北极海冰密集度数据融合研究OA北大核心

Sea ice concentration data are important for global ocean monitoring and climate-change-response re-search.To develop Arctic sea ice concentration fusion data with higher resolution and smaller errors,this study uses multisource sea ice concentration data,with Operational Sea Surface Temperature and Ice Analysis(OSTIA)data as the fusion background field.The following scheme is adopted to perform the fusion study.First,quality control of the existing five sea ice data is performed;second,the systematic error in each data is revised via the probability density matching method using the Ocean and Sea Ice Satellite Application Facility(OSI SAF)data as the bench-mark;thereafter,the data are decomposed into low-frequency and high-frequency information by means of wavelet decomposition,and fusion is calculated for both these types of information.Thereafter,wavelet decomposition is used to decompose the data into low-frequency information and high-frequency information,and the low-frequency information and high-frequency information are calculated and processed via Kalman filtering.Finally,wavelet reconstruction is employed to fuse the data to generate the fusion data of day-by-day Arctic sea ice density with a resolution of 0.05°.Upon comparing with the internationally recognized Optimum Interpolation Sea Surface Tem-perature(OISST)data and OSTIA sea ice density data,the validation results demonstrate that the fusion data,OISST sea surface temperature data,and OSTIA sea ice density data are highly consistent in the spatial distribution of the Arctic,with the correlation coefficients exceeding 0.967.Compared with previous research results,deviation of the fusion data from OISST data is reduced from-1.170%to-0.108%and that from OSTIA data is reduced from 0.276%to-0.156%;in addition,the root mean square error(RMSE)between the fusion data and OISST data is reduced from 9.835%to 8.010%and that between the fusion data and OSTIA data is reduced from 7.427%to 5.140%.The bias as well as RMSE of these fusion data has been significantly improved with high quality.