LIU Tingting, YUAN Menglin, LI Yachao, YANG Fan. Spatiotemporal Variations and Drivers of Austral Summer Surface Temperature over the Antarctic Getz Ice Shelf Based on FY-3 Satellite DataJ. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20260100
Citation: LIU Tingting, YUAN Menglin, LI Yachao, YANG Fan. Spatiotemporal Variations and Drivers of Austral Summer Surface Temperature over the Antarctic Getz Ice Shelf Based on FY-3 Satellite DataJ. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20260100

Spatiotemporal Variations and Drivers of Austral Summer Surface Temperature over the Antarctic Getz Ice Shelf Based on FY-3 Satellite Data

  • Objectives: The Getz Ice Shelf, Antarctica’s eighth largest, is a region of high surface melt potential, projected to be a melt hotspot throughout this century. Meltwater can lead to ice shelf deformation, hydrofracturing and disintegration, processes that are directly linked to the ice surface temperature (IST). IST is a critical indicator of its surface energy budget and mass balance. Chinese FY-3 MERSI series data possess the advantages of a wide swath and high spatial resolution, but their application in Antarctic ice shelf surface temperature monitoring is currently insufficient. Therefore, the objective is to retrieve high-resolution IST over the Getz Ice Shelf using FY-3 MERSI data and to investigate its spatiotemporal variations and driving factors. Methods: We applied the MERSI-ISC algorithm to FY-3A MERSI-I (2008–2014) and FY-3D MERSI-II (2019–2024) data to retrieve austral summer (October to the following March) IST over the Getz Ice Shelf at a 250 m spatial resolution. The algorithm adopted a directional emissivity to correct the retrieval errors caused by the wide range of sensor viewing angles (0–70°) in MERSI. Real-time atmospheric water vapor content is retrieved directly from MERSI data. An atmospheric correction scheme is developed for the thermal infrared band of MERSI under polar atmospheric conditions. The IST is subsequently calculated directly using the Planck’s equation. Time-series IST variation data were obtained through fitting and statistical analysis by introducing the annual temperature cycle model. Following validation with automatic weather stations data and cross-comparison with MODIS IST, we analyzed the IST’s spatiotemporal variations, characterized significant warm events, and investigated the underlying driving factors. Results: (1) Validation based on data from automatic weather stations shows an RMSE of 2.01 K. Cross-validation against MODIS IST indicates a discrepancy of merely 0.19 K between MERSI-I and MERSI-II retrieval results, suggesting good inter-sensor consistency in IST retrieval. (2) Time series analysis reveals that the mean summer IST was 257.68 K during 2008–2014 and 258.04 K during 2019–2024, with neither period exhibiting a statistically significant trend. However, an anomalous warming event exceeding 5 K was observed in March 2013, abruptly reversing the typical seasonal cooling and resulting in a higher monthly average IST for March than for February. Meteorological analysis linked this anomaly to an anticyclone in the Amundsen Sea, which drove strong poleward transport of moisture and heat. The consequent increase in mid- and low-level cloud cover enhanced longwave radiation, leading to rapid surface warming. (3) Spatially, the relatively warmer signals were observed in the central sector near the grounding line, with the warm area accounting for 8.51% of the total ice-shelf area. This warming was primarily driven by sensible heat flux associated with katabatic winds. Pronounced warming corresponded to higher wind speeds, as enhanced wind speeds significantly strengthened the sensible heat flux. The Pearson correlation coefficient between effective wind speed and warming intensity was 0.51 (p < 0.01). Furthermore, the heavily crevassed western part of the ice shelf exhibited lower albedo. This reduction amplified net shortwave radiation absorption, leading to higher IST, and an approximately 20% increase in annual melt days. A strong negative correlation between albedo and IST (R = -0.89, p < 0.01) further corroborates the aforementioned mechanism. This process highlights how crevasses amplify surface melting and potentially increase the risk of ice shelf disintegration. Conclusions: These findings demonstrate the potential of FY-3 MERSI data, with their wide swath and high spatial resolution, for refined monitoring of thermal variability of Antarctic ice shelves, and provide new insights into the spatial patterns and driving factors of IST and warm events on the Getz Ice Shelf.
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