AUTHOR=Zhao Hui-Jun , Xiao Dong , Bian Lin-Gen , Wu Wei , Yang Hai-Wei , Chen Qi , Liang Tian , Sun Lan-Dong TITLE=Seasonal prediction and possible causes of sudden losses of sea-ice in the Weddell Sea in recent years based on potential oceanic and atmospheric factors JOURNAL=Frontiers in Environmental Science VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2023.1135165 DOI=10.3389/fenvs.2023.1135165 ISSN=2296-665X ABSTRACT=

The seasonal prediction of sea-ice concentration (SIC), especially sudden loss events, is always challenging. Weddell Sea SIC experienced two unprecedented decline events, falling from 2.21% in the austral winter of 2015 to 0.02% in the austral summer of 2016 and then falling to −2.32% in the austral spring of 2017. This study proposes several statistical prediction models for Weddell Sea SIC and performs them for a period that includes the sudden decline events. We identified six potential oceanic and atmospheric factors at different leading times that relate to the variability of the Weddell Sea SIC, including the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Niño12 sea surface temperature (SST), Southeastern Indian Ocean (SEIO) SST, Antarctic sea level pressure (SLP), and Weddell Sea surface air temperature (SAT). Multiple linear regression models were employed to establish equations to simulate the variation of Weddell Sea SIC under three groups of climate factors for 1979–2012. These models could effectively reproduce the low-frequency variation of SIC in the Weddell Sea during the simulation period and the high-frequency values through two kinds of error-correction methods developed in this study. After applying these error correction methods, the correlation coefficients (absolute errors) of these models were enhanced (decreased) during the simulation period. In the prediction period of 2013–2018, the corrected models generally predicted well the sudden losses of Weddell Sea SIC. The possible primary factors influencing these sudden losses were the PDO, Niño12 SST, Southern Annular Mode (SAM), and SAT during 2015–2016 and the AMO, PDO, Niño12 SST, SAM, and SAT during 2016–2017.