On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting

Following the successful assimilation of European remote sensing satellite (ERS) scatterometer winds for weather analysis and forecasting, we further develop this methodology for the assimilation of the NASA scatterometer (NSCAT) and QuikSCAT Ku-band scatterometer data. Besides retrieval problems in cases of a confused sea state, the quality control (QC) developed here identifies cases with rain on a mind vector cell (WVC) by WVC basis. The elimination of such geophysical conditions is a prerequisite to arrive at a successful assimilation of Ku band scatterometer data. Moreover, me propose to assimilate ambiguous winds rather than radar backscatter measurements, as is being done at most meteorological centers assimilating ERS scatterometer data. After our quality assessment, NSCAT winds still have more difficult ambiguity removal properties than ERS winds, A further testing of the data assimilation method proposed is being carried out at the European Center for Medium-range Weather Forecasts in NSCAT impact experiments. A normalized wind inversion residual is used for QC, In order to determine a threshold for the rejection of poor quality wind solutions, the inversion residual and the wind vector departure from the ECMWF model, are correlated. We end up rejecting around 7.4% of wind vector solutions and 4.2% of the NSCAT WVC's, In order to perform a qualitative assessment of this rejection, comparisons to collocated SSM/I rain and ECMWF minds are used. Confused sea state and presence of rain seem to be the most likely causes for the rejection of WVC's, As expected, the remaining number of ambiguities is larger than in the case of the ERS scatterometer but dependent on wind direction. The proposed cost function for the assimilation of NSCAT winds in weather analysis contains up to four ambiguous minds, the derived QC information, and the probability of each wind solution, We believe that the results of our study can be successfully extended for the interpretation and retrieval of good quality winds from QuikSCAT and their assimilation in weather analysis.