Towards a Correction of ASCAT Ocean Measurements for Rain Effects
Lin, Wenming1; Portabella, Marcos1; Stoffelen, Ad2; Verhoef, Anton2; Weissman, David3; Johnson, Teresa3; Wolf, Justin3
1Institut de Cičncies del Mar – CSIC, SPAIN; 2Royal Netherlands Meteorological Institute (KNMI), NETHERLANDS; 3School of Engineering and Applied Science, Hofstra University, UNITED STATES
The presence of rain corrupts the relationship between the sea surface wind and satellite radar backscatter measurements, leading to poor-quality scatterometer wind retrievals. Rain affects both the C-band backscatter measurements and sea surface wind variability due to wind downbursts. These effects have been evaluated using collocated Tropical Rainfall Measuring Mission (TRMM) data, European Centre for Medium Range Weather Forecasts (ECMWF) model wind data, Active Microwave Instrument (AMI) scatterometer data onboard the European Remote Sensing Satellites (ERS) , and Advanced Scatterometer (ASCAT) data onboard the Metop satellite series . Refs.  and  demonstrate that for C-band radar systems such as the AMI scatterometer and ASCAT, the rain-induced backscatter is dominated by rain perturbation on the sea surface (or "splashing") for low and moderate rain rate conditions. In this paper, a simplified model for the ASCAT backscatter under rainy conditions is presented as a summation of the wind-induced backscatter and the rain-splashing-induced backscatter. The backscatter bias (or rain-splashing-induced backscatter) varies with incidence angle, rain rate and wind speed. It is positive at low wind speeds and negative at high wind speeds. As expected, the rain-induced backscatter impact is the highest at low winds, as the rain splashing effect roughens the relatively smooth wind-induced sea surface. The performance of the simple model is then evaluated by running the ASCAT Wind Data Processor (AWDP) for one month of ASCAT, TRMM/TMI and ECMWF collocations with and without the rain correction model. The results show that the proposed rain correction method indeed reduces the Vector Root-Mean-Square (VRMS) difference between ASCAT and ECMWF winds, as well as increases the consistency between the corrected backscatter triplets and the forward model or Geophysical Model Function (GMF). However, for heavy rain conditions, large inconsistencies between the corrected triplets and the GMF are found, indicating a model overestimation of the rain-induced bias. In other words, the rain attenuation effect is not negligible and has to be accounted for in heavy rain conditions. Future model improvements should also account for the backscatter impact of the variability increase with increasing rain rate.
Current efforts are focused on further improving and validating the proposed model using ASCAT data collocated with high resolution rain measurements from the US meteorological radar network (NEXRAD) and the TRMM Precipitation Radar (PR) instrument. A preliminary assessment of the model in terms of ASCAT-derived wind quality will be shown at the conference.
 C. Nie and D.G. Long, "A C-Band Wind/Rain Backscatter Model", IEEE Trans. Geosci. Remote Sens., 2007, 45(3), 621-631.
 M. Portabella, , A. Stoffelen, W. Lin, A. Turiel, A. Verhoef, J. Verspeek and J. Ballabrera-Poy, "Rain effects on ASCAT-retrieved winds: toward an improved quality control", IEEE Trans. Geosci. And Remote Sens., 2012, 50(7), 2495-2506.