• Alpers, W., and B. Brümmer, 1994: Atmospheric boundary layer rolls observed by the synthetic aperture radar aboard the ERS-1 satellite. J. Geophys. Res., 99 , 1261312621.

    • Search Google Scholar
    • Export Citation
  • Brown, R., 1980: Longitudinal instabilities and secondary flows in the planetary boundary layer: A review. Rev. Geophys. Space Phys., 18 , 683697.

    • Search Google Scholar
    • Export Citation
  • Dankert, H., J. Horstmann, and W. Rosenthal, 2003: Ocean wind fields retrieved from radar-image sequences. J. Geophys. Res., 108 .3352, doi:10.1029/2003JC002056.

    • Search Google Scholar
    • Export Citation
  • Donelan, M., and W. Pierson, 1987: Radar scattering and equilibrium ranges in wind-generated waves with application to scatterometry. J. Geophys. Res., 92 , 49715029.

    • Search Google Scholar
    • Export Citation
  • Drobinski, P., and R. C. Foster, 2003: On the origin of near-surface streaks in the neutrally-stratified planetary boundary layer. Bound.-Layer Meteor., 108 , 247256.

    • Search Google Scholar
    • Export Citation
  • Feser, F., R. Weisse, and H. von Storch, 2001: Multi-decadal atmospheric modeling for Europe yields multi-purpose data. Eos, Trans. Amer. Geophys. Union, 82 , 305310.

    • Search Google Scholar
    • Export Citation
  • Fetterer, F., D. Gineris, and C. Wackerman, 1998: Validating a scatterometer wind algorithm for ERS-1 SAR. IEEE Trans. Geosci. Remote Sens., 36 , 479492.

    • Search Google Scholar
    • Export Citation
  • Gerling, T., 1986: Structure of the surface wind field from Seasat SAR. J. Geophys. Res., 91 , 23082320.

  • Horstmann, J., W. Koch, S. Lehner, and R. Tonboe, 2000: Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization. IEEE Trans. Geosci. Remote Sens., 38 , 21222131.

    • Search Google Scholar
    • Export Citation
  • Horstmann, J., W. Koch, S. Lehner, and R. Tonboe, 2002: Ocean winds from RADARSAT-1 ScanSAR. Can. J. Remote Sens., 28 , 524533.

  • Horstmann, J., H. Schiller, J. Schulz-Stellenfleth, and S. Lehner, 2003: Global wind retrieval from SAR. IEEE Trans. Geosci. Remote Sens., 41 , 22772286.

    • Search Google Scholar
    • Export Citation
  • Jacob, D., R. Podzun, and M. Claussen, 1995: REMO—A model for climate research and weather prediction. Proc. Int. Workshop on Limited-Area and Variable Resolution Models, Beijing, China, WMO, 273–278.

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Koch, W., 2004: Directional analysis of SAR images aiming at wind direction. IEEE Trans. Geosci. Remote Sens., 42 , 702710.

  • Laur, H., P. Bally, P. Meadows, S. J. B. Schättler, and E. Lopinto, 1998: Derivation of the backscattering coefficient σ0 in ESA ERS-1/2.SAR.PRI data products. Tech. Note ES-TN-RS-PM-HL09, issue 2, Revision 5b, ESA, Frascati, Italy, 47 pp.

  • Lehner, S., J. Horstmann, W. Koch, and W. Rosenthal, 1998: Mesoscale wind measurements using recalibrated ERS SAR images. J. Geophys. Res., 103 , 78477856.

    • Search Google Scholar
    • Export Citation
  • Lehner, S., J. Schulz-Stellenfleth, B. Schättler, H. Breit, and J. Horstmann, 2000: Wind and wave measurements using complex ERS-2 SAR wave mode data. IEEE Trans. Geosci. Remote Sens., 38 , 22462257.

    • Search Google Scholar
    • Export Citation
  • Levy, G., and R. A. Brown, 1998: Detecting planetary boundary layer rolls from SAR. Remote Sensing of the Pacific Ocean from Satellites, R. A. Brown, Ed., Earth Ocean and Space, 128–134.

    • Search Google Scholar
    • Export Citation
  • Monaldo, F., D. Thompson, R. Beal, W. Pichel, and P. Clemente-Colon, 2001: Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements. IEEE Trans. Geosci. Remote Sens., 39 , 25872600.

    • Search Google Scholar
    • Export Citation
  • Quilfen, Y., B. Chapron, T. Elfouhaily, K. Katsaros, and J. Tournadre, 1998: Observation of tropical cyclones by high-resolution scatterometry. J. Geophys. Res., 103 , 77677786.

    • Search Google Scholar
    • Export Citation
  • Stoffelen, A., and D. Anderson, 1997: Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4. J. Geophys. Res., 102 , 57675780.

    • Search Google Scholar
    • Export Citation
  • Vachon, P. W., and F. Dobson, 1996: Validation of wind vector retrieval from ERS-1 SAR images over the ocean. Global Atmos. Ocean Syst., 5 , 177187.

    • Search Google Scholar
    • Export Citation
  • von Storch, H., H. Langenberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128 , 36643673.

    • Search Google Scholar
    • Export Citation
  • Weisse, R., F. Feser, and H. Gunther, 2002: A 40-year high-resolution wind and wave hindcast in the southern North Sea. Proc. Seventh Int. Workshop on Wave Hindcasting and Forecasting, Banff, AB, Canada, Department for the Environment, Canada Meteorological Service, 97–104.

  • Weisse, R., H. von Storch, and F. Feser, 2005: Northeast Atlantic and North Sea storminess as simulated by a regional climate model during 1958–2001 and comparison with observations. J. Climate, 18 , 465479.

    • Search Google Scholar
    • Export Citation
  • Young, G. S., D. A. R. Kristovich, M. R. Hjelmfelt, and R. C. Foster, 2002: Rolls, streets, waves, and more: A review of quasi-two-dimensional structures in the atmospheric boundary layer. Bull. Amer. Meteor. Soc., 83 , 9971001.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 111 64 0
PDF Downloads 75 46 0

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

View More View Less
  • 1 GKSS Research Center Geesthacht, Institute for Coastal Research, Geesthacht, Germany
Restricted access

Abstract

Wind vectors over the ocean were extracted from a large number of synthetic aperture radar (SAR) images from the European Remote Sensing Satellites (ERS-1 and ERS-2). The wind directions are inferred from the orientation of wind streaks that are imaged by the SAR, while the wind speeds are retrieved by inversion of the C-band model CMOD4. The derived wind directions and speeds were compared to wind vectors from the numerical Regional Model (REMO) that are available hourly on a 55-km grid. The large number of comparisons and independent weather situations allowed for an analysis of subsets that are classified by SAR-derived wind speed. A strong decrease of the standard deviation of directional differences with increasing wind speed was found. Biases of directional differences depend on SAR wind speed as well. Furthermore, the influence of the temporal difference between SAR overflight and model and an automatic image filtering on the directional error is demonstrated. Overall, reasonable fields of wind vectors were extracted from SAR imagery in 70 of 80 cases. These fields provide valuable information for validation of numerical models of the atmosphere and case studies of coastal wind fields.

Corresponding author address: Wolfgang Koch, GKSS Research Center Geesthacht, Institute for Coastal Research, Max-Planck-Strasse 1, D-21502 Geesthacht, Germany. Email: wolfgang.koch@gkss.de

Abstract

Wind vectors over the ocean were extracted from a large number of synthetic aperture radar (SAR) images from the European Remote Sensing Satellites (ERS-1 and ERS-2). The wind directions are inferred from the orientation of wind streaks that are imaged by the SAR, while the wind speeds are retrieved by inversion of the C-band model CMOD4. The derived wind directions and speeds were compared to wind vectors from the numerical Regional Model (REMO) that are available hourly on a 55-km grid. The large number of comparisons and independent weather situations allowed for an analysis of subsets that are classified by SAR-derived wind speed. A strong decrease of the standard deviation of directional differences with increasing wind speed was found. Biases of directional differences depend on SAR wind speed as well. Furthermore, the influence of the temporal difference between SAR overflight and model and an automatic image filtering on the directional error is demonstrated. Overall, reasonable fields of wind vectors were extracted from SAR imagery in 70 of 80 cases. These fields provide valuable information for validation of numerical models of the atmosphere and case studies of coastal wind fields.

Corresponding author address: Wolfgang Koch, GKSS Research Center Geesthacht, Institute for Coastal Research, Max-Planck-Strasse 1, D-21502 Geesthacht, Germany. Email: wolfgang.koch@gkss.de

Save