Retrieval Climatic Parameters Over Ocean Surface And The Application

Global climate is closely linked to human being, which is a hot topic. Traditional research on climate parameters near sea surface was based on buoy and in situ observations, which restrict the development because of small observed region and limited observation data. Now satellite is considered to be a good alternative to obtain knowledge of ocean. Satellites could attain long-time and large-scale oceanic climatic data, which help us understand global ocean and atmosphere activities clearly.The two main tasks of this paper are to retrieve climatic parameters over sea surface from satellites data and to apply the retrieval results into heat flux estimation and climatic study. A new method is proposed to derive long-scale monthly mean air temperature (Ta) and relative humidity (RH) near sea surface from satellite data with artificial neural networks (ANN). Compared with the in situ observations, the root mean square (rms) of Ta and RH are 0.87℃ and 3.73%, respectively. The TOVS data are used to obtain the outline of Ta and dew-point temperature (Td) from the 1000mb to 10mb with the synchronous physical method. The method based on Bowen ratio and ANN model are adopted to get instantaneous Ta and Td parameters near sea surface from the outline. The rms of Ta and Td are 1.85K and 2.59K, respectively. The results are reasonable.One month of AMSR-E data is analyzed used as a case to retrieve real time climate parameters of SST, Ta, RH and wind speed. The twelve channels of AMSR-E are divided into four cases, under which the four parameters are test. The best case is chose to retrieval the four parameters. Compared the results with TAO data, the rms of SST, Ta, RH and wind speed are 0.55℃, 0.74℃, 3.24% and 1.11m/s, respectively. Up to now, the accuracies of them are best.All the above results are applied to study interaction on sea-air surface. Both...