Spatiotemporal analysis of sea ice in the Weddell Sea of Antarctic based on GTWR

基于全球时间序列(GTWR)的南极威德尔海海冰时空分析

阅读:3

Abstract

This study investigates the spatiotemporal dynamics of Antarctic sea ice concentration (SIC) and its interactions with environmental factors from 2011 to 2023, focusing on the Weddell Sea. SIC products derived from MODIS data were assessed and compared with six widely used datasets, including AMSR2/NT2 and MWRI/NT2. Among these, MWRI/NT2 exhibited the highest consistency with MODIS-derived SIC, achieving a correlation coefficient of 0.94, the lowest bias (0.23%), and the smallest mean absolute deviation (MAD) and root mean square deviation (RMSD), making it the preferred dataset for further analysis. Seasonal trends reveal that SIC experienced the most significant decline during autumn (-10.7 ± 2.3 × 10³ km² yr⁻¹) and the smallest reduction in winter (-1.3 ± 0.5 × 10³ km² yr⁻¹). Correlation analysis identified sea surface temperature (SST), wind speed, and latent heat flux (LHF) as the primary drivers of seasonal SIC variability, with SST exhibiting strong negative correlations across all seasons (r = -0.81, p < 0.01). Spatially, SIC in the Weddell Sea displayed significant heterogeneity in its relationship with environmental factors. SST demonstrated a negative correlation with SIC, particularly in the western Weddell Sea, with lags of -3 to -5 months. LHF consistently promoted sea ice growth, with the strongest influence along the eastern Weddell Sea coast. Zonal and meridional winds exhibited both promoting and suppressing effects on SIC depending on the region and time period, reflecting complex wind-sea ice interactions. Mean sea level pressure (MSLP) showed opposing effects: suppressing SIC in the northern Weddell Sea and promoting it in the southern Weddell Sea. The use of geographically and temporally weighted regression (GTWR) allowed the quantification of the spatial and temporal heterogeneity of these factors, with LHF identified as the most influential variable (median standardized coefficient = 1.44). These findings highlight the intricate interplay between atmospheric, oceanic, and sea ice dynamics in the Weddell Sea and provide a framework for understanding the drivers of sea ice variability under changing climatic conditions.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。