highlighting the relationship to the domain-total lightning count. Statistical techniques, including stepwise, multiple linear regression and logistic regression, are applied to sounding and gridded mesoanalysis data to predict the domain-total lightning count and individual gridbox 3-h-long lightning probability, respectively. Applications of these forecast models to an independent dataset from 2013 suggest some utility in probabilistic lightning forecasts from the regression analyses. Implementation of this technique into an operational forecast setting to supplement short-term lightning forecast guidance is discussed and demonstrated. Severe-thunderstorm-report predictive models are found to be less skillful, which may partially be due to substantial population biases noted in storm reports over central and southern Arizona.

Download Full-text