Abstract A good assessment of the information content of scatterometer winds is particularly important in order to assimilate them in weather analysis. Besides retrieval problems in cases of a confused sea state, a particularly acute problem of Ku-band scatterometry is the sensitivity to rain. Elimination of poor quality data is therefore a prerequisite for the successful use of the National Aeronautics and Space Administration (NASA) Scatterometer (NSCAT) or QuikSCAT winds. Following the quality control for the European Remote-Sensing Satellite and NSCAT scatterometers performed at the Royal Netherlands Meteorological Institute, the authors further develop this methodology for QuikSCAT and define a quality indicator called the normalized residual (Rn). In order to characterize and validate the normalized residual, the authors use collocated Special Sensor Microwave Imager rain and European Centre for Medium-Range Weather Forecasts wind data. The results show indeed correlation between Rn and data quality...
[1]
B. Stiles,et al.
A Multi-dimensional Histogram Technique For Flagging Rain Contamination on QuikSCAT
,
2000
.
[2]
David L. T. Anderson,et al.
Scatterometer Data Interpretation: Measurement Space and Inversion
,
1997
.
[3]
H. V. Hulst.
Light Scattering by Small Particles
,
1957
.
[4]
Ad Stoffelen,et al.
On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting
,
2000,
IEEE Trans. Geosci. Remote. Sens..
[5]
David G. Long,et al.
Tradeoffs in the design of a spaceborne scanning pencil beam scatterometer: application to SeaWinds
,
1997,
IEEE Trans. Geosci. Remote. Sens..
[6]
Lars Isaksen,et al.
ERS scatterometer wind data impact on ECMWF's tropical cyclone forecasts
,
2000,
IEEE Trans. Geosci. Remote. Sens..