Seasonal cycles of snow algal blooms intensify surface melting on Antarctic ice shelves

• Published in: Scientific reports Vol. 15; no. 1; pp. 23139 - 19
• Main Authors: Liang, Dong, Zhang, Lu, Cheng, Qing, Zhu, Qi, Liu, Yiming, Bashir, Barjeece, Kong, Weidong, Kong, Lingyi
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.07.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1046; 704/106/125; 704/172/4081; Algae; Algal blooms; Antarctic ice shelf; Antarctic Regions; Approximation; Big earth data; Biomass; Biotic factors; Causality; Climate Change; Climatic conditions; Correlation analysis; Data mining; Eutrophication; Freezing; Glaciers; Heat; Humanities and Social Sciences; Ice; Ice Cover; Ice shelves; MSI; multidisciplinary; Ocean circulation; Remote sensing; SAR; Satellites; Science; Science (multidisciplinary); Sea level; Seasons; Snow; Snow algae; Snowmelt; Temperature; Trends; Antarctic Regions; Antarctica; Weddell Sea; Antarctic ice shelf; MSI; Snowmelt; Big earth data; SAR; Snow algae
• ISSN: 2045-2322; 2045-2322
• 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.