Downscaling surface wind predictions from numerical weather prediction models in complex terrain with WindNinja

Wind predictions in complex terrain are important for a number of applications. Dynamic downscaling of numerical weather prediction (NWP) model winds with a high-resolution wind model is one way to obtain a wind forecast that accounts for local terrain effects, such as wind speed-up over ridges, flo...

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Bibliographic Details
Published inAtmospheric chemistry and physics Vol. 16; no. 8; pp. 5229 - 5241
Main Authors Wagenbrenner, Natalie S, Forthofer, Jason M, Lamb, Brian K, Shannon, Kyle S, Butler, Bret W
Format Journal Article
LanguageEnglish
Published Katlenburg-Lindau Copernicus GmbH 27.04.2016
Copernicus Publications
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Summary:Wind predictions in complex terrain are important for a number of applications. Dynamic downscaling of numerical weather prediction (NWP) model winds with a high-resolution wind model is one way to obtain a wind forecast that accounts for local terrain effects, such as wind speed-up over ridges, flow channeling in valleys, flow separation around terrain obstacles, and flows induced by local surface heating and cooling. In this paper we investigate the ability of a mass-consistent wind model for downscaling near-surface wind predictions from four NWP models in complex terrain. Model predictions are compared with surface observations from a tall, isolated mountain. Downscaling improved near-surface wind forecasts under high-wind (near-neutral atmospheric stability) conditions. Results were mixed during upslope and downslope (non-neutral atmospheric stability) flow periods, although wind direction predictions generally improved with downscaling. This work constitutes evaluation of a diagnostic wind model at unprecedented high spatial resolution in terrain with topographical ruggedness approaching that of typical landscapes in the western US susceptible to wildland fire.
ISSN:1680-7324
1680-7316
1680-7324
DOI:10.5194/acp-16-5229-2016