The Improvement Of HY2-SCAT Wind Retrieval Algorithm Based On MSS And2DVAR Method

Sea surface wind field, especially the high spatial and temporal resolution windproduct, is one of the important parameters in meteorological and oceanographicapplications. The traditional methods to obtain sea surface wind are from buoys, ships,platforms, etc. However, buoys and ships cover very limited regions of the globalocean at irregular intervals of time and space, and the lack of observations is a moreacute problem. Since the1970s, with the development of satellite remote sensingtechnology, satellite-derived winds, with high temporal and spatial resolution, widelycoverage become available. Among onboard-instruments, the scatterometer is the keysensor which can provide wind speed and wind direction.The HY2-SCAT instrument was carried on-board the HY-2A polar satellite, andits products have been operationally released by the National Satellite OceanApplication Service (NSOAS) since January2012. The operational system providesthe retrieval winds using Maximum-likelihood estimation (MLE) method and medianfilter ambiguity removal. However, the quality of the winds retrieved from theHY2-SCAT scatterometer depends on the sub-satellite cross-track location. Inparticular, the poor azimuth separation or diversity between views in the nadir regionresults in poor quality wind product.An improved scheme, i.e., a multiple solution scheme (MSS) and atwo-dimensional variational analysis method (2DVAR) was proposed as alternative tothe above standard procedure by Royal Netherlands Meteorological Institute (KNMI).Retrieved wind data from the MSS and2DVAR method were used to HY2-SCATobservations, the probability of every ambiguous solution of being the “true” wind isempirically derived through the probability model function. Both the ambiguoussolution and its probability used in the ambiguity removal procedure to obtain aunique wind vector. A comparison between the standard wind retrieval and the new improved schemeis then performed, using buoy observations for validation. The R.M.S. error of windspeed and direction are1.2m/s and15.8°for the MSS wind data, and1.3m/s and23.9°for the MLE wind data, respectively, which means MSS wind data is more inagreement with the buoy data than the MLE wind data. Moreover, a comparison ofwind fields at the typhoon (SOULIK) case is performed. And it shows that theimproved winds are more spatially consistent, meteorologically balanced, and realistic.Moreover, we compared the distribution of wind fields at the typhoon (Soulik) case,and found the MSS winds are more spatially consistent and meteorologically balancedthan the MLE winds.