Royal Dutch Meteorological Institute; Ministery Of Infrastructure And The Environment

The C-band geophysical model function (GMF) CMOD7 has been developed based on intercalibrated ERS and ASCAT C-band scatterometers. It is therefore valid for their combined incidence angle range (Stoffelen et al., 2017).

The ERS and ASCAT backscatter measurements have a stability and intercalibration well within 0.1 dB (Belmonte et al., 2017), which corresponds to a wind component bias at nominal speeds of better than 0.1 m/s.

Input to the GMF are so-called stress-equivalent 10m winds, u10s, which may be obtained from ground references, such as moored buoys or Numerical Weather Prediction Models (de Kloe et al., 2017). Known atmospheric effects, not sensed by a microwave instrument, but affecting real 10m winds are corrected in u10s, namely atmospheric stability and mass density. Thus u10s is thought to have a direct relationship with ocean roughness and kinematic (wind) stress.

CMOD7 has been developed as a successor of CMOD5.N. CMOD5.N is superseded by CMOD7 now, but it is still available here.

The clear mismatch between CMOD5.N and the backscatter measurements at low wind speeds was fixed. An independently developed ASCAT C-band GMF, C2013, which performs particularly well for low winds was adopted to improve low winds for the ASCAT incidence angle range (Ricciardulli and Wentz, 2013).

Wind retrievals with CMOD5.N show wind speed probability distribution functions (PDFs) that undesirably depend on wind vector cell (WVC) position across the swath. To overcome this effect, a higher order calibration was applied, which matches the wind speed pdfs for all WVCs of ASCAT and ERS.

The resulting CMOD7 GMF indeed shows overall improved performance on all relevant quality parameters as compared to CMOD5.N. It is found that the standard deviations of error for wind speed and wind direction of ASCAT are improved. The same holds for the maximum-likelihood estimates, showing an improved consistency with the local triplet of backscatter measurements.
Binary tables and Pyhon script (6.3 MB, use the "gunzip" and "tar -xf" commands to unpack on Unix/Linux). The package contains binary CMOD7 tables for little endian and big endian platforms. A Python script is included to read in the table and plot the GMF. More technical information can be found in the comments and descriptions in the script.
Stoffelen, A., J. Verspeek, J. Vogelzang and A. Verhoef,
The CMOD7 Geophysical Model Function for ASCAT and ERS Wind Retrievals
IEEE Journal of Selected Topics in Applied Earth O, 2017, 10, 5, 2123-2134, doi:10.1109/JSTARS.2017.2681806.

Belmonte Rivas, M., A. Stoffelen, J. Verspeek, A. Verhoef, X. Neyt and C. Anderson,
Cone Metrics: A New Tool for the Intercomparison of Scatterometer Records
IEEE Journal of Selected Topics in Applied Earth O, 2017, 10, 5, 2195-2204, doi:10.1109/JSTARS.2017.2647842.

de Kloe, J., A. Stoffelen and A. Verhoef,
Improved Use of Scatterometer Measurements by Using Stress-Equivalent Reference Winds
IEEE Journal of Selected Topics in Applied Earth O, 2017, 10, 5, 2340-2347, doi:10.1109/JSTARS.2017.2685242.

Ricciardulli, L. and F. Wentz,
Towards a climate data record of ocean vector winds: The new RSS ASCAT
in: Proc. Int. Ocean Vector Wind Sci. Team Meet., Kona, HI, USA, May 2013. Available here.
Further information
Please contact the KNMI scatterometer team.

Near real time Wind Products
OSI SAF Wind Climate Data Records
Discontinued Wind Products
R&D work