耦合模式中北太平洋和北大西洋海表面温度年代际可预报性和预报技巧的季节依赖性

doi:10.11867/j. issn. 1001-8166.2017.04.0382

地球科学进展 ›› 2017, Vol. 32 ›› Issue (4): 382 -395. doi: 10.11867/j. issn. 1001-8166.2017.04.0382

容新尧 ¹(

), 刘征宇 ^2, ³, 段晚锁 ⁴

1.中国气象科学研究院灾害天气国家重点实验室,北京 100081
2.Department of Atmospheric and Oceanic Sciences & Center for Climatic Research, University of Wisconsin-Madison,Madison Wisconsin,USA
3.北京大学物理学院大气与海洋科学系,北京 100871
4.中国科学研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

收稿日期:2016-10-19 修回日期:2017-01-20 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);科技部全球变化研究项目(编号:2012CB955201)资助

Seasonal Dependence of the North Pacific and North Atlantic SST Predictability and Forecast Skill

Xinyao Rong ¹( ), Zhengyu Liu ^2, ³, Yun Liu ², Wansuo Duan ⁴

1.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
2.Department of Atmospheric and Oceanic Sciences & Center for Climatic Research, University of Wisconsin-Madison,Madison Wisconsin, USA
3.Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University,Beijing 100871,China
4.State Key Laboratory of Numerical Modeling for Ateospheric Sciences and GeophysicalFluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

Received:2016-10-19 Revised:2017-01-20 Online:2017-04-20 Published:2017-04-20
About author:
First author:Rong Xinyao(1979-), male, Sanya City, Hainan Province, Associate professor. Research areas include climate numerical simulation and prediction.E-mail:rongur@camscma.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 Basic Research Program of China (No.2012CB955201)

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利用一个全球耦合环流模式在理想模式框架下进行了3组动力预报试验,研究了北太平洋和北大西洋海表面温度异常(SSTA)的年代际可预报性和预报技巧。结果表明北太平洋年平均SSTA在年代际尺度上可预报性和预报技巧表现较低,明显弱于北大西洋。通过分析不同季节平均SSTA的可预报性与预报技巧,发现北太平洋中西部区域冬季平均SSTA的年代际可预报性和预报技巧显著高于其他季节,其量值和北大西洋相当,表现为明显的季节依赖性;北大西洋SSTA的可预报性和预报技巧也显示了随季节变化的特征。进一步分析表明,北太平洋SSTA年代际可预报性和预报技巧的季节依赖性归因于北太平洋冬季SSTA的年与年之间再现机制,这一再现机制源于北太平洋混合层显著的季节变化;而北大西洋SSTA的可预报性和预报技巧的季节依赖性则可能与其他过程(如大西洋年代际涛动)的季节变化有关。研究结果表明,对于年代际气候预报,如果考虑所关注指标的季节平均,则可能在某些季节获得比年平均更高的预报技巧。

关键词: 北太平洋, 北大西洋, 年代际预测, 季节依赖性, 耦合模式

In this paper, the decadal predictability and forecast skill of the Sea Surface Temperature Anomalies (SSTA) in the North Pacific and North Atlantic Ocean were investigated by conducting three sets of perfect model forecast experiments using a global coupled general circulation model. The results show that the annual mean SSTA in the North Pacific is less predictable on decadal time scale, with the forecast skill notably weaker than that of the North Atlantic. By analyzing the predictability and forecast skill of seasonal mean SSTA, it is found that the decadal predictability and forecast skill of the winter mean (JFM) SSTA in the central and western North Pacific are significantly higher than those of other seasons, and the magnitude is comparable with that of the North Atlantic. The predictability and forecast skill of the North Atlantic SSTA also show seasonal variations. Further analysis indicates that the seasonal dependence of the SSTA decadal predictability and forecast skill in the North Pacific is due to the winter-to-winter reemergence mechanism of SSTA in the North Pacific, which results from the seasonal variation of the mixed layer depth of the North Pacific Ocean. While the seasonal dependence of the North Atlantic SSTA predictability and forecast skill might be related to seasonal variations of other processes, such as the Atlantic Decadal Oscillation. The results of this paper suggest that for decadal climate prediction, if the forecast skill of the seasonal mean is taken into account, we might obtain higher than annual mean forecast skill for some seasons.

Key words: North Pacific, North Atlantic, Decadal prediction, Seasonal dependence, Coupled GCM.

中图分类号:

P467

图1 年平均上层海洋热容量(400 m)异常的EOF第一模态时间系数
(a)北太平洋(120°E~110°W,20°~60°N)区域;(b)北大西洋(80°W~10°E,20°~80°N)区域;图中黑线代表真值,红线和绿线分别为Nudging和EnKF同化的结果;横坐标的时间点0对应控制试验的第135年

Fig.1 Temporal coefficients of the first EOF mode of the upper ocean heat content (400 m)
(a) The North Pacific (120°E~110°W, 20°~60°N) region; (b) the North Atlantic (80°W~10°E, 20°~80°N) region. The black lines represent the true values, and the red and green lines are the result of assimilation from Nudging and EnKF, respectively. The abscissa of the time zero represents the 135 ^th year of control run

图2 控制试验模拟的年平均SST异常的年代际潜在可预报性分布

Fig.2 Decadal potential predictability of annual mean SSTA of control run

图3 北太平洋和北大西洋年平均SSTA前3个EOF模态时间系数的RMSE随预报时间(年)的变化
EOF分解的区域同图1 ;左列为北太平洋结果,右列为北大西洋的结果;从上往下分别代表EOF的第一、第二、第三模态;红色线为PERFO预报,绿色和蓝色线分别代表Nudging和EnKF预报,黄色线为持续性预报;图中横坐标为预报时间,0表示预报前一年平均异常(同化结果);图中右上角数字表示各个EOF模态的解释方差

Fig.3 RMSE of the temporal coefficients of the first three EOF modes for North Pacific and North Atlantic SSTA
The areas of EOF decomposition are same as Fig.1 ; The left and right panels are the results of North Pacific and the North Atlantic, respectively.From top to bottom: The first, second and third EOF mode. The red, green, blue and yellow lines denote the PERFO, Nudging,EnKF and persistence forecasts, respectively. The abscissa represents the forecast time, and the value at time zero is the annual mean calculated by the previous year’s SSTA (assimilation result). The number shown on the upper right corner of each panel represents the explained variance of each EOF mode

图4 控制试验模拟的季节平均的SST异常的年代际潜在可预报性分布
(a)冬季(JFM);(b)春季(AMJ);(c)夏季(JAS);(d)秋季(OND)

Fig.4 Decadal potential predictability of the seasonal mean SSTA derived from control run
(a) Winter (JFM); (b) Spring (AMJ); (c) Summer (JAS); (d) Autumn (OND)

图5 年平均以及不同季节平均的北太平洋SSTA的RMSE随预报时间的变化
(a)PERFO预报;(b)Nudging预报;(c)EnKF预报;(d)持续性预报

Fig.5 Temporal evolution of the RMSE of the annual mean and seasonal mean SSTA averaged over the North Pacific region
(a) PERFO forecast; (b) Nudging forecast; (c) EnKF forecast; (d) Persistence forecast

图6 年平均以及不同季节平均的北大西洋SSTA的RMSE随预报时间的变化
(a)PERFO预报;(b)Nudging预报;(c)EnKF预报;(d)持续性预报

Fig.6 Temporal evolution of the RMSE of the annual mean and seasonal mean SSTA averaged over the North Atlantic region
(a) PERFO forecast; (b) Nudging forecast; (c) EnKF forecast; (d) Persistence forecast

图7 年平均以及季节平均的区域平均SSTA的超前滞后相关系数
(a)北太平洋区域;(b)北大西洋区域;横坐标为滞后时间(年)

Fig.7 Lead-lag correlation coefficients of the annual mean and seasonal mean SSTA averaged over different regions
(a) The North Pacific region; (b) The North Atlantic region. The abscissa represents the lag time (years)

图8 北太平洋季节平均SSTA和温度异常的相关系数随超前—滞后时间以及深度的变化
(a)冬季(JFM);(b)春季(AMJ);(c)夏季(JAS);(d)秋季(OND);零表示对应季节的中间月份,正值表示温度滞后SSTA

Fig.8 Time-depth section of the lead-lag correlation coefficients between the seasonal mean and monthly mean SSTA averaged over the North Pacific region
(a) Winter (JFM); (b) Spring (AMJ); (c) Summer (JAS); (d) Autumn (OND).The abscissa represents the lag time (years), zero indicates the middle month of the corresponding season and a positive value indicates the temperature lags the SSTA

图9 模式控制试验模拟(红色)和观测(黑色)的(a)北太平洋和(b)北大西洋区域平均的混合层深度(单位:m)的季节变化(观测资料取自参考文献[37])

Fig.9 Seasonal variation of the mixed layer depth (unit: m) averaged over (a) the North Pacific and (b) North Atlantic regions from control run (red) and observations (black) (The observations are taken from reference [37])

图10 北大西洋季节平均的SSTA和温度异常的相关系数随超前—滞后时间以及深度的变化
(a)冬季(JFM);(b)春季(AMJ);(c)夏季(JAS);(d)秋季(OND);图中横坐标为滞后时间(年),零表示对应季节的中间月份,正值表示温度滞后SSTA

Fig.10 Time-depth section of the lead-lag correlation coefficients between the seasonal mean and monthly mean SSTA averaged over the North Atlantic region
(a) Winter (JFM); (b) Spring (AMJ); (c) Summer (JAS); (d) Autumn (OND).The abscissa represents the lag time (years), zero indicates the middle month of the corresponding season and a positive value indicates the temperature lags the SSTA

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