浪致混合对2016年北太平洋海表温度季节性预测的影响

赵一丁; 尹训强; 宋亚娟; 乔方利

doi:10.3969/j.issn.0253-4193.2019.03.006

浪致混合对2016年北太平洋海表温度季节性预测的影响

doi: 10.3969/j.issn.0253-4193.2019.03.006

1.
中国海洋大学海洋与大气科学学院, 山东青岛 266100;自然资源部第一海洋研究所, 山东青岛 266061
2.
自然资源部第一海洋研究所, 山东青岛 266061;青岛海洋科学与技术试点国家实验室区域海洋动力学与数值模拟功能实验室, 山东青岛 266071;自然资源部海洋环境科学和数值模拟重点实验室, 山东青岛 266061

基金项目: 国家重点研发计划（2016YFC1401407）；青岛海洋科学与技术国家实验室重大科研专项（2016ASKJ16）；中国科学技术部资助中-澳海洋工程研究中心国际合作项目（2016YFE0101400）；海洋公益性行业科研专项（201505013）；全球变化和海气相互作用专项（GASI-IPOVAI-05，GASI-IPOVAI-06）

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出版历程
- 收稿日期: 2018-02-14
- 修回日期: 2018-05-07

Effect of wave-induced mixing on sea surface temperature seasonal prediction in the North Pacific in 2016

1.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China;First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
2.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266071, China;Key Lab of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China

摘要

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。
- 季节性预测 /
- 北太平洋 /
- 海表温度 /
- 浪致混合 /
- 气候模式
Abstract: 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.
- seasonal prediction /
- North Pacific /
- SST /
- wave-induced mixing /
- climate model

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