海洋科学2025，Vol.49Issue(2)：25-33,9.DOI:10.11759/hykx20230902001
北极海冰密集度数据融合研究
A study of data fusion on Arctic sea ice concentration
摘要
Abstract
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.关键词
海冰密集度/小波变换/卡尔曼滤波/概率密度函数匹配法Key words
sea ice concentration/wavelet transform/Kalman filtering/probability density function matching method分类
海洋科学引用本文复制引用
王安,何宜军,殷千惠..北极海冰密集度数据融合研究[J].海洋科学,2025,49(2):25-33,9.基金项目
国家重点研究与发展计划项目(2021YFC2803301) （2021YFC2803301）
江苏省研究生研究与实践创新计划项目(Nos.KYCX23_1347)National Key Research and Development Program of China,No.2021YFC2803301 （Nos.KYCX23_1347）
Postgraduate Research&Practice Innovation Pro-gram of Jiangsu Province,No.KYCX23_1347 （）
