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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 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
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
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.
Abstract
Contibutions of divergent and rotational wind components to the synoptic-scale kinetic energy balance are described using rawinsonde data at 3 and 6 h intervals from NASA’s fourth Atmospheric Variability Experiment (AVE 4). Two intense thunderstorm complexes occurred during the period. Energy budgets am described for the entire computational region and for limited volumes that enclosed storm-induced, upper-level wind maxima touted poleward of the convection.
Although small in magnitude, the divergent wind component played an important role in the cross-contour generation and horizontal flux divergence of kinetic energy. The importance of V D appears directly related to the presence and intensity of convection. Although K D usually comprised lm than 10% of the total kinetic energy content generation of kinetic energy by V D was a major factor in the creation of upper-level wind maxima to the north of the storm complexes. Omission of the divergent wind apparently would lead to serious misrepresentations of the energy balance. A random error analysis is presented to assess confidence limits in the various energy parameters.
Abstract
Contibutions of divergent and rotational wind components to the synoptic-scale kinetic energy balance are described using rawinsonde data at 3 and 6 h intervals from NASA’s fourth Atmospheric Variability Experiment (AVE 4). Two intense thunderstorm complexes occurred during the period. Energy budgets am described for the entire computational region and for limited volumes that enclosed storm-induced, upper-level wind maxima touted poleward of the convection.
Although small in magnitude, the divergent wind component played an important role in the cross-contour generation and horizontal flux divergence of kinetic energy. The importance of V D appears directly related to the presence and intensity of convection. Although K D usually comprised lm than 10% of the total kinetic energy content generation of kinetic energy by V D was a major factor in the creation of upper-level wind maxima to the north of the storm complexes. Omission of the divergent wind apparently would lead to serious misrepresentations of the energy balance. A random error analysis is presented to assess confidence limits in the various energy parameters.
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
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.
