基于CORA资料的中国海海表面温度季节和年际变化特征分析
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摘要
基于1986—2008年的中国近海及邻近海域再分析产品(CORA),采用经验正交函数分解方法(EOF)分析了海表面温度(SST)的季节及年际变化特征,并用相应的SODA、AVHRR以及Levitus资料对CORA做了对比评估。相比于AVHRR而言,CORA资料SST的偏差和均方根误差均小于SO-DA,相比Levitus资料而言CORA资料温度盐度的均方根误差随深度的变化皆小于SODA。CORA与SODA资料相比,两者前3个模态的时空分布大体一致,区别在于CORA资料能更好地反映参量的一些细微特征。结果表明,CORA资料能很好的刻画中国近海SST的季节、年际变化特征,尤其是黑潮流经区域SST的局地变化特征。季节EOF第二模态显示的是SST对由风引起的潜热释放的响应特征。第三模态刻画了冬夏转换季的分布特征,主要揭示了东北-西南走向的锋面特征。SST年际变化与ENSO密切相关,区域平均的南海SSTA与Nino指数的吻合程度CORA优于SODA。
The sea surface temperature(SST) of China Ocean Reanalysis(CORA) from 1986 to 2008 is validated using Simple Ocean Data Assimilation(SODA),Levitus and Advanced Very High Resolution Radiometer(AVHRR) dataset.Comparing with AVHRR,the bias and root mean square error(RMSE) of CORA are less than that of SODA.Comparing with Levitus,the RMSE of COAR is also less than that of SODA.The results of Empirical Orthogonal Function(EOF) analysis show that the first three modes of CORA have similar temporal and spatial variations with those of SODA dataset,and the main differences are that CORA can represent more subtle features than SODA.The seasonal and interannual variability of SST in the coastal China seas can be well presented by CORA data.The second mode of EOF reveals the SST response to wind-induced latent heat.The third mode presents the northeast-southwestern distribution of SST front,which is coincident to the transitionally seasonal characters between summer and winter.The interannual variability of SST is closely related to ENSO.The regional average of SSTA of CORA in the South China Sea has more coincident correlation to Nino indexes than that of SODA.
The sea surface temperature(SST) of China Ocean Reanalysis(CORA) from 1986 to 2008 is validated using Simple Ocean Data Assimilation(SODA),Levitus and Advanced Very High Resolution Radiometer(AVHRR) dataset.Comparing with AVHRR,the bias and root mean square error(RMSE) of CORA are less than that of SODA.Comparing with Levitus,the RMSE of COAR is also less than that of SODA.The results of Empirical Orthogonal Function(EOF) analysis show that the first three modes of CORA have similar temporal and spatial variations with those of SODA dataset,and the main differences are that CORA can represent more subtle features than SODA.The seasonal and interannual variability of SST in the coastal China seas can be well presented by CORA data.The second mode of EOF reveals the SST response to wind-induced latent heat.The third mode presents the northeast-southwestern distribution of SST front,which is coincident to the transitionally seasonal characters between summer and winter.The interannual variability of SST is closely related to ENSO.The regional average of SSTA of CORA in the South China Sea has more coincident correlation to Nino indexes than that of SODA.
引文
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[24]王东晓,周发琇,李永平.南海表层水温和海面热收支的年循环特征[J].海洋学报,1997,19(3):33—44.
[25]Han G J,Li W,Zhang X F,et al.A regional ocean reanalysis system for coastal waters of China and adjacent seas[J].Advances in AtmosphericSciences,2011,28(3):682—690.
[26]Chu P C,Wang G H.Identification of the South China Sea subtropical front using hydrographic data[J].Journal of Oceanography,2003,59(1):65—78.
[2]毛汉礼.南黄海和东海北部夏季水文特征及海水类型的初步分析[J].海洋学集刊,1964,1:23—37.
[3]任允武,孙国栋,毛汉礼.南黄海和东海北部冬季水文特征及海水类型的初步分析[J].海洋学集刊,1964,1:78—125.
[4]汤明义,刘宇中,李洪海.渤黄及东海北部平均表面水温场季节变化特征及其成因的初步分析[J].海洋学报,1989,11(5):544—553.
[5]吴德星,李强,林霄沛,等.1990—1999渤海SSTA年际变化的特征[J].中国海洋大学学报,2005,35:173—176.
[6]Chu P C,Haeger S D,Carron M J.A parameter model for the Yellow Sea thermal variability[J].1997,102(C5):10499—10507.
[7]翁学传,张启龙.渤、黄、东海水温日变化特征[J].海洋科学,1993,6:49—54.
[8]阎俊岳,李江龙.东海及临近地区百年来的温度变化[J].海洋学报,1997,19(6):121—126.
[9]Park W S.Interannual and inter-decadal variations of sea surface temperature in the East Asian marginal seas[J].Progress in Oceanography,2000,47:191—204.
[10]于非,许一.东海SST长期变化趋势研究[J].海洋科学进展,2003,21(4):477—481.
[11]周发琇,于慎余.南海表层水温的低频振荡[J].海洋学报.1991,13(3):333—338.
[12]王卫强,王东晓,齐义泉.南海表层水温年际变化的大尺度特征[J].海洋学报,2000,22(4):8—16.
[13]王东晓,秦曾灏,周发琇.南海年际尺度海气相互作用的初探[J].气象学报,1997,55(1):33—42.
[14]Xie S P,Xie Q,Wang D X.Summer upwelling in the South China Sea and its role in regional climate variations[J].Journal of Geophysical Re-search,2003,108(c8):3261.
[15]王桂华,黄韦艮,王辉.利用HOAPS资料研究南海海气界面热通量时空分布[J].海洋学报,2006,28:1—8.
[16]Wang C,Wang W Q,Wang D X,et al.Interannual variability of the South China Sea associated with El Nino[J].J Geophys Res,2006,111:21—39.
[17]Zhang L P,Wu L X,Lin X P,et al.Modes and mechanisms of sea surface temperature low-frequency variations over the coastal China seas[J].J Geophys Res,2010,115:13—25.
[18]Tomoaki O,Song Y,Kitoh A.Sea surface temperature in the South China Sea An index for the Asian monsoon and ENSO system[J].Journal ofthe Meteorological Society of Japan,1997,75:1091—1107.
[19]Wang Y G,Fang G H,Wei Z X,et al.Chen H.Y..Interannual variation of the South China Sea circulation and its relation to El Nino,as seenfrom a variable grid global ocean model[J].J Geophys Res,2006,111:1—19.
[20]Xie S P,Xie Q,Wang D X,et al.Summer upwelling in the South China Sea and its role in regional climate variations[J].J Geophys Res,2003,56:45—76.
[21]陈锦年,伍玉梅,何宜军.中国近海海气界面热通量的反演[J].海洋学报,2006,28:26—35.
[22]孙龙,于华明,王朋,等.东中国海及毗邻海域海面风场季节及年际变化特征分析[J].海洋预报,2010,27:30—37.
[23]曾丽丽,施平,王东晓.南海蒸发和净淡水通量的季节和年际变化[J].地球物理学报,2009,52:929—938.
[24]王东晓,周发琇,李永平.南海表层水温和海面热收支的年循环特征[J].海洋学报,1997,19(3):33—44.
[25]Han G J,Li W,Zhang X F,et al.A regional ocean reanalysis system for coastal waters of China and adjacent seas[J].Advances in AtmosphericSciences,2011,28(3):682—690.
[26]Chu P C,Wang G H.Identification of the South China Sea subtropical front using hydrographic data[J].Journal of Oceanography,2003,59(1):65—78.