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- Author or Editor: Lawrence D. Carey x
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Abstract
Many studies over the past several decades have attempted to correlate trends in lightning (e.g., rates, polarity) to severe weather occurrence. These studies mainly used cloud-to-ground (CG) lightning information due to the ease of data availability, high detection efficiency, and broad coverage across the United States, with somewhat inconclusive results. Conversely, it has been demonstrated that trends in total lightning are more robustly correlated to severe weather occurrence, with rapid increases in total lightning observed 10s of minutes prior to the onset of severe weather. Unfortunately, total lightning observations are not as numerous, or available over the same areal coverage domain, as provided by CG networks. Relatively few studies have examined concurrent trends in both total and CG lightning within the same severe thunderstorm, or even large sets of thunderstorms using an objective lightning jump algorithm. Multiple studies have shown that the total flash rate rapidly increases prior to the onset of severe weather. What is untested within the same framework is the use of CG information to perform the same task. Herein, total and CG lightning trends for 711 thunderstorms occurring in four regions of the country were examined to demonstrate the increased utility that total lightning provides over CG lightning, specifically within the framework of developing a useful lightning-based severe weather warning decision support tool. Results indicate that while both lightning datasets demonstrate the presence of increased lightning activity prior to the onset of severe weather, the use of total lightning trends was more effective than CG trends [probability of detection (POD), 79% versus 66%; false alarm rate (FAR), 36% versus 53%; critical success index (CSI), 55% versus 38%; Heidke skill score (HSS), 0.71 versus 0.55]. Moreover, 40% of false alarms associated with total lightning, and 16% of false alarms with CG lightning trends, occurred when a lightning jump associated with a severe weather “warning” was already in effect. If these false alarms are removed, the FAR drops from 36% to 22% for total lightning and from 53% to 44% for CG lightning. Importantly, average lead times prior to severe weather occurrence were higher using total lightning as compared with CG lightning (20.65 versus 13.54 min). The ultimate goal of this study was to demonstrate the increased utility of total lightning information that the Geostationary Lightning Mapper (GLM) will provide to operational meteorology in anticipation of severe convective weather on a hemispheric scale once Geostationary Operational Environmental Satellite-R (GOES-R) is deployed in the next decade.
Abstract
Many studies over the past several decades have attempted to correlate trends in lightning (e.g., rates, polarity) to severe weather occurrence. These studies mainly used cloud-to-ground (CG) lightning information due to the ease of data availability, high detection efficiency, and broad coverage across the United States, with somewhat inconclusive results. Conversely, it has been demonstrated that trends in total lightning are more robustly correlated to severe weather occurrence, with rapid increases in total lightning observed 10s of minutes prior to the onset of severe weather. Unfortunately, total lightning observations are not as numerous, or available over the same areal coverage domain, as provided by CG networks. Relatively few studies have examined concurrent trends in both total and CG lightning within the same severe thunderstorm, or even large sets of thunderstorms using an objective lightning jump algorithm. Multiple studies have shown that the total flash rate rapidly increases prior to the onset of severe weather. What is untested within the same framework is the use of CG information to perform the same task. Herein, total and CG lightning trends for 711 thunderstorms occurring in four regions of the country were examined to demonstrate the increased utility that total lightning provides over CG lightning, specifically within the framework of developing a useful lightning-based severe weather warning decision support tool. Results indicate that while both lightning datasets demonstrate the presence of increased lightning activity prior to the onset of severe weather, the use of total lightning trends was more effective than CG trends [probability of detection (POD), 79% versus 66%; false alarm rate (FAR), 36% versus 53%; critical success index (CSI), 55% versus 38%; Heidke skill score (HSS), 0.71 versus 0.55]. Moreover, 40% of false alarms associated with total lightning, and 16% of false alarms with CG lightning trends, occurred when a lightning jump associated with a severe weather “warning” was already in effect. If these false alarms are removed, the FAR drops from 36% to 22% for total lightning and from 53% to 44% for CG lightning. Importantly, average lead times prior to severe weather occurrence were higher using total lightning as compared with CG lightning (20.65 versus 13.54 min). The ultimate goal of this study was to demonstrate the increased utility of total lightning information that the Geostationary Lightning Mapper (GLM) will provide to operational meteorology in anticipation of severe convective weather on a hemispheric scale once Geostationary Operational Environmental Satellite-R (GOES-R) is deployed in the next decade.
Abstract
Relationships between lightning and lightning jumps and physical updraft properties are frequently observed and generally understood. However, a more intensive characterization of how lightning relates to traditional radar-based metrics of storm intensity may provide further operational utility. This study addresses the supercell storm mode because of the intrinsic relationship between a supercell’s characteristic rotating updraft–downdraft couplet, or mesocyclone, and its prolific ability to produce severe weather. Lightning and radar measurements of a diverse sample of 19 supercell thunderstorms were used to assess the conceptual model that lightning and the mesocyclone may be linked by the updraft’s role in the formation and enhancement of each. Analysis of early stages of supercell development showed that the initial lightning jump occurred prior to the time of mesocyclogenesis inferred from three methods by median values of 5–10 min. Comparison between lightning jumps and subsequent increases in mesocyclonic rotation indicated that lightning can also be used to infer or confirm imminent strengthening or reintensification of the mesocyclone. Stronger relationships emerged in supercells that exhibited more robust updrafts, in which 85% of lightning jumps were associated with at least one increase in rotation and 77% of observed increases in rotation were temporally associated with a lightning jump. Preliminary results from analysis of the relationship between lightning jumps and intensification of the low-level mesocyclone in tornadic supercells also offer motivation for the future analysis of lightning data with respect to downdraft-related processes.
Abstract
Relationships between lightning and lightning jumps and physical updraft properties are frequently observed and generally understood. However, a more intensive characterization of how lightning relates to traditional radar-based metrics of storm intensity may provide further operational utility. This study addresses the supercell storm mode because of the intrinsic relationship between a supercell’s characteristic rotating updraft–downdraft couplet, or mesocyclone, and its prolific ability to produce severe weather. Lightning and radar measurements of a diverse sample of 19 supercell thunderstorms were used to assess the conceptual model that lightning and the mesocyclone may be linked by the updraft’s role in the formation and enhancement of each. Analysis of early stages of supercell development showed that the initial lightning jump occurred prior to the time of mesocyclogenesis inferred from three methods by median values of 5–10 min. Comparison between lightning jumps and subsequent increases in mesocyclonic rotation indicated that lightning can also be used to infer or confirm imminent strengthening or reintensification of the mesocyclone. Stronger relationships emerged in supercells that exhibited more robust updrafts, in which 85% of lightning jumps were associated with at least one increase in rotation and 77% of observed increases in rotation were temporally associated with a lightning jump. Preliminary results from analysis of the relationship between lightning jumps and intensification of the low-level mesocyclone in tornadic supercells also offer motivation for the future analysis of lightning data with respect to downdraft-related processes.
Abstract
A detailed case study analysis of four thunderstorms is performed using polarimetric and multi-Doppler capabilities to provide specificity on the physical and dynamical drivers behind lightning jumps. The main differences between small increases in the total flash rate and a lightning jump are the increases in graupel mass and updraft volumes ≥10 m s−1 between the −10° and −40°C isotherms. Updraft volumes ≥10 m s−1 increased in magnitude at least 3–5 min in advance of the increase in both graupel mass and total flash rate. Updraft volumes ≥10 m s−1 are more robustly correlated to total flash rate than maximum updraft speed over a thunderstorm’s entire life cycle. However, peak updraft speeds increase prior to 8 of the 12 lightning jumps examined. Decreases in mean and median flash footprint size during increases in total lightning are observed in all four thunderstorms and are most notable during development stages within the most intense storms. However, this inverse relationship breaks down on larger storm scales as storms mature and anvils and stratiform regions developed with time. Promisingly, smaller flash sizes are still collocated with the strongest updraft speeds, while larger flash sizes are observed within weaker updraft regions. The results herein emphasize the following for lightning jump applications: both the lightning jump sigma level and the resultant magnitude of the total flash rate must be employed in conjunction to assess storm intensity using lightning data. The sigma-level magnitude of the lightning jump is the early warning that indicates that rapid intensification is occurring, while the magnitude of the total flash rate provides insight into the size and maintenance of the updraft volume and graupel mass. These cases serve as conceptual models for future applications of the lightning jump algorithm for hazardous weather monitoring.
Abstract
A detailed case study analysis of four thunderstorms is performed using polarimetric and multi-Doppler capabilities to provide specificity on the physical and dynamical drivers behind lightning jumps. The main differences between small increases in the total flash rate and a lightning jump are the increases in graupel mass and updraft volumes ≥10 m s−1 between the −10° and −40°C isotherms. Updraft volumes ≥10 m s−1 increased in magnitude at least 3–5 min in advance of the increase in both graupel mass and total flash rate. Updraft volumes ≥10 m s−1 are more robustly correlated to total flash rate than maximum updraft speed over a thunderstorm’s entire life cycle. However, peak updraft speeds increase prior to 8 of the 12 lightning jumps examined. Decreases in mean and median flash footprint size during increases in total lightning are observed in all four thunderstorms and are most notable during development stages within the most intense storms. However, this inverse relationship breaks down on larger storm scales as storms mature and anvils and stratiform regions developed with time. Promisingly, smaller flash sizes are still collocated with the strongest updraft speeds, while larger flash sizes are observed within weaker updraft regions. The results herein emphasize the following for lightning jump applications: both the lightning jump sigma level and the resultant magnitude of the total flash rate must be employed in conjunction to assess storm intensity using lightning data. The sigma-level magnitude of the lightning jump is the early warning that indicates that rapid intensification is occurring, while the magnitude of the total flash rate provides insight into the size and maintenance of the updraft volume and graupel mass. These cases serve as conceptual models for future applications of the lightning jump algorithm for hazardous weather monitoring.
Abstract
The Geostationary Operational Environmental Satellite-14 (GOES-14) Imager operated in 1-min Super Rapid Scan Operations for GOES-R (SRSOR) mode during summer and fall of 2012 to emulate the high temporal resolution sampling of the GOES-R Advanced Baseline Imager (ABI). The current GOES operational scan interval is 15–30 min, which is too coarse to capture details important for severe convective storm forecasting including 1) when indicators of a severe storm such as rapid cloud-top cooling, overshooting tops, and above-anvil cirrus plumes first appear; 2) how satellite-observed cloud tops truly evolve over time; and 3) how satellite cloud-top observations compare with radar and lightning observations at high temporal resolution. In this paper, SRSOR data, radar, and lightning observations are used to analyze five convective storms, four of which were severe, to address these uncertainties. GOES cloud-top cooling, increased lightning flash rates, and peak precipitation echo tops often preceded severe weather, signaling rapid intensification of the storm updraft. Near the time of several severe hail or damaging wind events, GOES cloud-top temperatures and radar echo tops were warming rapidly, which indicated variability in the storm updraft that could have allowed the hail and wind gusts to reach the surface. Above-anvil cirrus plumes were another prominent indicator of impending severe weather. Detailed analysis of storms throughout the 2012 SRSOR period indicates that 57% of the plume-producing storms were severe and 85% of plumes from severe storms appeared before a severe weather report with an average lead time of 18 min, 9 min earlier than what would be observed by GOES operational scanning.
Abstract
The Geostationary Operational Environmental Satellite-14 (GOES-14) Imager operated in 1-min Super Rapid Scan Operations for GOES-R (SRSOR) mode during summer and fall of 2012 to emulate the high temporal resolution sampling of the GOES-R Advanced Baseline Imager (ABI). The current GOES operational scan interval is 15–30 min, which is too coarse to capture details important for severe convective storm forecasting including 1) when indicators of a severe storm such as rapid cloud-top cooling, overshooting tops, and above-anvil cirrus plumes first appear; 2) how satellite-observed cloud tops truly evolve over time; and 3) how satellite cloud-top observations compare with radar and lightning observations at high temporal resolution. In this paper, SRSOR data, radar, and lightning observations are used to analyze five convective storms, four of which were severe, to address these uncertainties. GOES cloud-top cooling, increased lightning flash rates, and peak precipitation echo tops often preceded severe weather, signaling rapid intensification of the storm updraft. Near the time of several severe hail or damaging wind events, GOES cloud-top temperatures and radar echo tops were warming rapidly, which indicated variability in the storm updraft that could have allowed the hail and wind gusts to reach the surface. Above-anvil cirrus plumes were another prominent indicator of impending severe weather. Detailed analysis of storms throughout the 2012 SRSOR period indicates that 57% of the plume-producing storms were severe and 85% of plumes from severe storms appeared before a severe weather report with an average lead time of 18 min, 9 min earlier than what would be observed by GOES operational scanning.
Abstract
Thirty-nine thunderstorms are examined using multiple-Doppler, polarimetric, and total lightning observations to understand the role of mixed-phase kinematics and microphysics in the development of lightning jumps. This sample size is larger than those of previous studies on this topic. The principal result of this study is that lightning jumps are a result of mixed-phase updraft intensification. Larger increases in intense updraft volume (≥10 m s−1) and larger changes in peak updraft speed are observed prior to lightning jump occurrence when compared to other nonjump increases in total flash rate. Wilcoxon–Mann–Whitney rank sum testing yields p values ≤ 0.05, indicating statistical independence between lightning jump and nonjump distributions for these two parameters. Similar changes in mixed-phase graupel mass magnitude are observed prior to lightning jumps and nonjump increases in total flash rate. The p value for the graupel mass change is p = 0.096, so jump and nonjump distributions for the graupel mass change are not found to be statistically independent using the p = 0.05 significance level. The timing of updraft volume, speed, and graupel mass increases is found to be 4–13 min in advance of lightning jump occurrence. Also, severe storms without lightning jumps lack robust mixed-phase updrafts, demonstrating that mixed-phase updrafts are not always a requirement for severe weather occurrence. Therefore, the results of this study show that lightning jump occurrences are coincident with larger increases in intense mixed-phase updraft volume and peak updraft speed than smaller nonjump increases in total flash rate.
Abstract
Thirty-nine thunderstorms are examined using multiple-Doppler, polarimetric, and total lightning observations to understand the role of mixed-phase kinematics and microphysics in the development of lightning jumps. This sample size is larger than those of previous studies on this topic. The principal result of this study is that lightning jumps are a result of mixed-phase updraft intensification. Larger increases in intense updraft volume (≥10 m s−1) and larger changes in peak updraft speed are observed prior to lightning jump occurrence when compared to other nonjump increases in total flash rate. Wilcoxon–Mann–Whitney rank sum testing yields p values ≤ 0.05, indicating statistical independence between lightning jump and nonjump distributions for these two parameters. Similar changes in mixed-phase graupel mass magnitude are observed prior to lightning jumps and nonjump increases in total flash rate. The p value for the graupel mass change is p = 0.096, so jump and nonjump distributions for the graupel mass change are not found to be statistically independent using the p = 0.05 significance level. The timing of updraft volume, speed, and graupel mass increases is found to be 4–13 min in advance of lightning jump occurrence. Also, severe storms without lightning jumps lack robust mixed-phase updrafts, demonstrating that mixed-phase updrafts are not always a requirement for severe weather occurrence. Therefore, the results of this study show that lightning jump occurrences are coincident with larger increases in intense mixed-phase updraft volume and peak updraft speed than smaller nonjump increases in total flash rate.
Abstract
Wind warnings are the second-most-frequent advisory issued by the U.S. Air Force’s 45th Weather Squadron (45WS) at Cape Canaveral, Florida. Given the challenges associated with nowcasting convection in Florida during the warm season, improvements in 45WS warnings for convective wind events are desired. This study aims to explore the physical bases of dual-polarization radar signatures within wet downbursts around Cape Canaveral and identify signatures that may assist the 45WS during real-time convective wind nowcasting. Data from the 45WS’s C-band dual-polarization radar were subjectively analyzed within an environmental context, with quantitative wind measurements recorded by weather tower sensors for 32 threshold-level downbursts with near-surface winds ≥ 35 kt (1 kt ≈ 0.51 m s−1) and 32 null downbursts. Five radar signatures were identified in threshold-level downburst-producing storms: peak height of 1-dB differential reflectivity Z DR column, peak height of precipitation ice signature, peak reflectivity, height below 0°C level where Z DR increases to 3 dB within a descending reflectivity core (DRC), and vertical Z DR gradient within DRC. Examining these signatures directly in updraft–downdraft cycles that produced threshold-level winds yielded mean lead times of 20.0–28.2 min for cumulus and mature stage signatures and 12.8–14.9 min for dissipating stage signatures, with higher signature test values generally yielding higher skill scores. A conceptual test of utilizing signatures within earlier cells in multicell storms to indirectly predict the potential for intense downbursts in later cells was performed, which offered increased lead times and skill scores for an Eulerian forecast region downstream from the storm initiation location.
Abstract
Wind warnings are the second-most-frequent advisory issued by the U.S. Air Force’s 45th Weather Squadron (45WS) at Cape Canaveral, Florida. Given the challenges associated with nowcasting convection in Florida during the warm season, improvements in 45WS warnings for convective wind events are desired. This study aims to explore the physical bases of dual-polarization radar signatures within wet downbursts around Cape Canaveral and identify signatures that may assist the 45WS during real-time convective wind nowcasting. Data from the 45WS’s C-band dual-polarization radar were subjectively analyzed within an environmental context, with quantitative wind measurements recorded by weather tower sensors for 32 threshold-level downbursts with near-surface winds ≥ 35 kt (1 kt ≈ 0.51 m s−1) and 32 null downbursts. Five radar signatures were identified in threshold-level downburst-producing storms: peak height of 1-dB differential reflectivity Z DR column, peak height of precipitation ice signature, peak reflectivity, height below 0°C level where Z DR increases to 3 dB within a descending reflectivity core (DRC), and vertical Z DR gradient within DRC. Examining these signatures directly in updraft–downdraft cycles that produced threshold-level winds yielded mean lead times of 20.0–28.2 min for cumulus and mature stage signatures and 12.8–14.9 min for dissipating stage signatures, with higher signature test values generally yielding higher skill scores. A conceptual test of utilizing signatures within earlier cells in multicell storms to indirectly predict the potential for intense downbursts in later cells was performed, which offered increased lead times and skill scores for an Eulerian forecast region downstream from the storm initiation location.
Abstract
Ten years (1997–2006) of summer (June–August) daytime (1400–0000 UTC) Weather Surveillance Radar-1988 Doppler data for Houston, Texas, were examined to determine the best radar-derived predictors of the first cloud-to-ground lightning flash from a convective cell. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to cloud-to-ground lightning data from the National Lightning Detection Network (NLDN). Combinations of three radar reflectivity values (30, 35, and 40 dBZ) at four isothermal levels (−10°, −15°, −20°, and updraft −10°C) and a new radar-derived product, vertically integrated ice (VII), were used to optimize a radar-based lightning forecast algorithm. Forecasts were also delineated by range and the number of times a cell was identified and tracked by the modified SCIT algorithm. This study objectively analyzed 67 384 unique cells and 1 028 510 lightning flashes to find the best lightning forecast criteria. Results show that using 30 dBZ at the −15° or −20°C isotherm on cells within 75 km of the radar that have been tracked for at least two consecutive scans produces the best lightning forecasts with a critical success index (CSI) of 0.68. The best VII predictor values were 0.42 or 0.58 kg m−2 on cells within 75 km of the radar that have been tracked for at least two consecutive scans, producing a CSI of 0.67. Lead times for these predictors were 10.0 and 13.4 min, respectively. Lead times greater than 10 min occurred with less stringent predictors (e.g., 30 dBZ at −10°C or VII greater than 0.25 kg m−2 on cells within 125 km with a minimum track count of 2), but lower CSI values result. In general, cells tracked for multiple scans provide higher CSIs and lead times than decreasing the range from the radar or changing the reflectivity threshold and height.
Abstract
Ten years (1997–2006) of summer (June–August) daytime (1400–0000 UTC) Weather Surveillance Radar-1988 Doppler data for Houston, Texas, were examined to determine the best radar-derived predictors of the first cloud-to-ground lightning flash from a convective cell. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to cloud-to-ground lightning data from the National Lightning Detection Network (NLDN). Combinations of three radar reflectivity values (30, 35, and 40 dBZ) at four isothermal levels (−10°, −15°, −20°, and updraft −10°C) and a new radar-derived product, vertically integrated ice (VII), were used to optimize a radar-based lightning forecast algorithm. Forecasts were also delineated by range and the number of times a cell was identified and tracked by the modified SCIT algorithm. This study objectively analyzed 67 384 unique cells and 1 028 510 lightning flashes to find the best lightning forecast criteria. Results show that using 30 dBZ at the −15° or −20°C isotherm on cells within 75 km of the radar that have been tracked for at least two consecutive scans produces the best lightning forecasts with a critical success index (CSI) of 0.68. The best VII predictor values were 0.42 or 0.58 kg m−2 on cells within 75 km of the radar that have been tracked for at least two consecutive scans, producing a CSI of 0.67. Lead times for these predictors were 10.0 and 13.4 min, respectively. Lead times greater than 10 min occurred with less stringent predictors (e.g., 30 dBZ at −10°C or VII greater than 0.25 kg m−2 on cells within 125 km with a minimum track count of 2), but lower CSI values result. In general, cells tracked for multiple scans provide higher CSIs and lead times than decreasing the range from the radar or changing the reflectivity threshold and height.
Abstract
This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate [i.e., lightning jump (LJ)]. An automated storm tracking method is used to identify storm “clusters” and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama, and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer and relate to higher maximum expected size of hail, vertical integrated liquid, and lightning flash rates (area normalized) than do the clusters without an LJ (LJ0). The respective mean radar-derived and lightning values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg m−2 (18 kg m−2), and 0.05 flash min−1 km−2 (0.01 flash min−1 km−2). Furthermore, the LJ1 clusters are also characterized by slower-decaying autocorrelation functions, a result that implies a less “random” behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm’s dissipation. Depending on the LJ strength (i.e., varying thresholds), these values typically range between 20 and 60 min, with stronger jumps indicating more time until storm decay. This study’s results support the hypothesis that the LJ is a proxy for the storm’s kinematic and microphysical state rather than a coincidental value.
Abstract
This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate [i.e., lightning jump (LJ)]. An automated storm tracking method is used to identify storm “clusters” and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama, and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer and relate to higher maximum expected size of hail, vertical integrated liquid, and lightning flash rates (area normalized) than do the clusters without an LJ (LJ0). The respective mean radar-derived and lightning values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg m−2 (18 kg m−2), and 0.05 flash min−1 km−2 (0.01 flash min−1 km−2). Furthermore, the LJ1 clusters are also characterized by slower-decaying autocorrelation functions, a result that implies a less “random” behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm’s dissipation. Depending on the LJ strength (i.e., varying thresholds), these values typically range between 20 and 60 min, with stronger jumps indicating more time until storm decay. This study’s results support the hypothesis that the LJ is a proxy for the storm’s kinematic and microphysical state rather than a coincidental value.
