ENSEMBLES耦合模式对全球陆地季风区夏季降水的年代际预测能力评估

doi:10.11867/j. issn. 1001-8166.2017.04.0409

地球科学进展 ›› 2017, Vol. 32 ›› Issue (4): 409 -419. doi: 10.11867/j. issn. 1001-8166.2017.04.0409

张丽霞 ^1, ²(

), 张文霞 ^1, ³, 周天军 ^1, ³, 吴波 ¹

1. 中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京 100029
2. 南京信息工程大学气象灾害预报预警与评估协同创新中心,江苏南京 210044
3.中国科学院大学,北京 100049

收稿日期:2016-10-19 修回日期:2017-02-05 出版日期:2017-04-20
基金资助:
公益性行业(气象)科研专项项目“基于FGOALS-s、CMA和CESM气候系统模式的年代际集合预测系统的建立与研究”(编号:GYHY201506012);国家自然科学基金项目“20世纪全球季风变化模拟和未来变化预估”(编号:41330423)资助

Assessment of the Decadal Prediction Skill on Global Land Summer Monsoon Precipitation in the Coupled Models of ENSEMBLES

Lixia Zhang ^1, ², Wenxia Zhang ^1, ³( ), Tianjun Zhou ^1, ³, Bo Wu ¹

1. LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,Chian
2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044,China
3. University of Chinese Academy of Sciences, Beijing 100049,China

Received:2016-10-19 Revised:2017-02-05 Online:2017-04-20 Published:2017-04-20
About author:
First author:Zhang Lixia(1982-),female,Baoding County, Hebei Province,Associate Professor.Research areas include changes of drought and flood over monsoon regions.E-mail:lixiazhang@mail.iap.ac.cn
Supported by:
Foundation item:Project supported by the R&D Special Fund for Public Welfare Industry (Meteorology) “Development and research of ensemble decadal climate prediction system based on global climate models FGOALS-s, CAMS and CESM”(No.GYHY201506012);The National Natural Science Foundation of China “Global monsoon: 20 ^th Century change simulation and future change”(No: 41330423)

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全球季风区降水对当地社会经济、全球大尺度环流及能量循环至关重要。采用欧洲联盟ENSEMBLES计划Stream 2的年代际回报试验,评估了其对1960—2015年全球陆地季风夏季降水年代际变化的回报能力,并探讨了北半球陆地季风区夏季(NHSM)降水年代际变化可预报性的可能来源。分析发现 ENSEMBLES对全球及南球陆地季风区夏季降水的年代际回报技巧不高,但其对NHSM降水具有一定的预报能力,能合理回报出观测中NHSM降水在1960年至1970s末期的减弱趋势和1990s之后的增强趋势,其缺陷在于模式中NHSM降水最小值出现在1970s末期,较之观测提前了近10年,未能回报出1980s中期至1990s初期NHSM的干旱期。mega-ENSO与大西洋多年代际振荡(AMO)是影响NHSM降水年代际变化的2个重要驱动因子。分析发现模式回报的NHSM降水与mega-ENSO、大西洋多年代际振荡(AMO)的正相关明显大于观测,能合理再现2个指数在1960年至1970s末期和1990s后的变化趋势,是模式对这2个时段内NHSM降水回报技巧的重要来源。虽然ENSEMBLES对AMO的年代际变化具有较高的回报能力(与观测的最大相关系数高达0.85),但是对mega-ENSO的回报技巧较弱,进而限制了模式1980s中期至1990s初NHSM的年代际预报技巧。因此,提高模式对mega-ENSO的预报能力,是提升NHSM降水年代际预报水平的重要途径。

关键词: 全球季风, 年代际预测, 可预报性, 耦合模式

Global monsoon precipitation plays a crucial role in the local social economy and global large-scale circulation and energy cycle. Using the decadal prediction output for 1960-2015 from ENSEMBLES Stream 2, the decadal hindcast skill of climate models on global land monsoon precipitation and the potential source of predictability were examined in this paper. It is found that the decadal variation of global and southern hemispheric land monsoon precipitation is not well hindcasted by ENSEMBLES. However, the Northern Hemispheric land Summer Monsoon (NHSM) precipitation in hindcast is well predicted, including the observed downward trend from 1960 to the late 1970s and upward trend since the 1990s. The main deficiency is that the minimum NHSM precipitation occured in mid-1970s, which is 10-year earlier than the observation, leading to poor prediction of NHSM precipitation from the mid-1980s to early 1990s. Mega-ENSO and Atlantic Multi-decadal Oscillation (AMO) are the two main factored that modulate the decadal variation of NHSM precipitation. The result shows that the relationships of NHSM precipitation with mega-ENSO and AMO in ENSENBLES are higher than the observation. The climate models well predicted the increase from 1960 to the late 1970s and decrease trend since the 1990s of mega-ENSO and AMO. It is the primary source of the prediction skill on NHSM changes during the two periods. Although AMO is well predicted by ENSEMBLES (highest correlation coefficient with observation is 0.85), the prediction skill of mega-ENSO is limited, leading to poor performance in predicting NHSM precipitation from the mid-1980s to early 1990s. Thus, improving the prediction of mega-ENSO can be seen as one important method of better decadal prediction of NHSM precipitation.

Key words: Global monsoon, Decadal prediction, Predictability, Coupled mode.

中图分类号:

P426.6

图1 ENSEMBLES多模式集合(MME)平均预测的(a) 第1~4 年和(b)第6~9年平均夏季降水距平与观测的相关系数分布
打点区域通过了10%显著性检验水平;其中北半球夏季是5~9月平均,南半球夏季是11月到来年3月平均

Fig.1 The correlation coefficient of summer precipitation anomalies between MME prediction and observation averaged over the hindcast years (a) 1~4 years and (b) 6~9 years
The dotted areas are statistically significant at 10% level;The summer precipitation in northern hemisphere and southern hemisphere is that averaged from May to September and from November to March, respectively

图2 ENSEMBLES多模式集合(MME)平均预测的(a) 第1~4 年和(b)第6~9年平均夏季降水距平与观测之间的均方根技巧评分(RMSSS)的水平分布
打点区域通过了10%显著性检验水平;其中北半球夏季是5~9月平均,南半球夏季是11月到来年3月平均

Fig.2 The distribution of Root Mean Square Skill Score (RMSSS)of summer precipitation anomalies between MME prediction and observation averaged over the hindcast years (a) 1~4 years and (b) 6~9 years
The dotted areas are statistically significant at 10% level; The summer precipitation in northern hemisphere and southern hemisphere is that averaged from May to September and from Novermber to March, respectively

图3 模式预测的陆地季风区区域平均的4年平均夏季降水距平与观测的相关系数随预报时长的变化
(a)北半球陆地季风区夏季降水;(b) 南半球陆地季风区夏季降水;(c)全球陆地季风区夏季降水。其中黑色实线和灰色虚线分别代表所有多模式集合(MME)平均和不同模式成员结果,全球季风区夏季降水是(a)与(b)的平均

Fig.3 The evolution of correlation coefficient between model predicted 4 years summer mean precipitation and that of observation regional average
(a) Northern hemispheric land monsoon;(b) Southern hemispheric land monsoon;(c) Global land monsoon regions. The black and dashed lines show the MME and individual realization, respectively. The global land monsoon summer precipitation is the average of (a) and (b)

图4 标准化之后模式预测的第(a) 1~4 年平均,(b)2~5年,(c)3~6年,(d)4~7年,(e)5~8年和(f)6~9年及相应年份观测的NHSM降水距平
黑色实线为观测,灰色实线和虚线分别代表多模式集合平均和每个模式成员结果

Fig.4 The normalized precipitation anomalies evolution regional averaged over northern hemispheric land monsoon region (black and blue lines) and northern hemispheric summer monsoon circulation (red and green lines) in observation and MME hindcast for the (a) 1~4 years, (b) 2~5 years, (c) 3~6 years, (d) 4~7 years, (e) 5~8 years and (f) 6~9 years
The black line, grey line and grey dashed lines denote the observation, multimodel ensemble mean and each realization, respectively

图5 模式预测的第1~4年和第6~9年平均的北半球夏季降水与mega-ENSO指数的相关系数(a),(c) 观测,(b),(d) MME
划线区域通过10%显著性检验,mega-ENSO指数定义为西太平洋K型区域平均的SST与东太平洋三角形区域平均的SST之差(具体区域见参考文献[7])

Fig.5 The correlation coefficient between model predicted precipitation in boreal summer and the corresponding mega-ENSO index for the 1~4 years (left panel) and 6~9 years (right panel) derived from (a),(c) observation, (b),(d) MME
The dotted areas are statistically significant at 10% level. The mega-ENSO index is defined as the SST difference between the western Pacific K-shape area and eastern Pacific triangle (The regions where the mega-ENSO defined can be found in reference[7])

图6 模式预测的第1~4年(a),(b)和第6~9年(c),(d)平均的北半球夏季降水与AMO指数的相关系数(a),(c) 观测,(b),(d) MME
划线区域通过10%显著性检验,AMO指数定义为(0°~60°N, 80°~0°W)区域平均SST距平与(60°S~60°N)区域平均SST距平之差 ^{[

27
]}

Fig.6 The correlation coefficient between model predicted precipitation in boreal summer and the corresponding AMO index for the 1~4 years(left panel) and 6~9 years (right panel) derived from (a),(c) observation, (b),(d) MME
The dotted areas are statistically significant at 10% level; The AMO index is defined as area-averaged SST anomalies in the (0°~60°N, 80°~0°W) minus the area-averaged near global SST anomalies in the (60°S~60°N) ^{[

27
]}

图7 标准化之后多模式集合平均预测的第(a) 1~4 年平均,(b)2~5年,(c)3~6年,(d)4~7年,(e)5~8年和(f)6~9年及相应年份观测的AMO指数和mega-ENSO指数距平

Fig.7 The normalized AMO and mega-ENSO indices evolutions in MME hindcast and observation for (a) 1~4 years, (b) 2~5 years, (c) 3~6 years, (d) 4~7 years, (e) 5~8 years and (f) 6~9 years

图8 模式预测的4年平均夏季(a) AMO指数与 (b)mega-ENSO指数与观测的相关系数随预报时长的变化

Fig.8 The evolution of correlation coefficient between model predicted 4 years summer mean (a) AMO index and (b) mega-ENSO index and that of observation

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