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Henry E. Fuelberg
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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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Henry E. Fuelberg
and
James E. Hoke
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Henry E. Fuelberg
and
Dennis E. Buechler

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.

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Dennis E. Buechler
and
Henry E. Fuelberg

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.

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Phillip E. Shafer
and
Henry E. Fuelberg

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.

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Scott D. Rudlosky
and
Henry E. Fuelberg

Abstract

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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Scott D. Rudlosky
and
Henry E. Fuelberg

Abstract

The National Lightning Detection Network (NLDN) underwent a major upgrade during 2002–03 that increased its sensitivity and improved its performance. It is important to examine cloud-to-ground (CG) lightning distributions before and after this upgrade because CG characteristics depend on both measurement capabilities and meteorological variability. This study compares preupgrade (1996–99, 2001) and postupgrade (2004–09) CG distributions over the contiguous United States to examine the influence of the recent upgrade and to provide baseline postupgrade averages. Increased sensitivity explains most of the differences in the pre- and postupgrade distributions, including a general increase in total CG and positive CG (+CG) flash densities. The increase in +CG occurs despite the use of a greater weak +CG threshold for removing ambiguous +CG reports (post 15 kA versus pre 10 kA). Conversely, the average +CG percentage decreased from 10.61% to 8.65% following the upgrade. The average +CG (−CG) multiplicity increased from 1.10 (2.05) before to 1.54 (2.41) after the upgrade. Since true +CG flashes rarely contain more than one return stroke, explanations for the greater than unity +CG multiplicities remain unclear. Postupgrade results indicate that regions with mostly weak peak current +CG flashes now exhibit greater average +CG multiplicities, whereas regions with mainly strong +CG flashes now exhibit smaller average +CG multiplicities. The combination of NLDN performance, meteorological conditions, and physical differences in first −CG return strokes over saltwater produce maxima in −CG multiplicity and peak current over the coastal waters of the southeast United States.

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Scott D. Rudlosky
and
Henry E. Fuelberg

Abstract

Storm severity in the mid-Atlantic region of the United States is examined using lightning, radar, and model-derived information. Automated Warning Decision Support System (WDSS) procedures are developed to create grids of lightning and radar parameters, cluster individual storm features, and data mine the lightning and radar attributes of 1252 severe and nonsevere storms. The study first examines the influence of serial correlation and uses autocorrelation functions to document the persistence of lightning and radar parameters. Decorrelation times are found to vary by parameter, storm severity, and mathematical operator, but the great majority are between three and six lags, suggesting that consecutive 2-min storm samples (following a storm) are effectively independent after only 6–12 min. The study next describes the distribution of lightning jumps in severe and nonsevere storms, differences between various types of severe storms (e.g., severe wind only), and relationships between lightning and radar parameters. The 2σ lightning jump algorithm (with a 10 flashes min−1 activation threshold) yields 0.92 jumps h−1 for nonsevere storms and 1.44 jumps h−1 in severe storms. Applying a 10-mm maximum expected size of hail (MESH) threshold to the 2σ lightning jump algorithm reduces the frequency of lightning jumps in nonsevere storms to 0.61 jumps h−1. Although radar-derived parameters are comparable between storms that produce severe wind plus hail and those that produce tornadoes, tornadic storms exhibit much greater intracloud (IC) and cloud-to-ground (CG) flash rates. Correlations further illustrate that lightning data provide complementary storm-scale information to radar-derived measures of storm intensity.

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Max R. Marchand
and
Henry E. Fuelberg

Abstract

This study presents a new method for assimilating lightning data into numerical models that is suitable at convection-permitting scales. The authors utilized data from the Earth Networks Total Lightning Network at 9-km grid spacing to mimic the resolution of the Geostationary Lightning Mapper (GLM) that will be on the Geostationary Operational Environmental Satellite-R (GOES-R). The assimilation procedure utilizes the numerical Weather Research and Forecasting (WRF) Model. The method (denoted MU) warms the most unstable low levels of the atmosphere at locations where lightning was observed but deep convection was not simulated based on the absence of graupel. Simulation results are compared with those from a control simulation and a simulation employing the lightning assimilation method developed by Fierro et al. (denoted FO) that increases water vapor according to a nudging function that depends on the observed flash rate and simulated graupel mixing ratio. Results are presented for three severe storm days during 2011 and compared with hourly NCEP stage-IV precipitation observations. Compared to control simulations, both the MU and FO assimilation methods produce improved simulated precipitation fields during the assimilation period and a short time afterward based on subjective comparisons and objective statistical scores (~0.1, or 50%, improvement of equitable threat scores). The MU generally performs better at simulating isolated thunderstorms and other weakly forced deep convection, while FO performs better for the case having strong synoptic forcing. Results show that the newly developed MU method is a viable alternative to the FO method, exhibiting utility in producing thunderstorms where observed, and providing improved analyses at low computational cost.

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