Abstract
To further understand the prediction skill for the interannual variability of the sea ice concentration (SIC) in specific regions of the Arctic, this paper evaluates the NCEP Climate Forecast System version 2 (CFSv2), in predicting the autumn SIC and its interannual variability over the Barents–East Siberian Seas (BES). It is found that CFSv2 presents much better prediction skill for the September SIC over BES than the Arctic as a whole at 1–6-month leads, and high prediction skill for the interannual variability of the SIC over BES is displayed at 1–2-month leads after removing the linear trend. CFSv2 can reasonably reproduce the relationship between the SIC over BES in September and such factors as the surface air temperature (SAT), 200-hPa geopotential height, sea surface temperature (SST), and North Atlantic Oscillation. In addition, it is found that the prescribed SIC initial condition in August as an input to CFSv2 is also essential. Therefore, the above atmospheric and oceanic factors, as well as an accurate initial condition of SIC, all contribute to a high prediction skill for SIC over BES in September. Based on a statistical prediction method, the contributions from individual predictability sources are further identified. The high prediction skill of CFSv2 for the interannual variability of SIC over BES is largely attributable to its accurate predictions of the SAT and SST, as well as a better initial condition of SIC.
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Supported by the National Key Research and Development Program of China (2022YFE0106800), National Natural Science Foundation of China (42230603), and Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (311021001).
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Xie, Y., Fan, K. & Yang, H. Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents–East Siberian Seas by CFSv2?. J Meteorol Res 38, 53–68 (2024). https://doi.org/10.1007/s13351-024-3051-z
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DOI: https://doi.org/10.1007/s13351-024-3051-z