引用本文:	孟佳佳,杨宇星,王法明.GFDL模式对太平洋海表面温度的年际和年代际变率的模拟评估[J].海洋科学,2016,40(4):140-148.

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GFDL模式对太平洋海表面温度的年际和年代际变率的模拟评估
孟佳佳^1,2,3,4, 杨宇星^1,3,4, 王法明^1,3,4
1.中国科学院海洋研究所;2.中国科学院大学;3.中国科学院海洋环流与波动重点实验室;4.青岛海洋科学与技术国家实验室海洋动力过程与气候功能实验室

摘要:

为评估美国地球物理流体动力学实验室(Geophysical Fluid Dynamics Laboratory, GFDL)模式CM3、ESM2M 和ESM2G对太平洋海表面温度的年际和年代际变率的模拟能力, 本文利用GFDL 历史试验模拟结果和美国海洋大气局(National Oceanic and Atmospheric Administration, NOAA)提供的扩展重建的海表温度(Extended Reconstructed Sea Surface Temperature, ERSST)资料, 比较模式模拟和观测的厄尔尼诺-南方涛动(El Ni?o-Southern Oscillation, ENSO)和太平洋年代际振荡(Pacific Decadal Oscillation, PDO)的时空分布、周期及可预报性等。结果表明: 三个模式均可以较好地模拟太平洋主要年际信号ENSO 和年代际信号PDO, ESM2G 对ENSO 的模拟最好, CM3 对PDO的模拟与观测更为接近。研究结果为进一步利用模式探讨ENSO 和PDO的物理机制提供可能的参考。

关键词: GFDL(Geophysical Fluid Dynamics Laboratory)模式 ENSO(El Niño-Southern Oscillation) PDO(Pacific Decadal Oscillation) 可预报性

DOI：10.11759/hykx20150211001

分类号:

基金项目:中国科学院战略性先导科技专项(XDA11010102)国家自然科学基金委员会创新研究群体科学基金(41421005); 国家自然科学基金委员会与山东省联合基金(U1406401)

Evaluation of interannual and decadal variations of Pacific SST simulated by GFDL models

MENG Jia-jia,YANG Yu-xing,WANG Fa-ming

Abstract:

In this paper, we evaluated the ability of the Geophysical Fluid Dynamic Laboratory (GFDL) models CM3, ESM2M, and ESM2G to simulate the interannual and decadal variations of Pacific sea surface temperature (SST) by comparing the temporal and spatial distributions, periods, and predictions of observed and simulated El Ni?o-Southern Oscillations (ENSOs) and Pacific Decadal Oscillations (PDOs), based on the output of historical experiments using GFDL models and extended reconstructed sea surface temperature (ERSST) data from the National Oceanic and Atmospheric Administration (NOAA). In general, the models captured well the interannual signals of the ENSO and the decadal signals of the PDO. ENSO is correctly simulated by ESM2G, while the PDO simulations by CM3 closely resemble those of observations. These results may be referenced in future studies of the physical mechanisms of the ENSO and PDO.

Key words: GFDL (Geophysical Fluid Dynamics Laboratory) models ENSO (El Niño-Southern Oscillation) PDO (Pacific Decadal Oscillation) predictability