doi:  10.3878/j.issn.1006-9895.1702.16231
欧亚大陆积雪对我国春季气候可预报性的影响

Impacts of Eurasian Snow Condition on Spring Climate Predictability over China by a Global Climate Model
摘要点击 621  全文点击 485  投稿时间:2016-09-14  
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基金:  国家自然科学基金面上项目41575080
中文关键词:  欧亚积雪  春季气候  可预报性
英文关键词:  Eurasian snow conditions  Spring climate  Climate predictability
  
作者中文名作者英文名单位
陈红CHEN Hong中国科学院大气物理研究所国际气候与环境科学中心, 北京 100029
引用:陈红.2017.欧亚大陆积雪对我国春季气候可预报性的影响[J].大气科学,41(4):727-738,doi:10.3878/j.issn.1006-9895.1702.16231.
Citation:CHEN Hong.2017.Impacts of Eurasian Snow Condition on Spring Climate Predictability over China by a Global Climate Model[J].Chinese Journal of Atmospheric Sciences (in Chinese),41(4):727-738,doi:10.3878/j.issn.1006-9895.1702.16231.
中文摘要:
      利用大气环流模式IAP9L_CoLM,通过两组集合后报试验,考察了欧亚大陆积雪对我国春季气候可预报性的影响。一组试验为常规后报试验,积雪是由模式陆面过程预报得到的,另一组试验为积雪试验,模式积分过程中欧亚大陆雪水当量由微波遥感积雪资料替代,一天替换一次。通过分析两组试验后报结果的差异,来考察欧亚大陆积雪对我国春季( 3~5月)气候可预报性的影响。分析表明:欧亚大陆积雪模拟水平的改善能提高春季欧亚大陆中高纬环流场(海平面气压场和中、高层位势高度场)的可预报性,模式对我国春季气温异常的年际变化和空间分布的可预报能力也有显著增强。对我国春季降水,虽然预报技巧较低,但引入较真实的欧亚积雪作用后,由于中高纬环流场预报技巧的改进导致降水的预测能力也有所改进。个例分析也表明,欧亚中高纬春季积雪异常模拟水平的改善导致了欧亚中高纬贝加尔湖及以南区域环流场可预报性的提高,最终使中国东部区域春季气候异常模拟技巧得以改善。以上结果也证实,欧亚大陆积雪是影响东亚区域春季气候的一个重要因子,要提高模式对中国春季气候的预报技巧,积雪模拟水平的改进是非常必要的。
Abstract:
      Two ensemble experiments with an atmospheric general circulation climate model (IAP9L_CoLM) were conducted to investigate the impacts of realistic Eurasian snow condition on spring climate predictability over China. In one ensemble simulation, snow condition was allowed to evolve interactively; in the other ensemble simulation, the snow condition was prescribed according to microwave remote snow water equivalent depth data. Differences between the two experiments were assessed to evaluate the impact of realistic Eurasian snow condition on simulated climate anomalies in the spring. Looking at sea level pressure and geopotential height at the middle and upper levels, it was found that the IAP9L_CoLM prediction skill was enhanced at the middle-high latitudes of Eurasia with improved Eurasian snow condition. Furthermore, the results indicate that the predictive skill of IAP9L_CoLM for both interannual variation and spatial distribution of surface air temperature over China was obviously improved with prescribed snow condition over Eurasia. For spring precipitation over China, although the predictive skill was low, the potential predictability increased with more realistic snow condition. One case study also showed that with the improved simulation of snow condition over Eurasia, the predictive skill for large scale circulation anomalies over the middle-high latitudes of Eurasia was increased, which finally led to a better hindcast of spring climate anomalies over China. Overall, this study suggests that Eurasian snow condition can potentially affect the spring climate anomalies over China. Thereby the predictive ability for Eurasian snow condition must be improved for better prediction of spring climate over China.
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