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Abstract
It has been hypothesized that intense convective-scale “hot” towers play a role in tropical cyclogenesis via dynamic and thermodynamic feedbacks on the larger-scale circulation. In this study the authors investigate the role that widespread and/or intense lightning-producing convection (i.e., electrically hot towers) present in African easterly waves (AEWs) may play in tropical cyclogenesis over the east Atlantic Ocean.
The 700-hPa meridional wind from the NCEP–NCAR reanalysis dataset was analyzed to divide the waves into northerly, southerly, trough, and ridge phases. The AEWs were subsequently divided into waves that developed into tropical storms (i.e., developing) and those that did not develop into tropical storms (i.e., nondeveloping). Finally, composites were created using various NCEP variables, lightning data gathered with the Zeus network and worldwide lightning location network (WWLLN), and brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset.
Results indicate that in all regions examined the developing waves seem to be associated with more widespread and/or intense lightning-producing convection. This increased convection associated with the developing waves might be related to the increased midlevel moisture, low-level vorticity, low-level convergence, upper-level divergence, and increased upward vertical motion found to be associated with the developing waves. In addition, the phasing of the convection with the AEWs as they move from East Africa to the central Atlantic shows some variability, which may have implications for tropical cyclogenesis.
Abstract
It has been hypothesized that intense convective-scale “hot” towers play a role in tropical cyclogenesis via dynamic and thermodynamic feedbacks on the larger-scale circulation. In this study the authors investigate the role that widespread and/or intense lightning-producing convection (i.e., electrically hot towers) present in African easterly waves (AEWs) may play in tropical cyclogenesis over the east Atlantic Ocean.
The 700-hPa meridional wind from the NCEP–NCAR reanalysis dataset was analyzed to divide the waves into northerly, southerly, trough, and ridge phases. The AEWs were subsequently divided into waves that developed into tropical storms (i.e., developing) and those that did not develop into tropical storms (i.e., nondeveloping). Finally, composites were created using various NCEP variables, lightning data gathered with the Zeus network and worldwide lightning location network (WWLLN), and brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset.
Results indicate that in all regions examined the developing waves seem to be associated with more widespread and/or intense lightning-producing convection. This increased convection associated with the developing waves might be related to the increased midlevel moisture, low-level vorticity, low-level convergence, upper-level divergence, and increased upward vertical motion found to be associated with the developing waves. In addition, the phasing of the convection with the AEWs as they move from East Africa to the central Atlantic shows some variability, which may have implications for tropical cyclogenesis.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was designed to acquire aircraft, surface, and satellite observations of particle size distributions during cold season precipitation events for the purposes of validating and improving upon satellite-based retrievals of precipitation and the representation of cloud and precipitation processes within numerical weather prediction schemes. During an intensive observation period on 22 January 2007, an instrumented aircraft measured ice crystal size distributions, ice and liquid water contents, and atmospheric state parameters within a broad shield of precipitation generated by a passing midlatitude cyclone. The 94-GHz CloudSat radar acquired vertical profiles of radar reflectivity within light to moderate snowfall, coincident with C3VP surface and aircraft instrumentation. Satellite-based retrievals of cold season precipitation require relationships between remotely sensed quantities, such as radar reflectivity or brightness temperature, and the ice water content present within the sampled profile.
In this study, three methods for simulating CloudSat radar reflectivity are investigated by comparing Mie spheres, single dendrites, and fractal aggregates represented within scattering databases or parameterizations. It is demonstrated that calculations of radar backscatter from nonspherical crystal shapes are required to represent the vertical trend in CloudSat radar reflectivity for this particular event, as Mie resonance effects reduce the radar backscatter from precipitation-sized particles larger than 1 mm. Remaining differences between reflectivity from nonspherical shapes and observations are attributed to uncertainty in the mass–diameter relationships for observed crystals and disparities between naturally occurring crystals and shapes assumed in the development of ice crystal scattering databases and parameterizations.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was designed to acquire aircraft, surface, and satellite observations of particle size distributions during cold season precipitation events for the purposes of validating and improving upon satellite-based retrievals of precipitation and the representation of cloud and precipitation processes within numerical weather prediction schemes. During an intensive observation period on 22 January 2007, an instrumented aircraft measured ice crystal size distributions, ice and liquid water contents, and atmospheric state parameters within a broad shield of precipitation generated by a passing midlatitude cyclone. The 94-GHz CloudSat radar acquired vertical profiles of radar reflectivity within light to moderate snowfall, coincident with C3VP surface and aircraft instrumentation. Satellite-based retrievals of cold season precipitation require relationships between remotely sensed quantities, such as radar reflectivity or brightness temperature, and the ice water content present within the sampled profile.
In this study, three methods for simulating CloudSat radar reflectivity are investigated by comparing Mie spheres, single dendrites, and fractal aggregates represented within scattering databases or parameterizations. It is demonstrated that calculations of radar backscatter from nonspherical crystal shapes are required to represent the vertical trend in CloudSat radar reflectivity for this particular event, as Mie resonance effects reduce the radar backscatter from precipitation-sized particles larger than 1 mm. Remaining differences between reflectivity from nonspherical shapes and observations are attributed to uncertainty in the mass–diameter relationships for observed crystals and disparities between naturally occurring crystals and shapes assumed in the development of ice crystal scattering databases and parameterizations.
Abstract
This study presents further evidence in support of an in situ, noninductive charging mechanism as the process likely responsible for significant electrification of the trailing stratiform regions of mesoscale convective systems (MCSs). In contrast to previous studies of MCS electrification that have investigated observations of radar reflectivity and cloud-to-ground lightning in the horizontal (e.g., Orville et al.; Rutledge et al.), here the relationship between the location and occurrence of cloud-to-ground lightning in the stratiform regions of midlatitude and tropical MCSs and the vertical profile of radar reflectivity are examined. The vertical profile of radar reflectivity at elevations above the 0°C level is used as a proxy for the amount of mass present in the mixed-phase region of the stratiform clouds, which in turn is related to the generation of charge through a noninductive charging mechanism.
To further explore the relationship between radar reflectivity, mixed-phase microphysics, and in situ charging by means of a noninductive mechanism, we present calculations with a simple one-dimensional model used to diagnose the presence of supercooled liquid water between the 0° and −20°C levels in the stratiform region. We use the model to contrast two cases: 1) a case in which reflectivities greater than 15 dBZ existed above the 0°C level in the stratiform clouds, cloud-to-ground lightning occurred, and moderate amounts of supercooled liquid water were present in the stratiform region (as inferred from the model results); 2) a case where no lightning was observed in the stratiform region, reflectivities above the 0°C level were less than 15 dBZ, and very little supercooled water was present (as inferred from the model results). Based on observations in several MCSs, we show that the number of cloud-to-ground lightning flashes in the stratiform region is highly correlated with the vertical radar reflectivity profile.
Abstract
This study presents further evidence in support of an in situ, noninductive charging mechanism as the process likely responsible for significant electrification of the trailing stratiform regions of mesoscale convective systems (MCSs). In contrast to previous studies of MCS electrification that have investigated observations of radar reflectivity and cloud-to-ground lightning in the horizontal (e.g., Orville et al.; Rutledge et al.), here the relationship between the location and occurrence of cloud-to-ground lightning in the stratiform regions of midlatitude and tropical MCSs and the vertical profile of radar reflectivity are examined. The vertical profile of radar reflectivity at elevations above the 0°C level is used as a proxy for the amount of mass present in the mixed-phase region of the stratiform clouds, which in turn is related to the generation of charge through a noninductive charging mechanism.
To further explore the relationship between radar reflectivity, mixed-phase microphysics, and in situ charging by means of a noninductive mechanism, we present calculations with a simple one-dimensional model used to diagnose the presence of supercooled liquid water between the 0° and −20°C levels in the stratiform region. We use the model to contrast two cases: 1) a case in which reflectivities greater than 15 dBZ existed above the 0°C level in the stratiform clouds, cloud-to-ground lightning occurred, and moderate amounts of supercooled liquid water were present in the stratiform region (as inferred from the model results); 2) a case where no lightning was observed in the stratiform region, reflectivities above the 0°C level were less than 15 dBZ, and very little supercooled water was present (as inferred from the model results). Based on observations in several MCSs, we show that the number of cloud-to-ground lightning flashes in the stratiform region is highly correlated with the vertical radar reflectivity profile.
Abstract
Observation of the vertical profile of precipitation over the global Tropics is a key objective of the Tropical Rainfall Measuring Mission (TRMM) because this information is central to obtaining vertical profiles of latent heating. This study combines both TRMM precipitation radar (PR) and Lightning Imaging Sensor (LIS) data to examine “wet-season” vertical structures of tropical precipitation across a broad spectrum of locations in the global Tropics. TRMM-PR reflectivity data (2A25 algorithm) were utilized to produce seasonal mean three-dimensional relative frequency histograms and precipitation ice water contents over grid boxes of approximately 5°–10° in latitude and longitude. The reflectivity histograms and ice water contents were then combined with LIS lightning flash densities and 2A25 mean rainfall rates to examine regional relationships between precipitation vertical structure, precipitation processes, and lightning production.
Analysis of the reflectivity vertical structure histograms and lightning flash density data reveals that 1) relative to tropical continental locations, wet-season isolated tropical oceanic locations exhibit relatively little spatial (and in some instances seasonal) variability in vertical structure across the global Tropics; 2) coastal locations and areas located within 500–1000 km of a continent exhibit considerable seasonal and spatial variability in mean vertical structure, often resembling “continental” profiles or falling intermediate to that of tropical continental and isolated oceanic regimes; and 3) interior tropical continental locations exhibit marked variability in vertical structure both spatially and seasonally, exhibiting a continuum of characteristics ranging from a near-isolated oceanic profile observed over the central Amazon and India to a more robust continental profile observed over regions such as the Congo and Florida. Examination of regional and seasonal mean conditional instability for a small but representative subset of the geographic locations suggests that tropospheric thermodynamic structure likely plays a significant role in the regional characteristics of precipitation vertical structure and associated lightning flash density.
In general, the largest systematic variability in precipitation vertical structure observed between all of the locations examined occurred above the freezing level. It is important that subfreezing temperature variability in the vertical reflectivity structures was well reflected in the seasonal mean lightning flash densities and ice water contents diagnosed for each location. In turn, systematically larger rainfall rates were observed on a pixel-by-pixel basis in locations with larger precipitation ice water content and lightning flash density. These results delineate, in a regional sense, the relative importance of mixed-phase precipitation production across the global Tropics.
Abstract
Observation of the vertical profile of precipitation over the global Tropics is a key objective of the Tropical Rainfall Measuring Mission (TRMM) because this information is central to obtaining vertical profiles of latent heating. This study combines both TRMM precipitation radar (PR) and Lightning Imaging Sensor (LIS) data to examine “wet-season” vertical structures of tropical precipitation across a broad spectrum of locations in the global Tropics. TRMM-PR reflectivity data (2A25 algorithm) were utilized to produce seasonal mean three-dimensional relative frequency histograms and precipitation ice water contents over grid boxes of approximately 5°–10° in latitude and longitude. The reflectivity histograms and ice water contents were then combined with LIS lightning flash densities and 2A25 mean rainfall rates to examine regional relationships between precipitation vertical structure, precipitation processes, and lightning production.
Analysis of the reflectivity vertical structure histograms and lightning flash density data reveals that 1) relative to tropical continental locations, wet-season isolated tropical oceanic locations exhibit relatively little spatial (and in some instances seasonal) variability in vertical structure across the global Tropics; 2) coastal locations and areas located within 500–1000 km of a continent exhibit considerable seasonal and spatial variability in mean vertical structure, often resembling “continental” profiles or falling intermediate to that of tropical continental and isolated oceanic regimes; and 3) interior tropical continental locations exhibit marked variability in vertical structure both spatially and seasonally, exhibiting a continuum of characteristics ranging from a near-isolated oceanic profile observed over the central Amazon and India to a more robust continental profile observed over regions such as the Congo and Florida. Examination of regional and seasonal mean conditional instability for a small but representative subset of the geographic locations suggests that tropospheric thermodynamic structure likely plays a significant role in the regional characteristics of precipitation vertical structure and associated lightning flash density.
In general, the largest systematic variability in precipitation vertical structure observed between all of the locations examined occurred above the freezing level. It is important that subfreezing temperature variability in the vertical reflectivity structures was well reflected in the seasonal mean lightning flash densities and ice water contents diagnosed for each location. In turn, systematically larger rainfall rates were observed on a pixel-by-pixel basis in locations with larger precipitation ice water content and lightning flash density. These results delineate, in a regional sense, the relative importance of mixed-phase precipitation production across the global Tropics.
Abstract
Estimating raindrop size has been a long-standing objective of polarimetric radar–based precipitation retrieval methods. The relationship between the differential reflectivity Z dr and the median volume diameter D 0 is typically derived empirically using raindrop size distribution observations from a disdrometer, a raindrop physical model, and a radar scattering model. Because disdrometers are known to undersample large raindrops, the maximum drop diameter D max is often an assumed parameter in the rain physical model. C-band Z dr is sensitive to resonance scattering at drop diameters larger than 5 mm, which falls in the region of uncertainty for D max. Prior studies have not accounted for resonance scattering at C band and D max uncertainty in assessing potential errors in drop size retrievals. As such, a series of experiments are conducted that evaluate the effect of D max parameterization on the retrieval error of D 0 from a fourth-order polynomial function of C-band Z dr by varying the assumed D max through the range of assumptions found in the literature. Normalized bias errors for estimating D 0 from C-band Z dr range from −8% to 15%, depending on the postulated error in D max. The absolute normalized bias error increases with C-band Z dr, can reach 10% for Z dr as low as 1–1.75 dB, and can increase from there to values as large as 15%–45% for larger Z dr, which is a larger potential bias error than is found at S and X band. Uncertainty in D max assumptions and the associated potential D 0 retrieval errors should be noted and accounted for in future C-band polarimetric radar studies.
Abstract
Estimating raindrop size has been a long-standing objective of polarimetric radar–based precipitation retrieval methods. The relationship between the differential reflectivity Z dr and the median volume diameter D 0 is typically derived empirically using raindrop size distribution observations from a disdrometer, a raindrop physical model, and a radar scattering model. Because disdrometers are known to undersample large raindrops, the maximum drop diameter D max is often an assumed parameter in the rain physical model. C-band Z dr is sensitive to resonance scattering at drop diameters larger than 5 mm, which falls in the region of uncertainty for D max. Prior studies have not accounted for resonance scattering at C band and D max uncertainty in assessing potential errors in drop size retrievals. As such, a series of experiments are conducted that evaluate the effect of D max parameterization on the retrieval error of D 0 from a fourth-order polynomial function of C-band Z dr by varying the assumed D max through the range of assumptions found in the literature. Normalized bias errors for estimating D 0 from C-band Z dr range from −8% to 15%, depending on the postulated error in D max. The absolute normalized bias error increases with C-band Z dr, can reach 10% for Z dr as low as 1–1.75 dB, and can increase from there to values as large as 15%–45% for larger Z dr, which is a larger potential bias error than is found at S and X band. Uncertainty in D max assumptions and the associated potential D 0 retrieval errors should be noted and accounted for in future C-band polarimetric radar studies.
Abstract
The comparison of satellite and high-quality, ground-based estimates of precipitation is an important means to assess the confidence in satellite-based algorithms and to provide a benchmark for their continued development and future improvement. To these ends, it is beneficial to identify sources of estimation uncertainty, thereby facilitating a precise understanding of the origins of the problem. This is especially true for new datasets such as the Integrated Multisatellite Retrievals for GPM (IMERG) product, which provides global precipitation gridded at a high resolution using measurements from different sources and techniques. Here, IMERG is evaluated against a dense network of gauges in the mid-Atlantic region of the United States. A novel approach is presented, leveraging ancillary variables in IMERG to attribute the errors to the individual instruments or techniques within the algorithm. As a whole, IMERG exhibits some misses and false alarms for rain detection, while its rain-rate estimates tend to overestimate drizzle and underestimate heavy rain with considerable random error. Tracing the errors to their sources, the most reliable IMERG estimates come from passive microwave satellites, which in turn exhibit a hierarchy of performance. The morphing technique has comparable proficiency with the less skillful satellites, but infrared estimations perform poorly. The approach here demonstrated that, underlying the overall reasonable performance of IMERG, different sources have different reliability, thus enabling both IMERG users and developers to better recognize the uncertainty in the estimate. Future validation efforts are urged to adopt such a categorization to bridge between gridded rainfall and instantaneous satellite estimates.
Abstract
The comparison of satellite and high-quality, ground-based estimates of precipitation is an important means to assess the confidence in satellite-based algorithms and to provide a benchmark for their continued development and future improvement. To these ends, it is beneficial to identify sources of estimation uncertainty, thereby facilitating a precise understanding of the origins of the problem. This is especially true for new datasets such as the Integrated Multisatellite Retrievals for GPM (IMERG) product, which provides global precipitation gridded at a high resolution using measurements from different sources and techniques. Here, IMERG is evaluated against a dense network of gauges in the mid-Atlantic region of the United States. A novel approach is presented, leveraging ancillary variables in IMERG to attribute the errors to the individual instruments or techniques within the algorithm. As a whole, IMERG exhibits some misses and false alarms for rain detection, while its rain-rate estimates tend to overestimate drizzle and underestimate heavy rain with considerable random error. Tracing the errors to their sources, the most reliable IMERG estimates come from passive microwave satellites, which in turn exhibit a hierarchy of performance. The morphing technique has comparable proficiency with the less skillful satellites, but infrared estimations perform poorly. The approach here demonstrated that, underlying the overall reasonable performance of IMERG, different sources have different reliability, thus enabling both IMERG users and developers to better recognize the uncertainty in the estimate. Future validation efforts are urged to adopt such a categorization to bridge between gridded rainfall and instantaneous satellite estimates.
Abstract
On 30 May 1998, a tornado devastated the town of Spencer, South Dakota. The Spencer tornado (rated F4 on the Fujita tornado intensity scale) was the third and most intense of five tornadoes produced by a single supercell storm during an approximate 1-h period. The supercell produced over 76% positive cloud-to-ground (CG) lightning and a peak positive CG flash rate of 18 flashes min−1 (5-min average) during a 2-h period surrounding the tornado damage. Earlier studies have reported anomalous positive CG lightning activity in some supercell storms producing violent tornadoes. However, what makes the CG lightning activity in this tornadic storm unique is the magnitude and timing of the positive ground flashes relative to the F4 tornado. In previous studies, supercells dominated by positive CG lightning produced their most violent tornado after they attained their maximum positive ground flash rate, whenever the rate exceeded 1.5 flashes min−1. Further, tornadogenesis often occurred during a lull in CG lightning activity and sometimes during a reversal from positive to negative polarity. Contrary to these findings, the positive CG lightning flash rate and percentage of positive CG lightning in the Spencer supercell increased dramatically while the storm was producing F4 damage on Spencer.
These results have important implications for the use of CG lightning in the nowcasting of tornadoes and for the understanding of cloud electrification in these unique storms. In order to further explore these issues, the authors present detailed analyses of storm evolution and structure using Sioux Falls, South Dakota, (KFSD) Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and Doppler velocity and National Lightning Detection Network (NLDN) CG lightning data. The analyses suggest that a merger between the Spencer supercell and a squall line on its rear flank may have provided the impetus for both the F4 tornadic damage and the dramatic increase in positive CG lightning during the tornado, possibly explaining the difference in timing compared to past studies.
Abstract
On 30 May 1998, a tornado devastated the town of Spencer, South Dakota. The Spencer tornado (rated F4 on the Fujita tornado intensity scale) was the third and most intense of five tornadoes produced by a single supercell storm during an approximate 1-h period. The supercell produced over 76% positive cloud-to-ground (CG) lightning and a peak positive CG flash rate of 18 flashes min−1 (5-min average) during a 2-h period surrounding the tornado damage. Earlier studies have reported anomalous positive CG lightning activity in some supercell storms producing violent tornadoes. However, what makes the CG lightning activity in this tornadic storm unique is the magnitude and timing of the positive ground flashes relative to the F4 tornado. In previous studies, supercells dominated by positive CG lightning produced their most violent tornado after they attained their maximum positive ground flash rate, whenever the rate exceeded 1.5 flashes min−1. Further, tornadogenesis often occurred during a lull in CG lightning activity and sometimes during a reversal from positive to negative polarity. Contrary to these findings, the positive CG lightning flash rate and percentage of positive CG lightning in the Spencer supercell increased dramatically while the storm was producing F4 damage on Spencer.
These results have important implications for the use of CG lightning in the nowcasting of tornadoes and for the understanding of cloud electrification in these unique storms. In order to further explore these issues, the authors present detailed analyses of storm evolution and structure using Sioux Falls, South Dakota, (KFSD) Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and Doppler velocity and National Lightning Detection Network (NLDN) CG lightning data. The analyses suggest that a merger between the Spencer supercell and a squall line on its rear flank may have provided the impetus for both the F4 tornadic damage and the dramatic increase in positive CG lightning during the tornado, possibly explaining the difference in timing compared to past studies.
Abstract
The Integrated Multisatellite Retrievals for GPM (IMERG), a global high-resolution gridded precipitation dataset, will enable a wide range of applications, ranging from studies on precipitation characteristics to applications in hydrology to evaluation of weather and climate models. These applications focus on different spatial and temporal scales and thus average the precipitation estimates to coarser resolutions. Such a modification of scale will impact the reliability of IMERG. In this study, the performance of the Final Run of IMERG is evaluated against ground-based measurements as a function of increasing spatial resolution (from 0.1° to 2.5°) and accumulation periods (from 0.5 to 24 h) over a region in the southeastern United States. For ground reference, a product derived from the Multi-Radar/Multi-Sensor suite, a radar- and gauge-based operational precipitation dataset, is used. The TRMM Multisatellite Precipitation Analysis (TMPA) is also included as a benchmark. In general, both IMERG and TMPA improve when scaled up to larger areas and longer time periods, with better identification of rain occurrences and consistent improvements in systematic and random errors of rain rates. Between the two satellite estimates, IMERG is slightly better than TMPA most of the time. These results will inform users on the reliability of IMERG over the scales relevant to their studies.
Abstract
The Integrated Multisatellite Retrievals for GPM (IMERG), a global high-resolution gridded precipitation dataset, will enable a wide range of applications, ranging from studies on precipitation characteristics to applications in hydrology to evaluation of weather and climate models. These applications focus on different spatial and temporal scales and thus average the precipitation estimates to coarser resolutions. Such a modification of scale will impact the reliability of IMERG. In this study, the performance of the Final Run of IMERG is evaluated against ground-based measurements as a function of increasing spatial resolution (from 0.1° to 2.5°) and accumulation periods (from 0.5 to 24 h) over a region in the southeastern United States. For ground reference, a product derived from the Multi-Radar/Multi-Sensor suite, a radar- and gauge-based operational precipitation dataset, is used. The TRMM Multisatellite Precipitation Analysis (TMPA) is also included as a benchmark. In general, both IMERG and TMPA improve when scaled up to larger areas and longer time periods, with better identification of rain occurrences and consistent improvements in systematic and random errors of rain rates. Between the two satellite estimates, IMERG is slightly better than TMPA most of the time. These results will inform users on the reliability of IMERG over the scales relevant to their studies.
Abstract
Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed “lightning jumps.” Herein, the authors document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms from the Tennessee Valley; Washington, D.C.; Dallas, Texas; and Houston, Texas, were examined in this study. Of the 107 thunderstorms, 69 thunderstorms fall into the category of nonsevere and 38 into the category of severe. From the dataset of 69 isolated nonsevere thunderstorms, an average, peak, 1-min flash rate of 10 flashes per minute was determined. A variety of severe thunderstorm types were examined for this study, including a mesoscale convective system, mesoscale convective vortex, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 nonsevere, 38 severe) were from the Tennessee Valley and Washington, D.C., and these 85 thunderstorms tested six lightning jump algorithm configurations (Gatlin, Gatlin 45, 2σ, 3σ, Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2σ lightning jump algorithm had a high probability of detection (POD; 87%), a modest false-alarm rate (FAR; 33%), and a solid Heidke skill score (0.75). These statistics exceed current NWS warning statistics with this dataset; however, this algorithm needs further testing because there is a large difference in sample sizes. A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 min. The overall goal of this study is to advance the development of an operationally applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the Geostationary Operational Environmental Satellite Series R (GOES-R) Geostationary Lightning Mapper.
Abstract
Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed “lightning jumps.” Herein, the authors document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms from the Tennessee Valley; Washington, D.C.; Dallas, Texas; and Houston, Texas, were examined in this study. Of the 107 thunderstorms, 69 thunderstorms fall into the category of nonsevere and 38 into the category of severe. From the dataset of 69 isolated nonsevere thunderstorms, an average, peak, 1-min flash rate of 10 flashes per minute was determined. A variety of severe thunderstorm types were examined for this study, including a mesoscale convective system, mesoscale convective vortex, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 nonsevere, 38 severe) were from the Tennessee Valley and Washington, D.C., and these 85 thunderstorms tested six lightning jump algorithm configurations (Gatlin, Gatlin 45, 2σ, 3σ, Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2σ lightning jump algorithm had a high probability of detection (POD; 87%), a modest false-alarm rate (FAR; 33%), and a solid Heidke skill score (0.75). These statistics exceed current NWS warning statistics with this dataset; however, this algorithm needs further testing because there is a large difference in sample sizes. A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 min. The overall goal of this study is to advance the development of an operationally applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the Geostationary Operational Environmental Satellite Series R (GOES-R) Geostationary Lightning Mapper.
Abstract
Dual-Doppler radar data from the Tropical Rainfall Measuring Mission Large Scale Biosphere–Atmosphere Experiment in Amazonia (TRMM-LBA) field campaign are used to determine characteristic kinematic and reflectivity vertical structures associated with precipitation features observed during the wet season in the southwest region of Amazonia. Case studies of precipitating systems during TRMM-LBA as well as overarching satellite studies have shown large differences in convective intensity associated with changes that develop in low-level easterly flow [east regime (ER)] and westerly flow [west regime (WR)]. This study attempts to examine the vertical kinematic and heating structure of convection across the spectrum of precipitation features that occurred in each regime.
Results show that convection in the ER is characterized by more intense updrafts and larger radar reflectivities above the melting level, in agreement with results from lightning detection networks. These regime differences are consistent with contrasts in composite thermal buoyancy between the regimes: above the boundary layer, the environment in the ER is characterized by a greater virtual temperature excess for near-surface rising parcels. Both regimes showed a peak in intensity during the late afternoon hours, as evidenced by radar reflectivity and kinematic characteristics, consistent with previous studies of rainfall and lightning in the Rondônia (TRMM-LBA) region. After sunset, however, convective intensity in the WR decreases much more abruptly compared to the ER. In the stratiform–weak convective region, the ER showed both reflectivity and kinematic characteristics of classic stratiform structure after sunset through the early morning hours, consistent with the life cycle of mesoscale conjective systems (MCSs). Apparent heating (Q 1) profiles were constructed for each regime assuming the vertical advection of dry static energy was the dominant forcing term. The resulting profiles show a peak centered near 8 km in the convective regions of both regimes, although the ER has a broader maximum compared to the WR. The breadth of the ER diabatic heating peak is consistent with the more dominant role of ice processes in ER convection.
Abstract
Dual-Doppler radar data from the Tropical Rainfall Measuring Mission Large Scale Biosphere–Atmosphere Experiment in Amazonia (TRMM-LBA) field campaign are used to determine characteristic kinematic and reflectivity vertical structures associated with precipitation features observed during the wet season in the southwest region of Amazonia. Case studies of precipitating systems during TRMM-LBA as well as overarching satellite studies have shown large differences in convective intensity associated with changes that develop in low-level easterly flow [east regime (ER)] and westerly flow [west regime (WR)]. This study attempts to examine the vertical kinematic and heating structure of convection across the spectrum of precipitation features that occurred in each regime.
Results show that convection in the ER is characterized by more intense updrafts and larger radar reflectivities above the melting level, in agreement with results from lightning detection networks. These regime differences are consistent with contrasts in composite thermal buoyancy between the regimes: above the boundary layer, the environment in the ER is characterized by a greater virtual temperature excess for near-surface rising parcels. Both regimes showed a peak in intensity during the late afternoon hours, as evidenced by radar reflectivity and kinematic characteristics, consistent with previous studies of rainfall and lightning in the Rondônia (TRMM-LBA) region. After sunset, however, convective intensity in the WR decreases much more abruptly compared to the ER. In the stratiform–weak convective region, the ER showed both reflectivity and kinematic characteristics of classic stratiform structure after sunset through the early morning hours, consistent with the life cycle of mesoscale conjective systems (MCSs). Apparent heating (Q 1) profiles were constructed for each regime assuming the vertical advection of dry static energy was the dominant forcing term. The resulting profiles show a peak centered near 8 km in the convective regions of both regimes, although the ER has a broader maximum compared to the WR. The breadth of the ER diabatic heating peak is consistent with the more dominant role of ice processes in ER convection.
