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- Author or Editor: Dennis Buechler x
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Abstract
The effects of echo shape and radar viewing angle on detecting small thunderstorms with the NEXRAD storm identification algorithms are examined. The amorphous low level echo shapes are modeled as ellipses with major axes ranging from 5–15 km and minor axes varying between 2–5 km. The model echoes are then used to create a “probability of detection” chart that demonstrates the impact of storm asymmetry on cell identification. Moreover, we examine the algorithm performance on small thunderstorms observed near Huntsville, Alabama and Kennedy Space Center, Florida. The two thunderstorms observed near Huntsville also produced microbursts. The probability of storm detection using the NEXRAD default values for both Huntsville cases is less than 0,5 at the time of the first lightning discharge and less than 0.4 at microbursts onset. The Kennedy Space Center storms were already electrically active when the probability of detection was 0.5 or less. A new algorithm based on the analysis of 15 storms observed in Florida, Alabama and New Mexico is proposed that would identify storms as having Lightning if 40 dBZ reflectivity is present at the −10°C level and the echo top exceeds 9 km. This algorithm would have a 100% probability of detecting lightning producing storms 4–33 min before the first flash, a 7% false alarm rate and a critical success index of 93%.
Abstract
The effects of echo shape and radar viewing angle on detecting small thunderstorms with the NEXRAD storm identification algorithms are examined. The amorphous low level echo shapes are modeled as ellipses with major axes ranging from 5–15 km and minor axes varying between 2–5 km. The model echoes are then used to create a “probability of detection” chart that demonstrates the impact of storm asymmetry on cell identification. Moreover, we examine the algorithm performance on small thunderstorms observed near Huntsville, Alabama and Kennedy Space Center, Florida. The two thunderstorms observed near Huntsville also produced microbursts. The probability of storm detection using the NEXRAD default values for both Huntsville cases is less than 0,5 at the time of the first lightning discharge and less than 0.4 at microbursts onset. The Kennedy Space Center storms were already electrically active when the probability of detection was 0.5 or less. A new algorithm based on the analysis of 15 storms observed in Florida, Alabama and New Mexico is proposed that would identify storms as having Lightning if 40 dBZ reflectivity is present at the −10°C level and the echo top exceeds 9 km. This algorithm would have a 100% probability of detecting lightning producing storms 4–33 min before the first flash, a 7% false alarm rate and a critical success index of 93%.
Abstract
Budgets of divergent and rotational components of kinetic energy (KD and KR) are examined for four upper level wind speed maxima that develop during the fourth Atmospheric Variability Experiment (AVE IV) and the first AVE-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME I). A similar budget analysis for a low-level jet stream during AVE-SESAME I also is performed. Special radiosonde data at 3 or 6 h intervals and mesoscale horizontal spacing (AVE-SESAME I only) are a major advantage to the cases selected. Previous studies have attributed the development of upper level wind maxima during AVE IV to the presence of mesoscale convective complexes. They appear to be similarly formed, or at least enhanced, during the SESAME case; however, strong preexisting dynamics and less reliable wind data make the determination more difficult.
The energetics of the four upper level speed maxima is found to have several similarities. The dominant source of KD is cross-contour flow by the divergent wind, and KD provides a major source of KR via a conversion process. Conversion from available potential energy provides an additional source of KR in three of the cases. Horizontal maps reveal that the conversions involving KD are maximized in regions poleward of the convection, i.e., where the speed maxima form.
Low level jet development during AVE-SESAME I appears to be assisted by convective activity to the west. Enhanced low level convergence produces conversion from available potential energy to KD and then to KR. These aspects are similar to those occurring in the upper-level speed maxima.
Abstract
Budgets of divergent and rotational components of kinetic energy (KD and KR) are examined for four upper level wind speed maxima that develop during the fourth Atmospheric Variability Experiment (AVE IV) and the first AVE-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME I). A similar budget analysis for a low-level jet stream during AVE-SESAME I also is performed. Special radiosonde data at 3 or 6 h intervals and mesoscale horizontal spacing (AVE-SESAME I only) are a major advantage to the cases selected. Previous studies have attributed the development of upper level wind maxima during AVE IV to the presence of mesoscale convective complexes. They appear to be similarly formed, or at least enhanced, during the SESAME case; however, strong preexisting dynamics and less reliable wind data make the determination more difficult.
The energetics of the four upper level speed maxima is found to have several similarities. The dominant source of KD is cross-contour flow by the divergent wind, and KD provides a major source of KR via a conversion process. Conversion from available potential energy provides an additional source of KR in three of the cases. Horizontal maps reveal that the conversions involving KD are maximized in regions poleward of the convection, i.e., where the speed maxima form.
Low level jet development during AVE-SESAME I appears to be assisted by convective activity to the west. Enhanced low level convergence produces conversion from available potential energy to KD and then to KR. These aspects are similar to those occurring in the upper-level speed maxima.
Abstract
Budgets of divergent and rotational components of kinetic energy (KD and KR) are investigated for two periods of intense convection. Derivations of the budget equations are presented for limited volumes in terms of VD and VR . The two periods being studied are AVE IV (synoptic scale data at 3 or 6 h intervals) and AVE-SESAME 1 (meso α-male data every 3 h). Energetics are presented for each composite period, and for individual observation times. Two types of sensitivity analyses establish confidence limits in the energy parameters.
Results from the two cases exhibit many similarities. The most striking are major increases in KD (which is generally quite small) and its budget terms with convective development. During storm activity, major sources of KD are provided by divergent cross-contour generation and dissipation. The major difference between the cases is the opposite conversion between KD and KR. This is due to differing contributions of the various conversion components which arise from the different scales of data and synoptic settings. Current findings for the convective environment contrast ready with those for larger areas and longer times. Also, results emphasize that proper representation of convectively active areas at smaller scales requires numerical models that adequately describe the energetics involving KD.
Abstract
Budgets of divergent and rotational components of kinetic energy (KD and KR) are investigated for two periods of intense convection. Derivations of the budget equations are presented for limited volumes in terms of VD and VR . The two periods being studied are AVE IV (synoptic scale data at 3 or 6 h intervals) and AVE-SESAME 1 (meso α-male data every 3 h). Energetics are presented for each composite period, and for individual observation times. Two types of sensitivity analyses establish confidence limits in the energy parameters.
Results from the two cases exhibit many similarities. The most striking are major increases in KD (which is generally quite small) and its budget terms with convective development. During storm activity, major sources of KD are provided by divergent cross-contour generation and dissipation. The major difference between the cases is the opposite conversion between KD and KR. This is due to differing contributions of the various conversion components which arise from the different scales of data and synoptic settings. Current findings for the convective environment contrast ready with those for larger areas and longer times. Also, results emphasize that proper representation of convectively active areas at smaller scales requires numerical models that adequately describe the energetics involving KD.
Abstract
The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite has previously been used to build climatologies of mean lightning flash rate across the global tropics and subtropics. This new work explores climatologies of thunderstorm occurrence as seen by LIS and the conditional mean flash rates when thunderstorms do occur. The region where thunderstorms are seen most often by LIS extends slightly farther east in central Africa than the corresponding region with the highest total mean annual flash rates. Presumably this reflects a difference between more frequent thunderstorm initiation in the east and upscale growth as storms move westward. There are some differences between locations with the greatest total lightning flash counts and those where thunderstorms occur most often. The greatest conditional mean flash rates—considering only those TRMM orbits that do have lightning in a given grid box—are found in subtropical regions. The highest values are in Argentina, with the central United States, Pakistan, eastern China, and the east coast of Australia also having particularly high values.
Abstract
The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite has previously been used to build climatologies of mean lightning flash rate across the global tropics and subtropics. This new work explores climatologies of thunderstorm occurrence as seen by LIS and the conditional mean flash rates when thunderstorms do occur. The region where thunderstorms are seen most often by LIS extends slightly farther east in central Africa than the corresponding region with the highest total mean annual flash rates. Presumably this reflects a difference between more frequent thunderstorm initiation in the east and upscale growth as storms move westward. There are some differences between locations with the greatest total lightning flash counts and those where thunderstorms occur most often. The greatest conditional mean flash rates—considering only those TRMM orbits that do have lightning in a given grid box—are found in subtropical regions. The highest values are in Argentina, with the central United States, Pakistan, eastern China, and the east coast of Australia also having particularly high values.
Abstract
A technique is presented for generating convective tendency products by combining satellite images with observations of cloud-to-ground lightning activity. Rapid scan (5-min) infrared satellite images are used to define the areal distribution of convection. Lightning flash rate trends provide diagnostic and predictive information pertaining to the growth and decay of the thunderstorms. A single derived product from these data can show the location of the lightning activity and convective cores, the spatial distribution of convective rainfall, the remaining cloudy and statiform rain areas, and the growing and decaying storms. Examples are given to illustrate how the flash rate trend may produce a much different and more useful portrayal of storm evolution than the time rate-of-change change of cloud-top blackbody temperatures. This difference can be exacerbated in mesoscale convective weather systems where the cirrus debris can mask the life history of the embedded convective elements.
Abstract
A technique is presented for generating convective tendency products by combining satellite images with observations of cloud-to-ground lightning activity. Rapid scan (5-min) infrared satellite images are used to define the areal distribution of convection. Lightning flash rate trends provide diagnostic and predictive information pertaining to the growth and decay of the thunderstorms. A single derived product from these data can show the location of the lightning activity and convective cores, the spatial distribution of convective rainfall, the remaining cloudy and statiform rain areas, and the growing and decaying storms. Examples are given to illustrate how the flash rate trend may produce a much different and more useful portrayal of storm evolution than the time rate-of-change change of cloud-top blackbody temperatures. This difference can be exacerbated in mesoscale convective weather systems where the cirrus debris can mask the life history of the embedded convective elements.
Abstract
The Geostationary Lightning Mapper (GLM) is an instrument designed to continuously monitor lightning. It is on the GOES-16 and GOES-17 satellites, viewing much of the Western Hemisphere equatorward of 55°. Besides recording lightning-flash information, it transmits background visible-band images of its field of view every 2.5 min. The background images are not calibrated or geolocated, and they only have ~10-km grid spacing, but their 2.5-min sampling can potentially fill temporal gaps between full-disk imagery from the GOES satellites’ Advanced Baseline Imager. This paper applies an initial calibration and geolocation of the GLM background images and focuses on animations for two cases: a volcanic eruption in Guatemala and a severe thunderstorm complex in Argentina. Those locations typically have 10-min intervals between full-disk scans. Prior to April 2019, the interval was 15 min. Despite coarse horizontal resolution, the rapid updates from GLM background images appear to be useful in these cases. The 3 June 2018 eruption of Fuego Volcano appears in the GLM background imagery as an initial darkening of the pixels very near the volcano and then an outward expansion of the dark ash cloud. The GLM background imagery lacks horizontal textural detail but compensates for this lack with temporal detail. The ash cloud resembles a dark blob steadily expanding from frame to frame. Animation of the severe thunderstorm scene reveals vertical wind shear, with northerly low-level flow across a growing cumulus field and west-northwesterly upper-level flow at anvil level. Convective initiation is seen, as are propagating outflow boundaries and overshooting convective cloud tops.
Abstract
The Geostationary Lightning Mapper (GLM) is an instrument designed to continuously monitor lightning. It is on the GOES-16 and GOES-17 satellites, viewing much of the Western Hemisphere equatorward of 55°. Besides recording lightning-flash information, it transmits background visible-band images of its field of view every 2.5 min. The background images are not calibrated or geolocated, and they only have ~10-km grid spacing, but their 2.5-min sampling can potentially fill temporal gaps between full-disk imagery from the GOES satellites’ Advanced Baseline Imager. This paper applies an initial calibration and geolocation of the GLM background images and focuses on animations for two cases: a volcanic eruption in Guatemala and a severe thunderstorm complex in Argentina. Those locations typically have 10-min intervals between full-disk scans. Prior to April 2019, the interval was 15 min. Despite coarse horizontal resolution, the rapid updates from GLM background images appear to be useful in these cases. The 3 June 2018 eruption of Fuego Volcano appears in the GLM background imagery as an initial darkening of the pixels very near the volcano and then an outward expansion of the dark ash cloud. The GLM background imagery lacks horizontal textural detail but compensates for this lack with temporal detail. The ash cloud resembles a dark blob steadily expanding from frame to frame. Animation of the severe thunderstorm scene reveals vertical wind shear, with northerly low-level flow across a growing cumulus field and west-northwesterly upper-level flow at anvil level. Convective initiation is seen, as are propagating outflow boundaries and overshooting convective cloud tops.
Abstract
The visual, radar, and lightning characteristics of a severe thunderstorm that spawned a large F3 tornado near Almena, Kansas, on 3 June 1999 are documented. The storm is interesting in that it made a transition from a low-precipitation to classic supercell then back to low-precipitation supercell again prior to dissipation after sunset. The storm remarkably produced only 17 cloud-to-ground lightning flashes during its 4.5-h lifetime, despite vertically integrated liquid (VIL) values reaching 95 kg m−2, reflectivities of 50 dBZ or greater at altitudes of 14 km, and baseball-size hail at the surface. In contrast, total lightning rates inferred from a portable lightning detector during the large tornado were very high, approximately 100 per minute, as expected for a storm of this size and intensity.
Abstract
The visual, radar, and lightning characteristics of a severe thunderstorm that spawned a large F3 tornado near Almena, Kansas, on 3 June 1999 are documented. The storm is interesting in that it made a transition from a low-precipitation to classic supercell then back to low-precipitation supercell again prior to dissipation after sunset. The storm remarkably produced only 17 cloud-to-ground lightning flashes during its 4.5-h lifetime, despite vertically integrated liquid (VIL) values reaching 95 kg m−2, reflectivities of 50 dBZ or greater at altitudes of 14 km, and baseball-size hail at the surface. In contrast, total lightning rates inferred from a portable lightning detector during the large tornado were very high, approximately 100 per minute, as expected for a storm of this size and intensity.
Abstract
Data from a single Weather Surveillance Radar-1988 Doppler (WSR-88D) and the National Lightning Detection Network are used to examine the characteristics of the convective storms that produced a severe tornado outbreak, including three tornadoes that reached F3 intensity, within Tropical Storm Beryl's remnants on 16 August 1994. Comparison of the radar data with reports of tornadoes suggests that only 13 cells produced the 29 tornadoes that were documented in Georgia and the Carolinas on that date. Six of these cells spawned multiple tornadoes, and the radar data confirm the presence of miniature supercells. One of the cells was identifiable on radar for 11 h, spawning tornadoes over a time period spanning approximately 6.5 h. Several other tornadic cells also exhibited great longevity, with cell lifetimes longer than ever previously documented in a landfalling tropical cyclone (TC) tornado event. This event is easily the most intense TC tornado outbreak yet documented with WSR-88Ds.
Time–height analyses of the three strongest tornadic supercells are presented in order to document storm kinematic structure and to show how these storms appear at different ranges from a WSR-88D. In addition, cloud-to-ground (CG) lightning data are examined in Beryl's remnants. Although the tornadic cells were responsible for most of Beryl's CG lightning, their flash rates were only weak to moderate, and in all the tornadic storms the lightning flashes were almost entirely negative in polarity. A few of the single-tornado storms produced no detectable CG lightning at all. There is evidence that CG lightning rates decreased during the tornadoes, compared to 30-min periods before the tornadoes. A number of the storms spawned tornadoes just after producing their final CG lightning flashes. Contrary to the findings for flash rates, both peak currents and positive flash percentages were larger in Beryl's nontornadic storms than in the tornadic ones.
Abstract
Data from a single Weather Surveillance Radar-1988 Doppler (WSR-88D) and the National Lightning Detection Network are used to examine the characteristics of the convective storms that produced a severe tornado outbreak, including three tornadoes that reached F3 intensity, within Tropical Storm Beryl's remnants on 16 August 1994. Comparison of the radar data with reports of tornadoes suggests that only 13 cells produced the 29 tornadoes that were documented in Georgia and the Carolinas on that date. Six of these cells spawned multiple tornadoes, and the radar data confirm the presence of miniature supercells. One of the cells was identifiable on radar for 11 h, spawning tornadoes over a time period spanning approximately 6.5 h. Several other tornadic cells also exhibited great longevity, with cell lifetimes longer than ever previously documented in a landfalling tropical cyclone (TC) tornado event. This event is easily the most intense TC tornado outbreak yet documented with WSR-88Ds.
Time–height analyses of the three strongest tornadic supercells are presented in order to document storm kinematic structure and to show how these storms appear at different ranges from a WSR-88D. In addition, cloud-to-ground (CG) lightning data are examined in Beryl's remnants. Although the tornadic cells were responsible for most of Beryl's CG lightning, their flash rates were only weak to moderate, and in all the tornadic storms the lightning flashes were almost entirely negative in polarity. A few of the single-tornado storms produced no detectable CG lightning at all. There is evidence that CG lightning rates decreased during the tornadoes, compared to 30-min periods before the tornadoes. A number of the storms spawned tornadoes just after producing their final CG lightning flashes. Contrary to the findings for flash rates, both peak currents and positive flash percentages were larger in Beryl's nontornadic storms than in the tornadic ones.
Abstract
Optical lightning observations from low-Earth orbit play an important role in our understanding of long-term global lightning trends. Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measurement Mission (TRMM) satellite (1997-2015) and International Space Station (2017-present) capture optical emissions produced by lightning. This study uses the well-documented TRMM LIS performance to determine if the ISS LIS performs well enough to bridge the gap between TRMM LIS and the new generation of Geostationary Lightning Mappers (GLMs). The average events per group and groups per flash for ISS LIS are 3.6 and 9.9, which are 25% and 10% lower than TRMM LIS, respectively. ISS LIS has 30% lower mean group energy density and 30-50% lower mean flash energy density than TRMM LIS in their common (+/−38 degree) latitude range. These differences are likely the result of larger pixel areas for ISS LIS over most of the field-of-view due to off-nadir pointing, combined with viewing obstructions and possible engineering differences. For both instruments, radiometric sensitivity decreases radially from the center of the array to the edges. ISS LIS sensitivity falls-off faster and more-variably, contributed to by the off-nadir pointing. Event energy density analysis indicate some anomalous hotspot pixels in the ISS LIS pixel array that were not present with the TRMM LIS. Despite these differences, ISS LIS provides similar parameter values to TRMM LIS with the expectation of somewhat lower lightning detection capability. In addition, recalculation of the event, group, and flash areas for both LIS datasets are strongly recommended since the archived values in the current release versions have significant errors.
Abstract
Optical lightning observations from low-Earth orbit play an important role in our understanding of long-term global lightning trends. Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measurement Mission (TRMM) satellite (1997-2015) and International Space Station (2017-present) capture optical emissions produced by lightning. This study uses the well-documented TRMM LIS performance to determine if the ISS LIS performs well enough to bridge the gap between TRMM LIS and the new generation of Geostationary Lightning Mappers (GLMs). The average events per group and groups per flash for ISS LIS are 3.6 and 9.9, which are 25% and 10% lower than TRMM LIS, respectively. ISS LIS has 30% lower mean group energy density and 30-50% lower mean flash energy density than TRMM LIS in their common (+/−38 degree) latitude range. These differences are likely the result of larger pixel areas for ISS LIS over most of the field-of-view due to off-nadir pointing, combined with viewing obstructions and possible engineering differences. For both instruments, radiometric sensitivity decreases radially from the center of the array to the edges. ISS LIS sensitivity falls-off faster and more-variably, contributed to by the off-nadir pointing. Event energy density analysis indicate some anomalous hotspot pixels in the ISS LIS pixel array that were not present with the TRMM LIS. Despite these differences, ISS LIS provides similar parameter values to TRMM LIS with the expectation of somewhat lower lightning detection capability. In addition, recalculation of the event, group, and flash areas for both LIS datasets are strongly recommended since the archived values in the current release versions have significant errors.
Abstract
Previous total lightning climatology studies using Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) observations were reported at coarse resolution (0.5°) and employed significant spatial and temporal smoothing to account for sampling limitations of TRMM’s tropical to subtropical low-Earth-orbit coverage. The analysis reported here uses a 16-yr reprocessed dataset to create a very high-resolution (0.1°) climatology with no further spatial averaging. This analysis reveals that Earth’s principal lightning hotspot occurs over Lake Maracaibo in Venezuela, while the highest flash rate density hotspot previously found at the lower 0.5°-resolution sampling was found in the Congo basin in Africa. Lake Maracaibo’s pattern of convergent windflow (mountain–valley, lake, and sea breezes) occurs over the warm lake waters nearly year-round and contributes to nocturnal thunderstorm development 297 days per year on average. These thunderstorms are very localized, and their persistent development anchored in one location accounts for the high flash rate density. Several other inland lakes with similar conditions, that is, deep nocturnal convection driven by locally forced convergent flow over a warm lake surface, are also revealed.
Africa is the continent with the most lightning hotspots, followed by Asia, South America, North America, and Australia. A climatological map of the local hour of maximum flash rate density reveals that most oceanic total lightning maxima are related to nocturnal thunderstorms, while continental lightning tends to occur during the afternoon. Most of the principal continental maxima are located near major mountain ranges, revealing the importance of local topography in thunderstorm development.
Abstract
Previous total lightning climatology studies using Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) observations were reported at coarse resolution (0.5°) and employed significant spatial and temporal smoothing to account for sampling limitations of TRMM’s tropical to subtropical low-Earth-orbit coverage. The analysis reported here uses a 16-yr reprocessed dataset to create a very high-resolution (0.1°) climatology with no further spatial averaging. This analysis reveals that Earth’s principal lightning hotspot occurs over Lake Maracaibo in Venezuela, while the highest flash rate density hotspot previously found at the lower 0.5°-resolution sampling was found in the Congo basin in Africa. Lake Maracaibo’s pattern of convergent windflow (mountain–valley, lake, and sea breezes) occurs over the warm lake waters nearly year-round and contributes to nocturnal thunderstorm development 297 days per year on average. These thunderstorms are very localized, and their persistent development anchored in one location accounts for the high flash rate density. Several other inland lakes with similar conditions, that is, deep nocturnal convection driven by locally forced convergent flow over a warm lake surface, are also revealed.
Africa is the continent with the most lightning hotspots, followed by Asia, South America, North America, and Australia. A climatological map of the local hour of maximum flash rate density reveals that most oceanic total lightning maxima are related to nocturnal thunderstorms, while continental lightning tends to occur during the afternoon. Most of the principal continental maxima are located near major mountain ranges, revealing the importance of local topography in thunderstorm development.
