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Henry E. Fuelberg
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Henry E. Fuelberg and James E. Hoke
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Phillip E. Shafer and Henry E. Fuelberg

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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.

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Phillip E. Shafer and Henry E. Fuelberg

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.

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Dennis E. Buechler and Henry E. Fuelberg

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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.

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Henry E. Fuelberg and Dennis E. Buechler

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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.

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Carol L. Belt and Henry E. Fuelberg

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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.

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Henry E. Fuelberg and Paul J. Meyer

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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.

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Henry E. Fuelberg and Matthew F. Printy

Meso β-scale rawinsonde data from the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) V period (20–21 May 1979) are used to diagnose atmospheric variability in the environment of a convective area. As the storms developed, temperatures increased in the upper stratosphere; however, cooling was observed nearer to the surface and in the lower stratosphere. Height rises above 400 mb produced a mesohigh over the convective area that was most pronounced near 200 mb. Weaker height falls occurred in the lower troposphere.

Wind patterns underwent especially interesting fluctuations. North of the convective area, upper-level winds increased significantly during storm development. Southeast of the convection, however, winds near 200 mb decreased approximately 50% during a 3 h period coinciding with the most active storms. On the other hand, winds at 400 mb almost doubled during the same 3 h period. Strong low-level convergence, upper-level divergence, and ascending motion developed after storm initiation.

Much more detailed study is required to understand this fascinating case. However, many of the current findings about the meso β-scale storm environment are consistent with those previously attributed to feedback mechanisms from severe thunderstorms.

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Scott D. Rudlosky and Henry E. Fuelberg

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Seasonal, regional, and storm-scale variations of cloud-to-ground (CG) lightning characteristics in Florida are presented. Strong positive CG (+CG) and negative CG (−CG) flashes (i.e., having large peak current) are emphasized since they often are associated with strong storms, structural damage, and wildfire ignitions. Although strong −CG flashes are most common during the warm season (May–September) over the peninsula, the greatest proportion of strong +CG flashes occurs during the cool season (October–April) over the panhandle. The warm season exhibits the smallest +CG percentage but contains the greatest +CG flash densities, due in part to more ambiguous +CG reports (15–20 kA). The more frequent occurrence of ambiguous +CG reports helps explain the unusually small average +CG peak current during the warm season, whereas strong +CG reports (>20 kA) appear to be responsible for the greater average warm season +CG multiplicity. The −CG flash density, multiplicity, and peak current appear to be directly related, exhibiting their greatest values during the warm season when deep storms are most common. A case study examines the atmospheric conditions and storm-scale processes associated with two distinct groups of storms on 13–14 May 2007. Although these groups of storms form in close proximity, several factors combine to produce predominately strong +CG and −CG flashes in the northern (south Georgia) and southern (north Florida) regions, respectively. Results suggest that heat and smoke very near preexisting wildfires are key ingredients in producing reversed-polarity (+CG dominated) storms that often ignite subsequent wildfires.

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