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Kristen Kehrer, Brian Graf, and William P. Roeder

Abstract

This paper evaluates the use of precipitable water (PW) from the global positioning system (GPS) in lightning prediction. Additional independent verification of an earlier model is performed. This earlier model used binary logistic regression with the following four predictor variables optimally selected from a candidate list of 23 candidate predictors: the current precipitable water value for a given time of the day, the change in GPS PW over the past 9 h, the K index, and the electric field mill value. The K index was used as a measure of atmospheric stability, which, of the traditional stability measures, has been shown to work best in the area and season under study. This earlier model was not optimized for any specific forecast interval, but showed promise for 6- and 1.5-h forecasts. Two new models were developed and verified. These new models were optimized for two operationally significant forecast intervals. The first model was optimized for the 0.5-h lightning advisories issued by the U.S. Air Force’s 45th Weather Squadron. An additional 1.5 h was allowed for sensor dwell, communication, calculation, analysis, and advisory decision by the forecaster. Therefore, the 0.5-h advisory model became a 2-h forecast model for lightning within the 45th Weather Squadron advisory areas. The second model was optimized for major ground processing operations supported by the 45th Weather Squadron, which can require lightning forecasts with a lead time of up to 7.5 h. Using the same 1.5-h lag as in the other new model, this became a 9-h forecast model for lightning within 37 km (20 n mi) of the 45th Weather Squadron advisory areas. The two new models were built using binary logistic regression and a list of 26 candidate predictor variables: the current GPS PW value, the K index, and 24 candidate variables of the change in GPS PW levels over 0.5-h increments up to 12 h. The new 2-h model found the following four predictors to be statistically significant, listed in decreasing order of contribution to the forecast: the 0.5-h change in GPS PW, the 7.5-h change in GPS PW, the current GPS PW value, and the K index. The new 9-h forecast model found the following five independent variables to be statistically significant, listed in decreasing order of contribution to the forecast: the current GPS PW value, the 8.5-h change in GPS PW, the 3.5-h change in GPS PW, the 12-h change in GPS PW, and the K index. In both models, the GPS PW parameters had better correlation to the lightning forecast than did the K index, a widely used thunderstorm index. Possible future improvements to this study are discussed.

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Gary P. Ellrod, James P. Nelson III, Michael R. Witiw, Lynda Bottos, and William P. Roeder

Abstract

Several experimental products derived from Geostationary Operational Environmental Satellite (GOES) Sounder retrievals (vertical profiles of temperature and moisture) have been developed to assist weather forecasters in assessing the potential for convective downbursts. The product suite currently includes the wind index (WINDEX), a dry microburst index, and the maximum difference in equivalent potential temperature (θ e) from the surface to 300 hPa. The products are displayed as color-coded boxes or numerical values, superimposed on GOES visible, infrared, or water vapor imagery, and are available hourly, day and night, via the Internet. After two full summers of evaluation, the products have been shown to be useful in the assessment of atmospheric conditions that may lead to strong, gusty surface winds from thunderstorms. Two case studies are presented: 1) a severe downburst storm in southern Arizona that produced historic surface wind speeds and damage, and 2) multiple dry and wet downbursts in western Kansas that resulted in minor damage. Verification involved comparing the parameters with radiosonde data, numerical model first guess data, or surface wind reports from airports, mesonetworks, or storm spotters. Mean absolute WINDEX from the GOES retrievals differed from the mean surface wind gust reports by <2 kt (1 m s−1) for 82 events, but underestimated wind gusts for 7 nighttime events by 22 kt (11 m s−1). GOES WINDEX was also slightly better than that derived from the concurrent National Centers for Environmental Prediction’s Eta Model first guess. There are plans to incorporate these downburst parameters into a future upgrade of the National Weather Service’s Advanced Weather Interactive Processing System, with the option to derive them from either GOES Sounder data, radiosondes, or numerical model forecast data.

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Jonathan L. Case, Mark M. Wheeler, John Manobianco, Johnny W. Weems, and William P. Roeder

Abstract

Seven years of wind and temperature data from a high-resolution network of 44 towers at the Kennedy Space Center and Cape Canaveral Air Force Station were used to develop an objective method for identifying land breezes, which are defined as seaward-moving wind shift lines in this study. The favored meteorological conditions for land breezes consisted of surface high pressure in the vicinity of the Florida peninsula, mainly clear skies, and light synoptic onshore flow and/or the occurrence of a sea breeze during the afternoon preceding a land breeze. The land breeze characteristics are examined for two events occurring under different weather regimes—one with light synoptic onshore flow and no daytime sea breeze, and another following a daytime sea breeze under a prevailing offshore flow. Land breezes were found to occur over east-central Florida in all months of the year and had varied onset times and circulation depths. Land breezes were most common in the spring and summer months and least common in the winter. The average onset times were ∼4–5 h after sunset from May to July and ∼6.5–8 h after sunset from October to January. Land breezes typically moved from the west or southwest during the spring and summer, from the northwest in the autumn, and nearly equally from all directions in the winter. Shallow land breezes (<150-m depth) were typically not associated with the afternoon sea breeze and behaved like density currents, exhibiting the largest temperature decreases and latest onset times. Deep land breezes (>150-m depth) were most often preceded by an afternoon sea breeze, had the smallest horizontal temperature gradients, and experienced a mean onset time that is 4 h earlier than that of shallow land breezes.

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Michael E. Splitt, Jaclyn A. Shafer, Steven M. Lazarus, and William P. Roeder

Abstract

A tropical cyclone (TC) wind speed probability forecast product developed at the Cooperative Institute for Research in the Atmosphere (CIRA) and adopted by the National Hurricane Center (NHC) is evaluated for U.S. land-threatening and landfalling events over four hurricane seasons from 2004 to 2007. A key element of this work is the discernment of risk associated with the interval forecast probabilities for the three wind speed categories (i.e., 34, 50, and 64 kt, where 1 kt = 0.52 m s−1). A quantitative assessment of the interval probabilities (0–12, 12–24, 24–36, 36–48, 48–72, 72–96, and 96–120 h) is conducted by converting them into binary (yes–no) forecasts using decision thresholds that are selected using the true skill statistic (TSS) and the Heidke skill score (HSS). The NHC product performs well as both the HSS and TSS demonstrate skill out to the 48–72- and 72–120-h intervals, respectively. Overall, reliability diagrams and bias scores indicate that the NHC product has a tendency to overforecast event likelihood for cases where the forecast probabilities exceed 60%. Specifically, the NHC product tends to overforecast for the 34-kt category but underforecasts for the 64-kt category, especially at later forecast intervals. Results for the 50-kt category are mixed but also exhibit a tendency to underforecast during the latter intervals. Decision thresholds range from 1% to 55% depending on the selection method, wind speed category, and time interval. Given that the average forecast probabilities decrease with forecast hour, small forecast probabilities may be meaningful. The HSS is recommended over the TSS for decision threshold selection because the use of the TSS introduces significant bias and the HSS is less sensitive to filtering of correct negatives.

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Michael E. Splitt, Steven M. Lazarus, Sarah Collins, Denis N. Botambekov, and William P. Roeder

Abstract

Probabilistic wind speed forecasts for tropical cyclones from Monte Carlo–type simulations are assessed within a theoretical framework for a simple unbiased Gaussian system that is based on feature size and location error that mimic tropical cyclone wind fields. Aspects of the wind speed probability data distribution, including maximum expected probability and forecast skill, are assessed. Wind speed probability distributions are shown to be well approximated by a bounded power-law distribution when the feature size is smaller than the location error and tends toward a U-shaped distribution as the location error becomes small. Forecast skill (i.e., true and Heidke skill scores) is shown to be highly dependent on the probability forecast data distribution. Forecasts from the National Hurricane Center (NHC) Wind Speed Probability Forecast Product are used to assess the applicability of the simple system in the interpretation and evaluation of a more advanced system.

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Corey G. Amiot, Lawrence D. Carey, William P. Roeder, Todd M. McNamara, and Richard J. Blakeslee

Abstract

Wind warnings are the second-most-frequent advisory issued by the U.S. Air Force’s 45th Weather Squadron (45WS) at Cape Canaveral, Florida. Given the challenges associated with nowcasting convection in Florida during the warm season, improvements in 45WS warnings for convective wind events are desired. This study aims to explore the physical bases of dual-polarization radar signatures within wet downbursts around Cape Canaveral and identify signatures that may assist the 45WS during real-time convective wind nowcasting. Data from the 45WS’s C-band dual-polarization radar were subjectively analyzed within an environmental context, with quantitative wind measurements recorded by weather tower sensors for 32 threshold-level downbursts with near-surface winds ≥ 35 kt (1 kt ≈ 0.51 m s−1) and 32 null downbursts. Five radar signatures were identified in threshold-level downburst-producing storms: peak height of 1-dB differential reflectivity Z DR column, peak height of precipitation ice signature, peak reflectivity, height below 0°C level where Z DR increases to 3 dB within a descending reflectivity core (DRC), and vertical Z DR gradient within DRC. Examining these signatures directly in updraft–downdraft cycles that produced threshold-level winds yielded mean lead times of 20.0–28.2 min for cumulus and mature stage signatures and 12.8–14.9 min for dissipating stage signatures, with higher signature test values generally yielding higher skill scores. A conceptual test of utilizing signatures within earlier cells in multicell storms to indirectly predict the potential for intense downbursts in later cells was performed, which offered increased lead times and skill scores for an Eulerian forecast region downstream from the storm initiation location.

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Dawn L. Sanderson, Edward D. White, Andrew J. Geyer, William P. Roeder, and Alex J. Gutman

Abstract

Air Force Manual 91–203 (AFMAN 91–203) directs that a lightning warning be issued when lightning is occurring within a 5 nautical mile (n mi; 1 n mi = 1.852 km) radius of a predetermined location. The 45th Weather Squadron (45 WS), located on the central eastern coast of Florida, provides weather support to Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick Air Force Base. The primary objective of this study is to optimize the lightning warning safety buffer; in particular, to determine if the 5 n mi safety radius can be reduced while maintaining a desired level of safety. The research uses processed Lightning Detection and Ranging II (LDAR-II) data from 2013 to 2016 to map the movement of preexisting lightning storms using ellipses. These ellipses are updated with every lightning flash. The distance from the ellipse boundary of each flash occurring outside the ellipse is recorded. Those exterior flash distances are then used to find the best-fit distribution from which the stand-off distance for the desired level of safety can be calculated. The distances from the edge of the ellipse are fit to a Weibull distribution and a reduction in the radius by 1 to 4 or 5 n mi is selected as the optimized balance between safety and operational impact. The 4 or 5 n mi radii are tested with a resulting failure rate of 3.58%, with an average savings of 130.75 false alarms and 15.7 8-h man days a year for the months of May–September.

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