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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
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.
Abstract
Operational VAS satellite retrievals and derived parameters used in forecasting severe local storms were evaluated against corresponding radiosonde values. VAS products also were compared with the first-guess input to the retrieval algorithm. The evaluation methodology was to pair each radiosonde observation (RAOB) with the closest VAS retrieval within 50 km during a 4-month period in 1986.
VAS temperatures wore found to agree closely with radiosonde values; however, VAS dewpoints showed somewhat less agreement. VAS/RAOB sounding differences were poorly correlated with the number of pixels from which the retrievals were prepared. VAS discrepancies usually wore not well correlated with first-guess errors. A disappointing finding is that the retrievals degraded the first guess about as often as they improved it. VAS did tend to improve large first-guess errors, but not even this was guaranteed. Horizontal gradients of VAS products generally were stronger than those from radiosondes. VAS precipitable water agreed better with the ground truth than did dewpoints at individual levels, but VAS thicknesses were not much improved over the already accurate VAS temperatures.
Results for the severe storms forecasting parameters indicated that VAS/RAOB discrepancies increased with the amount of manipulation required during computation. VAS parameters incorporating observed surface data tended to give better results than those that did not. Of all the parameters examined, VAS-derived lifted index exhibited the best agreement with RAOB versions. VAS positive buoyant energy showed disappointingly poor comparisons. VAS retrievals provided poor measures of the low-level negative buoyant energy that must be overcome before convection can begin. Agreements between VAS/RAOB versions of the K index, total totals index, Showalter index, and several other parameters were intermediate to those of positive buoyant energy and lifted index.
Abstract
Operational VAS satellite retrievals and derived parameters used in forecasting severe local storms were evaluated against corresponding radiosonde values. VAS products also were compared with the first-guess input to the retrieval algorithm. The evaluation methodology was to pair each radiosonde observation (RAOB) with the closest VAS retrieval within 50 km during a 4-month period in 1986.
VAS temperatures wore found to agree closely with radiosonde values; however, VAS dewpoints showed somewhat less agreement. VAS/RAOB sounding differences were poorly correlated with the number of pixels from which the retrievals were prepared. VAS discrepancies usually wore not well correlated with first-guess errors. A disappointing finding is that the retrievals degraded the first guess about as often as they improved it. VAS did tend to improve large first-guess errors, but not even this was guaranteed. Horizontal gradients of VAS products generally were stronger than those from radiosondes. VAS precipitable water agreed better with the ground truth than did dewpoints at individual levels, but VAS thicknesses were not much improved over the already accurate VAS temperatures.
Results for the severe storms forecasting parameters indicated that VAS/RAOB discrepancies increased with the amount of manipulation required during computation. VAS parameters incorporating observed surface data tended to give better results than those that did not. Of all the parameters examined, VAS-derived lifted index exhibited the best agreement with RAOB versions. VAS positive buoyant energy showed disappointingly poor comparisons. VAS retrievals provided poor measures of the low-level negative buoyant energy that must be overcome before convection can begin. Agreements between VAS/RAOB versions of the K index, total totals index, Showalter index, and several other parameters were intermediate to those of positive buoyant energy and lifted index.
Abstract
Synoptic-scale kinetic energy budgets are computed using 3 and 6 h rawinsonde data during a period of intense convective activity. Modification by the storms of their surrounding synoptic-scale environments is determined by calculating budgets over limited volumes that just enclose two squall lines.
Large generation of kinetic energy is associated with areas of convection. Of particular interest is major transport of kinetic energy out of the volumes near the level of the jet stream. Kinetic energy generated in the lower levels of the storm environments is carried aloft by large-scale upward vertical motion. Transfer of kinetic energy from grid to subgrid scales of motion leads to a loss of energy in the storm environment.
Temporal variations in the generation, flux divergence and dissipation terms of the kinetic energy budget are related to the life cycles of the squall lines. Maximum energy conversion and transport occur near the time of maximum storm intensity while smaller values are observed during the development and decay stages. Spatial fields of the energy terms show that the most intense energy processes occurring during the period are associated with the squall lines. The energy fields move with the squall line and synoptic map features.
Abstract
Synoptic-scale kinetic energy budgets are computed using 3 and 6 h rawinsonde data during a period of intense convective activity. Modification by the storms of their surrounding synoptic-scale environments is determined by calculating budgets over limited volumes that just enclose two squall lines.
Large generation of kinetic energy is associated with areas of convection. Of particular interest is major transport of kinetic energy out of the volumes near the level of the jet stream. Kinetic energy generated in the lower levels of the storm environments is carried aloft by large-scale upward vertical motion. Transfer of kinetic energy from grid to subgrid scales of motion leads to a loss of energy in the storm environment.
Temporal variations in the generation, flux divergence and dissipation terms of the kinetic energy budget are related to the life cycles of the squall lines. Maximum energy conversion and transport occur near the time of maximum storm intensity while smaller values are observed during the development and decay stages. Spatial fields of the energy terms show that the most intense energy processes occurring during the period are associated with the squall lines. The energy fields move with the squall line and synoptic map features.
Abstract
An analysis is conducted to assess the sensitivity of kinematic parameters to random errors contained in rawinsonde data. Parameters considered are relative vorticity, vorticity advection, horizontal divergence, kinematic vertical motion and temperature advection. Input data are from the AYE-SESAME I experiment which coincides with the Red River Valley tornado outbreak (10–11 April 1979). National Weather Service rawinsonde data describe the effects of data errors on the synoptic scale, while the addition of 16 special sites permits a description of sensitivity on the meso-α scale.
Qualitative and quantitative analyses show that horizontal divergence is the most affected of the parameters studied, while vorticity advection ranks second. At 850, 500 and 300 mb, assumed data errors do not preclude detection of the major forcing processes associated with the tornado outbreak. Although the two scales of analysis respond somewhat differently to the data perturbations, fields from both sets of data usually show the same major features.
Abstract
An analysis is conducted to assess the sensitivity of kinematic parameters to random errors contained in rawinsonde data. Parameters considered are relative vorticity, vorticity advection, horizontal divergence, kinematic vertical motion and temperature advection. Input data are from the AYE-SESAME I experiment which coincides with the Red River Valley tornado outbreak (10–11 April 1979). National Weather Service rawinsonde data describe the effects of data errors on the synoptic scale, while the addition of 16 special sites permits a description of sensitivity on the meso-α scale.
Qualitative and quantitative analyses show that horizontal divergence is the most affected of the parameters studied, while vorticity advection ranks second. At 850, 500 and 300 mb, assumed data errors do not preclude detection of the major forcing processes associated with the tornado outbreak. Although the two scales of analysis respond somewhat differently to the data perturbations, fields from both sets of data usually show the same major features.
Abstract
Kinetic energy budgets are computed during a cold air outbreak in association with strong jet stream activity over the eastern United States. The period is characterized by large generation of kinetic energy due to cross-contour flow. Horizontal export and dissipation of energy to subgrid scales of motion constitute the important energy sinks.
Rawinsonde data at 3 and 6 h intervals during a 36 h period are used in the analysis and reveal that energy fluctuations on a time scale of less than 12 h are generally small even though the overall energy balance does change considerably during the period in conjunction with an upper level trough which moves through the region. An error analysis of the energy budget terms suggests that this major change in the budget is not due to random errors in the input data but is caused by the changing synoptic situation. The study illustrates the need to consider the time and space scales of associated weather phenomena in interpreting energy budgets obtained through use of higher frequency data.
Abstract
Kinetic energy budgets are computed during a cold air outbreak in association with strong jet stream activity over the eastern United States. The period is characterized by large generation of kinetic energy due to cross-contour flow. Horizontal export and dissipation of energy to subgrid scales of motion constitute the important energy sinks.
Rawinsonde data at 3 and 6 h intervals during a 36 h period are used in the analysis and reveal that energy fluctuations on a time scale of less than 12 h are generally small even though the overall energy balance does change considerably during the period in conjunction with an upper level trough which moves through the region. An error analysis of the energy budget terms suggests that this major change in the budget is not due to random errors in the input data but is caused by the changing synoptic situation. The study illustrates the need to consider the time and space scales of associated weather phenomena in interpreting energy budgets obtained through use of higher frequency data.
Abstract
Time tendencies of operationally prepared Visible-Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) retrievals and derived products are evaluated by comparing them against corresponding tendencies from radiosonde soundings. Temperature and dewpoint trends from the two sources are compared, as are trends of thickness and precipitable water. VAS retrieval tendencies also are compared with those of the first-guess limited-area fine-mesh model (LFM) input to determine relationships and/or improvements. Time intervals of 6 h receive the greatest attention; however, 3- and 9-h periods also are considered.
Agreements between VAS and radiosonde observation (RAOB) trends generally are found to be very poor, with correlations between two versions usually less than .5. VAS trends compare less favorably with the “ground truth” than do trends of LFM data, which served as first guess. VAS-RAOB trends of vertically integrated parameters, that is, thickness and precipitable water, agree somewhat better than those of temperature and dewpoint, but correlations still are very poor. In evaluating 3-, 6-, and 9-h intervals, statistical agreements between VAS and radiosonde trends are found to improve considerably with increasing time intervals. VAS trends are found to degrade the first-guess (LFM) trend about as often as they improve it.
Abstract
Time tendencies of operationally prepared Visible-Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) retrievals and derived products are evaluated by comparing them against corresponding tendencies from radiosonde soundings. Temperature and dewpoint trends from the two sources are compared, as are trends of thickness and precipitable water. VAS retrieval tendencies also are compared with those of the first-guess limited-area fine-mesh model (LFM) input to determine relationships and/or improvements. Time intervals of 6 h receive the greatest attention; however, 3- and 9-h periods also are considered.
Agreements between VAS and radiosonde observation (RAOB) trends generally are found to be very poor, with correlations between two versions usually less than .5. VAS trends compare less favorably with the “ground truth” than do trends of LFM data, which served as first guess. VAS-RAOB trends of vertically integrated parameters, that is, thickness and precipitable water, agree somewhat better than those of temperature and dewpoint, but correlations still are very poor. In evaluating 3-, 6-, and 9-h intervals, statistical agreements between VAS and radiosonde trends are found to improve considerably with increasing time intervals. VAS trends are found to degrade the first-guess (LFM) trend about as often as they improve it.
