Kumar, A; Srivastava, A; Yadav, J; Mohan, R (2020). Spatio-temporal changes and prediction of Amery ice shelf, east Antarctica: A remote sensing and statistics-based approach. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 267, 110648.

The Amery ice shelf (AIS) dynamics and mass balance play key role to decipher changes in the global climate scenario. The spatio-temporal changes in morphology of the AIS were studied into a number of transects at 5 km uniform intervals using multi-dated Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite data (2001-2016) of the austral summer months (January-March). Past ice shelf extents have been reconstructed and future ice shelf extents were estimated for 5- and 10-year time periods. The rate changes of AIS extent were estimated using the linear regression analysis and cross-validated with the coefficient of determination (R-2) and root-mean-square error (RMSE) methods. Further, the changes in shelf extent were linked to prevailing factors viz. mass changes, Southern Annular Mode (SAM) index, and ocean-air temperatures. The study reveals that the AIS extent has been prograded at the rate of 994 m/year with an average 14.5 km increase in the areal extents during 2001-2016, as compared to the year 2001, whereas, the maximum advancement in ice shelf extent was recorded during the 2006-2016 period. Based on the linear regression analysis, the predicted ice shelf extents (i. e., the summer 2021 and 2016) show progradation in all the transects. About 52% of transects exhibit +/- 200 m RMSE values, indicating better agreement between the estimated and satellite-based ice-shelf position. The recent changes (2017-2019) observed in the ice shelf are cross validated with predicted ice self-extent rates. The eastern part of Mackenzie Bay to Ingrid Christensen coast recorded advancement in the ice shelf extents and mass which is the feedback of positive SAM along with a decrease in the temperatures (air temperature and sea surface temperature). The present study demonstrates that the combined use of satellite imagery and statistical techniques can be useful in quantifying and predicting ice shelf morphological variability.