Climate prediction of the seasonal sea ice early melt onset in the Bering Sea

Abstract

The Bering Sea is a marginal sea that stretches between the Bering Strait and the Aleutian Islands to the west of Alaska, connecting the Arctic and Pacific Oceans. Sea ice in the Bering Sea is not only a crucial component of the Arctic climate system but also has significant impacts on various sectors. Based on the impact of large-scale circulation anomalies on sea ice melting, this paper develops a statistical forecasting model for the seasonal sea ice early melt onset (EMO) in the Bering Sea using the interannual increment prediction method. The prediction model considers three physically meaningful predictors: January Beaufort High (P1-H500), November sea-level pressure (P2-SLP) over Eastern Siberia, and November snow cover over the Eastern European Plain (P3-Snowc) are considered. The January Beaufort High can influence the sea surface temperature (SST) anomaly in the Bering Sea through ocean-atmosphere interactions, and this SST anomaly can persist from January to March. Subsequently, it affects the EMO in the Bering Sea. The P2-SLP exhibits a close association with the east part of mid-latitude North Pacific SST in November. The colder mid-latitude North Pacific SST anomalies, which persist from November until January and February of the following year, will be accompanied by warmer SST anomalies in the Bering Sea, which result in a decreased sea-ice extent and a later-than-usual EMO. The Arctic dipole anomaly in January is one of the ways in which the P3-Snowc affects the EMO in the following year. The predicted EMO shows good agreement with the observed EMO in the cross-validation test for 1981−2022, with a temporal correlation coefficient of 0.45, exceeding the 99% confidence level. The prediction accuracy of the prediction model for positive and negative abnormal years of EMO is 60% and 41%.