David W. Sharp’s research while affiliated with National Park Service and other places

The use of local mesoscale models has significantly increased during the past decade. The availability of the Weather Research and Forecasting-Environmental Modeling System (WRF-EMS) and its high degree of configurability has brought modeling capabilities to many Weather Forecast Offices (WFOs) within the National Weather Service. The WFO in Melbourne (MLB), FL is exploring enhancements to their local modeling approach. Development and testing is centered on giving WFO meteorologists detailed depictions of alternative forecast outcomes during hazardous weather situations and improving the ease and flexibility of on-demand model execution according to selectable pre-configurations. Alternative outcomes help bolster forecaster confidence regarding the measure of relative uncertainties associated with a particular weather situation, while on-demand capabilities allow forecasters to request certain domain options and configurations tailored to fit their current need. With science-steering in mind, the purpose is to develop and test functionalities that might enhance a WFO's ability to more effectively exercise local decision support, continuity of operations, and service backup to sister offices. This paper will discuss the configuration of multiple two-way and three-way nested domains for each of its service backup areas, including West Central Florida, the Florida Keys, and Puerto Rico (including the U.S. Virgin Islands). The development of unique software designed to function as the forecaster interface by which domain and configuration selections can be made will also be discussed.

The National Hurricane Center Hurricane Probability Program, which estimated the probability of a tropical cyclone passing within a specific distance of a selected set of coastal stations, was replaced by the more general Tropical Cyclone Surface Wind Speed Probabilities in 2006. A Monte Carlo (MC) method is used to estimate the probabilities of 34-, 50-, and 64-kt (1 kt = 0.51 m s(-1)) winds at multiple time periods through 120 h. Versions of the MC model are available for the Atlantic, the combined eastern and central North Pacific, and the western North Pacific. This paper presents a verification of the operational runs of the MC model for the period 2008-11 and describes model improvements since 2007. The most significant change occurred in 2010 with the inclusion of a method to take into account the uncertainty of the track forecasts on a case-by-case basis, which is estimated from the spread of a dynamical model ensemble and other parameters. The previous version represented the track uncertainty from the error distributions from the previous 5 yr of forecasts from the operational centers, with no case-to-case variability. Results show the MC model provides robust estimates of the wind speed probabilities using a number of standard verification metrics, and that the inclusion of the case-by-case measure of track uncertainty improved the probability estimates. Beginning in 2008, an older operational wind speed probability table product was modified to include information from the MC model. This development and a verification of the new version of the table are described.

The Kennedy Space Center (KSC) Hail Monitor System, a joint effort of the NASA KSC Physics Lab and the KSC Engineering Services Contract (ESC) Applied Technology Lab, was first deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) (Reges, 2008) in conjunction with Colorado State University have been instrumental in validation testing using duplicate hail monitor systems at sites in the hail prone high plains of Colorado. The KSC Hail Monitor System (HMS), consisting of three stations positioned approximately 500 ft from the launch pad and forming an approximate equilateral triangle, as shown in Figure 1, was first deployed to Pad 39B for support of STS-115. Two months later, the HMS was deployed to Pad 39A for support of STS-116. During support of STS-117 in late February 2007, an unusually intense (for Florida standards) hail event occurred in the immediate vicinity of the exposed space shuttle and launch pad. Hail data of this event was collected by the HMS and analyzed (Lane, 2008). Support of STS-118 revealed another important application of the hail monitor system. Ground Instrumentation personnel checked the hail monitors daily when a vehicle was on the launch pad, with special attention after any storm suspected of containing hail. If no hail was recorded by the HMS, the vehicle and pad inspection team had no need to conduct a thorough inspection of the vehicle immediately following a storm. On the afternoon of July 13, 2007, hail on the ground was reported by observers at the Vehicle Assembly Building (VAB) and Launch Control Center (LCC), about three miles west of Pad 39A, as well as at several other locations at KSC. The HMS showed no impact detections, indicating that the shuttle had not been damaged by any of the numerous hail events which occurred on that day. This scenario repeated itself many times up until the last shuttle launch as shown in Table 1.

Versions of the Advanced Regional Prediction

Lightning kills more people annually in Florida than any other weather phenomenon. Therefore, advancing high-resolution, short-fused lightning information for the protection of human lives is of great importance to the National Weather Service (NWS). During a two month experiment during June and July 2009, the NWS Melbourne, FL Weather Forecast Office (WFO) conducted an experiment to test the capability and skill of issuing lightning advisories and warnings for pre-determined point locations in East Central Florida. During the experiment, a forecaster continually monitored WSR-88D radar base data and derived products upon an Advanced Weather Interactive Processing System (AWIPS) workstation during the peak convective hours of 1200 to 1600 LST. Complementary analysis tools, including the System for Convection Analysis and Nowcasting (SCAN) and the Four-Dimensional Stormcell Investigator (FSI), further helped ascertain convective trends conducive to electrification near the Melbourne (KMLB) and Orlando (KMCO) International Airports. In conjunction with the detailed radar-based analyses, the Lightning Detection and Ranging (LDAR) network surrounding the Kennedy Space Center was instrumental in tracking the initiation and evolution of total lightning signals aloft within cells of interest. When forecaster confidence of (cloud to ground; CG) lightning onset in close proximity to KMLB and KMCO became high, experimental lightning advisories and/or warnings were composed and locally archived (not released externally). The lightning products were produced with a desired 30-minute (10-minute) advisory (warning) lead time for a five mile radius of each airport, to account for the sporadic nature of sequential CG strikes and to increase the public safety factor. For verification purposes, all CG lightning strikes were plotted and evaluated to determine whether any strikes occurred within the advisory/warning radii, and if so, at what time. This data was then used to calculate Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI) and average lead time statistics for the lightning advisory and warning products. The verification results showed that lightning advisories and warnings were issued for point locations (surrounded by a five mile radii safety margin) with a considerable degree of success and favorable lead times. Demonstrating skill for advanced warnings of CG lightning strikes for specific locations has important implications. Ultimately, the results could lead to the incorporation of lightning advisories and warnings into WFO operations to provide incident support for emergency officials and to help protect high-density gatherings of people at outdoor events.

Prior to launch, the space shuttle might be described as a very large thermos bottle containing substantial quantities of cryogenic fuels. Because thermal insulation is a critical design requirement, the external wall of the launch vehicle fuel tank is covered with an insulating foam layer. This foam is fragile and can be damaged by very minor impacts, such as that from small- to medium-size hail, which may go unnoticed. In May 1999, hail damage to the top of the External Tank (ET) of STS-96 required a rollback from the launch pad to the Vehicle Assembly Building (VAB) for repair of the insulating foam. Because of the potential for hail damage to the ET while exposed to the weather, a vigilant hail sentry system using impact transducers was developed as a hail damage warning system and to record and quantify hail events. The Kennedy Space Center (KSC) Hail Monitor System, a joint effort of the NASA and University Affiliated Spaceport Technology Development Contract (USTDC) Physics Labs, was first deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) in conjunction with Colorado State University were and continue to be active in testing duplicate hail monitor systems at sites in the hail prone high plains of Colorado. The KSC Hail Monitor System (HMS), consisting of three stations positioned approximately 500 ft from the launch pad and forming an approximate equilateral triangle (see Figure 1), was deployed to Pad 39B for support of STS-115. Two months later, the HMS was deployed to Pad 39A for support of STS-116. During support of STS-117 in late February 2007, an unusual hail event occurred in the immediate vicinity of the exposed space shuttle and launch pad. Hail data of this event was collected by the HMS and analyzed. Support of STS-118 revealed another important application of the hail monitor system. Ground Instrumentation personnel check the hail monitors daily when a vehicle is on the launch pad, with special attention after any storm suspected of containing hail. If no hail is recorded by the HMS, the vehicle and pad inspection team has no need to conduct a thorough inspection of the vehicle immediately following a storm. On the afternoon of July 13, 2007, hail on the ground was reported by observers at the VAB, about three miles west of Pad 39A, as well as at several other locations around Kennedy Space Center. The HMS showed no impact detections, indicating that the shuttle had not been damaged by any of the numerous hail events which occurred that day.

A sea surface temperature (SST) analysis system designed to initialize short-term atmospheric model forecasts is evaluated for a month-long, relatively clear period in May 2004. System inputs include retrieved SSTs from the Geostationary Operational Environmental Satellite (GOES)-East and the Moderate Reso-lution Imaging Spectroradiometer (MODIS). The GOES SSTs are processed via a sequence of quality control and bias correction steps and are then composited. The MODIS SSTs are bias corrected and checked against the background field (GOES composites) prior to assimilation. Buoy data, withheld from the analyses, are used to bias correct the MODIS and GOES SSTs and to evaluate both the composites and analyses. The bias correction improves the identification of residual cloud-contaminated MODIS SSTs. The largest analysis system improvements are obtained from the adjustments associated with the creation of the GOES composites (i.e., a reduction in buoy/GOES composite rmse on the order of 0.3°–0.5°C). A total of 120 analyses (80 night and 40 day) are repeated for different experimental configurations designed to test the impact of the GOES composites, MODIS cloud mask, spatially varying background error covariance and decorrelation length scales, data reduction, and anisotropy. For the May 2004 period, the nighttime MODIS cloud mask is too conservative, at times removing good SST data and degrading the analyses. Nocturnal error variance estimates are approximately half that of the daytime and are relatively spatially homogeneous, indicating that the nighttime composites are, in general, superior. A 30-day climatological SST gradient is used to create anisotropic weights and a spatially varying length scale. The former improve the analyses in regions with significant SST gradients and sufficient data while the latter reduces the analysis rmse in regions where the innovations tend to be well correlated with distinct and persistent SST gradients (e.g., Loop Current). Data thinning reduces the rmse by expediting analysis convergence while simulta-neously enhancing the computational efficiency of the analysis system. Based on these findings, an opera-tional analysis configuration is proposed.

Climatologies of CG lightning frequency and density based on flow regime were created by the AMU in Phase I of this work (Lambert et al. 2006) and used by NWS MLB forecasters to create a first guess climatological lightning threat index map. An example is shown in Figure 7. The forecasters modify this first guess map based on a subjective analysis of the observed and forecast parameters that affect thunderstorm formation. The goal of the work described herein was to create climatological soundings based on flow regime as another tool the forecasters can use to adjust the first-guess map (Short 2006). The climatological vertical profiles of temperature, dew point, wind speed and direction were generated for each flow regime from daily morning soundings at JAX, TBW, MFL and XMR during the warm season, from a 16 year database spanning 1989-2004. Daily flow regime classifications, based on research at FSU, were the same as used in Phase I. The resulting climatological soundings were formatted for analysis and display by NSHARP and were delivered to NWS MLB in June 2006 where they are now being used operationally to assist in creating the daily lightning threat index map. While the NWS MLB creates these maps only for their CWA (see Figure 1), the 13 July case demonstrates the utility of the soundings. Had individuals planning outdoor activities in the Tampa area had access to a map like this, it would have at least made them think about changing their plans. More information about the lightning threat index map and how it is created, as well as the flow regimes and the resulting lightning climatologies, can be found at the URL: www.srh.noaa.gov/mlb/amu-mlb/LTG/ltgclimothreat.htm.