• Bouttier, F., Ed., 2009: AROME system documentation, 19 pp. [Available online at http://www.cnrm.meteo.fr/arome/doc/arodoc.pdf.]

  • Costa, P., , P. Miranda, , and A. Estanqueiro, 2006: Development and validation of the Portuguese wind atlas. Proc. European Wind Energy Conf. and Exhibition, Athens, Greece, EWEA, BL3.336. [Available online at http://www.ewec2006proceedings.info/allfiles2/841_Ewec2006fullpaper.pdf.]

    • Search Google Scholar
    • Export Citation
  • Dazhang, T., , S. G. Geotis, , R. E. Passarelli, , A. L. Hansen, , and C. L. Frush, 1984: Evaluation of an alternating-PRF method for extending the range of unambiguous Doppler velocity. Preprints, 22nd Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 523–527.

    • Search Google Scholar
    • Export Citation
  • Delaunay, D., , S. Louineau, , and T. Clarenc, 2009: A new atlas for the region “Provence-Alpes-Cote D’Azur.” Proc. European Wind Energy Conf. and Exhibition, Marseille, France, EWEA, PO.91. [Available online at http://www.ewec2009proceedings.info/programme/all.php#.]

    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., , and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. Academic Press, 567 pp.

  • Järvinen, H., , K. Salonen, , M. Lindskog, , A. Huuskonen, , S. Niemelä, , and R. Eresmaa, 2009: Doppler radar radial winds in HIRLAM. Part I: Observation modelling and validation. Tellus, 61A, 278287.

    • Search Google Scholar
    • Export Citation
  • Lindskog, M., , K. Salonen, , H. Järvinen, , and D. B. Michelson, 2004: Doppler radar wind data assimilation with HIRLAM 3DVAR. Mon. Wea. Rev., 132, 10811092.

    • Search Google Scholar
    • Export Citation
  • Mortensen, N. G., , L. Landberg, , I. Troen, , and E. L. Petersen, 1993: Wind Atlas Analysis and Application Program (WAsP). Risø National Laboratory, Roskilde, Denmark, 126 pp.

    • Search Google Scholar
    • Export Citation
  • Salonen, K., , H. Järvinen, , and M. Lindskog, 2003: Model for Doppler radar radial winds. Preprints, 31st Conf. on Radar Meteorology, Vol. 1, Seattle, WA, Amer. Meteor. Soc., 142–145.

    • Search Google Scholar
    • Export Citation
  • Salonen, K., , H. Järvinen, , R. Eresmaa, , and S. Niemelä, 2007: Bias estimation of Doppler-radar radial-wind observations. Quart. J. Roy. Meteor. Soc., 133, 15011507.

    • Search Google Scholar
    • Export Citation
  • Salonen, K., , H. Järvinen, , S. Järvenoja, , S. Niemelä, , and R. Eresmaa, 2008: Doppler radar radial wind data in NWP model validation. Meteor. Appl., 15, 97102.

    • Search Google Scholar
    • Export Citation
  • Salonen, K., , G. Haase, , R. Eresmaa, , H. Hohti, , and H. Järvinen, 2011: Towards the operational use of Doppler radar radial winds in HIRLAM. Atmos. Res., 100, 190200.

    • Search Google Scholar
    • Export Citation
  • Saltikoff, E., , A. Huuskonen, , H. Hohti, , Koistinen J., , and H. Järvinen, 2010: Quality assurance in the FMI Doppler radar network. Boreal Environ. Res., 15, 579594.

    • Search Google Scholar
    • Export Citation
  • Seity, Y., , P. Brousseau, , S. Malardel, , G. Hello, , P. Bénard, , F. Bouttier, , C. Lac, , and V. Masson, 2011: The AROME-France convective scale operational model. Mon. Wea. Rev., 139, 976991.

    • Search Google Scholar
    • Export Citation
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Application of Radar Wind Observations for Low-Level NWP Wind Forecast Validation

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  • 1 Finnish Meteorological Institute, Helsinki, Finland
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Abstract

The Finnish Meteorological Institute has produced a new numerical weather prediction model–based wind atlas of Finland. The wind atlas provides information on local wind conditions in terms of annual and monthly wind speed and direction averages. In the context of the wind atlas project, low-level Applications of Research to Operations at Mesoscale (AROME) model wind forecasts have been validated against radar radial wind observations and, as a comparison, against conventional radiosonde observations to confirm the realism of the wind forecasts. The results indicate that the systematic and random errors in the AROME wind forecasts are relatively small and are of the same order of magnitude independent of the validating observation type. The validation benefits from the high spatial and temporal resolution of the radar observations. There are over 4000 times as many radar observations as radiosonde observations available for the considered validation period of July 2008–May 2009.

Corresponding author address: Kirsti Salonen, Finnish Meteorological Institute, P.O. Box 503, FI-00101 Helsinki, Finland. E-mail: kirsti.salonen@fmi.fi

Abstract

The Finnish Meteorological Institute has produced a new numerical weather prediction model–based wind atlas of Finland. The wind atlas provides information on local wind conditions in terms of annual and monthly wind speed and direction averages. In the context of the wind atlas project, low-level Applications of Research to Operations at Mesoscale (AROME) model wind forecasts have been validated against radar radial wind observations and, as a comparison, against conventional radiosonde observations to confirm the realism of the wind forecasts. The results indicate that the systematic and random errors in the AROME wind forecasts are relatively small and are of the same order of magnitude independent of the validating observation type. The validation benefits from the high spatial and temporal resolution of the radar observations. There are over 4000 times as many radar observations as radiosonde observations available for the considered validation period of July 2008–May 2009.

Corresponding author address: Kirsti Salonen, Finnish Meteorological Institute, P.O. Box 503, FI-00101 Helsinki, Finland. E-mail: kirsti.salonen@fmi.fi
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