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  • Author or Editor: Kristin M. Calhoun x
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Stephanie A. Weiss
,
Donald R. MacGorman
, and
Kristin M. Calhoun

Abstract

This study uses data from the Oklahoma Lightning Mapping Array (OK-LMA), the National Lightning Detection Network, and the Norman, Oklahoma (KOUN), prototype Weather Surveillance Radar-1988 Doppler (WSR-88D) radar to examine the evolution and structure of lightning in the anvils of supercell storms as they relate to storm dynamics and microphysics. Several supercell storms within the domain of the OK-LMA were examined to determine whether they had lightning in the anvil region, and if so, the time and location of the initiation of the anvil flashes were determined. Every warm-season supercell storm had some flashes that were initiated in or near the stronger reflectivities of the parent storm and propagated 40–70 km downstream to penetrate well into the anvil. Some supercell storms also had flashes that were initiated within the anvil itself, 40–100 km beyond the closest 30-dBZ contour of the storm. These flashes were typically initiated in one of three locations: 1) coincident with a local reflectivity maximum, 2) between the uppermost storm charge and a screening-layer charge of opposite polarity near the cloud boundary, or 3) in a region in which the anvils from two adjoining storms intersected. In some storms, anvil flashes struck ground beneath a reflectivity maximum in which reflectivity ≥20 dBZ had extended below the 0°C isotherm, possibly leading to the formation of embedded convection. This relationship may be useful for identifying regions in which there is a heightened risk for cloud-to-ground strikes beneath anvil clouds. In one storm, however, anvil lightning struck ground even though this reflectivity signature was absent.

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Kevin C. Thiel
,
Kristin M. Calhoun
, and
Anthony E. Reinhart

Abstract

The recently deployed GOES-R series Geostationary Lightning Mapper (GLM) provides forecasters with a new, rapidly updating lightning data source to diagnose, forecast, and monitor atmospheric convection. Gridded GLM products have been developed to improve operational forecast applications, with variables including flash extent density (FED), minimum flash area (MFA), and total optical energy (TOE). While these gridded products have been evaluated, there is a continual need to integrate these products with other datasets available to forecasters such as radar, satellite imagery, and ground-based lightning networks. Data from the Advanced Baseline Imager (ABI), Multi-Radar Multi-Sensor (MRMS) system, and one ground-based lightning network were compared against gridded GLM imagery from GOES-East and GOES-West in case studies of two supercell thunderstorms, along with a bulk study from 13 April to 31 May 2019, to provide further validation and applications of gridded GLM products from a data fusion perspective. Increasing FED and decreasing MFA corresponded with increasing thunderstorm intensity from the perspective of ABI infrared imagery and MRMS vertically integrated reflectivity products, and was apparent for more robust and severe convection. Flash areas were also observed to maximize between clean-IR brightness temperatures of 210–230 K and isothermal reflectivity at −10°C of 20–30 dBZ. TOE observations from both GLMs provided additional context of local GLM flash rates in each case study, due to their differing perspectives of convective updrafts.

Significance Statement

The Geostationary Lightning Mapper (GLM) is a lightning sensor on the current generation of U.S. weather satellites. This research shows how data from the space-based lightning sensor can be combined with radar, satellite imagery, and ground-based lightning networks to improve how forecasters monitor thunderstorms and issue warnings for severe weather. The rate of GLM flashes detected and the area they cover correspond well with radar and satellite signatures, especially in cases of intense and severe thunderstorms. When the GLM observes the same thunderstorm from the GOES-East and GOES-West satellites, the optical energy (brightness) of the flashes may help forecasters interpret the types of flashes observed from each sensor.

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Darrel M. Kingfield
,
Kristin M. Calhoun
,
Kirsten M. de Beurs
, and
Geoffrey M. Henebry

Abstract

Five years of 0.01° latitude × 0.01° longitude multiradar multisensor grids of composite reflectivity and vertically integrated signals from the maximum expected size of hail (MESH) and vertically integrated liquid (VIL) were created to examine the role of city size on thunderstorm occurrence and strength around four cities: Dallas–Fort Worth, Texas; Minneapolis–St. Paul, Minnesota; Oklahoma City, Oklahoma; and Omaha, Nebraska. A storm-tracking algorithm identified thunderstorm areas every minute and connected them together to form tracks. These tracks defined the upwind and downwind regions around each city on a storm-by-storm basis and were analyzed in two ways: 1) by sampling the maximum value every 10 min and 2) by accumulating the spatial footprint over its lifetime. Beyond examining all events, a subset of events corresponding to favorable conditions for urban modification was explored. This urban favorable (UF) subset consisted of nonsupercells occurring in the late afternoon/evening in the meteorological summer on weak synoptically forced days. When examining all thunderstorm events, regions at variable ranges upwind of all four cities generally had higher areal mean values of reflectivity, MESH, and VIL relative to downwind areas. In the UF subset, the larger cities (Dallas–Fort Worth and Minneapolis–St. Paul) had a 24%–50% increase in the number of downwind thunderstorms, resulting in a higher areal mean reflectivity, MESH, and VIL in this region. The smaller cities (Oklahoma City and Omaha) did not show such a downwind enhancement in thunderstorm occurrence and strength for the radar variables examined. This pattern suggests that larger cities could increase thunderstorm occurrence and intensity downwind of the prevailing flow under unique environmental conditions.

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Kristin M. Calhoun
,
Travis M. Smith
,
Darrel M. Kingfield
,
Jidong Gao
, and
David J. Stensrud

Abstract

A weather-adaptive three-dimensional variational data assimilation (3DVAR) system was included in the NOAA Hazardous Weather Testbed as a first step toward introducing warn-on-forecast initiatives into operations. NWS forecasters were asked to incorporate the data in conjunction with single-radar and multisensor products in the Advanced Weather Interactive Processing System (AWIPS) as part of their warning-decision process for real-time events across the United States. During the 2011 and 2012 experiments, forecasters examined more than 36 events, including tornadic supercells, severe squall lines, and multicell storms. Products from the 3DVAR analyses were available to forecasters at 1-km horizontal resolution every 5 min, with a 4–6-min latency, incorporating data from the national Weather Surveillance Radar-1988 Doppler (WSR-88D) network and the North American Mesoscale model. Forecasters found the updraft, vertical vorticity, and storm-top divergence products the most useful for storm interrogation and quickly visualizing storm trends, often using these tools to increase the confidence in a warning decision and/or issue the warning slightly earlier. The 3DVAR analyses were most consistent and reliable when the storm of interest was in close proximity to one of the assimilated WSR-88D, or data from multiple radars were incorporated into the analysis. The latter was extremely useful to forecasters in blending data rather than having to analyze multiple radars separately, especially when range folding obscured the data from one or more radars. The largest hurdle for the real-time use of 3DVAR or similar data assimilation products by forecasters is the data latency, as even 4–6 min reduces the utility of the products when new radar scans are available.

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Kelley M. Murphy
,
Lawrence D. Carey
,
Christopher J. Schultz
,
Nathan Curtis
, and
Kristin M. Calhoun

Abstract

A unique storm identification and tracking method is analyzed in varying storm environments within the United States spanning 273 hours in 2018. The methodology uses a quantity calculated through fusion of radar-based vertically integrated liquid (VIL) and satellite-based GLM flash rate density (FRD) called VILFRD to identify storms in space and time. This research analyzes GLM data use within VILFRD for the first time (method original: O), assesses four modifications to VILFRD implementation to find a more stable storm size with time (method new: N), larger storms (method original dilated: OD), or both (method new dilated: ND), and compares VILFRD methods with storm tracking using the 35-dBZ isosurface at −10°C (method non-VILFRD: NV). A case study analysis from 2019 is included to assess methods on a smaller scale and introduce a “lightning only” (LO) version of VILFRD. Large study results highlight that VILFRD-based storm identification produces smaller storms with more lightning than the NV method, and the NV method produces larger storms with a more stable size over time. Methods N and ND create smaller storm size fluctuations, but size changes more often. Dilation (OD, ND) creates larger storms and almost double the number of storms identified relative to nondilated methods (O, N, NV). The case study results closely resemble the large sample results and show that the LO method identifies storms with more lightning and shorter durations. Overall, these findings can aid in choice of storm tracking method based on desired user application and promote further testing of a lightning-only version of VILFRD.

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Clarice N. Satrio
,
Kristin M. Calhoun
,
P. Adrian Campbell
,
Rebecca Steeves
, and
Travis M. Smith

Abstract

While storm identification and tracking algorithms are used both operationally and in research, there exists no single standard technique to objectively determine performance of such algorithms. Thus, a comparative skill score is developed herein that consists of four parameters, three of which constitute the quantification of storm attributes—size consistency, linearity of tracks, and mean track duration—and the fourth that correlates performance to an optimal postevent reanalysis. The skill score is a cumulative sum of each of the parameters normalized from zero to one among the compared algorithms, such that a maximum skill score of four can be obtained. The skill score is intended to favor algorithms that are efficient at severe storm detection, i.e., high-scoring algorithms should detect storms that have higher current or future severe threat and minimize detection of weaker, short-lived storms with low severe potential. The skill score is shown to be capable of successfully ranking a large number of algorithms, both between varying settings within the same base algorithm and between distinct base algorithms. Through a comparison with manually created user datasets, high-scoring algorithms are verified to match well with hand analyses, demonstrating appropriate calibration of skill score parameters.

Significance Statement

With the growing number of options for storm identification and tracking techniques, it is necessary to devise an objective approach to quantify performance of different techniques. This study introduces a comparative skill score that assesses size consistency, linearity of tracks, mean track duration, and correlation to an optimal postevent reanalysis to rank diverse algorithms. This paper will show the capability of the skill score at highlighting algorithms that are efficient at detecting storms with higher severe potential, as well as those that closely resemble human-perceived storms through a comparison with manually created user datasets. The novel methodology will be useful in improving systems that rely on such algorithms, for both operational and research purposes focusing on severe storm detection.

Free access
Kristin M. Calhoun
,
Donald R. MacGorman
,
Conrad L. Ziegler
, and
Michael I. Biggerstaff

Abstract

A high-precipitation tornadic supercell storm was observed on 29–30 May 2004 during the Thunderstorm Electrification and Lightning Experiment. Observational systems included the Oklahoma Lightning Mapping Array, mobile balloon-borne soundings, and two mobile C-band radars. The spatial distribution and evolution of lightning are related to storm kinematics and microphysics, specifically through regions of microphysical charging and the location and geometry of those charge regions. Lightning flashes near the core of this storm were extraordinarily frequent, but tended to be of shorter duration and smaller horizontal extent than typical flashes elsewhere. This is hypothesized to be due to the charge being in many small pockets, with opposite polarities of charge close together in adjoining pockets. Thus, each polarity of lightning leader could propagate only a relatively short distance before reaching regions of unfavorable electric potential. In the anvil, however, lightning extended tens of kilometers from the reflectivity cores in roughly horizontal layers, consistent with the charge spreading through the anvil in broad sheets. The strong, consistent updraft of this high-precipitation supercell storm combined with the large hydrometeor concentrations to produce the extremely high flash rates observed during the analysis period. The strength and size of the updraft also contributed to unique lightning characteristics such as the transient hole of reduced lightning density and discharges in the overshooting top.

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Kristin M. Calhoun
,
Edward R. Mansell
,
Donald R. MacGorman
, and
David C. Dowell

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.

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Milind Sharma
,
Robin L. Tanamachi
,
Eric C. Bruning
, and
Kristin M. Calhoun

Abstract

We demonstrate the utility of transient polarimetric signatures (Z DR and K DP columns, a proxy for surges in a thunderstorm updraft) to explain variability in lightning flash rates in a tornadic supercell. Observational data from a WSR-88D and the Oklahoma lightning mapping array are used to map the temporal variance of polarimetric signatures and VHF sources from lightning channels. It is shown, via three-dimensional and cross-sectional analyses, that the storm was of inverted polarity resulting from anomalous electrification. Statistical analysis confirms that mean flash area in the Z DR column region was 10 times smaller than elsewhere in the storm. On an average, 5 times more flash initiations occurred within Z DR column regions, thereby supporting existing theory of an inverse relationship between flash initiation rates and lightning channel extent. Segmentation and object identification algorithms are applied to gridded radar data to calculate metrics such as height, width, and volume of Z DR and K DP columns. Variability in lightning flash rates is best explained by the fluctuations in Z DR column volume with a Spearman’s rank correlation coefficient value of 0.72. The highest flash rates occur in conjunction with the deepest Z DR columns (up to 5 km above environmental melting level) and largest volumes of Z DR columns extending up to the −20°C level (3 km above the melting level). Reduced flash rates toward the end of the analysis are indicative of weaker updrafts manifested as low Z DR column volumes at and above the −10°C level. These findings are consistent with recent studies linking lightning to the interplay between storm dynamics, kinematics, thermodynamics, and precipitation microphysics.

Open access
Kristin M. Calhoun
,
Kodi L. Berry
,
Darrel M. Kingfield
,
Tiffany Meyer
,
Makenzie J. Krocak
,
Travis M. Smith
,
Greg Stumpf
, and
Alan Gerard

Abstract

NOAA’s Hazardous Weather Testbed (HWT) is a physical space and research framework to foster collaboration and evaluate emerging tools, technology, and products for NWS operations. The HWT’s Experimental Warning Program (EWP) focuses on research, technology, and communication that may improve severe and hazardous weather warnings and societal response. The EWP was established with three fundamental hypotheses: 1) collaboration with operational meteorologists increases the speed of the transition process and rate of adoption of beneficial applications and technology, 2) the transition of knowledge between research and operations benefits both the research and operational communities, and 3) including end users in experiments generates outcomes that are more reliable and useful for society. The EWP is designed to mimic the operations of any NWS Forecast Office, providing the opportunity for experiments to leverage live and archived severe weather activity anywhere in the United States. During the first decade of activity in the EWP, 15 experiments covered topics including new radar and satellite applications, storm-scale numerical models and data assimilation, total lightning use in severe weather forecasting, and multiple social science and end-user topics. The experiments range from exploratory and conceptual research to more controlled experimental design to establish statistical patterns and causal relationships. The EWP brought more than 400 NWS forecasters, 60 emergency managers, and 30 broadcast meteorologists to the HWT to participate in live demonstrations, archive events, and data-denial experiments influencing today’s operational warning environment and shaping the future of warning research, technology, and communication for years to come.

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