{"title":"为什么 CFSv2 可以很好地预测巴伦支海-东西伯利亚海域九月份的北极海冰浓度及其年际变化?","authors":"Yifan Xie, Ke Fan, Hongqing Yang","doi":"10.1007/s13351-024-3051-z","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":48796,"journal":{"name":"Journal of Meteorological Research","volume":"101 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents–East Siberian Seas by CFSv2?\",\"authors\":\"Yifan Xie, Ke Fan, Hongqing Yang\",\"doi\":\"10.1007/s13351-024-3051-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":48796,\"journal\":{\"name\":\"Journal of Meteorological Research\",\"volume\":\"101 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Meteorological Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s13351-024-3051-z\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Meteorological Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s13351-024-3051-z","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
为了进一步了解北极特定区域海冰浓度年际变化的预测技能,本文评估了美国国家环境预报中心气候预报系统第 2 版(CFSv2)对巴伦支海-东西伯利亚海(BES)秋季海冰浓度及其年际变化的预测技能。研究发现,CFSv2 对巴伦支海-东西伯利亚海(BES)上空 9 月 SIC 的预测能力在 1-6 个月领先期要比对整个北极地区的预测能力强得多,在去除线性趋势后,CFSv2 对巴伦支海-东西伯利亚海(BES)上空 SIC 年际变化的预测能力在 1-2 个月领先期也很高。CFSv2 可以合理地再现 9 月份 BES 上的 SIC 与地表气温、200-hPa 位势高度、海面温度和北大西洋涛动等因素之间的关系。此外,还发现 8 月份规定的 SIC 初始条件作为 CFSv2 的输入也至关重要。因此,上述大气和海洋因素以及准确的 SIC 初始条件都有助于提高 9 月份 BES 上 SIC 的预测技能。根据统计预测方法,进一步确定了各个预测源的贡献。CFSv2 对 BES 上 SIC 年际变化的高预测技能主要归功于其对 SAT 和 SST 的准确预测,以及较好的 SIC 初始条件。
Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents–East Siberian Seas by CFSv2?
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.
期刊介绍:
Journal of Meteorological Research (previously known as Acta Meteorologica Sinica) publishes the latest achievements and developments in the field of atmospheric sciences. Coverage is broad, including topics such as pure and applied meteorology; climatology and climate change; marine meteorology; atmospheric physics and chemistry; cloud physics and weather modification; numerical weather prediction; data assimilation; atmospheric sounding and remote sensing; atmospheric environment and air pollution; radar and satellite meteorology; agricultural and forest meteorology and more.