地球科学进展 ›› 2021, Vol. 36 ›› Issue (2): 198 -210. doi: 10.11867/j.issn.1001-8166.2021.013

研究论文 上一篇    下一篇

第三极地区气温和积雪的季节—年际气候预测研究
汪芋君( ), 任宏利( ), 王琳   
  1. 中国气象科学研究院,灾害天气国家重点实验室,北京 100081
  • 收稿日期:2020-11-28 修回日期:2021-01-25 出版日期:2021-04-13
  • 通讯作者: 任宏利 E-mail:wangyujun181@mails.ucas.ac.cn;renhl@cma.gov.cn
  • 基金资助:
    国家重点研发计划项目“动力—统计相结合的东亚气候年际预测理论和方法研究”(2018YFC1506005);“基于过程扰动的多模式集合预测理论和方法研究”(2017YFC1502302)

Study of Seasonal-Interannual Climate Predictions of Temperature and Snow Depth over the Third Pole

Yujun WANG( ), Hongli REN( ), Lin WANG   

  1. State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Science,Beijing 100081,China
  • Received:2020-11-28 Revised:2021-01-25 Online:2021-04-13 Published:2021-04-19
  • Contact: Hongli REN E-mail:wangyujun181@mails.ucas.ac.cn;renhl@cma.gov.cn
  • About author:WANG Yujun (1997-), female, Xinyang City, Henan Province, Master student. Research areas include short-term climate prediction. E-mail: wangyujun181@mails.ucas.ac.cn
  • Supported by:
    the National Key Research and Development Program of China “Theory and method of interannual climate prediction over East Asian by combining both dynamical and statistical methods”(2018YFC1506005);“The theory and method of multi-model ensemble prediction based on process disturbance”(2017YFC1502302)

第三极地区气候多样、灾害频发,是影响全球和亚洲气候异常的关键区域,针对此地区开展季节—年际气候预测研究对于提高区域预报技巧以及减少灾害造成的影响具有重要的科学和指导意义。基于国家气候中心气候预测业务模式(BCC_CSM1.1m)的历史回报和预测数据,对第三极地区2 m气温和积雪的预测结果进行了确定性技巧评估,并分析了海洋因子对于预测技巧的调制作用。研究表明:该模式对于青藏高原及其周边地区气温和积雪的季节—年际气候预测具有一定的预测能力,对夏季气温的预测效果整体上好于冬季气温和积雪深度预测;预测技巧随着模式起报时间的提前而下降,但是存在技巧回升现象。研究也发现,海温异常因子对第三极地区的气候预测技巧具有不同程度的调制作用,厄尔尼诺等海洋信号能够通过直接和间接作用影响第三极地区的气候预测。

The Third Pole (TP) has diverse climate and frequent disasters and is a key area that affects global and Asian climate anomalies. The study of seasonal-interannual climate prediction in the TP area is of great scientific and guiding significance for improving regional forecasting skills and reducing the natural disaster impacts. Based on the hindcast data of BCC_CSM1.1m, we evaluated the prediction performance of 2m-air temperature (T2m) and snow depth over the TP by employing deterministic forecast verification methods and then analyzed the modulation of the Sea Surface Temperature Anomalies (SSTA). The results indicate that BCC_CSM1.1m has useful prediction skills in the TP area for the seasonal-interannual 2m-air temperature and snow depth predictions. The prediction skill of summer T2m is generally higher than winter T2m and snow depth. The predictivity of BCC_CSM1.1m is generally weaker for a longer lead time, but there is a skill-recovery. Meanwhile, SSTA could modulate the seasonal-interannual climate prediction over the TP and ocean signals such as El Ni?o show their direct and indirect influences on the predictability.

中图分类号: 

图1 不同起报时间下(LT=1~5) BCC_CSM1.1m模式对第三极地区2 m气温和积雪预报技巧ACC的年际变化
Fig.1 The annual change of ACC skills for 2m-air temperature and snow depth prediction with BCC_CSM1.1m at different Lead Time (LT=1~5) over the third pole area
图1 不同起报时间下(LT=1~5) BCC_CSM1.1m模式对第三极地区2 m气温和积雪预报技巧ACC的年际变化
Fig.1 The annual change of ACC skills for 2m-air temperature and snow depth prediction with BCC_CSM1.1m at different Lead Time (LT=1~5) over the third pole area
图2 多年平均ACC随提前起报时间的变化(LT=1~5)
Fig.2 Average ACC skills at different Lead Time (LT=1~5)
图2 多年平均ACC随提前起报时间的变化(LT=1~5)
Fig.2 Average ACC skills at different Lead Time (LT=1~5)
图3 BCC_CSM1.1m在不同起报时间下(LT=1~5)对夏季2 m气温的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.3 TCC skills for summer 2m-air temperature prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图3 BCC_CSM1.1m在不同起报时间下(LT=1~5)对夏季2 m气温的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.3 TCC skills for summer 2m-air temperature prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图4 BCC_CSM1.1m在不同起报时间下(LT=1~5)对冬季2 m气温的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.4 TCC skills for winter 2 m-air temperature prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图4 BCC_CSM1.1m在不同起报时间下(LT=1~5)对冬季2 m气温的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.4 TCC skills for winter 2 m-air temperature prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图5 BCC_CSM1.1m在不同起报时间下(LT=1~5)对冬季积雪的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.5 TCC skills for snow depth prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图5 BCC_CSM1.1m在不同起报时间下(LT=1~5)对冬季积雪的TCC技巧
打点区域表示通过可信度为95%的显著性检验,轮廓线为海拔4 000 m以上的青藏高原的国内部分
Fig.5 TCC skills for snow depth prediction with BCC_CSM1.1m at different Lead Time (LT=1~5)
The stippled area represents the statistical significance above the 95% confidence level, and the outline is the domestic part of the Qinghai-Tibet Plateau with an altitude above 4 000 m
图6 夏季2 m气温预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.6 Correlation coefficient between summer 2m-air temperature ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图6 夏季2 m气温预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.6 Correlation coefficient between summer 2m-air temperature ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图7 冬季2 m气温预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.7 Correlation coefficient between winter 2m-air temperature ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图7 冬季2 m气温预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.7 Correlation coefficient between winter 2m-air temperature ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图8 第三极积雪预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.8 Correlation coefficient between Tsd ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图8 第三极积雪预报技巧与提前0~3个季节的SSTA的相关系数分布图
打点区域表示通过可信度为95%的显著性检验
Fig.8 Correlation coefficient between Tsd ACC skills and SSTA at 0~3 lead season(s)
The stippled area represents the statistical significance at the 95% confidence level
图9 冬季2 m气温预测技巧与各Ni?o海温指数的相关系数
实线(虚线)表示通过95%(99%)的显著性检验
Fig.9 Correlation coefficients between 2m-air temperature ACC skills in winter and Ni?o indices
Solid line (dotted line) represent the statistical significance at the 95% (99%) confidence level
图9 冬季2 m气温预测技巧与各Ni?o海温指数的相关系数
实线(虚线)表示通过95%(99%)的显著性检验
Fig.9 Correlation coefficients between 2m-air temperature ACC skills in winter and Ni?o indices
Solid line (dotted line) represent the statistical significance at the 95% (99%) confidence level
图10 夏季2 m气温预测技巧与各Ni?o海温指数的相关系数
实线表示通过95%的显著性检验
Fig.10 Correlation coefficients between 2m-air temperature ACC skills in summer and Ni?o indices
Solid line represent the statistical significance at the 95% confidence level
图10 夏季2 m气温预测技巧与各Ni?o海温指数的相关系数
实线表示通过95%的显著性检验
Fig.10 Correlation coefficients between 2m-air temperature ACC skills in summer and Ni?o indices
Solid line represent the statistical significance at the 95% confidence level
图11 第三极地区2 m气温与各海温指数的相关系数分布图
夏季气温(a,c)和冬季气温(b,d),打点区域表示通过可信度为95%的显著性检验
Fig.11 Correlation coefficient between 2m-air temperature in the TP area and SST indices
2m-air temperature in summer (a,c); 2m-air temperature in winter (b,d). The stipple area represents the statistical significance at the 95% confidence level
图11 第三极地区2 m气温与各海温指数的相关系数分布图
夏季气温(a,c)和冬季气温(b,d),打点区域表示通过可信度为95%的显著性检验
Fig.11 Correlation coefficient between 2m-air temperature in the TP area and SST indices
2m-air temperature in summer (a,c); 2m-air temperature in winter (b,d). The stipple area represents the statistical significance at the 95% confidence level
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