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作 者:Zeliang Liao Yubing Cheng Ying Jiang Mengmeng Li Bin Cheng Stein Sandven
机构地区:[1]School of Computer Science and Engineering,Sun Yat-Sen University,Guangzhou,People’s Republic of China [2]Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing,People’s Republic of China [3]Henan Academy of Big Dat1,Zhengzhou University,Zhengzhou,People’s Republic of China [4]Meteorological Department,Finnish Meteorological Institute,Helsinki,Finland [5]Acoustic and Oceanography Department,Nansen Environmental and Remote Sensing Center,Bergen,Norway
出 处:《International Journal of Digital Earth》2023年第1期3085-3104,共20页国际数字地球学报(英文)
基 金:supported by the Key-Area Research and Development Program of Guangdong Province,China(No.2021B0101190003);the Natural Science Foundation of Guangdong Province,China(No.2022A1515010831);BC was partly supported by the European Union’s Horizon 2020 research and innovation program(727890-INTAROS)in the early phase of SIMBA data analyzes and partly by Polar Regions in the Earth System project(PolarRES,grant 101003590)during the finalization stage of this work.
摘 要:Digital information on sea ice extent,thickness,volume,and distribution is crucial for understanding Earth's climate system.The Snow and Ice Mass Balance Apparatus(SIMBA)is used to determine snow and ice temperatures in Arctic,Antarctic,ice-covered seas,and boreal lakes.Snow depth and ice thickness are derived from SIMBA temperature regimes(SIMBA_ET and SIMBA_HT).In warm conditions,SiMBA_ET temperature-based ice thickness may have errors due to the isothermal vertical profile.SIMBA_HT provides a visible ice-bottom interface for manual quantification.We propose an unmanned approach,combining neural networks,wavelet analysis,and Kalman filtering(NWK),to mathematically establish NwK and retrieve ice bottoms from various SIMBA_HT datasets.In the Arctic,NWK-derived total thickness showed a bias range of-5.64 cm to 4.01 cm and a correlation coefficient of 95%-99%.For Baltic Sea ice,values ranged from 1.31 cm to 2.41 cm(88%-98%correlation),and for boreal lake ice,-0.7 cm to 2.6 cm(75%-83%correlation).During ice growth,thermal equilibrium,and melting,the bias varied from-3.93 cm to 2.37 cm,-1.92 cm to 0.04 cm,and-4.90 cm to 3.96 cm,with correlation coefficients of 76%-99%.These results demonstrate NWK's robustness in retrieving ice bottom evolution in different water environments.
关 键 词:Sea ice thickness lake ice thickness ice-bottom evolution nonlinear filtering
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