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The mean error characteristics of two series of forecasts of the tropical flow were studied. By using as initial conditions analyses made with and without the FGGE special observing system, the impact that initial data has on the accuracy of the forecasts is estimated.
The forecast skill of a simple dynamically inspired statistical model of the Northern Hemisphere 500 mb height field is evaluated in spectral and physical space for a variety of forecast lead times (1-32 days) and predictand averaging times (1-32 days). The model includes viscous damping, wave propagation, climatology and implicit stochastic forcing. The largest model skill was found for forecasts of the zonal flow and the largest waves. In general, the largest forecast skills were also associated with the largest forecast error, there being a slight geographic phase shift of the skill with respect to the error. Model skills for climate (time-averaged) forecasts are greater when using instantaneous rather than time averages to forecast time averages. Analysis of model errors suggests areas for improvement in representing forcing terms and model physics. However, the model error fields are largely 'white noise' which suggests that global forecast skills substantially larger than those obtained here are unlikely to be achieved by more sophisticated models.
The overall performance characteristics of a limited area, hydrostatic, fine (52 km) mesh, primitive equation, numerical weather prediction model are determined in anticipation of satellite data assimilations with the model. The synoptic and mesoscale predictive capabilities of version 2.0 of this model, the Mesoscale Atmospheric Simulation System (MASS 2.0), were evaluated. The two part study is based on a sample of approximately thirty 12h and 24h forecasts of atmospheric flow patterns during spring and early summer. The synoptic scale evaluation results benchmark the performance of MASS 2.0 against that of an operational, synoptic scale weather prediction model, the Limited area Fine Mesh (LFM). The large sample allows for the calculation of statistically significant measures of forecast accuracy and the determination of systematic model errors. The synoptic scale benchmark is required before unsmoothed mesoscale forecast fields can be seriously considered.
A report is presented regarding the synoptic- and mesoscale predictive capabilities of a regional-scale numerical weather prediction model known as the Mesoscale Atmospheric Simulation System (MASS, Version 2.0). The development of this model has been discussed by Kaplan et al. (1982). An evaluation of the performance of MASS 2.0 is based on the study of a sample of approximately thirty 12 h and 24 h forecasts of atmospheric flow patterns over the U.S. during spring and early summer of 1982. A description of model systems is provided, and synoptic-scale evaluation methods are considered along with aspects of mesoscale evaluation methodology, examples of coherent mesoscale information provided by MASS 2.0, the results of a diagnostic study of mesoscale convective systems (MCS), and the results of a limited real-time forecast experiment.
The author has identified the following significant results. Satellite-derived snow cover data improves forecasts of stream flow but not at a statistically significant amount and should not be used exclusively because of persistent cloud cover. Based upon reconstruction runs, satellite data can be used to augment snow-flight data in the Upper Snake, Boise, Dworshak, and Hungry Horse basins. Satellite data does not compare well with aerial snow-flight data in the Libby basin.
A mesoscale resolution biogeochemical survey was carried out in the vicinity of the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site during the summer of 1996. Real-time nowcasting and forecasting of the flow field facilitated adaptive sampling of several eddy features in the area. Variations in upper ocean nutrient and pigment distributions were largely controlled by vertical isopycnal displacements associated with the mesoscale field. Shoaling density surfaces tended to introduce cold, nutrient-rich water into the euphotic zone, while deepening isopycnals displaced nutrient-depleted water downward. Chlorophyll concentration was generally enhanced in the former case and reduced in the latter. Eddy-induced upwelling at the base of the euphotic zone was affected by features of two different types captured in this survey: (1) a typical mid-ocean cyclone in which doming of the main thermocline raised the near-surface stratification upward; and (2) a mode water eddy composed of a thick lens of 18 C water, which pushed up the seasonal thermocline and depressed the main thermocline. Model hindcasts using all available data provide a four-dimensional context in which to interpret temporal trends at the BATS site and two other locations during the two weeks subsequent to the survey. Observed changes in near-surface structure at the BATS site included shoaling iscpycnals, increased nutrient availability at the base of the euphotic zone, and enhanced chlorophyll concentration within the euphotic zone. These trends are explicable in terms of a newly formed cyclone that impinged upon the site during this time period. These observations reveal that eddy upwelling has a demonstrable impact on the way in which the nitrate-density relationship changes with depth from the aphotic zone into the euphotic zone. A similar transition is present in the BATS record, suggesting that eddy-driven upwelling events are present in the time series of upper ocean biogeochemical properties. The variability in main thermocline temperature and nitrate in this synoptic spatial survey spans the range observed in these quantities in the 10-year time series available at BATS to date (1988-1998).
A mesoscale resolution biogeochemical survey was carried out in the vicinity of the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site during the summer of 1996. Real-time nowcasting and forecasting of the flow field facilitated adaptive sampling of several eddy features in the area. Variations in upper ocean nutrient and pigment distributions were largely controlled by vertical isopycnal displacements associated with the mesoscale field. Shoaling density surfaces tended to introduce cold, nutrient-rich water into the euphotic zone, while deepening isopycnals displaced nutrient-depleted water downward. Chlorophyll concentration was generally enhanced in the former case and reduced in the latter. Eddy-induced upwelling at the base of the euphotic zone was affected by features of two different types captured in this survey-, (1) a typical mid-ocean cyclone in which doming of the main thermocline raised the near-surface stratification upward and (2) a mode water eddy composed of a thick lens of 18C water, which pushed up the seasonal thermocline and depressed the main thermocline. Model hindcasts using all available data provide a four-dimensional context in which to interpret temporal trends at the BATS site and two other locations during the 2 weeks subsequent to the survey. Observed changes in near-surface structure at the BATS site included shoaling isopycnals, increased nutrient availability at the base of the euphotic zone, and enhanced chlorophyll concentration within the cuphotic zone. These trends are explicable in terms of a newly formed cyclone that impinged upon the site during this time period. These observations reveal that eddy upwelling has a demonstrable impact on the way in which the nitrate-density relationship changes with depth from the aphotic zone into the euphotic zone. A similar transition is present in the BATS record, suggesting that eddy-driven upwelling events are present in the time series of upper ocean biogeochemical properties. The variability in main thermocline temperature and nitrate in this synoptic spatial survey spans the range observed in these quantities in the 10-year time series available at BATS to date (1988-1998).
NASA Water Resources works within Earth sciences to leverage investments of space-based observation, model results, and development and deployment of enabling technologies, systems, and capabilities into water resources management decision support tools for the sustainable use of water. Earth science satellite observations and modelling products provide a huge volume of valuable data in both near-real-time and extended back nearly 50 years about the Earth's land surface conditions such as land cover type, vegetation type and health, precipitation, snow, soil moisture, and water levels and radiation. Observations of this type combined with models and analysis enable satellite-based assessment of the water cycle. With increasing population pressure and water usage coupled with climate variability and change, water issues are being reported by numerous groups as the most critical environmental problems facing us in the 21st century. Competitive uses and the prevalence of river basins and aquifers that extend across boundaries engender political tensions between communities, stakeholders and countries. The NASA Water Resources Program has the objective to provide NASA products to help deal with these issues with the goal for the sustainable use of water. The Water Resources program organizes its projects under five functional themes: 1) stream-flow and flood forecasting; 2) water consumptive use (includes evapotranspiration) and irrigation; 3) drought; 4) water quality; and 5) climate and water resources. NASA primarily works with national and international groups such as other US government agencies (NOAA, EPA, USGS, USAID) and various other groups to maximize the widest use of the water products. A summary of NASA's water activities linked to helping solve issues for developing countries will be highlighted.
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.
Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.
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.
Single Doppler radar techniques are used to study the precipitation and kinematic structure of microburst-producing storms. Radar data collected by NCAR radars during the Joint Airport Weather Studies (JAWS) experiment are presented along with rawinsonde data taken at Denver, Colorado near the times of microburst occurrence. The radar reflectivity and velocity structure of the storms exhibited great variability, with no unique signature indicating a microburst was imminent. Detection of descending divergent flow is probably not a microburst forecasting tool, nor can the presence of rotation be used as a precursor at present. Convergent flow aloft was a prominent feature in all events. Its occurrence with a descending precipitation shaft and/or at high altitudes is a good indicator of a downdraft. It is concluded that convergent flow is a very important microburst forecasting clue, particularly when coupled with the entrainment of Theta(e) air and a dry-adiabatic lapse rate below cloud base.
Relations between stratospheric wind errors, initial states and 500 mb skill are investigated using the GLAS general circulation model initialized with FGGE data. Erroneous stratospheric winds are seen in all current general circulation models, appearing also as weak shear above the subtropical jet and as cold polar stratospheres. In this study it is shown that the more anticyclonic large-scale flows are correlated with large forecast stratospheric winds. In addition, it is found that for North America the resulting errors are correlated with initial state jet stream accelerations while for East Asia the forecast winds are correlated with initial state jet strength. Using 500 mb skill scores over Europe at day 5 to measure forecast performance, it is found that both poor forecast skill and excessive stratospheric winds are correlated with more anticyclonic large-scale flows over North America. It is hypothesized that the resulting erroneous kinetic energy contributes to the poor forecast skill, and that the problem is caused by a failure in the modeling of the stratospheric energy cycle in current general circulation models independent of vertical resolution.
A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?
A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASAs Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlantas Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the studys trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 20-knot over-predictions and 20-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?
Develop climatologies of gridded CG lightning densities and frequencies of occurrence for the Melbourne, FL National Weather Service (NWS MLB) county warning area. These grids are used to create a first-guess field for the lightning threat index map that is available on the NWS MLB NASA KSCIKT website. Forecasters previously created this map from scratch. Having the climatologies as a background field will increase consistency between forecasters and decrease their workload. Delivered all files containing the lightning climatologies, the data, and the code used to create the climatologies to NWS MLB. Completed and distributed a final memorandum describing how the climatologies were created. All the files were installed on the NWS MLB computer system, and then the code was compiled and tested to ensure that it worked properly on their operating system. The climatologies and their descriptions are posted on the NWS MLB website. Forecasting Low-Level Convergent Bands Under Southeast Flow Provide guidance to operational personnel that will help improve their forecasts of cloud bands under large-scale southeast flow. When these bands occur, they can lead to cloud, rain, and thunderstorm occurrences that adversely affect launch, landing, and ground operations at Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Completed the first draft of the final report. The conclusions from this task indicated low-level wind speed and direction, low-level high pressure ridge position, east coast sea breeze front activity and upper-level jet streak position have the greatest influence on convergent band formation and movement during southeasterly flow.
The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.
A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.