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NASA NTRS2003

Adaptation of Mesoscale Weather Models to Local Forecasting

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation.

Manobianco, John T.↗

NASA NTRS2020

A Systematic Review of Local to Regional Yield Forecasting Approaches and Frequently Used Data Resources

Forecasting crop yields, or providing an expectation of ex-ante harvest amounts, is highly relevant to the whole agricultural production chain. Farmers can adapt their management, traders or insurers their pricing schemes, suppliers their stocks, logistic companies their routes, national authorities their food balance sheets to guide import or export and, finally, international aid organizations can mobilize reliefs. Evidence has grown in the literature that such forecasts with a meaningful lead time are possible on various geographic scales and for a broad range of crops. Here, we present a systematic review of the methods applied in end-of-season yield forecasting and three frequently used data sources: weather data, satellite data and crop masks. Our literature database comprises 362 studies (2004–2019) which were evaluated regarding methods, crops, regions, data sources, lead time and performance. Moreover, we present 24 sources of real-time and predictive weather data, 21 sources of remote sensing data and 16 crop masks. Yield forecasting in our literature sample has been performed for 44 crops in 71 countries, also including many non-staple crops, but with an apparent bias in regions and crops. Forecasting performance depends on various factors, including crop, region, method, lead time to harvest and input diversity. Our systematic review supports a broader application of locally successful approaches at larger scales by providing a comprehensive, accessible compendium of necessary information for yield forecasting. We discuss improvement potentials with respect to methodological approaches and available data sources. We additionally suggest standardization procedures for future forecasting studies and encourage studying additional crops and geographic regions. Implications of forecasts for different target groups on different scales and the adaptation towards climate change are also discussed.

Seasonal crop yield forecasting↗

NASA NTRS2009

An Anomaly Correlation Skill Score for the Evaluation of the Performance of Hyperspectral Infrared Sounders

With the availability of very accurate forecasts, the metric of accuracy alone for the evaluation of the performance of a retrieval system can produce misleading results. A useful characterization of the quality of a retrieval system and its potential to contribute to an improved weather forecast is its skill, which we define as the ability to make retrievals of geophysical parameters which are closer to the truth than the six hour forecast, when the truth differs significantly from the forecast. We illustrate retrieval skill using one day of AMSU and AIRS data with three different retrieval algorithms, which result in retrievals for more than 90% of the potential retrievals under clear and cloudy conditions. Two of the three algorithms have better than 1 K rms "RAOB quality" accuracy on the troposphere, but only one has skill between 900 and 100 mb. AIRS was launched on the EOS Aqua spacecraft in May 2002 into a 705 km polar sun-synchronous orbit with accurately maintained 1:30 PM ascending node. Essentially uninterrupted data are freely available since September 2002.

retrieval↗

NASA NTRS2010

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

NASA NTRS2005

Objective Lightning Probability Forecasting for Kennedy Space Center and Cape Canaveral Air Force Station

Five logistic regression equations were created that predict the probability of cloud-to-ground lightning occurrence for the day in the KSC/CCAFS area for each month in the warm season. These equations integrated the results from several studies over recent years to improve thunderstorm forecasting at KSC/CCAFS. All of the equations outperform persistence, which is known to outperform NPTI, the current objective tool used in 45 WS lightning forecasting operations. The equations also performed well in other tests. As a result, the new equations will be added to the current set of tools used by the 45 WS to determine the probability of lightning for their daily planning forecast. The results from these equations are meant to be used as first-guess guidance when developing the lightning probability forecast for the day. They provide an objective base from which forecasters can use other observations, model data, consultation with other forecasters, and their own experience to create the final lightning probability for the 1100 UTC briefing.

Lambert, Winifred↗

NASA NTRS1994

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Todling, Ricardo↗

NASA NTRS2015

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

NASA NTRS2008

Impact of Local Sensors

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and the CCAFS (XMR) daily rawinsonde observations (RAOB) to issue and verify wind advisories and warnings for operations. These observations are also used by the National Weather Service (NWS) Spaceflight Meteorology Group (SMG) in Houston, Texas and the NWS Melbourne, Florida (NWS MLB) to initialize their locally-run mesoscale models. In addition, SMG uses these observations to support shuttle landings at the Shuttle Landing Facility (SLF). Due to impending budget cuts, some or all of the KSC/CCAFS wind towers on the east-central Florida mainland and the XMR RAOBs may be eliminated. The locations of the mainland towers and XMR RAOB site are shown in Figure I. The loss of these data may impact the forecast capability of the 45 WS, SMG and NWS MLB. The AMU was tasked to conduct an objective independent modeling study to help determine how important these observations are to the accuracy of the model output used by the forecasters. To accomplish this, the Applied Meteorology Unit (AMU) performed a sensitivity study using the Weather Research and Forecasting (WRF) model initialized with and without KSC/CCAFS wind tower and XMR RAOB data.

Watson, Leela R.↗

NASA NTRS2004

Link Design and Planning for Mars Reconnaissance Orbiter (MRO) Ka-band (32 GHz) Telecom Demonstration

NASA is planning an engineering telemetry demonstration with Mars Reconnaissance Orbiter (MRO). Capabilities of Ka-band (32 GHz) for use with deep space mission are demonstrated using the link optimization algorithms and weather forecasting. Furthermore, based on the performance of previous deep space missions with Ka-band downlink capabilities, experiment plans are developed for telemetry operations during superior solar conjunction. A general overview of the demonstration is given followed by a description of the mission planning during cruise, the primary science mission and superior conjunction. As part of the primary science mission planning the expected data return for various data optimization methods is calculated. These results indicate that, given MRO's data rates, a link optimized to use of at most two data rates, subject to a minimum availability of 90%, performs almost as well as a link with no limits on the number of data rates subject to the same minimum availability.

Ka-band↗

NASA NTRS2005

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Lambert, Winnie↗

NASA NTRS1988

Tropical synoptic signatures in composited 6.7 micrometer water vapor imagery

A model of the signatures of a synoptic development as seen in 6.7-micron water vapor channel imagery has been constructed from a composite of cases for a moisture burst over the eastern Pacific Ocean. The characteristics revealed in these composites are discussed and compared with the signatures of the moisture bursts as seen in satellite-derived visual and window channel IR imagery. A test of the forecast capability of the model was performed on 120 consecutive days, including 29 moisture bursts. After 2 hours of training, a meteorologist was able to forecast 19 (65 percent) of the bursts at least 24 hours in advance. In 6 cases, bursts were forecast when none occurred.

Thompson, A. H.↗

NASA NTRS1991

Fitting dynamic models to the Geosat sea level observations in the tropical Pacific Ocean. I - A free wave model

Free, equatorially trapped sinusoidal wave solutions to a linear model on an equatorial beta plane are used to fit the Geosat altimetric sea level observations in the tropical Pacific Ocean. The Kalman filter technique is used to estimate the wave amplitude and phase from the data. The estimation is performed at each time step by combining the model forecast with the observation in an optimal fashion utilizing the respective error covariances. The model error covariance is determined such that the performance of the model forecast is optimized. It is found that the dominant observed features can be described qualitatively by basin-scale Kelvin waves and the first meridional-mode Rossby waves. Quantitatively, however, only 23 percent of the signal variance can be accounted for by this simple model.

Fu, Lee-Lueng↗

NASA NTRS2007

Using Flow Regime Lightning and Sounding Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourne, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (httl://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in East Central Florida, especially during the warm season months of May September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Until recently, the forecasters created each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent was to improve consistency between forecasters while allowing them to focus on the mesoscale detail of the forecast. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) in which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities, or number of strikes per specified area. The soundings used to determine the flow regimes were taken at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), FL, and the lightning data for the strike densities came from the National Lightning Detection Network (NLDN). The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at FSU and NWS TAE provided this data and supporting software for the work performed by the AMU.

Lambert, Winifred↗

NASA NTRS2006

Using Flow Regime Lightning and Sounding Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourne, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in East Central Florida, especially during the warm season months of May September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to improve consistency between forecasters while allowing them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) in which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities, or number of strikes per specified area. The soundings used to determine the flow regimes were taken at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), FL, and the lightning data for the strike densities came from the National Lightning Detection Network (NLDN). The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at FSU and NWS TAE provided this data and supporting software for the work performed by the AMU.

Lambert, Winifred↗

NASA NTRS2024

Use of Forecast Atmosphere for Earth Entry, Descent, and Landing Modeling

Flight mechanics simulations are used to characterize the performance of Earth entry, descent, and landing vehicles. Atmospheric prediction models are often a key component of these simulations. Global atmospheric models are used for both engineering design due to their ability to define atmospheric properties over a large swath of locations and times as well as used for the availability of atmospheric uncertainties in the models that can be used in statistical performance analysis. However for day-of-flight operations, the use of forecast atmospheres based on more current measurements are beneficial to the accuracy of the performance prediction, including landing locations. Reanalysis of these forecasts can also be used for post-flight analysis, including trajectory reconstruction. This paper describes how forecast atmospheres can be beneficial for Earth entry, descent, and landing analysis and ways these models can be implemented in simulations.

Soumyo Dutta↗

NASA NTRS2014

MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

MAG4 is a technique of forecasting an active region's rate of production of major flares in the coming few days from a free-magnetic-energy proxy. We present a statistical method of measuring the difference in performance between MAG4 and comparable alternative techniques that forecast an active region's major-flare productivity from alternative observed aspects of the active region. We demonstrate the method by measuring the difference in performance between the "Present MAG4" technique and each of three alternative techniques, called "McIntosh Active-Region Class," "Total Magnetic Flux," and "Next MAG4." We do this by using (1) the MAG4 database of magnetograms and major-flare histories of sunspot active regions, (2) the NOAA table of the major-flare productivity of each of 60 McIntosh active-region classes of sunspot active regions, and (3) five technique-performance metrics (Heidke Skill Score, True Skill Score, Percent Correct, Probability of Detection, and False Alarm Rate) evaluated from 2000 random two-by-two contingency tables obtained from the databases. We find that (1) Present MAG4 far outperforms both McIntosh Active-Region Class and Total Magnetic Flux, (2) Next MAG4 significantly outperforms Present MAG4, (3) the performance of Next MAG4 is insensitive to the forward and backward temporal windows used, in the range of one to a few days, and (4) forecasting from the free-energy proxy in combination with either any broad category of McIntosh active-region classes or any Mount Wilson active-region class gives no significant performance improvement over forecasting from the free-energy proxy alone (Present MAG4).

Falconer, David A.↗

NASA NTRS2014

MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

Falconer, David A.↗

NASA NTRS2011

Performance of Airborne Precision Spacing Under Realistic Wind Conditions and Limited Surveillance Range

With the expected worldwide increase of air traffic during the coming decade, both the Federal Aviation Administration's (FAA's) Next Generation Air Transportation System (NextGen), as well as Eurocontrol's Single European Sky ATM Research (SESAR) program have, as part of their plans, air traffic management (ATM) solutions that can increase performance without requiring time-consuming and expensive infrastructure changes. One such solution involves the ability of both controllers and flight crews to deliver aircraft to the runway with greater accuracy than they can today. Previous research has shown that time-based spacing techniques, wherein the controller assigns a time spacing to each pair of arriving aircraft, can achieve this goal by providing greater runway delivery accuracy and producing a concomitant increase in system-wide performance. The research described herein focuses on one specific application of time-based spacing, called Airborne Precision Spacing (APS), which has evolved over the past ten years. This research furthers APS understanding by studying its performance with realistic wind conditions obtained from atmospheric sounding data and with realistic wind forecasts obtained from the Rapid Update Cycle (RUC) short-range weather forecast. In addition, this study investigates APS performance with limited surveillance range, as provided by the Automatic Dependent Surveillance-Broadcast (ADS-B) system, and with an algorithm designed to improve APS performance when ADS-B surveillance data is unavailable. The results presented herein quantify the runway threshold delivery accuracy of APS under these conditions, and also quantify resulting workload metrics such as the number of speed changes required to maintain spacing.

Wieland, Frederick↗