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

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

Thunderstorms in central Florida frequently halt outdoor activities, requiring that one wait some prescribed time after an assumed last flash before safely resuming activities. The goal of this research is to develop a high-skill probabilistic method that can be used in high pressure real-world operations to terminate lightning warnings more quickly while maintaining safety. Probabilistic guidance tools are created for isolated warm season storms in central Florida using dual-polarized radar data at 1-min intervals. The parameters examined are maximum reflectivity and graupel presence at the 0°, −5°, −10°, −15°, and −20°C levels as well as composite reflectivity. Random samples of the radar data are used to train a generalized linear model (GLM) to make a probabilistic prediction whether a given flash is the storm’s last flash. The most statistically significant predictors for lightning cessation are found to be the storm’s maximum reflectivity in the composite and the 0°C levels, along with graupel presence or absence at the −5°, −10°, −15°, and −20°C levels. Statistical verification is used to analyze the performance of the two GLMs at different probability thresholds (95.0%, 97.5%, and 99.0%). When applying the cessation guidance as though storms are occurring in real time, results showed ~99% of the storms produced no additional lightning after the GLM suggested cessation had already occurred. Although these results are encouraging, the procedure must be tested on much larger datasets having different convective modes and different areal coverages to prove its value compared to operational forecasters.

Abstract

The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the coastal Gulf of Mexico and the southern Atlantic coast. TCTP is designed to aid forecasters in a time-limited environment. TCTP provides a “quick look” at regions where forecasters can then conduct detailed analyses. The pool of potential predictors included tornado reports and tropical cyclone data between 2000 and 2008, as well as storm environmental parameters. The original pool of 28 potential predictors is reduced to six using stepwise regression and logistic regression. These six predictors are 0–3-km wind shear, 0–3-km storm relative helicity, azimuth angle of the tornado report from the tropical cyclone, distance from the cyclone’s center, time of day, and 950–1000-hPa convective available potential energy. Mean Brier scores and Brier skill scores are computed for the entire TCTP-dependent dataset and for corresponding forecasts produced by the Storm Prediction Center (SPC). TCTP then is applied to four individual cyclone cases to qualitatively and quantitatively assess the parameter and compare its performance with SPC forecasts. Results show that TCTP has skill at identifying regions of tornado potential. However, tornadoes in some tropical systems are overpredicted, but underpredicted in others. TCTP 6-h forecast periods provide slightly poorer statistical performance than the 1-day tornado probability forecasts from SPC, probably because the SPC product includes forecaster guidance and because their forecasts are valid for longer periods (24 h).

Abstract

The preconvective environment of summer thunderstorms over the Florida Panhandle is investigated. Geostationary satellite imagery as well as surface and radiosonde data were examined during the summers of 1990 and 1991. Days were classified either as synoptically disturbed or undisturbed based on the imagery. The undisturbed days then were subjectively subdivided into those having strong, weak, or no convection. Composite sounding profiles of various meteorological parameters were constructed for each category of the undisturbed days. Composites of various stability indexes also were calculated.

Midtropospheric moisture (particularly from 700 to 500 mb) and low-level instability were the best thermodynamic parameters for forecasting convection over the Florida Panhandle. The surface-based lifted index was the most useful stability index for predicting convective development. Wind direction also was related to the degree of convective activity in the Florida Panhandle. The strong convection days tended to have low-level winds from the south or southwest. Low-level winds on the driest days generally had northerly and easterly components.

Abstract

Software build 9.0 for the Weather Surveillance Radar-1988 Doppler (WSR-88D) contains several new or improved algorithms for detecting severe thunderstorms. The WSR-88D Operational Support Facility supports testing and optimization of these algorithms by local National Weather Service offices. This paper presents a new methodology for using Storm Data in these local evaluations. The methodology defines specific conditions a storm cell must meet to be included in the evaluation. These conditions include cell intensity and duration, population density along the cell track, and any previous severe reports in the county where the storm is located. These requirements avoid including storm cells that may have produced severe weather where reports would be very unlikely. The technique provides a more accurate picture of algorithm performance than if Storm Data is used with no special considerations.

This study utilizes the new methodology with data currently available for the Tallahassee, Florida, county warning area (TLH CWA). It describes the performance of two algorithms used for detecting severe hail. The first is the Probability of Severe Hail (POSH), a component of the build 9.0 Hail Detection Algorithm. The second is the algorithm that calculates vertically integrated liquid (VIL).

Early results show that the recommended POSH threshold of 50% appears appropriate for the TLH CWA. This suggests that the height of the freezing level provides a reasonably good estimate of the best severe hail index (SHI). However, early results also indicate that the average wet-bulb temperature from 1000 to 700 mb (low-level wet-bulb temperature) might produce an even better indication of the SHI threshold. Similarly, the threshold for VIL is highly correlated to the low-level wet-bulb temperature. Finally, the VIL algorithm is found to perform as well as the POSH parameter if the best VIL threshold can be determined in advance. Since the database used in these evaluations was relatively small, these findings should be considered tentative.

Abstract

Cloud-to-ground lightning data from the National Lightning Detection Network are used to create a warm season (May–September) lightning climatology for the northern Gulf of Mexico coast for the 14-yr period 1989–2002. Each day is placed into one of five flow regimes based on the orientation of the low-level flow with respect to the coastline. This determination is made using the vector mean 1000–700-hPa wind data at Lake Charles and Slidell, Louisiana. Flash densities are calculated for daily, hourly, and nocturnal periods.

Spatial patterns of composite 24-h and nocturnal flash density indicate that lightning decreases in an east-to-west direction over the region. Flash densities for the 24-h period are greatest over land near the coast, with relative maxima located near Houston, Texas; Lake Charles, Baton Rouge, and New Orleans, Louisiana; Biloxi, Mississippi; and Mobile, Alabama. Flash densities during the nocturnal period are greatest over the coastal waters.

Lightning across the northern Gulf coast is closely related to the prevailing low-level synoptic flow, which controls the sea breeze, the dominant forcing mechanism during the warm season. Southwest flow, the most unstable and humid of the five regimes, exhibits the most flashes. In this case, sea-breeze-induced convection is located slightly inland from the coast. Northeast flow, the driest and most stable of the regimes, exhibits the least amount of lightning. The large-scale flow restricts the sea breeze to near the coastline.

Geographic features and local mesoscale circulations are found to affect lightning across the region. Geographic features include lakes, bays, marshes, swamps, and coastline orientations. Thermal circulations associated with these features interact with the main sea breeze to produce complex lightning patterns over the area.

Abstract

Pulse severe storms are single-cell thunderstorms that produce severe wind and/or severe hail for a brief period of time. These storms pose a major warm season forecasting problem since forecasters presently do not have sufficient guidance to know which, if any, of the cells that are observed will become severe. The empirical Probability of Severe (ProbSevere) model, developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS), fuses real-time data to produce short-term (0–60 min), statistically derived probabilistic forecasts of thunderstorm intensity. This study evaluates the ability of ProbSevere to predict pulse severe storms in the southeast United States. ProbSevere objects fitting the usual definition of a pulse severe environment were matched with severe events from Storm Data to create a dataset of ProbSevere objects that corresponded to pulse severe thunderstorms. A null dataset consisted of objects in pulse severe environments that did not match with a severe event. Results reveal that ProbSevere’s probabilities are small to moderate at the times corresponding to pulse severe events. While probabilities of nonsevere storms are generally smaller, there are a large number of outliers. Lightning flash rate is the only predictor relevant to this study that correlates strongly with increasingly favorable pulse storm probabilities. We conclude that ProbSevere provides forecasters only limited guidance as to whether a pulse severe event will soon occur. Developing a version of ProbSevere specifically for pulse severe storms would likely lead to better predictability for this mode of convection.

Abstract

Six years (1989–94) of cloud-to-ground lightning data are used to examine the distribution of lightning across the Florida panhandle and adjacent coastal waters and its relationship to the prevailing low-level flow. Only warm season data between 1 May and 31 October are used. The prevailing flow is determined by subdividing the low-level (1000–700 mb) vector mean wind into categories that are either parallel or perpendicular to various parts of the coastline. Moderate wind speeds (2–5 m s⁻¹) generally are found to be more conducive to producing lightning than stronger speeds. Wind speeds stronger than 5 m s⁻¹ likely inhibit the formation of the sea breeze, the main focus for summertime thunderstorms in the region.

Onshore, offshore, and parallel flows are found to play important roles in determining the patterns of flash locations in each flow regime. The complexity of the coastline also is found to have a major impact on the flash distributions. The prevailing wind direction is shown to be related to the time of peak afternoon lightning occurrence as well as the frequency of nighttime storms.

Abstract

The National Hurricane Center (NHC) has stated that guidance on tropical cyclone (TC) genesis is an operational forecast improvement need, particularly since numerical weather prediction models produce TC-like features and operationally required forecast lead times recently have increased. Using previously defined criteria for TC genesis in global models, this study bias corrects TC genesis forecasts from global models using multiple logistic regression. The derived regression equations provide 48- and 120-h probabilistic genesis forecasts for each TC genesis event that occurs in the Environment Canada Global Environmental Multiscale Model (CMC), the NCEP Global Forecast System (GFS), and the Met Office's global model (UKMET). Results show select global model output variables are good discriminators between successful and unsuccessful TC genesis forecasts. Independent verification of the regression-based probabilistic genesis forecasts during 2014 and 2015 are presented. Brier scores and reliability diagrams indicate that the forecasts generally are well calibrated and can be used as guidance for NHC’s Tropical Weather Outlook product. The regression-based TC genesis forecasts are available in real time online.