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- Author or Editor: Henry E. Fuelberg x
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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
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
This study develops and evaluates a statistical scheme for forecasting warm-season lightning over Florida. Four warm seasons of analysis data from the Rapid Update Cycle (RUC) and lightning data from the National Lightning Detection Network are used in a perfect prognosis technique to develop a high-resolution, gridded forecast guidance product for warm-season cloud-to-ground (CG) lightning over Florida. The most important RUC-derived parameters are used to develop equations producing 3-hourly spatial probability forecasts for one or more CG flashes, as well as the probability of exceeding various flash count percentile thresholds. Binary logistic regression is used to develop the equations for one or more flashes, while a negative binomial model is used to predict the amount of lightning, conditional on one or more flashes occurring. The scheme is applied to output from three mesoscale models during an independent test period (the 2006 warm season). The evaluation is performed using output from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13), the NCEP 12-km North American Mesoscale Model, and local high-resolution runs of the Weather Research and Forecasting (WRF) Model for a domain over south Florida. Forecasts from all three mesoscale models generally show positive skill through the 2100–2359 UTC period with respect to a model containing only climatology and persistence (L-CLIPER) and persistence alone. A forecast example using the high-resolution WRF Model is shown for 16–17 August 2006. Although the exact timing and placement of forecast lightning are not perfect, there generally is good agreement between the forecasts and their verification, with most of the observed lightning occurring within the higher forecast probability contours.
Abstract
This study develops and evaluates a statistical scheme for forecasting warm-season lightning over Florida. Four warm seasons of analysis data from the Rapid Update Cycle (RUC) and lightning data from the National Lightning Detection Network are used in a perfect prognosis technique to develop a high-resolution, gridded forecast guidance product for warm-season cloud-to-ground (CG) lightning over Florida. The most important RUC-derived parameters are used to develop equations producing 3-hourly spatial probability forecasts for one or more CG flashes, as well as the probability of exceeding various flash count percentile thresholds. Binary logistic regression is used to develop the equations for one or more flashes, while a negative binomial model is used to predict the amount of lightning, conditional on one or more flashes occurring. The scheme is applied to output from three mesoscale models during an independent test period (the 2006 warm season). The evaluation is performed using output from the National Centers for Environmental Prediction (NCEP) 13-km RUC (RUC13), the NCEP 12-km North American Mesoscale Model, and local high-resolution runs of the Weather Research and Forecasting (WRF) Model for a domain over south Florida. Forecasts from all three mesoscale models generally show positive skill through the 2100–2359 UTC period with respect to a model containing only climatology and persistence (L-CLIPER) and persistence alone. A forecast example using the high-resolution WRF Model is shown for 16–17 August 2006. Although the exact timing and placement of forecast lightning are not perfect, there generally is good agreement between the forecasts and their verification, with most of the observed lightning occurring within the higher forecast probability contours.
Abstract
Sixteen years of cloud-to-ground lightning data from the National Lightning Detection Network and morning radiosonde-derived parameters are used to develop a statistical scheme to provide improved forecast guidance for warm season afternoon and evening lightning for 11 areas of the Florida peninsula serviced by Florida Power and Light Corporation (FPL). Logistic regression techniques are used to develop equations predicting whether at least one flash will occur during the noon–midnight period in each area, as well as the amount of lightning that can be expected during this same period, conditional on at least one flash occurring. For the amount of lightning, the best results are achieved by creating four quartile categories of flash count based on climatology, and then using three logistic equations and a decision tree approach to determine the most likely quartile. A combination of forward stepwise screening and cross validation are used to select the best combination of predictors that are most likely to generalize to independent data. Results show the guidance equations to be superior to persistence on both the dependent dataset and during cross validation. The greatest skill scores are achieved for predicting whether at least one flash will occur, as well as predicting the number of flashes to within one quartile of that observed. These results demonstrate that the equations possess forecast skill and will provide useful guidance for the probability and amount of lightning in each of the 11 FPL service areas.
Abstract
Sixteen years of cloud-to-ground lightning data from the National Lightning Detection Network and morning radiosonde-derived parameters are used to develop a statistical scheme to provide improved forecast guidance for warm season afternoon and evening lightning for 11 areas of the Florida peninsula serviced by Florida Power and Light Corporation (FPL). Logistic regression techniques are used to develop equations predicting whether at least one flash will occur during the noon–midnight period in each area, as well as the amount of lightning that can be expected during this same period, conditional on at least one flash occurring. For the amount of lightning, the best results are achieved by creating four quartile categories of flash count based on climatology, and then using three logistic equations and a decision tree approach to determine the most likely quartile. A combination of forward stepwise screening and cross validation are used to select the best combination of predictors that are most likely to generalize to independent data. Results show the guidance equations to be superior to persistence on both the dependent dataset and during cross validation. The greatest skill scores are achieved for predicting whether at least one flash will occur, as well as predicting the number of flashes to within one quartile of that observed. These results demonstrate that the equations possess forecast skill and will provide useful guidance for the probability and amount of lightning in each of the 11 FPL service areas.
Abstract
A Limited Area Mesoscale Prediction System (LAMPS) model simulation and special 3-hour radiosonde dataset are used to investigate warm (dry) bands in 6,7 μm water vapor satellite imagery on 6–7 March 1982. The purpose is to reveal processes resulting in the formation and evolution of the dry features that appear as curving dark streaks in the imagery. Model soundings are input to a radiative transfer algorithm to generate synthetic 6.7 μm equivalent blackbody temperatures (TB ) which are compared with those from the Visible infrared Spin Scan Radiometer Atmospheric Sounder aboard the Geostationary Operational Environmental Satellite. Simulated and radiosonde-derived vertical velocity and humidity also are compared with the images. Finally, trajectories are calculated from both radiosonde data and LAMPS output.
The model reproduces major characteristics of the observed TB field. A “development” dry image feature occurs in conjunction with an upper level shortwave trough, and an “advective” feature is associated with a polar jet streak. Both model and observed TB features are associated with vorticity maxima. The development feature forms as moisture gradients are enhanced by differential subsidence early in the study period. Horizontal wind shear then narrows the incipient dry area into its streak-like shape. Trajectories reveal that air parcels ending in the development streak move with it, in northwesterly, subsiding flow throughout the study period. Near the leading edge of the streak, ahead of the short-wave trough, flow is southwesterly and ascending. Air parcels in the advective image feature sink in the wake of the vorticity maximum, move through it in the jet flow, and finally ascend ahead of it. Thus, warm TB regions do not equate with instantaneous subsidence patterns, but reflect a long history of parcel motions which can include ascent as well.
Abstract
A Limited Area Mesoscale Prediction System (LAMPS) model simulation and special 3-hour radiosonde dataset are used to investigate warm (dry) bands in 6,7 μm water vapor satellite imagery on 6–7 March 1982. The purpose is to reveal processes resulting in the formation and evolution of the dry features that appear as curving dark streaks in the imagery. Model soundings are input to a radiative transfer algorithm to generate synthetic 6.7 μm equivalent blackbody temperatures (TB ) which are compared with those from the Visible infrared Spin Scan Radiometer Atmospheric Sounder aboard the Geostationary Operational Environmental Satellite. Simulated and radiosonde-derived vertical velocity and humidity also are compared with the images. Finally, trajectories are calculated from both radiosonde data and LAMPS output.
The model reproduces major characteristics of the observed TB field. A “development” dry image feature occurs in conjunction with an upper level shortwave trough, and an “advective” feature is associated with a polar jet streak. Both model and observed TB features are associated with vorticity maxima. The development feature forms as moisture gradients are enhanced by differential subsidence early in the study period. Horizontal wind shear then narrows the incipient dry area into its streak-like shape. Trajectories reveal that air parcels ending in the development streak move with it, in northwesterly, subsiding flow throughout the study period. Near the leading edge of the streak, ahead of the short-wave trough, flow is southwesterly and ascending. Air parcels in the advective image feature sink in the wake of the vorticity maximum, move through it in the jet flow, and finally ascend ahead of it. Thus, warm TB regions do not equate with instantaneous subsidence patterns, but reflect a long history of parcel motions which can include ascent as well.
Abstract
Structure and correlation functions are used to describe atmospheric variability during the 10–11 April day of AVE–SESAME 1979 that coincided with the Red River Valley tornado outbreak. The special mesoscale rawinsonde data are employed in calculations involving temperature, geopotential height, horizontal wind speed and mixing ratio. Functional analyses are performed in both the lower and upper troposphere for the composite 24 h experiment period and at individual 3 h observation times.
Results show that mesoscale features are prominent during the composite period. Fields of mixing ratio and horizontal wind speed exhibit the greatest amounts of small-scale variance, whereas temperature and geopotential height contain the least. Results for the nine individual times show that small-scale variance is greatest during the convective outbreak. The functions also are used to estimate random errors in the rawinsonde data. Finally, sensitivity analyses are presented to quantify confidence limits of the structure functions.
Abstract
Structure and correlation functions are used to describe atmospheric variability during the 10–11 April day of AVE–SESAME 1979 that coincided with the Red River Valley tornado outbreak. The special mesoscale rawinsonde data are employed in calculations involving temperature, geopotential height, horizontal wind speed and mixing ratio. Functional analyses are performed in both the lower and upper troposphere for the composite 24 h experiment period and at individual 3 h observation times.
Results show that mesoscale features are prominent during the composite period. Fields of mixing ratio and horizontal wind speed exhibit the greatest amounts of small-scale variance, whereas temperature and geopotential height contain the least. Results for the nine individual times show that small-scale variance is greatest during the convective outbreak. The functions also are used to estimate random errors in the rawinsonde data. Finally, sensitivity analyses are presented to quantify confidence limits of the structure functions.
Fields of divergence, vertical motion, stability, and surface pressure tendency are examined at 3 h intervals for the first regional scale AVE-SESAME '79 (Atmospheric Variability Experiment—Severe Environmental Storms and Mesoscale Experiment) day. Two areas of severe storms formed during the period from 1200 GMT 10 April through 1200 GMT 11 April. The Red River Valley outbreak began during the afternoon of 10 April, while a second area formed in southwestern Texas during the early evening hours. Results show the rapid changes in environmental conditions associated with these two storm areas.
The propagation of an upper level jet streak into the region was a major factor in producing the Red River Valley outbreak. This streak was associated with the formation of a strong low-level jet and a small-scale surface pressure perturbation. The sudden development of a strong upper tropospheric wind maximum over Oklahoma and Kansas corresponded with major changes in kinematic parameters at that level. Instability over the Red River Valley was released by strong upward motion producing intense convection.
Similar features were responsible for the storms in southwestern Texas. Although this area was quite unstable, forcing mechanisms appear somewhat weaker than in the earlier outbreak.
Fields of divergence, vertical motion, stability, and surface pressure tendency are examined at 3 h intervals for the first regional scale AVE-SESAME '79 (Atmospheric Variability Experiment—Severe Environmental Storms and Mesoscale Experiment) day. Two areas of severe storms formed during the period from 1200 GMT 10 April through 1200 GMT 11 April. The Red River Valley outbreak began during the afternoon of 10 April, while a second area formed in southwestern Texas during the early evening hours. Results show the rapid changes in environmental conditions associated with these two storm areas.
The propagation of an upper level jet streak into the region was a major factor in producing the Red River Valley outbreak. This streak was associated with the formation of a strong low-level jet and a small-scale surface pressure perturbation. The sudden development of a strong upper tropospheric wind maximum over Oklahoma and Kansas corresponded with major changes in kinematic parameters at that level. Instability over the Red River Valley was released by strong upward motion producing intense convection.
Similar features were responsible for the storms in southwestern Texas. Although this area was quite unstable, forcing mechanisms appear somewhat weaker than in the earlier outbreak.
Abstract
Polarimetric radar data are used to develop lightning cessation guidance for the Cape Canaveral area of central Florida. For this purpose, 80 nonsevere thunderstorm cells in 2012, mostly during the warm season, are analyzed. In-cloud and cloud-to-ground lightning data for the storms are obtained by combining information from the second-generation Lightning Detection and Ranging (LDAR-II) network and the National Lightning Detection Network (NLDN). Storms are tracked using the Warning Decision Support System–Integrated Information (WDSS-II) software, producing time series of radar- and lightning-derived parameters. The 80 storms are split into two categories: 1) 50 isolated storms whose lightning initiation sources are confined to the core or anvil region of the storm and 2) 30 nonisolated cells whose lightning channels are initiated in a nearby active storm and extended to the dissipating study cell. Trends in polarimetric radar parameters at different temperature levels are studied for 40 of the 50 isolated storms to develop cessation guidance. Results based on a completely independent sample of 10 storms reveal that the best-performing cessation algorithm utilizes the presence of graupel and horizontal reflectivity ≥35 dBZ at the −10°C temperature altitude. Lightning is not expected 10 min after both thresholds are no longer met. However, this relationship does not apply to nonisolated cells because a neighboring storm could still be electrically active. Results show that a stratiform cloud region connecting the decaying storm to an active storm might facilitate further channel propagation that might not have occurred otherwise. Thus, the proposed cessation guidelines are not recommended for nonisolated cells.
Abstract
Polarimetric radar data are used to develop lightning cessation guidance for the Cape Canaveral area of central Florida. For this purpose, 80 nonsevere thunderstorm cells in 2012, mostly during the warm season, are analyzed. In-cloud and cloud-to-ground lightning data for the storms are obtained by combining information from the second-generation Lightning Detection and Ranging (LDAR-II) network and the National Lightning Detection Network (NLDN). Storms are tracked using the Warning Decision Support System–Integrated Information (WDSS-II) software, producing time series of radar- and lightning-derived parameters. The 80 storms are split into two categories: 1) 50 isolated storms whose lightning initiation sources are confined to the core or anvil region of the storm and 2) 30 nonisolated cells whose lightning channels are initiated in a nearby active storm and extended to the dissipating study cell. Trends in polarimetric radar parameters at different temperature levels are studied for 40 of the 50 isolated storms to develop cessation guidance. Results based on a completely independent sample of 10 storms reveal that the best-performing cessation algorithm utilizes the presence of graupel and horizontal reflectivity ≥35 dBZ at the −10°C temperature altitude. Lightning is not expected 10 min after both thresholds are no longer met. However, this relationship does not apply to nonisolated cells because a neighboring storm could still be electrically active. Results show that a stratiform cloud region connecting the decaying storm to an active storm might facilitate further channel propagation that might not have occurred otherwise. Thus, the proposed cessation guidelines are not recommended for nonisolated cells.
