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

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: the January Beaufort High (P1-H500), the November sea-level pressure (P2-SLP) over eastern Siberia, and the November snow cover over the eastern European Plain (P3-Snowc). P1-H500 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. P2-SLP exhibits a close association with the east part of the midlatitude North Pacific SST in November. The colder midlatitude 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 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%, respectively.

摘要

基于大尺度环流异常对海冰消融的影响过程, 本文采用年际增量预测方法研制了白令海季节性海冰早期消融开始日期(EMO)的统计预测模型. 预测模型选取了3个具有明确物理意义的预测因子: 1月波弗特高压, 前期11月东西伯利亚地区海平面气压, 以及11月东欧平原积雪覆盖率. 1月波弗特高压可以通过海气相互作用影响白令海地区海温异常, 该海温异常能够从1月持续到3月, 进而影响白令海EMO. 11月东西伯利亚地区海平面气压与11月至次年2月北太平洋中纬度东部海温密切相关. 伴随着北太平洋中纬度东部冷海温异常的出现, 白令海地区会出现暖海温异常, 进而导致白令海海冰范围减少, EMO较晚. 1月北极偶极子异常是11月东欧平原积雪覆盖率影响次年白令海EMO的桥梁之一. 1981−2022年的交叉检验结果表明: 统计模型对白令海EMO具有较好的预测能力, 预测与观测的EMO之间时间相关系数达到了0.45, 超过了99%的置信水平. 统计模型对白令海EMO正常年份和异常年份的预测准确率分别为60%和41%.