ORIGINAL RESEARCH article
Sec. Remote Sensing Time Series Analysis
Spatiotemporal change analysis for snowmelt over the Antarctic shelves using Scatterometers (2000-2018)
- 1Polar Remote Sensing Section, National Centre for Polar and Ocean Research (NCPOR), India
- 22RMSI Private Limited, Noida, Uttar Pradesh, India, India
- 3Svalbard Integrated Arctic Earth Observing System (SIOS), Norway
Using scatterometer-based backscatter data, the spatial and temporal melt dynamics of Antarctic ice shelves were tracked from 2000 to 2018. We constructed melt onset and duration maps for the whole Antarctic shelves using a pixel-based, adaptive threshold approach based on backscatter during the transition period between winter and summer. We explored the climatic influences on the spatial extent and timing of snowmelt using meteorological data from automatic weather stations and investigate the climatic controls on the spatial extent and timing of snowmelt. Melt onset began in the latter week of November, peaks in the end of December/January, and then vanished in the first/second week of February on most shelves. On the Antarctic Peninsula, the average melt was 70 days, with the melt onset on 20 November for almost 50% of the region. In comparison to the Antarctic Peninsula, the Eastern Antarctic showed less melt duration, lasting 40−50 days. For the Larsen, Shackleton, Amery, and Fimbul ice shelf, there was a substantial link between melt area and air temperature. A significant correlation is found between increased temperature advection and high melt area for the Amery, Shackleton, and Larsen-C ice shelf. The teleconnections were found between melt area and the combined anomalies of Southern Annular Mode and Southern Oscillation Index. The most persistent and intensive melt occurred on the Antarctic Peninsula, West Ice Shelf, Shackleton Ice Shelf, and Amery Ice Shelf, which should be actively monitored for future stability.
Keywords: Antarctic shelves, Surface melt, Active remote sensing, scatterometer, air temperature
Received: 26 May 2022;
Accepted: 01 Aug 2022.
Copyright: © 2022 Luis, Alam and Jawak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Alvarinho J. Luis, National Centre for Polar and Ocean Research (NCPOR), Polar Remote Sensing Section, Vasco da Gama, India