John Manobianco

Workstation-Based Real-Time Mesoscale Modeling Designed for Weather Support to Operations at the Kennedy Space Center and Cape Canaveral Air Station

Abstract This paper describes the capabilities and operational utility of a version of the Mesoscale Atmospheric Simulation System (MASS) that has been developed to support operational weather forecasting at the Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS). The implementation of local, mesoscale modeling systems at KSC/CCAS is designed to provide detailed short-range (< 24 h) forecasts of winds, clouds, and hazardous weather such as thunderstorms. Short-range forecasting is a challenge for daily operations, and manned and unmanned launches since KSC/CCAS is located in central Florida where the weather during the warm season is dominated by mesoscale circulations like the sea breeze. For this application, MASS has been modified to run on a Stardent 3000 workstation. Workstation-based, real-time numerical modeling requires a compromise between the requirement to run the system fast enough so that the output can be used before expiration balanced against the desire to improve the simulati...

Verification of high-resolution RAMS forecasts over east-central Florida during the 1999 and 2000 summer months

This paper presents an objective and subjective verification of a high-resolution configuration of the Regional Atmospheric Modeling System (RAMS) over east-central Florida during the 1999 and 2000 summer months. Centered on the Cape Canaveral Air Force Station (CCAFS), the innermost nested grid of RAMS has a horizontal grid spacing of 1.25 km, thereby providing forecasts capable of modeling finescale phenomena such as ocean and river breezes, and convection. The RAMS is run operationally at CCAFS within the Eastern Range Dispersion Assessment System (ERDAS), in order to provide emergency response guidance during space operations. ERDAS uses RAMS wind and temperature fields for input into ERDAS diffusion algorithms; therefore, the accuracy of dispersion predictions is highly dependent on the accuracy of RAMS forecasts. The most substantial error in RAMS over east-central Florida is a surface-based cold temperature bias, primarily during the daylight hours. At the Shuttle Landing Facility, the RAMS point error statistics are not substantially different than the National Centers for Environment Prediction Eta Model; however, an objective evaluation consisting of only point error statistics cannot adequately determine the added value of a high-resolution model configuration. Thus, results from a subjective evaluation of the RAMS forecast sea breeze and thunderstorm initiation on the 1.25-km grid are also presented. According to the subjective verification of the Florida east coast sea breeze, the RAMS categorical and skill scores exceeded that of the Eta Model predictions in most instances. The RAMS skill scores in predicting thunderstorm initiation are much lower than the sea-breeze evaluation scores, likely resulting from the lack of a sophisticated data assimilation scheme in the current operational configuration.

An Objective Technique for Verifying Sea Breezes in High-Resolution Numerical Weather Prediction Models

An ongoing challenge in mesoscale numerical weather prediction (NWP) is to determine the ideal method for verifying the performance of high-resolution, detailed forecasts. Traditional objective techniques that evaluate NWP model performance based on point error statistics may not be positively correlated with the value of forecast information for certain applications of mesoscale NWP, and subjective evaluation techniques are often costly and time consuming. As a result, objective event-based verification methodologies are required in order to determine the added value of high-resolution NWP models. This paper presents a new objective technique to verify predictions of the sea-breeze phenomenon over eastcentral Florida by the Regional Atmospheric Modeling System (RAMS) NWP model. The contour error map (CEM) technique identifies sea-breeze transition times in objectively analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean postsea-breeze wind direction and wind speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique improves upon traditional objective verification techniques and previously used subjective verification methodologies because it is automated, accounts for both spatial and temporal variations, correctly identifies and verifies the sea-breeze transition times, and provides verification contour maps and simple statistical parameters for easy interpretation. The CEM algorithm details are presented and validated against independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation.

The Wind Forecast Improvement Project (WFIP): A Public–Private Partnership Addressing Wind Energy Forecast Needs

AbstractThe Wind Forecast Improvement Project (WFIP) is a public–private research program, the goal of which is to improve the accuracy of short-term (0–6 h) wind power forecasts for the wind energy industry. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that included the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models and, second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the United States (the upper Great Plains and Texas) and included 12 wind profiling radars, 12 sodars, several lidars and surface flux stations, 184 instrumented tall towers, and over 400 nacelle anemome...

A 7-Yr Climatological Study of Land Breezes over the Florida Spaceport

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 com...

Local Data Integration over East-Central Florida Using the ARPS Data Analysis System

The Applied Meteorology Unit has configured the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) to support operational short-range weather forecasting over east-central Florida, including the Kennedy Space Center and Cape Canaveral Air Force Station. The ADAS was modified to assimilate nationally and locally available in situ and remotely sensed observational data into a series of high-resolution gridded analyses every 15 min. The goal for running ADAS over east-central Florida is to generate real-time analysis products that may enhance weather nowcasts and short-range (,6 h) forecasts issued by the 45th Weather Squadron (45 WS), the Spaceflight Meteorology Group (SMG), and the National Weather Service (NWS) at Melbourne, Florida (MLB). The locally configured ADAS has the potential to provide added value because it ingests all operationally available data into a single grid analysis at high spatial and temporal resolutions. ADAS-generated grid analyses can provide forecasters with a tool to develop a more comprehensive understanding of evolving fine-scale weather features than could be obtained by individually examining the disparate data sources. The potential utility of this ADAS configuration to operational forecasters is demonstrated through a postanalysis case study of a thunderstorm outflow boundary that postponed an Atlas space launch mission, and a Florida coolseason squall line event. In the Atlas case study, a thunderstorm outflow boundary generated strong winds that exceeded the Atlas vehicle limits. A diagnosis of this event, using analysis products during the decaying phase of a Florida summer thunderstorm, illustrates the potential benefits that may be provided to forecasters supporting space launch and landing operations, and to NWS MLB meteorologists generating short-range forecast products. The evolution of analyzed cloud fields from the squall line event were used to track the areal coverage and tendencies of cloud ceiling and cloud-top heights that impact the evaluation of space operation weather constraints and NWS aviation products. These cases also illustrate how the analyses can provide guidance for nowcasts and short-range forecasts of Florida warm-season convection and fire-weather parameters. In addition, some of the sensitivities of the ADAS analyses to selected observational data sources are discussed. Recently, a real-time version of ADAS was implemented at both SMG and the NWS MLB forecast offices. Future plans of this ADAS configuration include incorporating additional observational datasets and designing visualization products for specific forecast tasks. Finally, the ultimate goal is to use these ADAS analyses to initialize a high-resolution numerical weather prediction model run locally at SMG and the NWS MLB, in order to develop a cycling scheme that preserves fine-scale features such as convective outflow boundaries in shortrange numerical forecasts.

Large scale deployment and operation of distributed sensor assets optimized for robust Mars exploration

The large scale dispersal of distributed sensor arrays across planetary surfaces has been proposed by several groups for the exploration of Mars. We survey a number of these concepts and discuss their intrinsic advantages as well as technical challenges relative to more traditional exploration modalities. Specifically, distributed sensors working in conjunction with traditional surface vehicles enable critical phenomena to be measured in previously inaccessible terrain over temporal and spatial scales not obtainable otherwise. We discuss how this strategy can be integrated into an overall science campaign and address several key issues in regards to returning the acquired data. Dispersion and data extraction studies performed for the global environmental micro sensors (GEMS) project will be presented in the context of Mars exploration and the search for life. The modeling results provide insight into optimum strategies for distributing probes and then extracting measured data either via an ad hoc network or direct exfiltration to an orbital asset.

GEMS: A Revolutionary Concept for Planetary and Space Exploration

A novel observing system known as Global Environmental MEMS Sensors (GEMS) offers the potential to significantly improve the ability to take in situ measurements for a variety of space missions. The GEMS concept features devices with completely integrated sensing, power, and communications with characteristic dimensions of just millimeters. Thousands of these low‐cost devices could potentially be deployed together from a spacecraft to enable distributed sensing in planetary and other space environments. The deployment of such probes is analyzed and discussed for various scenarios on Mars that would provide measurements with unprecedented spatial and temporal resolution. The extended coverage provided by the arrays would improve the ability to calibrate remote sensing data while also extending the areas traditionally measured by localized landers. The unique features of such a system could significantly improve the capabilities for planetary and space exploration in the near and far term.

Airborne Sensor Network for Atmospheric Profiling

The need for higher spatial/temporal resolution in-situ atmospheric sensing has been established by both weather and climate researchers. In order to address this need, an airborne wireless sensor network called GlobalSense is currently being developed. GlobalSense is based on low-cost airborne probes that collect environmental data as they fall slowly through the atmosphere and on portable base stations that receive the data being collected. This paper presents an overview of this GlobalSense system as well as preliminary results from ground-based system testing.

How Nanotechnology Can Revolutionize Meteorological Observing with Lagrangian Drifters

The idea of using Lagrangian drifters for atmospheric sampling has been prevalent for more than 50 years. Substantial reductions in platform mass, size, and cost can now be realized by leveraging current and expected advances in micro- and ultimately nanotechnology. Such advancements have inspired a new observing system called Global Environmental Micro Sensors (GEMS). The initial GEMS concept envisioned developing and deploying large numbers of devices as small as 50–100 μim in one or more dimensions. The GEMS concept was evaluated during a multiyear study from 2002 to 2005 for the NASA Institute for Advanced Concepts. The current GEMS prototype features a 1-m, super-pressure balloon filled with helium to make it neutrally buoyant at different levels in the atmosphere. Once deployed, the probe measures temperature, pressure, relative humidity, velocity, and position information using microsensors as it drifts passively with the wind. Field experiments with GEMS prototypes were conducted in 2007 for a pro...