Arctic Sea Ice Concentration Inversion Based On Improved ASI And Spatio-Temporal Variation Analysis

Global warming has become an big killer that threatening the melting of Arctic sea ice,in addition has evolved into a great environment problem.Sea ice concentration,as the main parameter of passive microwave remote sensing of sea ice,is one of the important parameters to describe the sea ice’s features.Sea ice concentration is widely used in the spatial distribution and range counting of sea ice,and has significant implications for navigation,climate research,weather,and sea ice prediction.The traditional ASI sea ice concentration inversion algorithm using high-frequency data is susceptible to external environmental influences,resulting in lower inversion accuracy.Based on this,this paper proposes an improved ASI sea ice concentration inversion algorithm based on different seasons and an improved ASI sea ice concentration inversion algorithm based on high and low frequency combination,and conducts spatio-temporal variation analysis of Arctic sea ice based on regional division.The main work and innovations are as follows:(1)Improvement of ASI sea ice concentration inversion algorithm based on different seasons: the problem of seasonal errors in traditional ASI algorithm,a seasonally improved ASI sea ice concentration inversion method is proposed.Firstly,this method divides the entire year data into four seasons and calculates the tie points’ value of water and ice for each season;Then,the ASI sea ice concentration inversion formulas for four seasons were fitted using cubic polynomials;Finally,the results of our method,ASI results,and Landsat visible light data were compared,and the results showed that our method improved the inversion accuracy of sea ice concentration.(2)Improvement of the ASI sea ice concentration inversion algorithm based on high and low frequency combination: In order to fix the issue,which low accuracy of traditional ASI sea ice concentration algorithms due to the susceptibility of the 89 GHz data of the ASI algorithm to external environmental influences,this paper proposes an improved ASI sea ice concentration inversion algorithm based on the high and low frequency combination.Firstly,based on the stability of low-frequency data,select pixels that are affected by the external environment;Then,fit a polynomial to correct the filtered data;Finally,the inversion results of our method,ASI results,and Landsat visible light data were compared,and the results showed that our method improved the inversion accuracy of sea ice concentration.(3)Analysis of spatio-temporal variation in Arctic sea ice based on regional division:In order to further explore the Arctic sea ice,this paper proposes a new method for studying Arctic sea ice changes.Firstly,based on the Arctic sea ice data from 1988 to 2020,we divide the Arctic into one-year ice regions,multi-year ice regions,coexisting regions of one-year ice and multi-year ice,coexisting regions of one-year ice and water,and water regions;Then,the changes were analyzed for each region separately.