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参考文献
BrethertonC S, WidmannM, DymnikovV P, et al. 1999. The effective number of spatial degrees of freedom of a time-varying field [J]. J. Climate, 12(7): 1990-2009. doi:10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2.
参考文献
ChenH, LinZ H. 2009. The potential predictability of the South China Sea summer monsoon in a dynamical seasonal prediction system[J]. Atmospheric and Oceanic Science Letters, 2(5): 271-276. doi:10.1080/16742834.2009.11446819.
参考文献
ChenW, HanF G, HuangR H. 2000. The interannual variability of East Asian winter monsoon and its relation to the summer monsoon[J]. Advances in Atmospheric Sciences, 17(1): 48-60. doi:10.1007/s00376-000-0042-5.
参考文献
ChenW, FengJ, WuR G. 2013. Roles of ENSO and PDO in the link of the East Asian winter monsoon to the following summer monsoon[J]. J. Climate, 26(2): 622-635. doi:10.1175/JCLI-D-12-00021.1.
参考文献
陈永利, 胡敦欣. 2003. 南海夏季风爆发与西太平洋暖池区热含量及对流异常[J]. 海洋学报, 25(3): 20-31. Chen Yongli, Hu Dunxin. 2003. The relation between the South China Sea summer monsoon onset and the heat content variations in the tropical western Pacific warm pool region[J]. Acta Oceanologica Sinica (in Chinese), 25(3): 20-31. doi:10.3321/j.issn:0253-4193.2003.03.003.
参考文献
戴念军, 谢安, 张勇. 2000. 南海夏季风活动的年际和年代际特征[J]. 气候与环境研究, 5(4): 363-374. Dai Nianjun, Xie An, Zhang Yong. 2000. Interannual and interdecadal variations of summer monsoon activities over the South China Sea[J]. Climatic and Environmental Research (in Chinese), 5(4): 363-374. doi:10.3969/j.issn.1006-9585.2000.04.004.
参考文献
DingR Q, LiJ P, TsengY H, et al. 2015. The Victoria mode in the North Pacific linking extratropical sea level pressure variations to ENSO [J]. J. Geophys. Res., 120(1): 27-45. doi:10.1002/2014JD022221.
参考文献
丁一汇, 李崇银, 柳艳菊, 等. 2002. 南海季风试验研究[J]. 气候与环境研究, 7(2): 202-208. Ding Yihui, Li Chongyin, Liu Yanju,et al. 2002. South China Sea monsoon experiment[J]. Climatic and Environmental Research (in Chinese), 7(2): 202-208. doi:10.3969/j.issn.1006-9585.2002.02.007.
参考文献
DingY H, LiuY J, LiangS J, et al. 2014. Interdecadal variability of the East Asian winter monsoon and its possible links to global climate change [J]. J. Meteor. Res., 28(5): 693-713. doi:10.1007/s13351-014-4046-y.
参考文献
董玉杰, 冯俊乔, 胡敦欣. 2016. 西太平洋暖池热含量与南海夏季风强度的关系[J]. 海洋科学, 40(3): 160-166. Dong Yujie, Feng Junqiao, Hu Dunxin. 2016. Relationship between heat content over the western pacific warm pool and intensity of South China Sea summer monsoon[J]. Journal of the Oceanic Sciences (in Chinese), 40(3): 160-166. doi:10.11759/hykx20150206002.
参考文献
冯娟, 李建平. 2009. 南海夏季风变化及其与全球大气和海温的关系[J]. 大气科学, 33(3): 568-580. Feng Juan, Li Jianping. 2009. Variation of the South China Sea summer monsoon and its association with the global atmosphere circulation and sea surface temperature[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 33(3): 568-580. doi:10.3878/j.issn.1006-9895.2009.03.14.
参考文献
FengJ Q, HuD X. 2017. How much does heat content of the western tropical Pacific Ocean modulate the South China Sea summer monsoon onset in the last four decades[J]. J. Geophys. Res., 119(7): 4029-4044. doi:10.1002/2013JC009683.
参考文献
GadgilS, RajeevanM, NanjundiahR. 2005. Monsoon prediction: Why yet another failure[J]. Current Science, 88(9): 1389-1400.
参考文献
GoswamiB N. 2004. Interdecadal change in potential predictability of the Indian summer monsoon[J]. Geophys. Res. Lett., 31(16): L16208. doi:10.1029/2004GL020337.
参考文献
谷德军, 纪忠萍, 王东晓, 等. 2007. 不同时间尺度上南海夏季风强度与海洋热力条件的关系[J]. 热带气象学报, 23(1): 14-20. Gu Dejun, Ji Zhongping, Wang Dongxiao,et al. 2007. The relationship between SCS summer monsoon intensity and oceanic thermodynamic variables at different time scale[J]. Journal of Tropical Meteorology (in Chinese), 23(1): 14-20. doi:10.3969/j.issn.1004-4965.2007.01.003.
参考文献
HuangR H, ChenJ L, WangL, et al. 2012. Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system [J]. Advances in Atmospheric Sciences, 29(5): 910-942. doi:10.1007/s00376-012-2015-x.
参考文献
黄少妮, 黄菲. 2013. 南海夏季风爆发早晚的海温预报指数[J]. 中国海洋大学学报, 43(10): 8-15. Huang Shaoni, Huang Fei. 2013. Sea surface temperature prediction indices for the South China Sea summer monsoon onset[J]. Periodical of Ocean University of China (in Chinese), 43(10): 8-15.
参考文献
JonesR H. 1975. Estimating the variance of time averages[J]. J. Appl. Meteor., 14(2): 159-163. doi:10.1175/1520-0450(1975)014<0159:ETVOTA>2.0.CO;2.
参考文献
KalnayE, KanamitsuM, KistlerR, et al. 1996. The NCEP/NCAR 40-Year reanalysis project [J]. Bull. Amer. Meteor. Soc., 77(3): 437-472. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.
参考文献
LiJ P, ChouJ F. 1997. Existence of the atmosphere attractor[J]. Science in China Series D: Earth Sciences, 40(2): 215-220. doi:10.1007/BF02878381.
参考文献
李霞, 梁建茵, 郑琳. 2007. 南海夏季风强度年代际变化基本特征[J]. 应用气象学报, 18(3): 330-339. Li Xia, Liang Jianyin, Zheng Lin. 2007. Interdecadal variabilities of SCS summer monsoon intensity[J]. Journal of Applied Meteorological Science (in Chinese), 18(3): 330-339. doi:10.3969/j.issn.1001-7313.2007.03.009.
参考文献
梁建茵, 吴尚森. 2003. 太平洋海温异常对南海西南季风建立早晚的影响——数值模拟研究[J]. 海洋学报, 25(1): 28-41. Liang Jianyin, Wu Shangsen. The study on the mechanism of SSTA in the Pacific Ocean affecting the onset of summer monsoon in the South China Sea—numerical experiments[J]. Acta Oceanologica Sinica (in Chinese), 25(1): 28-41. doi:10.3321/j.issn:0253-4193.2003.01.004.
参考文献
LiuQ Y, JiangX, XieS P, et al. 2004. A gap in the Indo-Pacific warm pool over the South China Sea in boreal winter: Seasonal development and interannual variability [J]. J. Geophys. Res., 109(C7): C07012. doi:10.1029/2003JC002179.
参考文献
LorenzE N. 1963. Deterministic nonperiodic flow[J]. J. Atmos. Sci., 20(2): 130-148. doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2.
参考文献
LorenzE N. 1965. A study of the predictability of a 28-variable atmospheric model[J]. Tellus, 17(3): 321-333. doi:10.1111/j.2153-3490.1965.tb01424.x.
参考文献
LuE, ChanJ C L. 1999. A unified monsoon index for South China[J]. J. Climate, 12(8): 2375-2385. doi:10.1175/1520-0442(1999)012<2375:AUMIFS>2.0.CO;2.
参考文献
MaddenR A. 2000. Estimates of the natural variability of time-averaged sea-level pressure[J]. Mon. Wea. Rev., 104(7): 942-952. doi:10.1175/1520-0493(1976)104<0942:EOTNVO>2.0.CO;2.
参考文献
毛江玉, 谢安, 宋焱云, 等. 2000. 海温及其变化对南海夏季风爆发的影响[J]. 气象学报, 58(5): 556-569. Mao Jiangyu, Xie An, Song Yanyun,et al. 2000. Impact of sea surface temperature and itd varions on the onsft of summer monsoon over South China Sea[J]. Acta Meteorologica Sinica (in Chinese), 58(5): 556-569. doi:10.11676/qxxb2000.058.
参考文献
邵勰, 黄平, 黄荣辉. 2015. 基于海温异常的南海夏季风爆发的可预报性分析[J]. 气象科学, 35(6): 684-690. Shao Xie, Huang Ping, Huang Ronghui. 2015. Predictability analysis on onset of South China Sea summer monsoon based on the sea surface temperature anomaly[J]. Journal of the Meteorological Sciences (in Chinese), 35(6): 684-690. doi:10.3969/2014jms.0053.
参考文献
施洪波, 周天军, 万慧, 等. 2008. SMIP2试验对亚洲夏季风的模拟能力及其可预报性的分析[J]. 大气科学, 32(1): 36-52. Shi Hongbo, Zhou Tianjun, Wan Hui,et al. 2008. SMIP2 experiment-based analysis on the simulation and potential predictability of Asian summer monsoon[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 32(1): 36-52. doi:10.3878/j.issn.1006-9895.2008.01.04.
参考文献
SmithT M, ReynoldsR W, PetersonT C, et al. 2008. Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880-2006) [J]. J. Climate, 21(10): 2283-2296. doi:10.1175/2007JCLI2100.1.
参考文献
TrenberthK E. 1984. Some effects of finite sample size and persistence on meteorological statistics. Part II: Potential predictability[J]. Mon. Wea. Rev., 112(12): 2369-2379. doi:10.1175/1520-0493(1984)112<2369:SEOFSS>2.0.CO;2.
参考文献
TrenberthK E. 1985. Potential predictability of geopotential heights over the Southern Hemisphere[J]. Mon. Wea. Rev., 113(1): 54-64. doi:10.1175/1520-0493(1985)113<0054:PPOGHO>2.0.CO;2.
参考文献
WangB, HuangF, WuZ W, et al. 2009. Multi-scale climate variability of the South China Sea monsoon: A review [J]. Dyn. Atmos. Oceans, 47(1-3): 15-37. doi:10.1016/j.dynatmoce.2008.09.004.
参考文献
WangL, HuangR H, GuL, et al. 2009. Interdecadal variations of the East Asian winter monsoon and their association with quasi-stationary planetary wave activity [J]. J. Climate, 22(18): 4860-4872. doi:10.1175/2009JCLI2973.1.
参考文献
WangL, ChenW. 2014. The East Asian winter monsoon: Re-amplification in the mid-2000s[J]. Chinese Science Bulletin, 59(4): 430-436. doi:10.1007/s11434-013-0029-0.
参考文献
WuG X, ZhangY S. 1998. Tibetan Plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea[J]. Mon. Wea. Rev., 126(4): 913-927. doi:10.1175/1520-0493(1998)126<0913:TPFATT>2.0.CO;2.
参考文献
吴洪宝, 王盘兴, 林开平. 2005. 广西夏季降水量潜在可预报性估计[J]. 应用气象学报, 16(4): 445-452. Wu Hongbao, Wang Panxing, Lin Kaiping. 2005. Estimate of potential predictability of summer precipitation in Guangxi. Journal of Applied Meteorological Science (in Chinese), 16(4): 445-452. doi: 10.11898/1001-7313.20050404.
参考文献
吴洪宝, 吴蕾. 2005. 气候变率诊断和预测方法 [M]. 北京: 气象出版社, 304-307. Wu Hongbao, Wu Lei. 2005. Methods of Diagnosing and Forecasting Climate Variability (in Chinese) [M]. Beijing: China Meteorogical Press, 304-307.
参考文献
WuR G, WenZ P, SongY, et al. 2010. An interdecadal change in Southern China summer rainfall around 1992/93 [J]. J. Climate, 23(9): 2389-2403. doi:10.1175/2009JCLI3336.1.
参考文献
吴尚森, 梁建茵, 李春晖. 2003. 南海夏季风强度与我国汛期降水的关系[J]. 热带气象学报, 19(S1): 25-36. Wu Shangsen, Liang Jianyin, Li Chunhui. 2003. Relationship between the intensity of South China Sea summer monsoon and the precipitation in raining seasons in China[J]. Journal of Tropical Meteorology (in Chinese), 19(S1): 25-36. doi:10.3969/j.issn.1004-4965.2003.z1.003.
参考文献
WuZ W, WangB, LiJ P, et al. 2009. An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO [J]. J. Geophys. Res., 114(D18): D18120. doi:10.1029/2009JD011733.
参考文献
WuZ W, YuL L. 2016. Seasonal prediction of the East Asian summer monsoon with a partial-least square model[J]. Climate Dyn., 46(9-10): 3067-3078. doi:10.1007/s00382-015-2753-4.
参考文献
于乐江, 胡敦欣, 冯俊乔. 2011. 太平洋和印度洋在南海夏季风爆发年代际变化中的作用[J]. 大气科学, 35(6): 1091-1104. Yu Lejiang, Hu Dunxin, Feng Junqiao. 2011. Role of the Pacific and the Indian Ocean in interdecadal variation of the South China Sea summer monsoon onset[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 35(6): 1091-1104. doi:10.3878/j.issn.1006-9895.2011.06.09.
参考文献
张利平, 夏军, 李崇银. 1999. 南海夏季风的年际变化及其对我国长江流域洪水的影响[J]. 自然杂志, 21(3): 167-169, 170. Zhang Liping, Xia Jun, Li Chongyin. 1999. Activity of SCSSM and its influences on flood in Yangtze River Basin[J]. Nature Magazine (in Chinese), 21(3): 167-169, 170. doi:10.3969/j.issn.0253-9608.1999.03.012.
参考文献
张秀芝, 李江龙, 王东晓. 2001. 热带海洋温跃层深度与南海夏季风强度关系探讨[J]. 海洋学报, 23(3): 26-34. Zhang Xiuzhi, Li Jianglong, Wang Dongxiao. 2002. The relationship between the thermocline depth of tropical ocean and the intensity of the South China Sea summer monsoon[J]. Acta Oceanologica Sinica (in Chinese), 23(3): 26-34. doi:10.3321/j.issn:0253-4193.2001.03.004.
参考文献
郑彬, 施能. 2006. 南海夏季风对华南夏季降水年代际变化的影响[J]. 大气科学学报, 29(4): 477-483. Zheng Bin, Shi Neng. 2006. Effects of South China Sea summer monsoon on the interdecadal variability of summer rainfall over South China[J]. Journal of Nanjing Institute of Meteorology (in Chinese), 29(4): 477-483. doi:10.3969/j.issn.1674-7097.2006.04.007.
参考文献
ZhengX G, NakamuraH, RenwickJ A. 2000. Potential predictability of seasonal means based on monthly time series of meteorological variables[J]. J. Climate, 13(14): 2591-2604. doi:10.1175/1520-0442(2000)013<2591:PPOSMB>2.0.CO;2.
参考文献
ZhuZ W, LiT. 2017. Empirical prediction of the onset dates of South China Sea summer monsoon[J]. Climate Dyn., 48(5-6): 1633-1645. doi:10.1007/s00382-016-3164-x.
目录 contents

    摘要

    基于NCEP/NCAR再分析资料,利用信噪比(SNR)方法研究了南海夏季风强度潜在可预报性的年代际变化,结果表明:南海夏季风强度潜在可预报性在20世纪80年代出现了由潜在可预报性偏低位相向偏高位相的年代际转折。进一步的研究发现,南海夏季风强度潜在可预报性和东印度洋—西太平洋(EIOWP)的海表温度(SST)存在明显的正相关。当EIOWP区域SST年际变率较大时,对南海夏季风影响较强,使得南海夏季风的外部信号增强,从而提高了潜在可预报性;当EIOWP区域SST年际变率较小时,对南海夏季风影响较弱,南海夏季风的外部信号进而减弱,潜在可预报性降低。

    Abstract

    Inter-decadal changes in potential predictability of the South China Sea summer monsoon (SCSSM) intensity has been investigated using the signal to noise ratio method and based on the National Centers for Environmental Prediction (NCEP/NCAR) reanalysis data. The potential predictability of the SCSSM intensity underwent a significant decadal change from a low potential predictability to a high potential predictability in the 1980s, followed by a decreasing trend in the early 2000s. Further analysis shows that the inter-decadal change in potential predictability of the SCSSM intensity has a significant positive correlation with sea surface temperature (SST) of the East Indian Ocean and the Western Pacific (EIOWP). The EIOWP area averaged SST with a high (low) phase of its inter-annual variability would have strong (weak) influence on the SCSSM and hence enhance (weaken) the SCSSM signal. As a result, the potential predictability of the SCSSM intensity tends to be high (low).

  • 1 引言

    南海是连接西太平洋、印度洋和海洋性大陆的重要枢纽,也是世界经济发展最重要的地区之一 (丁一汇等,2002)。研究发现南海与东亚冬季风联系密切,冬季强北风经东亚直至南海,南海海温出现异常,异常海温可能从春季持续至夏季进而影响周边地区大气环流和东亚夏季风,南海是东亚冬季风与夏季风之间循环的媒介 (Chen et al.,20002013Liu et al.,2004)。作为东亚季风的先行者,南海季风是连接印度洋、太平洋等地天气气候系统的桥梁 (丁一汇等,2002)。南海夏季风是东亚夏季风系统的重要成员之一,南海夏季风变化对东亚夏季风地区的雨带移动有着重要的指示意义,雨带分布的异常及极端降水带来的旱涝灾害造成了巨大的经济损失和人员伤亡 (张利平等,1999吴尚森等,2003),因此研究南海夏季风是十分有必要的。

    近年来,一些研究指出南海夏季风强度在20世纪70年代末存在明显的年代际转折。 郑彬和施能(2006)发现20世纪70年代南海夏季风强度和华南夏季降水的准两年变化从弱的负相关转为强的正相关; 李霞等(2007)指出南海夏季风强度在20世纪70年代末出现了年代际的转折;此外, Wu et al.(2010)提出南海夏季风在20世纪90年代出现明显的年代际转型,华南和南海地区夏季降水在20世纪90年代中期以后明显增多。

    前人大量研究指出南海夏季风变化主要受到周围海域的影响。 毛江玉等(2000)发现南海—西太平洋增温,海温纬向梯度较大,从而影响南海夏季风的爆发时间; 张秀芝等(2001)指出当冬、春季太平洋160°W以西至东印度洋为正深度距平,这一海域海洋热含量增强,西北太平洋气压较低,有利于南海夏季风增强; 陈永利和胡敦欣(2003)研究表明,南海夏季风爆发时间和前期的西太平洋暖池有一定联系,并且指出沃克环流是连接西太平洋和南海夏季风的桥梁; 冯娟和李建平(2009)研究了春夏季东印度洋—西太平洋和南海夏季风强度,结果表明两者存在显著的负相关; 于乐江等(2011)研究了南海夏季风爆发过程中海洋的作用,结果发现20世纪70年代之前印度洋在调节南海夏季风过程中起主要作用,70年代之后西太平洋起主要作用; 董玉杰等(2016)计算了西太平洋暖池热含量,探究西太平洋暖池对南海夏季风强度的影响,结果表明:当暖池热含量较高(低)时,西太平洋副热带高压较弱(强),印度洋上空沃克环流偏强(弱),南海地区越赤道气流增强(减弱),南海夏季风偏强(弱); Feng and Hu(2017)也指出西太平洋暖池是南海夏季风爆发早晚的重要影响因子。所以造成南海夏季风系统年代际转变的原因可能是西太平洋和印度洋调节的结果。

    然而,大气是一个混沌非线性系统,潜在可预报性是大气的固有属性 (Lorenz,19631965Li and Chou,1997),探究南海夏季风潜在可预报性变化对深入研究南海夏季风至关重要。 黄少妮和黄菲(2013)研究发现当太平洋年代际振荡(PDO)和厄尔尼诺或者拉尼娜事件处于同位相时,南海夏季风爆发日期的潜在可预报性更高; Chen and Lin(2009)对比再分析资料和模式资料探究了南海夏季风强度潜在可预报性,发现模式后报的南海夏季风强度和观测结果相关较高; 邵勰等(2015)利用前期热带纬向三极海表面温度(SST)得出南海夏季风爆发的预报时效可以提前至前一年的秋季; Zhu and Li(2017)分别基于季节预测和延伸期预报角度,采取了两种统计建模方法预测南海夏季风爆发时间。前人对于南海夏季风潜在可预报性的研究主要包括研究南海夏季风爆发时间的潜在可预报性和强度的潜在可预报性,对于南海夏季风爆发日期和强度的潜在可预报性研究主要基于季节或者年际尺度。关于南海夏季风强度潜在可预报性在年代际尺度上变化的研究很少。本文旨在研究南海夏季风强度潜在可预报性的年代际变化,并且探究南海夏季风强度潜在可预报性年代际变化的可能原因。

  • 2 资料与方法

  • 2.1 资料

    本文所用的SST数据来自美国国家海洋大气局(NOAA)提供的逐月海温格点数据,网格分辨率为2°(纬度)×2°(经度) (Smith et al.,2008);高度场和水平风场资料为美国国家环境预报中心和国家大气研究中心(NCEP/NCAR)提供的分辨率为2.5°(纬度)×2.5°(经度)的逐月(日)再分析资料,垂直方向选取850 hPa和500 hPa (Kalnay et al.,1996);所有资料起止时间为1948~2015年,一共68年;本文中南海夏季风特指6~8月。

    南海夏季风强度的定义有多种不同方式,根据不同气象要素定义的南海夏季风强度指数可以反映南海夏季风不同气候特征,本文选取了3个常用的南海夏季风强度指数:反映涡度切变的指数I-W (Wang B et al.,2009),以及西南季风指数I-DXZ (戴念军等,2000)和I-LC (Lu and Chan,1999)衡量南海夏季风强度。

  • 2.2 方法

    信噪比(Signal to Noise Ratio,简称为SNR)方法已被广泛应用于大气潜在可预报性研究 (Trenberth,1985Goswami,2004施洪波等,2008)。气候变量存在年际变率,分为两部分:一部分是信号,主要来自大气的外部强迫如太阳辐射、雪盖、海冰、海表面温度(SST)等,是可以被预报的;另一部分是噪声,主要来自天气扰动以及季节内振荡等,是不可以被预报的 (Trenberth,1984)。年际变率的强度用方差表示,年际方差中有多少可以被表示出即潜在可预报问题,信噪比方法可以衡量潜在可预报性的相对大小,即总方差(信号方差与噪声方差之和)与噪声方差的比值 (Trenberth,1984吴洪宝和吴蕾,2005):

    F=σˆm2σˆN2
    (1)

    其中,F为信噪比,σˆN2σˆm2是年际方差两个相互独立的估计,σˆm2是总的年际变率,是信号方差与噪声方差之和,σˆN2是月内(或季节内)方差,即噪声方差。

    信噪比计算方法主要分为两种:方差分析方法(ANOVA) (Jones,1975Zheng et al.,2000)与低频白噪声延伸法(LFWN) (Madden,2000)。本文将采用ANOVA方法探究南海夏季风潜在可预报性,ANOVA方法计算公式如下 (Trenberth,1984吴洪宝等,2005):

    F=s=1J(x's-x)2/(J-1)s=1Jt=1N(xst-x's)2/NJ(N-1)
    (2)

    其中,xst为已经消去年循环的气候变量的距平,年序号s=1, 2, 3, ..., J,季内日序号t=1, 2, 3, ..., Nx's表示第s年的月(或季)内平均:

    x's=1Nt=1Nxst
    (3)

    xx's的多年平均:

    x=1Js=1Jx's .
    (4)

    在计算两序列的显著性水平时由于序列自身自相关系数的影响,有效自由度会降低。有效自由度T*计算公式如下 (Bretherton et al.,1999Ding et al.,2015 ):

    T*=T1-rxry1+rxry
    (5)

    其中,T为时间序列长度,rxry分别为变量xy滞后一步的自相关系数。在本研究中有效自由度将用于相关系数的显著性检验。

  • 3 南海夏季风强度潜在可预报性的年代际变化特征

    首先,利用ANOVA方法计算了3类季风指数I-DXZ、I-LC和I-W信噪比序列(图1)。由图1可以看出,近70年来,3种季风指数的信噪比均呈现明显的年代际变化。I-DXZ和I-W的信噪比序列在20世纪80年代初经历了由潜在可预报性偏低位相向偏高位相的年代际转折,在2000年以后有明显的下降趋势;表1显示了三类季风指数的信噪比序列两两的相关系数,其中I-DXZ和I-W信噪比序列的相关系数高达0.96,而I-LC信噪比与其他两指数的信噪比序列相关较低。I-LC的信噪比序列虽然有明显的年代际变化,但是年代际转变不明显。 戴念军等(2000)定义南海夏季风强度指数为季风爆发开始到8月底结束,纬向风速大于0时,累加南海区域上各网格点的全风速值,最后经标准化处理后的数值,反映了海陆差异,与东亚夏季风环流密切联系; Wang B et al.(2009)定义南海夏季风强度指数定义为850 hPa(5°N~15°N,110°E~120°E)与(20°N~25°N,110°E~120°E)区域平均纬向风差,反映了南海夏季风增强时的气旋性环流系统,进一步指出南海夏季风与东亚夏季风环流联系密切。 Lu and Chan(1999)定义南海夏季风强度指数为1000 hPa(7.5°N~20°N,107.5°E~120°E)区域平均经向风。I-DXZ和I-W两类指数均侧重南海夏季纬向风,反映南海夏季风环流状况,与东亚夏季风联系密切;而I-LC侧重反映南海夏季经向热力差异。因此I-DXZ和I-W信噪比序列变化一致,I-LC信噪比序列与其他两指数的信噪比序列相关较低,接下来我们主要采用I-DXZ季风指数对南海夏季风强度潜在可预报性做进一步研究。

    图1
                            1948~2015年基于11年滑动窗口(11年滑动平均)南海夏季风强度指数信噪比(SNR)序列。蓝色曲线是I-DXZ信噪比序列,红色曲线是I-W信噪比序列,黑色曲线是I-LC信噪比序列,虚线为I-DXZ信噪比序列多年平均值

    图1 1948~2015年基于11年滑动窗口(11年滑动平均)南海夏季风强度指数信噪比(SNR)序列。蓝色曲线是I-DXZ信噪比序列,红色曲线是I-W信噪比序列,黑色曲线是I-LC信噪比序列,虚线为I-DXZ信噪比序列多年平均值

    Fig. 1 11-year running means of SNRs for the period of 1948-2015 for the three South China Sea summer monsoon (SCSSM) indices: I-DXZ (blue), I-W (red), and I-LC (black). The dashed line is the multi-year mean of SNR of I-DXZ

    表1 南海夏季风强度指数I-DXZI-LCI-W信噪比序列两两相关系数

    Table 1 Correlation coefficients between signal to noise ratios (SNRs) of the three South China Sea summer monsoon (SCSSM) indices: I-DXZ [index defined by Dai et al. (2000)], I-LC [index defined by Lu and Chan (1999)], and I-W [index defined mainly by Wang B (2009)]

    I-DXZ信噪比I-LC信噪比I-W信噪比
    I-DXZ信噪比-0.65*0.96*
    I-LC信噪比--0.6*
    I-W信噪比---

    注:*表示相关系数通过0.1显著性检验。

    为了探究引起南海夏季风强度潜在可预报性年代际变化的原因,首先将南海夏季风信号和噪声分离,图2是南海夏季风信噪比、信号方差和噪声方差的时间序列。从图2可以看出南海夏季风信号在20世纪80年代出现了由南海夏季风信号偏低位相向信号偏高位相的转折,和信噪比变化一致,两者相关系数高达0.95,通过了0.01的显著性检验;南海夏季风噪声和信噪比相关系数只有-0.15,两者关系并不显著,且噪声变化趋势稳定,没有经历明显的年代际转折。

    图2
                            1948~2015年基于11年滑动窗口的南海夏季风强度指数I-DXZ信噪比(黑色曲线)、信号方差(蓝色曲线)、噪声方差(红色曲线)时间序列。图中虚线为I-DXZ信噪比序列多年平均值

    图2 1948~2015年基于11年滑动窗口的南海夏季风强度指数I-DXZ信噪比(黑色曲线)、信号方差(蓝色曲线)、噪声方差(红色曲线)时间序列。图中虚线为I-DXZ信噪比序列多年平均值

    Fig. 2 The 11-year running mean of SNR (black), signal variance (blue), and noise variance (red) of I-DXZ for the period of 1948-2015. The dashed line is the multi-year mean of SNR of I-DXZ

    以上研究结果表明南海夏季风强度的潜在可预报性存在明显的年代际转折,南海夏季风强度潜在可预报性主要是由南海夏季风外部信号决定。然而,引起南海夏季风强度潜在可预报性变化的可能影响机制需要进一步的研究。

  • 4 南海夏季风强度的潜在可预报性和印度洋—太平洋的关系

    前期研究指出印太暖池对南海夏季风的局地影响较强 (冯娟和李建平,2009于乐江等,2011),因此海表面温度可能是影响南海夏季风强度潜在可预报性的主要因子。图3给出了南海夏季风信号方差和不同季节连续3个月的月平均SST的超前滞后相关系数的空间分布,由图3可以看出:在春季MAM(3~5月),东印度洋、西太平洋出现正相关区域,但是并不显著(图3a);东印度洋、西太平洋正相关区域从春夏季AMJ开始显著增强,显著性区域出现在苏门答腊岛西侧(图3b);夏季JJA(6~8月)达到最强,显著正相关区域出现在印度尼西亚海域和西太平洋地区(图3d);秋季JAS时期以后显著正相关区域缩小,出现在菲律宾东部海域(图3e、图3f、图3g);OND(10~12月)时期显著正相关区域消失(图3h)。

    图3
                            南海夏季风强度指数I-DXZ信号方差与不同季节连续3个月的月平均SST超前、滞后相关(滑动窗口为11年,填色区为通过了90%置信度水平):(a)MAM(3~5月);(b)AMJ(4~6月);(c)MJJ(5~7月);(d)JJA(6~8月);(e)JAS(7~9月);(f)ASO(8~10月);(g)SON(9~11月);(h)OND(10~12月)

    图3 南海夏季风强度指数I-DXZ信号方差与不同季节连续3个月的月平均SST超前、滞后相关(滑动窗口为11年,填色区为通过了90%置信度水平):(a)MAM(3~5月);(b)AMJ(4~6月);(c)MJJ(5~7月);(d)JJA(6~8月);(e)JAS(7~9月);(f)ASO(8~10月);(g)SON(9~11月);(h)OND(10~12月)

    Fig. 3 Correlation between the signal variance of I-DXZ and continuous three-month running averaged SST (11-year moving window) for the period 1948-2015: (a) MAM (March to May); (b) AMJ (April to June); (c) MJJ (May to July); (d) JJA (June to August); (e) JAS (July to September); (f) ASO (August to October); (g) SON (September to November); (h) OND (October to December). The colored areas are for values significant at or above the 90% confidence level

    为了进一步确定南海夏季风信号与印度洋—太平洋SST关系,我们选取东印度洋—西太平洋(20°S~20°N,80°E~150°E;EIOWP)区域SST作为海温指数。图4给出了EIOWP区域SST指数和南海夏季风信号方差的超前滞后相关。从图4可以看出,两者相关系数从春季MAM时期开始增加,春夏季AMJ和MJJ时期趋于稳定,随后迅速增加,在夏季JJA时期相关系数达到最大,达到0.748,秋季JAS时期以后相关系数明显减弱。以上结果反映了,海夏季风信号与夏季EIOWP区域SST存在明显正相关,通过了95%的置信度水平。

    图4
                            南海夏季风强度指数指数I-DXZ信号方差和EIOWP区域SST指数的超前、滞后相关(滑动窗口为11年;虚线为通过95%置信度水平),南海夏季风信号方差与JJA季节平均EIOWP区域SST的相关系数为0.748

    图4 南海夏季风强度指数指数I-DXZ信号方差和EIOWP区域SST指数的超前、滞后相关(滑动窗口为11年;虚线为通过95%置信度水平),南海夏季风信号方差与JJA季节平均EIOWP区域SST的相关系数为0.748

    Fig. 4 Correlation coefficient between the signal variance of I-DXZ and SST index area averaged over the East Indian Ocean and the Western Pacific (EIOWP) from MAM to OND on an 11-year moving window. The horizontal line represents the 95% confidence level. The correlation between the signal variance of I-DXZ and the EIOWP area averaged SST index in JJA is 0.748

    5给出了南海夏季风信号方差与JJA季节平均SST以及去除EIOWP区域SST信号(将南海夏季风信号方差与去除EIOWP区域SST海温指数的JJA季节平均SST求偏相关)相关系数的空间分布。图5a可以看出南海夏季风信号方差与东印度洋、西太平洋SST存在显著的正相关,南海夏季风信号方差和澳大利亚东南部海域和南太平洋的SST相关也很显著。从图5b可以发现去除EIOWP区域SST信号后,东印度洋和西太平洋相关区域明显消失,并且整个印度洋和太平洋均没有显著的相关区域,这表明南海夏季风信号和JJA季节平均EIOWP区域SST的关系密切,几乎不受到其他区域SST的影响。

    图5
                            (a)南海夏季风强度指数I-DXZ信号方差与同期SST相关;(b)南海夏季风信号方差(去除EIOWP区域SST信号)与JJA季节平均SST相关(滑动窗口为11年)。填色区为通过了90%置信度水平,蓝色框图为EIOWP区域(20°S~20°N,80°E~150°E)

    图5 (a)南海夏季风强度指数I-DXZ信号方差与同期SST相关;(b)南海夏季风信号方差(去除EIOWP区域SST信号)与JJA季节平均SST相关(滑动窗口为11年)。填色区为通过了90%置信度水平,蓝色框图为EIOWP区域(20°S~20°N,80°E~150°E)

    Fig. 5 Correlation maps of (a) the signal variance of I-DXZ with JJA averaged SST and (b) JJA averaged SST with the EIOWP area averaged SST signal removed on an 11-year moving window for the period 1948-2015. The colored areas are for values significant at or above the 90% confidence level. The blue rectangle indicates the region (20°S-20°N, 80°E-150°E)

    EIOWP区域SST是如何影响南海夏季风强度潜在可预报性?图6给出了JJA时期EIOWP区域SST方差和南海夏季风信号方差。从图6可以看出这两条曲线变化较一致,相关系数为0.73,通过了0.05的显著性检验。在20世纪80年代之前EIOWP区域SST年际变率较小,南海夏季风信号较弱;20世纪80年代以后EIOWP区域SST年际变率明显增大,在1990年中期达到最大,此时南海夏季风信号也达到最强;2000年以后EIOWP区域SST年际变率有下降趋势,南海夏季风信号也有所减弱。

    图6
                            1948~2015年南海夏季风强度指数I-DXZ信号方差(红色曲线)和JJA季节平均EIOWP区域SST方差(蓝色曲线)时间序列(滑动窗口11年),南海夏季风信号方差序列和JJA季节平均EIOWP区域SST方差序列的相关系数为0.73

    图6 1948~2015年南海夏季风强度指数I-DXZ信号方差(红色曲线)和JJA季节平均EIOWP区域SST方差(蓝色曲线)时间序列(滑动窗口11年),南海夏季风信号方差序列和JJA季节平均EIOWP区域SST方差序列的相关系数为0.73

    Fig. 6 Variance of the JJA averaged EIOWP area averaged index (blue line) and the signal variance of I-DXZ (red line) calculated with an 11-year window for the period of 1948-2015. The correlation between the signal variance of I-DXZ and the variance of the EIOWP area averaged SST index in JJA is 0.73

    为了进一步探究EIOWP区域SST的年际变率较大(小)时段,EIOWP区域SST对南海夏季风影响的差异,对南海夏季风弱信号1953~1988年时段和强信号1990~2010年时段南海夏季环流形势进行了比较。图7展示了两时段夏季850 hPa和500 hPa风场高度场回归至同期EIOWP区域SST指数的空间分布。在弱信号时段,850 hPa在南海西部,中南半岛上空存在一个微弱的反气旋,南海东部的菲律宾地区存在高度场正异常,伴随异常反气旋;但是南海上空没有明显的环流变化(图7a);500 hPa上中南半岛上空的反气旋仍然存在并且加强,从孟加拉湾西部到西太平洋上空均呈现高度场正异常,但是南海上空仍没有明显的环流存在(图7b)。在强信号时段,850 hPa南海东北部(20°N,115°E)出现反气旋环流异常,南海地区上空呈现出显著的高度场正异常,热带80°E~150°E区域表现为明显的东风异常(图7c);500 hPa上南海地区上空的反气旋仍然存在,南海地区上空显著的高度场加强,明显强于同一层次的弱信号时段的高度场(图7d),南海地区受到下沉气流控制,不利于南海地区对流系统的发展。结果表明EIOWP区域SST年际变率较大时段,对同期南海夏季风有较强的抑制作用;EIOWP区域SST年际变率较小时段,对同期南海夏季风影响较弱。

    图7
                            南海夏季风(a、b)弱信号时段(1953~1988年)和(c、d)强信号时段(1990~2010年)夏季(a、c)850 hPa和(b、d)500 hPa高度场、风场异常回归至JJA季节平均EIOWP区域平均SST指数,填色区域通过90%置信度水平,风矢量场通过90%置信度水平

    图7 南海夏季风(a、b)弱信号时段(1953~1988年)和(c、d)强信号时段(1990~2010年)夏季(a、c)850 hPa和(b、d)500 hPa高度场、风场异常回归至JJA季节平均EIOWP区域平均SST指数,填色区域通过90%置信度水平,风矢量场通过90%置信度水平

    Fig. 7 Regressions of JJA averaged (a, c) 850-hPa and (b, d) 500-hPa wind and geopotential height anomalies onto the EIOWP area averaged SST index (JJA) for (a, b) the low signal period (1953-1988) and the high signal period (1990-2010) of the SCSSM. The colored areas are for values significant at or above the 90% confidence level. The wind vectors are significant at the 90% confidence level

    以上研究结果表明:当EIOWP区域SST年际变率较大时,SST较强,对南海夏季风影响增强,进而增强了南海夏季风的外部信号,南海夏季风强度潜在可预报性升高;当EIOWP区域SST年际变率较小时,SST较弱,对南海夏季风影响减弱,进而削弱了南海夏季风的外部信号,南海夏季风强度潜在可预报性降低。

  • 5 结论和讨论

    本文利用NCEP/NCAR再分析资料,采用信噪比方法研究了南海夏季风强度潜在可预报性,结果表明:

    (1)南海夏季风强度潜在可预报性经历了明显的年代际转折,20世纪80年代之前南海夏季风强度潜在可预报性较低,80年代以后南海夏季风强度潜在可预报性较高。

    (2)在EIOWP区域SST年际变率较大时段,南海地区上空存在强大的反气旋性环流系统,南海地区受到下沉气流控制,SST对南海夏季风有较强抑制作用;在EIOWP区域SST年际变率较小时段,南海地区环流特征不明显,SST对南海夏季风影响较弱。

    (3)EIOWP区域SST年际变率较大(小),对南海夏季风影响增强(减弱),使得南海夏季风外部信号增强(减弱),南海夏季风强度潜在可预报性升高(降低)。

    近年来,很多学者基于模式模拟和统计方法提升东亚(南海)夏季风预报技巧 (Gadgil et al.,2005Wu et al.,2009Wu and Yu,2016),但是东亚(南海)夏季风预报效果并不理想。本文发现南海夏季风强度潜在可预报性在2000年以后有下降趋势,说明南海夏季风的预报效果降低可能是由自身的潜在可预报性降低造成。此外前人研究表明东亚冬季风在20世纪80年代经历了显著的年代际转折,东亚冬季风在1987年左右经历了由强到弱的年代际转折,并且在2000年以后强度增强 (Wang L et al.,2009Huang et al.,2012Ding et al.,2014), Wang and Chen(2014)进一步指出东亚冬季风在2000年以后增强主要受到乌拉尔山阻塞高压和北极海冰的影响。本研究得出南海夏季风强度潜在可预报性同样在20世纪80年代和2000年以后发生了明显的年代际变化,这与东亚冬季风强度的年代际变化时间吻合 (Chen et al.,20002013)。南海作为东亚冬季风与夏季风之间循环的媒介,南海夏季风强度潜在可预报性可能与东亚冬季风的年代际变化存在着联系,值得进一步探究。

    本文主要采用反映南海夏季风纬向热力差异的季风指数I-DXZ研究南海夏季风强度潜在可预报性 (戴念军等,2000),但是仍然存在其他从各个方面反映南海夏季风变化的环流指数,所以接下来可以尝试采用其他南海季风指数来衡量南海夏季风,进而探究南海夏季风强度潜在可预报性变化特征。此外南海夏季风系统不仅受到热带强迫如印度洋、西太平洋等海域的影响,还可能受到热带地区中东太平洋SST与西太平洋暖池共同作用(梁建茵和吴尚森,2003),全球变暖和PDO的共同作用 (谷德军等,2007)、青藏高原热力强迫 (Wu and Zhang,1998)等影响,因此接下来可以探究其他影响南海夏季风强度潜在可预报性变化的因子。

  • 参考文献(References)

    • 1

      Bretherton C S, Widmann M, Dymnikov V P, et al. 1999. The effective number of spatial degrees of freedom of a time-varying field [J]. J. Climate, 12(7): 1990-2009. doi:10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2.

    • 2

      Chen H, Lin Z H. 2009. The potential predictability of the South China Sea summer monsoon in a dynamical seasonal prediction system[J]. Atmospheric and Oceanic Science Letters, 2(5): 271-276. doi:10.1080/16742834.2009.11446819.

    • 3

      Chen W, Han F G, Huang R H. 2000. The interannual variability of East Asian winter monsoon and its relation to the summer monsoon[J]. Advances in Atmospheric Sciences, 17(1): 48-60. doi:10.1007/s00376-000-0042-5.

    • 4

      Chen W, Feng J, Wu R G. 2013. Roles of ENSO and PDO in the link of the East Asian winter monsoon to the following summer monsoon[J]. J. Climate, 26(2): 622-635. doi:10.1175/JCLI-D-12-00021.1.

    • 5

      陈永利, 胡敦欣. 2003. 南海夏季风爆发与西太平洋暖池区热含量及对流异常[J]. 海洋学报, 25(3): 20-31. Chen Yongli, Hu Dunxin. 2003. The relation between the South China Sea summer monsoon onset and the heat content variations in the tropical western Pacific warm pool region[J]. Acta Oceanologica Sinica (in Chinese), 25(3): 20-31. doi:10.3321/j.issn:0253-4193.2003.03.003.

    • 6

      戴念军, 谢安, 张勇. 2000. 南海夏季风活动的年际和年代际特征[J]. 气候与环境研究, 5(4): 363-374. Dai Nianjun, Xie An, Zhang Yong. 2000. Interannual and interdecadal variations of summer monsoon activities over the South China Sea[J]. Climatic and Environmental Research (in Chinese), 5(4): 363-374. doi:10.3969/j.issn.1006-9585.2000.04.004.

    • 7

      Ding R Q, Li J P, Tseng Y H, et al. 2015. The Victoria mode in the North Pacific linking extratropical sea level pressure variations to ENSO [J]. J. Geophys. Res., 120(1): 27-45. doi:10.1002/2014JD022221.

    • 8

      丁一汇, 李崇银, 柳艳菊, 等. 2002. 南海季风试验研究[J]. 气候与环境研究, 7(2): 202-208. Ding Yihui, Li Chongyin, Liu Yanju,et al. 2002. South China Sea monsoon experiment[J]. Climatic and Environmental Research (in Chinese), 7(2): 202-208. doi:10.3969/j.issn.1006-9585.2002.02.007.

    • 9

      Ding Y H, Liu Y J, Liang S J, et al. 2014. Interdecadal variability of the East Asian winter monsoon and its possible links to global climate change [J]. J. Meteor. Res., 28(5): 693-713. doi:10.1007/s13351-014-4046-y.

    • 10

      董玉杰, 冯俊乔, 胡敦欣. 2016. 西太平洋暖池热含量与南海夏季风强度的关系[J]. 海洋科学, 40(3): 160-166. Dong Yujie, Feng Junqiao, Hu Dunxin. 2016. Relationship between heat content over the western pacific warm pool and intensity of South China Sea summer monsoon[J]. Journal of the Oceanic Sciences (in Chinese), 40(3): 160-166. doi:10.11759/hykx20150206002.

    • 11

      冯娟, 李建平. 2009. 南海夏季风变化及其与全球大气和海温的关系[J]. 大气科学, 33(3): 568-580. Feng Juan, Li Jianping. 2009. Variation of the South China Sea summer monsoon and its association with the global atmosphere circulation and sea surface temperature[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 33(3): 568-580. doi:10.3878/j.issn.1006-9895.2009.03.14.

    • 12

      Feng J Q, Hu D X. 2017. How much does heat content of the western tropical Pacific Ocean modulate the South China Sea summer monsoon onset in the last four decades[J]. J. Geophys. Res., 119(7): 4029-4044. doi:10.1002/2013JC009683.

    • 13

      Gadgil S, Rajeevan M, Nanjundiah R. 2005. Monsoon prediction: Why yet another failure[J]. Current Science, 88(9): 1389-1400.

    • 14

      Goswami B N. 2004. Interdecadal change in potential predictability of the Indian summer monsoon[J]. Geophys. Res. Lett., 31(16): L16208. doi:10.1029/2004GL020337.

    • 15

      谷德军, 纪忠萍, 王东晓, 等. 2007. 不同时间尺度上南海夏季风强度与海洋热力条件的关系[J]. 热带气象学报, 23(1): 14-20. Gu Dejun, Ji Zhongping, Wang Dongxiao,et al. 2007. The relationship between SCS summer monsoon intensity and oceanic thermodynamic variables at different time scale[J]. Journal of Tropical Meteorology (in Chinese), 23(1): 14-20. doi:10.3969/j.issn.1004-4965.2007.01.003.

    • 16

      Huang R H, Chen J L, Wang L, et al. 2012. Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system [J]. Advances in Atmospheric Sciences, 29(5): 910-942. doi:10.1007/s00376-012-2015-x.

    • 17

      黄少妮, 黄菲. 2013. 南海夏季风爆发早晚的海温预报指数[J]. 中国海洋大学学报, 43(10): 8-15. Huang Shaoni, Huang Fei. 2013. Sea surface temperature prediction indices for the South China Sea summer monsoon onset[J]. Periodical of Ocean University of China (in Chinese), 43(10): 8-15.

    • 18

      Jones R H. 1975. Estimating the variance of time averages[J]. J. Appl. Meteor., 14(2): 159-163. doi:10.1175/1520-0450(1975)014<0159:ETVOTA>2.0.CO;2.

    • 19

      Kalnay E, Kanamitsu M, Kistler R, et al. 1996. The NCEP/NCAR 40-Year reanalysis project [J]. Bull. Amer. Meteor. Soc., 77(3): 437-472. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • 20

      Li J P, Chou J F. 1997. Existence of the atmosphere attractor[J]. Science in China Series D: Earth Sciences, 40(2): 215-220. doi:10.1007/BF02878381.

    • 21

      李霞, 梁建茵, 郑琳. 2007. 南海夏季风强度年代际变化基本特征[J]. 应用气象学报, 18(3): 330-339. Li Xia, Liang Jianyin, Zheng Lin. 2007. Interdecadal variabilities of SCS summer monsoon intensity[J]. Journal of Applied Meteorological Science (in Chinese), 18(3): 330-339. doi:10.3969/j.issn.1001-7313.2007.03.009.

    • 22

      梁建茵, 吴尚森. 2003. 太平洋海温异常对南海西南季风建立早晚的影响——数值模拟研究[J]. 海洋学报, 25(1): 28-41. Liang Jianyin, Wu Shangsen. The study on the mechanism of SSTA in the Pacific Ocean affecting the onset of summer monsoon in the South China Sea—numerical experiments[J]. Acta Oceanologica Sinica (in Chinese), 25(1): 28-41. doi:10.3321/j.issn:0253-4193.2003.01.004.

    • 23

      Liu Q Y, Jiang X, Xie S P, et al. 2004. A gap in the Indo-Pacific warm pool over the South China Sea in boreal winter: Seasonal development and interannual variability [J]. J. Geophys. Res., 109(C7): C07012. doi:10.1029/2003JC002179.

    • 24

      Lorenz E N. 1963. Deterministic nonperiodic flow[J]. J. Atmos. Sci., 20(2): 130-148. doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2.

    • 25

      Lorenz E N. 1965. A study of the predictability of a 28-variable atmospheric model[J]. Tellus, 17(3): 321-333. doi:10.1111/j.2153-3490.1965.tb01424.x.

    • 26

      Lu E, Chan J C L. 1999. A unified monsoon index for South China[J]. J. Climate, 12(8): 2375-2385. doi:10.1175/1520-0442(1999)012<2375:AUMIFS>2.0.CO;2.

    • 27

      Madden R A. 2000. Estimates of the natural variability of time-averaged sea-level pressure[J]. Mon. Wea. Rev., 104(7): 942-952. doi:10.1175/1520-0493(1976)104<0942:EOTNVO>2.0.CO;2.

    • 28

      毛江玉, 谢安, 宋焱云, 等. 2000. 海温及其变化对南海夏季风爆发的影响[J]. 气象学报, 58(5): 556-569. Mao Jiangyu, Xie An, Song Yanyun,et al. 2000. Impact of sea surface temperature and itd varions on the onsft of summer monsoon over South China Sea[J]. Acta Meteorologica Sinica (in Chinese), 58(5): 556-569. doi:10.11676/qxxb2000.058.

    • 29

      邵勰, 黄平, 黄荣辉. 2015. 基于海温异常的南海夏季风爆发的可预报性分析[J]. 气象科学, 35(6): 684-690. Shao Xie, Huang Ping, Huang Ronghui. 2015. Predictability analysis on onset of South China Sea summer monsoon based on the sea surface temperature anomaly[J]. Journal of the Meteorological Sciences (in Chinese), 35(6): 684-690. doi:10.3969/2014jms.0053.

    • 30

      施洪波, 周天军, 万慧, 等. 2008. SMIP2试验对亚洲夏季风的模拟能力及其可预报性的分析[J]. 大气科学, 32(1): 36-52. Shi Hongbo, Zhou Tianjun, Wan Hui,et al. 2008. SMIP2 experiment-based analysis on the simulation and potential predictability of Asian summer monsoon[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 32(1): 36-52. doi:10.3878/j.issn.1006-9895.2008.01.04.

    • 31

      Smith T M, Reynolds R W, Peterson T C, et al. 2008. Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880-2006) [J]. J. Climate, 21(10): 2283-2296. doi:10.1175/2007JCLI2100.1.

    • 32

      Trenberth K E. 1984. Some effects of finite sample size and persistence on meteorological statistics. Part II: Potential predictability[J]. Mon. Wea. Rev., 112(12): 2369-2379. doi:10.1175/1520-0493(1984)112<2369:SEOFSS>2.0.CO;2.

    • 33

      Trenberth K E. 1985. Potential predictability of geopotential heights over the Southern Hemisphere[J]. Mon. Wea. Rev., 113(1): 54-64. doi:10.1175/1520-0493(1985)113<0054:PPOGHO>2.0.CO;2.

    • 34

      Wang B, Huang F, Wu Z W, et al. 2009. Multi-scale climate variability of the South China Sea monsoon: A review [J]. Dyn. Atmos. Oceans, 47(1-3): 15-37. doi:10.1016/j.dynatmoce.2008.09.004.

    • 35

      Wang L, Huang R H, Gu L, et al. 2009. Interdecadal variations of the East Asian winter monsoon and their association with quasi-stationary planetary wave activity [J]. J. Climate, 22(18): 4860-4872. doi:10.1175/2009JCLI2973.1.

    • 36

      Wang L, Chen W. 2014. The East Asian winter monsoon: Re-amplification in the mid-2000s[J]. Chinese Science Bulletin, 59(4): 430-436. doi:10.1007/s11434-013-0029-0.

    • 37

      Wu G X, Zhang Y S. 1998. Tibetan Plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea[J]. Mon. Wea. Rev., 126(4): 913-927. doi:10.1175/1520-0493(1998)126<0913:TPFATT>2.0.CO;2.

    • 38

      吴洪宝, 王盘兴, 林开平. 2005. 广西夏季降水量潜在可预报性估计[J]. 应用气象学报, 16(4): 445-452. Wu Hongbao, Wang Panxing, Lin Kaiping. 2005. Estimate of potential predictability of summer precipitation in Guangxi. Journal of Applied Meteorological Science (in Chinese), 16(4): 445-452. doi: 10.11898/1001-7313.20050404.

    • 39

      吴洪宝, 吴蕾. 2005. 气候变率诊断和预测方法 [M]. 北京: 气象出版社, 304-307. Wu Hongbao, Wu Lei. 2005. Methods of Diagnosing and Forecasting Climate Variability (in Chinese) [M]. Beijing: China Meteorogical Press, 304-307.

    • 40

      Wu R G, Wen Z P, Song Y, et al. 2010. An interdecadal change in Southern China summer rainfall around 1992/93 [J]. J. Climate, 23(9): 2389-2403. doi:10.1175/2009JCLI3336.1.

    • 41

      吴尚森, 梁建茵, 李春晖. 2003. 南海夏季风强度与我国汛期降水的关系[J]. 热带气象学报, 19(S1): 25-36. Wu Shangsen, Liang Jianyin, Li Chunhui. 2003. Relationship between the intensity of South China Sea summer monsoon and the precipitation in raining seasons in China[J]. Journal of Tropical Meteorology (in Chinese), 19(S1): 25-36. doi:10.3969/j.issn.1004-4965.2003.z1.003.

    • 42

      Wu Z W, Wang B, Li J P, et al. 2009. An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO [J]. J. Geophys. Res., 114(D18): D18120. doi:10.1029/2009JD011733.

    • 43

      Wu Z W, Yu L L. 2016. Seasonal prediction of the East Asian summer monsoon with a partial-least square model[J]. Climate Dyn., 46(9-10): 3067-3078. doi:10.1007/s00382-015-2753-4.

    • 44

      于乐江, 胡敦欣, 冯俊乔. 2011. 太平洋和印度洋在南海夏季风爆发年代际变化中的作用[J]. 大气科学, 35(6): 1091-1104. Yu Lejiang, Hu Dunxin, Feng Junqiao. 2011. Role of the Pacific and the Indian Ocean in interdecadal variation of the South China Sea summer monsoon onset[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 35(6): 1091-1104. doi:10.3878/j.issn.1006-9895.2011.06.09.

    • 45

      张利平, 夏军, 李崇银. 1999. 南海夏季风的年际变化及其对我国长江流域洪水的影响[J]. 自然杂志, 21(3): 167-169, 170. Zhang Liping, Xia Jun, Li Chongyin. 1999. Activity of SCSSM and its influences on flood in Yangtze River Basin[J]. Nature Magazine (in Chinese), 21(3): 167-169, 170. doi:10.3969/j.issn.0253-9608.1999.03.012.

    • 46

      张秀芝, 李江龙, 王东晓. 2001. 热带海洋温跃层深度与南海夏季风强度关系探讨[J]. 海洋学报, 23(3): 26-34. Zhang Xiuzhi, Li Jianglong, Wang Dongxiao. 2002. The relationship between the thermocline depth of tropical ocean and the intensity of the South China Sea summer monsoon[J]. Acta Oceanologica Sinica (in Chinese), 23(3): 26-34. doi:10.3321/j.issn:0253-4193.2001.03.004.

    • 47

      郑彬, 施能. 2006. 南海夏季风对华南夏季降水年代际变化的影响[J]. 大气科学学报, 29(4): 477-483. Zheng Bin, Shi Neng. 2006. Effects of South China Sea summer monsoon on the interdecadal variability of summer rainfall over South China[J]. Journal of Nanjing Institute of Meteorology (in Chinese), 29(4): 477-483. doi:10.3969/j.issn.1674-7097.2006.04.007.

    • 48

      Zheng X G, Nakamura H, Renwick J A. 2000. Potential predictability of seasonal means based on monthly time series of meteorological variables[J]. J. Climate, 13(14): 2591-2604. doi:10.1175/1520-0442(2000)013<2591:PPOSMB>2.0.CO;2.

    • 49

      Zhu Z W, Li T. 2017. Empirical prediction of the onset dates of South China Sea summer monsoon[J]. Climate Dyn., 48(5-6): 1633-1645. doi:10.1007/s00382-016-3164-x.

李娇

机 构:

1. 南京信息工程大学气象灾害教育部重点实验室,南京 210044

2. 中国科学院大气物理研究所大气科学与地球流体力学数值模拟国家重点实验室,北京 100029

3. 河南省气候中心,郑州 450003

Affiliation:

1. Key Laboratory of Meteorological Disasters of the Ministry of Education and Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing 210044

2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

3. Henan Province Climate Center, Zhengzhou 450003

邮 箱:lijiao0606@126.com

作者简介:李娇,女,1994年出生,硕士,主要从事季风与可预报性研究。E-mail: lijiao0606@126.com

丁瑞强

机 构:

2. 中国科学院大气物理研究所大气科学与地球流体力学数值模拟国家重点实验室,北京 100029

4. 成都信息工程大学高原大气与环境四川省重点实验室,成都 610225

Affiliation:

2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

4. Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225

吴志伟

机 构:复旦大学大气科学研究院,上海 200433

Affiliation:Institute of Atmospheric Sciences, Fudan University, Shanghai 200433

角 色:通讯作者

Role:Corresponding author

邮 箱:zhiweiwu@fudan.edu.com

作者简介:吴志伟,E-mail: zhiweiwu@fudan.edu.com

秦箭煌

机 构:上海交通大学海洋学院,上海 200030

Affiliation:School of Oceanography, Shanghai Jiaotong University, Shanghai 200030

李保生

机 构:上海交通大学海洋学院,上海 200030

Affiliation:School of Oceanography, Shanghai Jiaotong University, Shanghai 200030

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I-DXZ信噪比I-LC信噪比I-W信噪比
I-DXZ信噪比-0.65*0.96*
I-LC信噪比--0.6*
I-W信噪比---
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图1 1948~2015年基于11年滑动窗口(11年滑动平均)南海夏季风强度指数信噪比(SNR)序列。蓝色曲线是I-DXZ信噪比序列,红色曲线是I-W信噪比序列,黑色曲线是I-LC信噪比序列,虚线为I-DXZ信噪比序列多年平均值

Fig. 1 11-year running means of SNRs for the period of 1948-2015 for the three South China Sea summer monsoon (SCSSM) indices: I-DXZ (blue), I-W (red), and I-LC (black). The dashed line is the multi-year mean of SNR of I-DXZ

表1 南海夏季风强度指数I-DXZI-LCI-W信噪比序列两两相关系数

Table 1 Correlation coefficients between signal to noise ratios (SNRs) of the three South China Sea summer monsoon (SCSSM) indices: I-DXZ [index defined by Dai et al. (2000)], I-LC [index defined by Lu and Chan (1999)], and I-W [index defined mainly by Wang B (2009)]

图2 1948~2015年基于11年滑动窗口的南海夏季风强度指数I-DXZ信噪比(黑色曲线)、信号方差(蓝色曲线)、噪声方差(红色曲线)时间序列。图中虚线为I-DXZ信噪比序列多年平均值

Fig. 2 The 11-year running mean of SNR (black), signal variance (blue), and noise variance (red) of I-DXZ for the period of 1948-2015. The dashed line is the multi-year mean of SNR of I-DXZ

图3 南海夏季风强度指数I-DXZ信号方差与不同季节连续3个月的月平均SST超前、滞后相关(滑动窗口为11年,填色区为通过了90%置信度水平):(a)MAM(3~5月);(b)AMJ(4~6月);(c)MJJ(5~7月);(d)JJA(6~8月);(e)JAS(7~9月);(f)ASO(8~10月);(g)SON(9~11月);(h)OND(10~12月)

Fig. 3 Correlation between the signal variance of I-DXZ and continuous three-month running averaged SST (11-year moving window) for the period 1948-2015: (a) MAM (March to May); (b) AMJ (April to June); (c) MJJ (May to July); (d) JJA (June to August); (e) JAS (July to September); (f) ASO (August to October); (g) SON (September to November); (h) OND (October to December). The colored areas are for values significant at or above the 90% confidence level

图4 南海夏季风强度指数指数I-DXZ信号方差和EIOWP区域SST指数的超前、滞后相关(滑动窗口为11年;虚线为通过95%置信度水平),南海夏季风信号方差与JJA季节平均EIOWP区域SST的相关系数为0.748

Fig. 4 Correlation coefficient between the signal variance of I-DXZ and SST index area averaged over the East Indian Ocean and the Western Pacific (EIOWP) from MAM to OND on an 11-year moving window. The horizontal line represents the 95% confidence level. The correlation between the signal variance of I-DXZ and the EIOWP area averaged SST index in JJA is 0.748

图5 (a)南海夏季风强度指数I-DXZ信号方差与同期SST相关;(b)南海夏季风信号方差(去除EIOWP区域SST信号)与JJA季节平均SST相关(滑动窗口为11年)。填色区为通过了90%置信度水平,蓝色框图为EIOWP区域(20°S~20°N,80°E~150°E)

Fig. 5 Correlation maps of (a) the signal variance of I-DXZ with JJA averaged SST and (b) JJA averaged SST with the EIOWP area averaged SST signal removed on an 11-year moving window for the period 1948-2015. The colored areas are for values significant at or above the 90% confidence level. The blue rectangle indicates the region (20°S-20°N, 80°E-150°E)

图6 1948~2015年南海夏季风强度指数I-DXZ信号方差(红色曲线)和JJA季节平均EIOWP区域SST方差(蓝色曲线)时间序列(滑动窗口11年),南海夏季风信号方差序列和JJA季节平均EIOWP区域SST方差序列的相关系数为0.73

Fig. 6 Variance of the JJA averaged EIOWP area averaged index (blue line) and the signal variance of I-DXZ (red line) calculated with an 11-year window for the period of 1948-2015. The correlation between the signal variance of I-DXZ and the variance of the EIOWP area averaged SST index in JJA is 0.73

图7 南海夏季风(a、b)弱信号时段(1953~1988年)和(c、d)强信号时段(1990~2010年)夏季(a、c)850 hPa和(b、d)500 hPa高度场、风场异常回归至JJA季节平均EIOWP区域平均SST指数,填色区域通过90%置信度水平,风矢量场通过90%置信度水平

Fig. 7 Regressions of JJA averaged (a, c) 850-hPa and (b, d) 500-hPa wind and geopotential height anomalies onto the EIOWP area averaged SST index (JJA) for (a, b) the low signal period (1953-1988) and the high signal period (1990-2010) of the SCSSM. The colored areas are for values significant at or above the 90% confidence level. The wind vectors are significant at the 90% confidence level

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  • 参考文献(References)

    • 1

      Bretherton C S, Widmann M, Dymnikov V P, et al. 1999. The effective number of spatial degrees of freedom of a time-varying field [J]. J. Climate, 12(7): 1990-2009. doi:10.1175/1520-0442(1999)012><1990:TENOSD>2.0.CO;2.

    • 2

      Chen H, Lin Z H. 2009. The potential predictability of the South China Sea summer monsoon in a dynamical seasonal prediction system[J]. Atmospheric and Oceanic Science Letters, 2(5): 271-276. doi:10.1080/16742834.2009.11446819.

    • 3

      Chen W, Han F G, Huang R H. 2000. The interannual variability of East Asian winter monsoon and its relation to the summer monsoon[J]. Advances in Atmospheric Sciences, 17(1): 48-60. doi:10.1007/s00376-000-0042-5.

    • 4

      Chen W, Feng J, Wu R G. 2013. Roles of ENSO and PDO in the link of the East Asian winter monsoon to the following summer monsoon[J]. J. Climate, 26(2): 622-635. doi:10.1175/JCLI-D-12-00021.1.

    • 5

      陈永利, 胡敦欣. 2003. 南海夏季风爆发与西太平洋暖池区热含量及对流异常[J]. 海洋学报, 25(3): 20-31. Chen Yongli, Hu Dunxin. 2003. The relation between the South China Sea summer monsoon onset and the heat content variations in the tropical western Pacific warm pool region[J]. Acta Oceanologica Sinica (in Chinese), 25(3): 20-31. doi:10.3321/j.issn:0253-4193.2003.03.003.

    • 6

      戴念军, 谢安, 张勇. 2000. 南海夏季风活动的年际和年代际特征[J]. 气候与环境研究, 5(4): 363-374. Dai Nianjun, Xie An, Zhang Yong. 2000. Interannual and interdecadal variations of summer monsoon activities over the South China Sea[J]. Climatic and Environmental Research (in Chinese), 5(4): 363-374. doi:10.3969/j.issn.1006-9585.2000.04.004.

    • 7

      Ding R Q, Li J P, Tseng Y H, et al. 2015. The Victoria mode in the North Pacific linking extratropical sea level pressure variations to ENSO [J]. J. Geophys. Res., 120(1): 27-45. doi:10.1002/2014JD022221.

    • 8

      丁一汇, 李崇银, 柳艳菊, 等. 2002. 南海季风试验研究[J]. 气候与环境研究, 7(2): 202-208. Ding Yihui, Li Chongyin, Liu Yanju,et al. 2002. South China Sea monsoon experiment[J]. Climatic and Environmental Research (in Chinese), 7(2): 202-208. doi:10.3969/j.issn.1006-9585.2002.02.007.

    • 9

      Ding Y H, Liu Y J, Liang S J, et al. 2014. Interdecadal variability of the East Asian winter monsoon and its possible links to global climate change [J]. J. Meteor. Res., 28(5): 693-713. doi:10.1007/s13351-014-4046-y.

    • 10

      董玉杰, 冯俊乔, 胡敦欣. 2016. 西太平洋暖池热含量与南海夏季风强度的关系[J]. 海洋科学, 40(3): 160-166. Dong Yujie, Feng Junqiao, Hu Dunxin. 2016. Relationship between heat content over the western pacific warm pool and intensity of South China Sea summer monsoon[J]. Journal of the Oceanic Sciences (in Chinese), 40(3): 160-166. doi:10.11759/hykx20150206002.

    • 11

      冯娟, 李建平. 2009. 南海夏季风变化及其与全球大气和海温的关系[J]. 大气科学, 33(3): 568-580. Feng Juan, Li Jianping. 2009. Variation of the South China Sea summer monsoon and its association with the global atmosphere circulation and sea surface temperature[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 33(3): 568-580. doi:10.3878/j.issn.1006-9895.2009.03.14.

    • 12

      Feng J Q, Hu D X. 2017. How much does heat content of the western tropical Pacific Ocean modulate the South China Sea summer monsoon onset in the last four decades[J]. J. Geophys. Res., 119(7): 4029-4044. doi:10.1002/2013JC009683.

    • 13

      Gadgil S, Rajeevan M, Nanjundiah R. 2005. Monsoon prediction: Why yet another failure[J]. Current Science, 88(9): 1389-1400.

    • 14

      Goswami B N. 2004. Interdecadal change in potential predictability of the Indian summer monsoon[J]. Geophys. Res. Lett., 31(16): L16208. doi:10.1029/2004GL020337.

    • 15

      谷德军, 纪忠萍, 王东晓, 等. 2007. 不同时间尺度上南海夏季风强度与海洋热力条件的关系[J]. 热带气象学报, 23(1): 14-20. Gu Dejun, Ji Zhongping, Wang Dongxiao,et al. 2007. The relationship between SCS summer monsoon intensity and oceanic thermodynamic variables at different time scale[J]. Journal of Tropical Meteorology (in Chinese), 23(1): 14-20. doi:10.3969/j.issn.1004-4965.2007.01.003.

    • 16

      Huang R H, Chen J L, Wang L, et al. 2012. Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system [J]. Advances in Atmospheric Sciences, 29(5): 910-942. doi:10.1007/s00376-012-2015-x.

    • 17

      黄少妮, 黄菲. 2013. 南海夏季风爆发早晚的海温预报指数[J]. 中国海洋大学学报, 43(10): 8-15. Huang Shaoni, Huang Fei. 2013. Sea surface temperature prediction indices for the South China Sea summer monsoon onset[J]. Periodical of Ocean University of China (in Chinese), 43(10): 8-15.

    • 18

      Jones R H. 1975. Estimating the variance of time averages[J]. J. Appl. Meteor., 14(2): 159-163. doi:10.1175/1520-0450(1975)014<0159:ETVOTA>2.0.CO;2.

    • 19

      Kalnay E, Kanamitsu M, Kistler R, et al. 1996. The NCEP/NCAR 40-Year reanalysis project [J]. Bull. Amer. Meteor. Soc., 77(3): 437-472. doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • 20

      Li J P, Chou J F. 1997. Existence of the atmosphere attractor[J]. Science in China Series D: Earth Sciences, 40(2): 215-220. doi:10.1007/BF02878381.

    • 21

      李霞, 梁建茵, 郑琳. 2007. 南海夏季风强度年代际变化基本特征[J]. 应用气象学报, 18(3): 330-339. Li Xia, Liang Jianyin, Zheng Lin. 2007. Interdecadal variabilities of SCS summer monsoon intensity[J]. Journal of Applied Meteorological Science (in Chinese), 18(3): 330-339. doi:10.3969/j.issn.1001-7313.2007.03.009.

    • 22

      梁建茵, 吴尚森. 2003. 太平洋海温异常对南海西南季风建立早晚的影响——数值模拟研究[J]. 海洋学报, 25(1): 28-41. Liang Jianyin, Wu Shangsen. The study on the mechanism of SSTA in the Pacific Ocean affecting the onset of summer monsoon in the South China Sea—numerical experiments[J]. Acta Oceanologica Sinica (in Chinese), 25(1): 28-41. doi:10.3321/j.issn:0253-4193.2003.01.004.

    • 23

      Liu Q Y, Jiang X, Xie S P, et al. 2004. A gap in the Indo-Pacific warm pool over the South China Sea in boreal winter: Seasonal development and interannual variability [J]. J. Geophys. Res., 109(C7): C07012. doi:10.1029/2003JC002179.

    • 24

      Lorenz E N. 1963. Deterministic nonperiodic flow[J]. J. Atmos. Sci., 20(2): 130-148. doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2.

    • 25

      Lorenz E N. 1965. A study of the predictability of a 28-variable atmospheric model[J]. Tellus, 17(3): 321-333. doi:10.1111/j.2153-3490.1965.tb01424.x.

    • 26

      Lu E, Chan J C L. 1999. A unified monsoon index for South China[J]. J. Climate, 12(8): 2375-2385. doi:10.1175/1520-0442(1999)012<2375:AUMIFS>2.0.CO;2.

    • 27

      Madden R A. 2000. Estimates of the natural variability of time-averaged sea-level pressure[J]. Mon. Wea. Rev., 104(7): 942-952. doi:10.1175/1520-0493(1976)104<0942:EOTNVO>2.0.CO;2.

    • 28

      毛江玉, 谢安, 宋焱云, 等. 2000. 海温及其变化对南海夏季风爆发的影响[J]. 气象学报, 58(5): 556-569. Mao Jiangyu, Xie An, Song Yanyun,et al. 2000. Impact of sea surface temperature and itd varions on the onsft of summer monsoon over South China Sea[J]. Acta Meteorologica Sinica (in Chinese), 58(5): 556-569. doi:10.11676/qxxb2000.058.

    • 29

      邵勰, 黄平, 黄荣辉. 2015. 基于海温异常的南海夏季风爆发的可预报性分析[J]. 气象科学, 35(6): 684-690. Shao Xie, Huang Ping, Huang Ronghui. 2015. Predictability analysis on onset of South China Sea summer monsoon based on the sea surface temperature anomaly[J]. Journal of the Meteorological Sciences (in Chinese), 35(6): 684-690. doi:10.3969/2014jms.0053.

    • 30

      施洪波, 周天军, 万慧, 等. 2008. SMIP2试验对亚洲夏季风的模拟能力及其可预报性的分析[J]. 大气科学, 32(1): 36-52. Shi Hongbo, Zhou Tianjun, Wan Hui,et al. 2008. SMIP2 experiment-based analysis on the simulation and potential predictability of Asian summer monsoon[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 32(1): 36-52. doi:10.3878/j.issn.1006-9895.2008.01.04.

    • 31

      Smith T M, Reynolds R W, Peterson T C, et al. 2008. Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880-2006) [J]. J. Climate, 21(10): 2283-2296. doi:10.1175/2007JCLI2100.1.

    • 32

      Trenberth K E. 1984. Some effects of finite sample size and persistence on meteorological statistics. Part II: Potential predictability[J]. Mon. Wea. Rev., 112(12): 2369-2379. doi:10.1175/1520-0493(1984)112<2369:SEOFSS>2.0.CO;2.

    • 33

      Trenberth K E. 1985. Potential predictability of geopotential heights over the Southern Hemisphere[J]. Mon. Wea. Rev., 113(1): 54-64. doi:10.1175/1520-0493(1985)113<0054:PPOGHO>2.0.CO;2.

    • 34

      Wang B, Huang F, Wu Z W, et al. 2009. Multi-scale climate variability of the South China Sea monsoon: A review [J]. Dyn. Atmos. Oceans, 47(1-3): 15-37. doi:10.1016/j.dynatmoce.2008.09.004.

    • 35

      Wang L, Huang R H, Gu L, et al. 2009. Interdecadal variations of the East Asian winter monsoon and their association with quasi-stationary planetary wave activity [J]. J. Climate, 22(18): 4860-4872. doi:10.1175/2009JCLI2973.1.

    • 36

      Wang L, Chen W. 2014. The East Asian winter monsoon: Re-amplification in the mid-2000s[J]. Chinese Science Bulletin, 59(4): 430-436. doi:10.1007/s11434-013-0029-0.

    • 37

      Wu G X, Zhang Y S. 1998. Tibetan Plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea[J]. Mon. Wea. Rev., 126(4): 913-927. doi:10.1175/1520-0493(1998)126<0913:TPFATT>2.0.CO;2.

    • 38

      吴洪宝, 王盘兴, 林开平. 2005. 广西夏季降水量潜在可预报性估计[J]. 应用气象学报, 16(4): 445-452. Wu Hongbao, Wang Panxing, Lin Kaiping. 2005. Estimate of potential predictability of summer precipitation in Guangxi. Journal of Applied Meteorological Science (in Chinese), 16(4): 445-452. doi: 10.11898/1001-7313.20050404.

    • 39

      吴洪宝, 吴蕾. 2005. 气候变率诊断和预测方法 [M]. 北京: 气象出版社, 304-307. Wu Hongbao, Wu Lei. 2005. Methods of Diagnosing and Forecasting Climate Variability (in Chinese) [M]. Beijing: China Meteorogical Press, 304-307.

    • 40

      Wu R G, Wen Z P, Song Y, et al. 2010. An interdecadal change in Southern China summer rainfall around 1992/93 [J]. J. Climate, 23(9): 2389-2403. doi:10.1175/2009JCLI3336.1.

    • 41

      吴尚森, 梁建茵, 李春晖. 2003. 南海夏季风强度与我国汛期降水的关系[J]. 热带气象学报, 19(S1): 25-36. Wu Shangsen, Liang Jianyin, Li Chunhui. 2003. Relationship between the intensity of South China Sea summer monsoon and the precipitation in raining seasons in China[J]. Journal of Tropical Meteorology (in Chinese), 19(S1): 25-36. doi:10.3969/j.issn.1004-4965.2003.z1.003.

    • 42

      Wu Z W, Wang B, Li J P, et al. 2009. An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO [J]. J. Geophys. Res., 114(D18): D18120. doi:10.1029/2009JD011733.

    • 43

      Wu Z W, Yu L L. 2016. Seasonal prediction of the East Asian summer monsoon with a partial-least square model[J]. Climate Dyn., 46(9-10): 3067-3078. doi:10.1007/s00382-015-2753-4.

    • 44

      于乐江, 胡敦欣, 冯俊乔. 2011. 太平洋和印度洋在南海夏季风爆发年代际变化中的作用[J]. 大气科学, 35(6): 1091-1104. Yu Lejiang, Hu Dunxin, Feng Junqiao. 2011. Role of the Pacific and the Indian Ocean in interdecadal variation of the South China Sea summer monsoon onset[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 35(6): 1091-1104. doi:10.3878/j.issn.1006-9895.2011.06.09.

    • 45

      张利平, 夏军, 李崇银. 1999. 南海夏季风的年际变化及其对我国长江流域洪水的影响[J]. 自然杂志, 21(3): 167-169, 170. Zhang Liping, Xia Jun, Li Chongyin. 1999. Activity of SCSSM and its influences on flood in Yangtze River Basin[J]. Nature Magazine (in Chinese), 21(3): 167-169, 170. doi:10.3969/j.issn.0253-9608.1999.03.012.

    • 46

      张秀芝, 李江龙, 王东晓. 2001. 热带海洋温跃层深度与南海夏季风强度关系探讨[J]. 海洋学报, 23(3): 26-34. Zhang Xiuzhi, Li Jianglong, Wang Dongxiao. 2002. The relationship between the thermocline depth of tropical ocean and the intensity of the South China Sea summer monsoon[J]. Acta Oceanologica Sinica (in Chinese), 23(3): 26-34. doi:10.3321/j.issn:0253-4193.2001.03.004.

    • 47

      郑彬, 施能. 2006. 南海夏季风对华南夏季降水年代际变化的影响[J]. 大气科学学报, 29(4): 477-483. Zheng Bin, Shi Neng. 2006. Effects of South China Sea summer monsoon on the interdecadal variability of summer rainfall over South China[J]. Journal of Nanjing Institute of Meteorology (in Chinese), 29(4): 477-483. doi:10.3969/j.issn.1674-7097.2006.04.007.

    • 48

      Zheng X G, Nakamura H, Renwick J A. 2000. Potential predictability of seasonal means based on monthly time series of meteorological variables[J]. J. Climate, 13(14): 2591-2604. doi:10.1175/1520-0442(2000)013<2591:PPOSMB>2.0.CO;2

    • 49

      Zhu Z W, Li T. 2017. Empirical prediction of the onset dates of South China Sea summer monsoon[J]. Climate Dyn., 48(5-6): 1633-1645. doi:10.1007/s00382-016-3164-x.

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