The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie poin...The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie point(STP).However,due to pronounced spatial heterogeneity in seawater and sea ice properties across the Arctic,the use of an STP often leads to regionally biased.To address this limitation,this study proposes a multi-tie point(MTP)sea ice thickness retrieval method based on SMOS brightness temperature and sea ice concentration time series.Multiple seawater and sea ice tie-point values are identified through point-by-point time series analysis,quality control,and statistical hypothesis testing,allowing spatial variability in radiometric properties to be explicitly considered.The MTP-based retrieval is applied to Arctic freeze-up conditions.Validation against independent SMOS thin sea ice thickness products shows that the MTP approach yields significantly reduced bias and root mean square error compared with the conventional STP method,with statistically significant improvements confirmed by paired t-tests.While retrieval accuracy stabilizes beyond a certain number of tie points,the preprocessing cost associated with tie-point selection increases substantially.Considering both accuracy and efficiency,the MTP framework provides a practical and robust approach for large-scale Arctic thin sea ice thickness retrieval and enables improved characterization of regional freezing processes and maximum ice thickness.展开更多
基金supported by the National Key Research and Development Program of China(Grant nos.2023YFC2809103,2024YFC2813505)the Fundamental Research Funds for the Central Universities(Grant nos.2042025kf0083,2042025gf0014)the Antarctic Zhongshan Ice and Space Environment National Observation and Research Station(Grant no.ZSNORS-20252702).
文摘The correlation between the Soil Moisture and Ocean Salinity(SMOS)L-band brightness temperature and thin sea ice thickness has been widely exploited using semi-empirical retrieval approaches based on a single-tie point(STP).However,due to pronounced spatial heterogeneity in seawater and sea ice properties across the Arctic,the use of an STP often leads to regionally biased.To address this limitation,this study proposes a multi-tie point(MTP)sea ice thickness retrieval method based on SMOS brightness temperature and sea ice concentration time series.Multiple seawater and sea ice tie-point values are identified through point-by-point time series analysis,quality control,and statistical hypothesis testing,allowing spatial variability in radiometric properties to be explicitly considered.The MTP-based retrieval is applied to Arctic freeze-up conditions.Validation against independent SMOS thin sea ice thickness products shows that the MTP approach yields significantly reduced bias and root mean square error compared with the conventional STP method,with statistically significant improvements confirmed by paired t-tests.While retrieval accuracy stabilizes beyond a certain number of tie points,the preprocessing cost associated with tie-point selection increases substantially.Considering both accuracy and efficiency,the MTP framework provides a practical and robust approach for large-scale Arctic thin sea ice thickness retrieval and enables improved characterization of regional freezing processes and maximum ice thickness.
