Model Estimates of Traffic Reduction in Storm Impacted En Route Airspace

Martin, Brian

doi:10.2514/6.2007-7889

Cited by 18 publications

(12 citation statements)

References 2 publications

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“…To account for uncertainty in weather predictions the probe of each flight trajectory is broadened to include a corridor centered on the route (MIT's Lincoln Labs introduced this approach 9 ). Between each fix pair segment of the route, the corridor is divided into a grid of one kilometer cells as shown in Fig.…”

Section: Algorithms 1 Weather Impact Identificationmentioning

confidence: 99%

A Concept for Tactical Reroute Generation, Evaluation and Coordination

Stewart

Askey

Hokit

2012

12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis And

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A concept is described that enables traffic managers to efficiently develop and coordinate tactical reroutes around convective weather, facilitating incremental decision making. Tactical reroutes are more precise and efficient than strategic ones, since weather predictions improve as look-ahead time decreases. Currently, tactical rerouting is prohibitively labor intensive as there is little automation assistance to identify flights projected to be affected by weather, to choose appropriate reroutes, and to coordinate them. In the United States, electronic means will soon be available for coordinating reroutes between traffic managers and en route controllers, making tactical rerouting a much more viable option for traffic managers. The Tactical Rerouting concept presented here takes advantage of this technology, and adds decision support capabilities that together increase throughput near a weather constraint and thereby reduce the need for larger scale, strategic Traffic Management Initiatives that frequently produce unnecessary delays.

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Section: Algorithms 1 Weather Impact Identificationmentioning

confidence: 99%

A Concept for Tactical Reroute Generation, Evaluation and Coordination

Stewart

Askey

Hokit

2012

12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis And

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“…The resulting available flow capacity ratio [Song et al, 2007[Song et al, , 2008 represents a non-dimensional measure ranging between zero (i.e., unusable airspace without any capacity) and unity (fully usable airspace without weather constraints). Note that today's airspace is burdened by the need for pilots to conform to jet routes while avoiding weather hazards [Martin et al, 2006;Martin, 2007] and constraints imposed by controller workload, which can seriously limit capacity [e.g., Histon et al, 2002]. Depending on the degree of automation in NextGen and SESAR, jet route conformance and controller workload constraints may become less of an issue.…”

Section: Translating Weather Into Aviation Impactmentioning

confidence: 99%

Translation of Ensemble Weather Forecasts into Probabilistic Air Traffic Capacity Impact

Steiner

Bateman

Megenhardt

et al. 2010

Air Traffic Control Quarterly

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Today's trend in probabilistic weather forecasting is toward utilizing ensemble prediction systems. In the Next Generation Air Transportation System (NextGen), ensemble-based weather forecasting will be a common practice. Therefore, this paper explores a novel approach of using highresolution, ensemble-based numerical weather prediction model data for weather-related, probabilistic aviation impact forecasting. The concept represents a paradigm shift from "creating ensembles of weather information" (e.g., maps of predicted weather hazard intensity) to "developing ensembles of aviation-relevant information" (maps of potential throughput as measured by the available flow capacity ratio), which entails a translation of weather forecasts into predictions of reduced airspace capacity. The proof-of-concept is exemplified by focusing on convective storms; however, in principal, the approach may be applicable to other aviation hazards, like turbulence, icing, or ceiling and visibility. The concept is most pertinent to strategic en route traffic flow management, but it also applies to terminal area applications. A probabilistic approach is appropriate for strategic planning horizons, for which deterministic weather forecasts are significantly less accurate and an ensemble of forecasts may provide guidance about the weather (and impact) uncertainty.

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“…Traffic reduction due to weather impact can be modeled in many different ways. 15 In this research, the weather-free prediction was first estimated, then the sector weather index was used to adjust the prediction. Assume that the sector demand starts to decay when the sector weather factor exceeds w low , and reaches 0 when the weather factor reaches w high .…”

Section: Weather Factormentioning

confidence: 99%

Weather-Weighted Periodic Auto Regressive Models for Sector Demand Prediction

Chen

Sridhar

2009

AIAA Guidance, Navigation, and Control Conference

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This paper describes a class of weather-weighted periodic auto-regressive sector demand prediction models. The periodic auto-regressive model captures both the mid-term (30 minutes to 2 hours) trend based on the historical data, and the short-term (less than 30 minutes) transient response based on recent observations. For severe weather days, the model uses the three-dimensional weather information, considering both storm locations and echo tops, to form a weather factor to adjust the predictions. Unlike the traditional trajectory-based sector demand prediction methods, which predict the behavior of the National Airspace System adequately for short durations of up to 20 minutes and are vulnerable to the weather uncertainties, this class of models provides reliable short to mid-term sector demand predictions which account for the weather uncertainty.

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Model Estimates of Traffic Reduction in Storm Impacted En Route Airspace

Cited by 18 publications

References 2 publications

A Concept for Tactical Reroute Generation, Evaluation and Coordination

A Concept for Tactical Reroute Generation, Evaluation and Coordination

Translation of Ensemble Weather Forecasts into Probabilistic Air Traffic Capacity Impact

Weather-Weighted Periodic Auto Regressive Models for Sector Demand Prediction

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