浪致混合对2016年北太平洋海表温度季节性预测的影响
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摘要
上层海洋通过海气交换影响大气-海洋耦合系统,海浪引起的垂向混合影响上层海洋结构,从而在气候预测过程中发挥着重要的作用。本文基于国家海洋局第一海洋研究所地球系统模式(FIO-ESM),以2016年为例,分别开展了耦合和关闭海浪模式情况下的短期气候预测实验,分析浪致混合对北太平洋海表温度(SST)季节性预测的影响。通过对模式预测的SST异常(SSTA)进行定量评估发现,浪致混合能够显著降低北太平洋高纬度海区预测误差,在(45°N,150°E)附近海区SSTA改善可达1℃,气候模式能够更好地预测SSTA的经向分布特征,特别是能够准确地反映25°～45°N海区SSTA分布特征。通过分析有浪和无浪两个实验的热收支贡献发现,垂向混合是导致上层海洋温度差异的主导影响因子。海浪通过改变垂向混合,使2016年北太平洋SST在高纬度海区大幅降低,在低纬度海区略有升高,最终提升了模式对北太平洋SST的季节性预测能力。
The vertical mixing induced by waves affects the structure of the upper ocean, which dominates the atmosphere-ocean coupling system through air-sea exchanges. Hence waves have an important effect on climate prediction. Based on the First Institute of Oceanography Earth System Model(FIO-ESM), a group of prediction experiments are conducted. One of the experiments is coupled with the wave model and the other is not. The prediction results in 2016 are applied to study the effects of wave-induced mixing on the seasonal prediction of the North Pacific sea surface temperature(SST). Considering the wave-induced mixing, the prediction error is significantly reduced at high latitudes of the North Pacific. The predicted sea surface temperature anomaly(SSTA) can be improved by 1℃ near(45°N, 150°E). The climate model well predicts the meridional distribution of SSTA, especially the distribution characteristics during 25°-45°N. Then, the heat budgets of the two experiments are analyzed to find the reason for this improvement. The result indicates that the vertical mixing is the main influencing factor. The wave-induced mixing causes SST to reduce substantially at high latitudes and to increase slightly at low latitudes in 2016, which plays a key role in SST seasonal prediction in the North Pacific.
The vertical mixing induced by waves affects the structure of the upper ocean, which dominates the atmosphere-ocean coupling system through air-sea exchanges. Hence waves have an important effect on climate prediction. Based on the First Institute of Oceanography Earth System Model(FIO-ESM), a group of prediction experiments are conducted. One of the experiments is coupled with the wave model and the other is not. The prediction results in 2016 are applied to study the effects of wave-induced mixing on the seasonal prediction of the North Pacific sea surface temperature(SST). Considering the wave-induced mixing, the prediction error is significantly reduced at high latitudes of the North Pacific. The predicted sea surface temperature anomaly(SSTA) can be improved by 1℃ near(45°N, 150°E). The climate model well predicts the meridional distribution of SSTA, especially the distribution characteristics during 25°-45°N. Then, the heat budgets of the two experiments are analyzed to find the reason for this improvement. The result indicates that the vertical mixing is the main influencing factor. The wave-induced mixing causes SST to reduce substantially at high latitudes and to increase slightly at low latitudes in 2016, which plays a key role in SST seasonal prediction in the North Pacific.
引文
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[27] Song Zhenya, Shu Qi, Bao Ying, et al. The prediction on the 2015/16 El Niňo event from the perspective of FIO-ESM[J]. Acta Oceanologica Sinica, 2015, 34(12): 67-71.
[28] Reynolds R W, Smith T M, Liu Chunying, et al. Daily high-resolution-blended analyses for sea surface temperature[J]. Journal of Climate, 2007, 20(22): 5473-5496.
[29] Huang Boyin, Xue Yan, Zhang Dongxiao, et al. The NCEP GODAS ocean analysis of the tropical Pacific mixed layer heat budget on seasonal to interannual time scales[J]. Journal of Climate, 2010, 23(18): 4901-4925.
[2] Mantua N J, Hare S R, Zhang Yuan, et al. A Pacific interdecadal climate oscillation with impacts on salmon production[J]. Bulletin of the American Meteorological Society, 1997, 78(6): 1069-1079.
[3] Overland J E, Alheit J, Bakun A, et al. Climate controls on marine ecosystems and fish populations[J]. Journal of Marine Systems, 2010, 79(3/4): 305-315.
[4] Lau K M, Lee J Y, Kim K M, et al. The North Pacific as a regulator of summertime climate over Eurasia and North America[J]. Journal of Climate, 2004, 17(4): 819-833.
[5] Hu Zengzhen, Huang Bohua. Interferential impact of ENSO and PDO on dry and wet conditions in the U.S. Great Plains[J]. Journal of Climate, 2009, 22(22): 6047-6065.
[6] Beattie J C, Elsberry R L. Western North Pacific monsoon depression formation[J]. Weather and Forecasting, 2012, 27(6): 1413-1432.
[7] Goddard L. Climate Predictions, Seasonal-to-Decadal[M]//Rasch P J. Climate Change Modeling Methodology. New York: Springer, 2012: 261-301.
[8] Li Jianping, Ding Ruiqiang. Temporal-spatial distribution of the predictability limit of monthly sea surface temperature in the global oceans[J]. International Journal of Climatology, 2013, 33(8): 1936-1947.
[9] Lienert F. Simulation and prediction of North Pacific Sea surface temperature[D]. Victoria: University of Victoria, 2011.
[10] Wen Caihong, Xue Yan, Kumar A. Seasonal prediction of North Pacific SSTs and PDO in the NCEP CFS hindcasts[J]. Journal of Climate, 2012, 25(17): 5689-5710.
[11] Hu Zengzhen, Kumar A, Huang Bohua, et al. Prediction skill of North Pacific variability in NCEP climate forecast system version 2: impact of ENSO and beyond[J]. Journal of Climate, 2014, 27(11): 4263-4272.
[12] Hasselmann K. Ocean circulation and climate change[J]. Tellus A: Dynamic Meteorology and Oceanography, 1991, 43(4): 82-103.
[13] Qiao Fangli, Yuan Yeli, Yang Yongzeng, et al. Wave-induced mixing in the upper ocean: distribution and application to a global ocean circulation model[J]. Geophysical Research Letters, 2004, 31(11): L11303.
[14] Qiao Fangli, Yuan Yeli, Ezer T, et al. A three-dimensional surface wave-ocean circulation coupled model and its initial testing[J]. Ocean Dynamics, 2010, 60(5): 1339-1355.
[15] Huang Chuanjiang, Qiao Fangli, Song Zhenya, et al. Improving simulations of the upper ocean by inclusion of surface waves in the Mellor-Yamada turbulence scheme[J]. Journal of Geophysical Research: Oceans, 2011, 116(C1): C01007.
[16] Huang Chuanjiang, Qiao Fangli, Shu Qi, et al. Evaluating austral summer mixed-layer response to surface wave-induced mixing in the Southern Ocean[J]. Journal of Geophysical Research: Oceans, 2012, 117(C11): C00J18.
[17] Zhao Xiao, Li Jianping, Zhang Wenjun. Summer persistence barrier of sea surface temperature anomalies in the central western north pacific[J]. Advances in Atmospheric Sciences, 2012, 29(6): 1159-1173.
[18] 宋振亚, 乔方利, 雷晓燕, 等. 大气-海浪-海洋环流耦合数值模式的建立及北太平洋SST模拟[J]. 水动力学研究与进展, 2007, 22(5): 543-548. Song Zhenya, Qiao Fangli, Lei Xiaoyan, et al. The establishment of an atmosphere-wave-ocean circulation coupled numerical model and its application in the North Pacific SST simulation[J]. Journal of Hydrodynamics, 2007, 22(5): 543-548.
[19] Zhao Y D, Yin X Q, Song Y J, et al. Seasonal prediction skills of FIO-ESM for the North Pacific SST and precipitation[J]. Acta Oceanologica Sinica, 2019, 38(1): 1-8.
[20] 袁业立, 乔方利, 华锋, 等. 近海环流数值模式的建立, 部分1: 海波的搅拌和波-流相互作用[J]. 水动力学研究与进展: A辑, 1999, 14(4B): 1-8. Yuan Yili, Qiao Fangli, Hua Feng, et al. The development of a coastal circulation numerical model: 1. Wave-induced mixing and wave-current interaction[J]. Chinese Journal of Hydrodynamics: Series A, 1999, 14(4B): 1-8.
[21] Collins W D, Rasch P J, Boville B A, et al. The formulation and atmospheric simulation of the community atmosphere model version 3 (CAM3)[J]. Journal of Climate, 2006, 19(11): 2144-2161.
[22] Smith R D, Gent P, Briegleb B, et al. The parallel ocean program (POP) reference manual[R]. Los Alamos: Los Alamos National Laboratory, 2010.
[23] 杨永增, 乔方利, 赵伟, 等. 球坐标系下MASNUM海浪数值模式的建立及其应用[J]. 海洋学报, 2005, 27(2): 1-7. Yang Yongzeng, Qiao Fangli, Zhao Wei, et al. MASNUM ocean wave numerical model in spherical coordinates and its application[J]. Haiyang Xuebao, 2005, 27(2): 1-7.
[24] Hunke E C, Lipscomb W H. CICE: the Los Alamos Sea Ice Model, Documentation and Software User's Manual Version 4.0[M]. Los Alamos: Los Alamos National Laboratory, 2008.
[25] Dickinson R E, Oleson K W, Bonan G, et al. The community land model and its climate statistics as a component of the community climate system model[J]. Journal of Climate, 2006, 19(11): 2302-2324.
[26] Qiao Fangli, Song Zhenya, Bao Ying, et al. Development and evaluation of an Earth System Model with surface gravity waves[J]. Journal of Geophysical Research: Oceans, 2013, 118(9): 4514-4524.
[27] Song Zhenya, Shu Qi, Bao Ying, et al. The prediction on the 2015/16 El Niňo event from the perspective of FIO-ESM[J]. Acta Oceanologica Sinica, 2015, 34(12): 67-71.
[28] Reynolds R W, Smith T M, Liu Chunying, et al. Daily high-resolution-blended analyses for sea surface temperature[J]. Journal of Climate, 2007, 20(22): 5473-5496.
[29] Huang Boyin, Xue Yan, Zhang Dongxiao, et al. The NCEP GODAS ocean analysis of the tropical Pacific mixed layer heat budget on seasonal to interannual time scales[J]. Journal of Climate, 2010, 23(18): 4901-4925.