Liang Dong, Zhang Lu, Cheng Qing, Zhu Qi, Liu Yiming, Bashir Barjeece, Kong Weidong, Kong Lingyi
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
Sci Rep. 2025 Jul 2;15(1):23139. doi: 10.1038/s41598-025-05129-3.
Antarctic ice shelves play a pivotal role in global sea-level regulation, yet their sensitivity to temperature variations, freeze-thaw cycles, and biotic factors such as snow algae remains under-explored. This study addresses the critical question: how do snow algae influence the melting dynamics of Antarctic ice shelves under changing climatic conditions? To answer this question, the study applies time-lag adjusted Pearson correlation and Granger causality tests to high-resolution Sentinel-1 and Sentinel-2 time-series data in Google Earth Engine. The findings demonstrate that algae biomass influences subsequent melting, underscoring snow algae's pivotal role in accelerating the melting of Antarctic ice shelves. This research emphasizes the need to integrate biotic factors in models of polar ice dynamics and climate change projections. The study also provides a workflow for snow algae and snowmelt analysis at high resolution over large areas, contributing to a deeper understanding of snowmelt and global sea-level rise.
南极冰架在全球海平面调节中起着关键作用,然而它们对温度变化、冻融循环以及诸如雪藻等生物因素的敏感性仍未得到充分探索。本研究解决了一个关键问题:在不断变化的气候条件下,雪藻如何影响南极冰架的融化动态?为了回答这个问题,该研究在谷歌地球引擎中对高分辨率哨兵 -1 和哨兵 -2 时间序列数据应用了时间滞后调整的皮尔逊相关性和格兰杰因果关系检验。研究结果表明,藻类生物量会影响随后的融化,突出了雪藻在加速南极冰架融化方面的关键作用。这项研究强调了在极地冰动力学模型和气候变化预测中纳入生物因素的必要性。该研究还提供了一个在大面积上进行高分辨率雪藻和融雪分析的工作流程,有助于更深入地理解融雪和全球海平面上升。