Identification

Title

Prediction of energy dissipation rates for aviation turbulence. Part I: Forecasting nonconvective turbulence

Abstract

Current automated aviation turbulence forecast algorithms diagnose turbulence from numerical weather prediction (NWP) model output by identifying large values in computed horizontal or vertical spatial gradients of various atmospheric state variables (velocity; temperature) and thresholding these gradients empirically to indicate expected areas of "light,'' "moderate,'' and "severe'' levels of aviation turbulence. This approach is obviously aircraft dependent and cannot accommodate the many different aircraft types that may be in the airspace. Therefore, it is proposed to provide forecasts of an atmospheric turbulence metric: the energy dissipation rate to the one-third power (EDR). A strategy is developed to statistically map automated turbulence forecast diagnostics or groups of diagnostics to EDR. The method assumes a lognormal distribution of EDR and uses climatological peak EDR data from in situ equipped aircraft in conjunction with the distribution of computed diagnostic values. These remapped values can then be combined to provide an ensemble mean EDR that is the final forecast. New mountain-wave-turbulence algorithms are presented, and the lognormal mapping is applied to them as well. The EDR forecasts are compared with aircraft in situ EDR observations and verbal pilot reports (converted to EDR) to obtain statistical performance metrics of the individual diagnostics and the ensemble mean. It is shown by one common performance metric, the area under the relative operating characteristics curve, that the ensemble mean provides better performance than forecasts from individual model diagnostics at all altitudes (low, mid-, and upper levels) and for two input NWP models.

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document

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http://n2t.net/ark:/85065/d7qc059j

codeSpace

Dataset language

eng

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Classification of spatial data and services

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geoscientificInformation

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title

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reference date

date type

publication

effective date

2016-01-01T00:00:00Z

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publication

effective date

2017-02-01T00:00:00Z

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Copyright 2017 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

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None

Responsible organisations

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contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

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pointOfContact

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