18 research outputs found

    Prototype Local Data Integration System and Central Florida Data Deficiency

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    This report describes the Applied Meteorology Unit's (AMU) task on the Local Data Integration System (LDIS) and central Florida data deficiency. The objectives of the task are to identify all existing meteorological data sources within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS), identify and configure an appropriate LDIS to integrate these data, and implement a working prototype to be used for limited case studies and data non-incorporation (DNI) experiments. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. The LDIS has the potential to provide added value for nowcasts and short term forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models. In combination with a suitable visualization tool, LDIS may provide users with a more complete and comprehensive understanding of evolving fine-scale weather features than could be developed by individually examining the disparate data sets over the same area and time. The utility of LDIS depends largely on the reliability and availability of observational data. Therefore, it is important to document all existing meteorological data sources around central Florida that can be incorporated by it. Several factors contribute to the data density and coverage over east central Florida including the level in the atmosphere, distance from KSC/CCAS, time, and prevailing weather. The central Florida mesonet consists of existing surface meteorological and hydrological data available from the Tampa NWS and data servers at Miami and Jacksonville. However the utility of these data for operational use is limited, mainly because there are relatively few additional meteorological observations within 50 km of KSC/CCAS to supplement existing METAR and KSC/CCAS tower reports

    Local Data Integration in East Central Florida Using the ARPS Data Analysis System

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    This paper describes the Applied Meteorology Unit's (AMU) efforts to configure, implement, and test a version of the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS; Brewster 1996) that assimilates all available data within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS). The objective for running a Local Data Integration System (LDIS) such as ADAS is to generate products which may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of ground and aerospace operations at KSC/CCAS. A LDIS such as ADAS has the potential to provide added value because it combines observational data to produce gridded analyses of temperature, wind, and moisture (including clouds) and diagnostic quantities such as vorticity, divergence, etc. at specified temporal and spatial resolutions. In this regard, a LDTS along with suitable visualization tools may provide users with a ignore complete and comprehensive understanding of evolving weather than could be developed by individually examining the disparate data sets over the same area and time. The AMU implemented a working prototype of the ADAS which does not run in real-time. Instead, the AMU is evaluating ADAS through post-analyses of weather events for a warm and cool season case. The case studies were chosen to investigate the capabilities and limitations of a LDIS such as ADAS including the impact of non-incorporation of specific data sources on the utility of the subsequent analyses

    Evaluation of the 29-km Eta Model. Part I: Objective Verification at Three Selected Stations

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    A subjective evaluation of the National Centers for Environmental Prediction 29-km (meso-) eta model during the 1996 warm (May-August) and cool (October-January) seasons is described. The overall evaluation assessed the utility of the model for operational weather forecasting by the U.S. Air Force 45th Weather Squadron, National Weather Service (NWS) Spaceflight Meteorology Group (SMG) and NWS Office in Melbourne, FL

    Evaluation of the 29-km Eta Model for Weather Support to the United States Space Program

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    The Applied Meteorology Unit (AMU) conducted a year-long evaluation of NCEP's 29-km mesoscale Eta (meso-eta) weather prediction model in order to identify added value to forecast operations in support of the United States space program. The evaluation was stratified over warm and cool seasons and considered both objective and subjective verification methodologies. Objective verification results generally indicate that meso-eta model point forecasts at selected stations exhibit minimal error growth in terms of RMS errors and are reasonably unbiased. Conversely, results from the subjective verification demonstrate that model forecasts of developing weather events such as thunderstorms, sea breezes, and cold fronts, are not always as accurate as implied by the seasonal error statistics. Sea-breeze case studies reveal that the model generates a dynamically-consistent thermally direct circulation over the Florida peninsula, although at a larger scale than observed. Thunderstorm verification reveals that the meso-eta model is capable of predicting areas of organized convection, particularly during the late afternoon hours but is not capable of forecasting individual thunderstorms. Verification of cold fronts during the cool season reveals that the model is capable of forecasting a majority of cold frontal passages through east central Florida to within +1-h of observed frontal passage

    An Extended Objective Evaluation of the 29-km Eta Model for Weather Support to the United States Space Program

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    This report describes the Applied Meteorology Unit's objective verification of the National Centers for Environmental Prediction 29-km eta model during separate warm and cool season periods from May 1996 through January 1998. The verification of surface and upper-air point forecasts was performed at three selected stations important for 45th Weather Squadron, Spaceflight Meteorology Group, and National Weather Service, Melbourne operational weather concerns. The statistical evaluation identified model biases that may result from inadequate parameterization of physical processes. Since model biases are relatively small compared to the random error component, most of the total model error results from day-to-day variability in the forecasts and/or observations. To some extent, these nonsystematic errors reflect the variability in point observations that sample spatial and temporal scales of atmospheric phenomena that cannot be resolved by the model. On average, Meso-Eta point forecasts provide useful guidance for predicting the evolution of the larger scale environment. A more substantial challenge facing model users in real time is the discrimination of nonsystematic errors that tend to inflate the total forecast error. It is important that model users maintain awareness of ongoing model changes. Such changes are likely to modify the basic error characteristics, particularly near the surface

    Contour Error Map Algorithm

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    The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields

    The evaluation of ASOS for the Kennedy Space Center's Shuttle Landing Facility

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    This report documents the Applied Meteorology Unit's (AMU) evaluation of the effectiveness and utility of the Automated Surface Observing System (ASOS) in terms of spaceflight operations and user requirements. In particular, the evaluation determines which of the Shuttle Landing Facility (SLF) observation requirements can be satisfied by ASOS. This report also includes a summary of ASOS' background, current configuration and specifications, system performance, and the possible concepts of operations for use of ASOS at the SLF. This evaluation stems from a desire by the Air Force to determine if ASOS units could be used to reduce the cost of SLF meteorological observations

    Report on the comparison of the scan strategies employed by the Patrick Air Force Base WSR-74C/McGill radar and the NWS Melbourne WSR-88D radar

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    The objective of this investigation is to determine whether the current standard WSR-88D radar (NEXRAD) scan strategies permit the use of the Melbourne WSR-88D to perform the essential functions now performed by the Patrick Air Force Base (PAFB) WSR-74C/McGill radar for evaluating shuttle weather flight rules (FR) and launch commit criteria (LCC). To meet this objective, the investigation compared the beam coverage patterns of the WSR-74C/McGill radar located at PAFB and the WSR-88D radar located at the Melbourne National Weather Service (NWS) Office over the area of concern for weather FR and LCC evaluations. The analysis focused on beam coverage within four vertical 74 km radius cylinders (1 to 4 km above ground level (AGL), 4 to 8 km AGL, 8 to 12 km AGL, and 1 to 12 km AGL) centered on Kennedy Space Center (KSC) Launch Complex 39A. The PAFB WSR-74C/McGill radar is approximately 17 km north-northeast of the Melbourne WSR-88D radar. The beam coverage of the WSR-88D using VCP 11 located at the Melbourne NWS Office is comparable (difference in percent of the atmosphere sampled between the two radars is 10 percent or less) within the area of concern to the beam coverage of the WSR-74C/McGill radar located at PAFB. Both radars provide good beam coverage over much of the atmospheric region of concern. In addition, both radars provide poor beam coverage (coverage less than 50 percent) over limited regions near the radars due to the radars' cone of silence and gaps in coverage within the higher elevation scans. Based on scan strategy alone, the WSR-88D radar could be used to perform the essential functions now performed by the PAFB WSR-74C/McGill radar for evaluating shuttle weather FR and LCC. Other radar characteristics may, however, affect the decision as to which radar to use in a given case

    Implementation and evaluation of the new wind algorithm in NASA's 50 MHz doppler radar wind profiler

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    The purpose of this report is to document the Applied Meteorology Unit's implementation and evaluation of the wind algorithm developed by Marshall Space Flight Center (MSFC) on the data analysis processor (DAP) of NASA's 50 MHz doppler radar wind profiler (DRWP). The report also includes a summary of the 50 MHz DRWP characteristics and performance and a proposed concept of operations for the DRWP

    Global Environmental Micro Sensors Test Operations in the Natural Environment

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    ENSCO, Inc. is developing an innovative atmospheric observing system known as Global Environmental Micro Sensors (GEMS). The GEMS concept features an integrated system of miniaturized in situ, airborne probes measuring temperature, relative humidity, pressure, and vector wind velocity. In order for the probes to remain airborne for long periods of time, their design is based on a helium-filled super-pressure balloon. The GEMS probes are neutrally buoyant and carried passively by the wind at predetermined levels. Each probe contains onboard satellite communication, power generation, processing, and geolocation capabilities. ENSCO has partnered with the National Aeronautics and Space Administration's Kennedy Space Center (KSC) for a project called GEMS Test Operations in the Natural Environment (GEMSTONE) that will culminate with limited prototype flights of the system in spring 2007. By leveraging current advances in micro and nanotechnology, the probe mass, size, cost, and complexity can be reduced substantially so that large numbers of probes could be deployed routinely to support ground, launch, and landing operations at KSC and other locations. A full-scale system will improve the data density for the local initialization of high-resolution numerical weather prediction systems by at least an order of magnitude and provide a significantly expanded in situ data base to evaluate launch commit criteria and flight rules. When applied to launch or landing sites, this capability will reduce both weather hazards and weather-related scrubs, thus enhancing both safety and cost-avoidance for vehicles processed by the Shuttle, Launch Services Program, and Constellation Directorates. The GEMSTONE project will conclude with a field experiment in which 10 to 15 probes are released over KSC in east central Florida. The probes will be neutrally buoyant at different altitudes from 500 to 3000 meters and will report their position, speed, heading, temperature, humidity, and pressure via satellite. The GEMS data will be validated against reference observations provided by current weather instrumentation located at KSC. This paper will report on the results of the GEMSTONE project and discuss the challenges encountered in developing an airborne sensor system
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