Weather Forecasting Accuracy for FAA Traffic Flow Management A Workshop Report (2003) / Chapter Skim
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2 Status of Aviation Weather Forecasting Research
2 Status of Aviation Weather Forecasting Research
Pages 10-34
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The second session of the workshop focused on research approaches and strategies to address convective weather forecasting. The discussions in this session were structured around four questions provided by the Federal Aviation Administration (FAA)
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STRATEGIES FOR IMPROVING CONVECTIVE FORECASTS Accurate prediction of convection in the 2- to 6-hour time range may not be amenable to an "engineered" solution without further research related to improved understanding of convection and the practical limits to its predictability. During the workshop, Richard Carbone of the National Center for Atmospheric Research (NCAR)
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Initial condition uncertainties, model physics, and chaotic evolution of convection are among the principal impediments to accurate forecasts. 24-Ho~r 1.-0~' QPF Verification .
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Employing the use of ensembles for probabilistic prediction can serve to quantify forecast uncertainty; however, knowledge is scant about true forecast sensitivities, initial state limitations, and how best to generate or select members of an ensemble. An optimist would attempt to observe initial states at a much higher temporal and spatial resolution, assuming model error per se is a small part of the problem.
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Fritsch noted that weather forecasting has traditionally focused on time- and space scales that, for the most part, are longer and larger, respectively, than the needs of the aviation industry. Specifically, forecasters have concentrated on synoptic-scale systems to forecast the "today, tonight, tomorrow" time period.
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From page 15... ...
Considering the multitude of nonlinearities that exist and interact in the atmosphere, the crude approximations applied in model initialization, and the various parameterization schemes and algorithms applied to output aviation parameters, undoubtedly, there can be large uncertainty and bias. Traffic flow management personnel not only recognize this inherent uncertainty when predicting weather but account for it through careful costbenef~t decision making in an effort to minimize the airlines' operating costs.
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Fritsch asserted that an alternative strategy to simply improving NWP may be necessary to provide the type of guidance needed by the aviation industry. One alternative would be to blend short-term observations-based statistical forecasting techniques with NWP output in a manner that will provide a time continuum of reliable quantitative measures of uncertainty that will fill the short-term gap created by the pre- and postprocessing required by NWP (see Figure 2-2~.
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Experience with isolated storms reveals low predictive skill at ranges greater than 1 hour, but such isolated convective storms are easily circumnavigated in the en-route environment. A multicellular linear storm complex or a mesoscale convective system can last for several hours and exhibit propagation speeds that are reasonably stable and thus enable skillful extrapolation forecasts out to 2 to 3 hours.
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From page 18... ...
Observations-based systems primarily use current conditions and trends to forecast convection. Examples of such systems include the Aviation Weather Research Program's Convective Weather Forecasts (Terminal Convective Weather Forecast, Regional Convective Weather Forecast, and National Convective Weather Forecast)
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· Use of NWP guidance in convective forecasts: Data fusion or expert system techniques need to be developed that combine numerical model forecasts, statistics, algorithmic observations, and human forecasts. For example, data fusion techniques could be developed to determine (1)
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Improvements should be expected in the S-year time frame for forecasts of multicellular systems that are forced by large-scale features. Improvements in forecasts of systems triggered by mesoscale features or elevated convection are farther down the road.
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Extending these results to moist convective flows suggests the following predictability timescales for these convective phenomena: Large mesoscale convective systems, 3 to 6 hours Squall lines, 2 to 3 hours Large thunderstorms, 1 to 2 hours Single convective cells, 10 to 60 minutes To examine the predictability of convection initiation, it is necessary to differentiate between cases that are strongly forced by large-scale
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Progress will only be made for this portion of the convective spectra by embracing probabilistic forecasting, possibly using ensemble techniques. Kelvin Droegemeier of the University of Oklahoma summarized the current state of research and development in the explicit prediction- both deterministic and stochastic deep convective storms.
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Research conducted during the past several years at the Center for Analysis and Prediction of Storms at the University of Oklahoma (Droegemeier, 1 997; Carpenter et al., 1999, Wang et al., 200 1; Weygandt et al., 2002; and Xue et al., 2003) has demonstrated considerable skill in the explicit prediction of convective storms, especially for events with moderate to strong mesa- or synoptic-scale forcing and in cases where high-resolution Doppler radar observations are available (see Figure 2-3~.
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Although sufficient information exists to capture some structure associated with storms to the south of Fort Worth, the tornadic storms to the north are completely absent - thus highlighting the value of radar data in storm-scale NWP.
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Indeed, the creation of suitable initial conditions for forecast models is the key element to successful storm-scale NWP. New observing systems, such as the planned phased array radar, along with current GPS water vapor sensing technologies, show great promise in this regard.
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Current understanding of model physics is sufficient to provide increasingly accurate convective forecasts- if observations of high spatial and temporal resolution are available to be blended with models. In particular, better observations of moisture could allow for significant improvements in model representations of convection.
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During the workshop, John McCarthy of the Naval Research Laboratory discussed techniques for presenting forecasts and potential strategies for the best use of convective forecasts in support of air traffic management. There is a significant disconnect between the language of convective nowcast and forecast capabilities provided by meteorologists and that of the nonmeteorological operational forecasting community.
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One key element he emphasized was the importance of having convective forecasts presented both graphically for use by human decision makers and in a numerical form suitable for use by air traffic management decision support tools. In addition, because highly accurate deterministic forecasts may be difficult to provide operationally a large fraction of the time (e.g., over 50 percent)
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Evans proposed that this would include development of probabilistic forecasts that can meaningfully be used by both humans and automated air traffic management and dispatch algorithms. For example, it would allow the translation of probabilistic forecasts into estimates of airspace and terminal capacity.2 In addition, better strategic mitigation planning capability should be possible by using optimized mitigation plans for cases where convection will only reduce traffic on routes and partially reduce capacities rather than a limited set of predefined options that only consider the very rare case of impenetrable weather.
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From page 30... ...
The RAPT software will utilize the 0- to 2-hour Regional Convective Weather Forecasts at a number of air traffic control facilities in 2003. Direct use of convective forecasts to assist air traffic users in making decisions about traffic routing, such as illustrated by RAPT, has significant implications for the presentation of convective weather forecasts and validation.
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From page 31... ...
" To answer this question, she started by defining the intended use of weather forecasts from an aviation perspective, which is to improve flight planning and thus maintain schedule integrity. Weather forecasts are used to predict the expected capacities in various en-route sectors of airspace as a function of space and time, route availability, including initial routes, alternate routes, miles in trail spacing, blockages, and flow-constrained areas; and terminal impacts, including the availability of alternate airports for landing en-route planes.
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A third alternative is to score an entire region in a way that characterizes the weather by spatial scale and whether the forecast has captured that spatial scale correctly. Schemes to verify forecasts must accommodate the meteorological developer's desire to improve overall forecast quality, the air traffic manager's interest in having the ability to trade off forecast capabilities, and the user's need for an easily interpreted measure of forecast quality.
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From page 33... ...
As other workshop participants noted, probabilistic forecasts are the key to verification and metrics of success in forecasts because skill measures for a single deterministic forecast are ambiguous. For example, evaluating a single deterministic forecast requires space-time averaging over designated windows to identify a "hit." Given the success in combining weather forecasts and air traffic control, Dr.
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Contrail formation could be limited using air traffic control and weather knowledge, thereby mitigating the climatic impact of aviation. With the ability to mitigate the climate impacts of aviation may come costs and responsibilities.
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