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Consolidated storm prediction for aviation (CoSPA)

Published in:
Proc. of the 2008 Integrated Communications, Navigation and Surveillance Conf., 20-24 January 2008.

Summary

Research over the last 10 years primarily funded by the FAA Aviation Weather Research Program (AWRP) has led to very successful development of forecasts of both convective and winter storms, using heuristic and numerical models, for aviation applications. We have reached a point where there are several overlapping capabilities, and the smorgasbord of choices has become confusing. Moreover, aviation-impacting winter and summer conditions can exist simultaneously - even within a single terminal area - so a consolidated forecast must work equally well for all storm conditions. Advances in computing and communications allow incorporation of new observing systems and scientific advancements in data assimilation and modeling toward large-scale, very high resolution forecast systems that were prohibitive just 10 years ago. Other government agencies, in addition to FAA, have needs for aviation-oriented forecasts, including at least the National Weather Service, NASA, Homeland Defense, Air Force and other DoD agencies. Further efficiencies will be realized by consolidating such efforts as well. These goals are well-aligned with the goals of the Next Generation Air Transportation System and its Joint Program and Development Office. The FAA Aviation Weather Research Program is leading development of the new Consolidated Storm Prediction for Aviation (CoSPA) effort, which will combine aviation-oriented storm research in a coordinated fashion, with the goal of eventually replacing operational legacy storm diagnostic and forecast products, as appropriate, that are also geared toward aviation (see Appendix A). While many of the current storm prediction products are derived using NOAA model forecast data, especially from the hourly updated 13-km Rapid Update Cycle (RUC) model over CONUS, CoSPA products will be related to a new generation of NOAA models now assimilating radar reflectivity and lightning, including the Rapid Refresh, its proposed nest - the High-Resolution Rapid Refresh (HRRR), and ensemble-based products from both. A kick-off meeting was held in June 2006 to discuss AWRP?s concepts for a consolidated aviation forecast, and to understand unmet user needs, major scientific development issues, and also to begin to explore issues associated with production and dissemination of a consolidated forecast. These findings are summarized below.
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Summary

Research over the last 10 years primarily funded by the FAA Aviation Weather Research Program (AWRP) has led to very successful development of forecasts of both convective and winter storms, using heuristic and numerical models, for aviation applications. We have reached a point where there are several overlapping capabilities, and...

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Wind prediction accuracy for air traffic management decision support tools

Published in:
Proc. 3rd Int. Air Traffic Management R&R Seminar, 13-16 June 2000, pp. 1-9.

Summary

Air traffic automation depends on accurate trajectory predictions. Flight tests show that wind errors are a large source of error. Wind-field accuracy is sufficient on average, but large errors occasionally exist that cause significant errors in trajectory-prediction. A year long study was conducted to better understand the wind-prediction errors, to establish metrics for quantifying large errors, and to validate two approaches to improve wind prediction accuracy. Three methods are discussed for quantifying large errors: percentage of point errors that exceed 10 m/s, probability distribution of point errors, and the number of hourly time periods with a high number of large errors. The baseline wind-prediction system evaluated for this study is the Rapid Update Cycle (RUC). Two approaches to improving the original RUC wind predictions are examined. The first approach is to enhance RUC in terms of increased model resolution, enhancement of the model physics, and increased observational input data. The second method is to augment the RUC output, in near-real time, through an optimal-interpolation scheme that incorporates the latest aircraft reports received since the last RUC update. Both approaches are shown to greatly reduce the occurrence of large wind errors.
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Summary

Air traffic automation depends on accurate trajectory predictions. Flight tests show that wind errors are a large source of error. Wind-field accuracy is sufficient on average, but large errors occasionally exist that cause significant errors in trajectory-prediction. A year long study was conducted to better understand the wind-prediction errors, to...

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