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Prediction of Energy Dissipation Rates for Aviation Turbulence. Part II: Nowcasting Convective and Nonconvective Turbulence

J. M. PearsonNational Center for Atmospheric Research, Boulder, Colorado

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R. D. SharmanNational Center for Atmospheric Research, Boulder, Colorado

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Abstract

In addition to turbulence forecasts, which can be used for strategic planning for turbulence avoidance, short-term nowcasts can augment longer-term forecasts by providing much more timely and accurate turbulence locations for real-time tactical avoidance of turbulence hazards, especially those related to short-lived convection. This paper describes a turbulence-nowcasting algorithm that combines recent short-term turbulence forecasts with all currently available direct turbulence observations and inferences of turbulence from other sources. Building upon the need to provide forecasts that are aircraft independent, the nowcasts provide estimates of an atmospheric metric of turbulence, namely, the energy dissipation rate to the one-third power (EDR). Some observations directly provide EDR, such as in situ observations from select commercial aircraft and ground-based radar algorithm output, whereas others must be translated to EDR. A strategy is provided for mapping turbulence observations, such as pilot reports (PIREPs), and inferences from other relevant observational data sources, such as observed surface wind gusts, into EDR. These remapped observation values can then be combined with short-term turbulence forecasts and other convective diagnostics of turbulence to provide a turbulence nowcast of EDR in the national airspace. Case studies are provided to illustrate the algorithm procedure and benefits. The EDR nowcasts are compared with aircraft in situ EDR observations and PIREPs converted to EDR to obtain metrics of statistical performance. It is shown by one common performance metric, the area under the relative operating characteristic curve, that the turbulence nowcasts with assimilated observations considerably outperform the corresponding turbulence forecasts.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Julia M. Pearson, jpearson@ucar.edu

Abstract

In addition to turbulence forecasts, which can be used for strategic planning for turbulence avoidance, short-term nowcasts can augment longer-term forecasts by providing much more timely and accurate turbulence locations for real-time tactical avoidance of turbulence hazards, especially those related to short-lived convection. This paper describes a turbulence-nowcasting algorithm that combines recent short-term turbulence forecasts with all currently available direct turbulence observations and inferences of turbulence from other sources. Building upon the need to provide forecasts that are aircraft independent, the nowcasts provide estimates of an atmospheric metric of turbulence, namely, the energy dissipation rate to the one-third power (EDR). Some observations directly provide EDR, such as in situ observations from select commercial aircraft and ground-based radar algorithm output, whereas others must be translated to EDR. A strategy is provided for mapping turbulence observations, such as pilot reports (PIREPs), and inferences from other relevant observational data sources, such as observed surface wind gusts, into EDR. These remapped observation values can then be combined with short-term turbulence forecasts and other convective diagnostics of turbulence to provide a turbulence nowcast of EDR in the national airspace. Case studies are provided to illustrate the algorithm procedure and benefits. The EDR nowcasts are compared with aircraft in situ EDR observations and PIREPs converted to EDR to obtain metrics of statistical performance. It is shown by one common performance metric, the area under the relative operating characteristic curve, that the turbulence nowcasts with assimilated observations considerably outperform the corresponding turbulence forecasts.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Julia M. Pearson, jpearson@ucar.edu
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