气候模式中海洋数据同化对热带降水偏差的影响

陈辉; 尹训强; 宋振亚; 宋亚娟; 鲍颖; 乔方利

气候模式中海洋数据同化对热带降水偏差的影响

国家海洋局第一海洋研究所, 山东青岛 266061;海洋环境科学与数值模拟国家海洋局重点实验室, 山东青岛 266061

基金项目: 国家自然科学基金委员会-山东省人民政府联合资助海洋科学研究中心项目(U1406404);中央级公益性科研院所基本科研业务费专项资金资助项目(2012G24);海洋公益性行业科研专项(201505013).

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出版历程
- 收稿日期: 2014-05-26
- 修回日期: 2015-03-20

The impacts of ocean data assimilation on tropical precipitation bias in a climate model

First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Key Lab of Marine Science and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China

摘要

摘要: 本文采用海洋卫星观测海表温度(SST)和海面高度异常(SLA)数据,对国家海洋局第一海洋研究所地球系统模式FIO-ESM(First Institute of Oceanography Earth System Model version 1.0)中海洋模式分量进行了集合调整卡尔曼滤波(EAKF)同化,对比分析了大气环流、湿度和云量对海洋数据同化的响应,探讨了海洋同化对热带降水模拟偏差的影响.结果表明:海洋数据同化能有效改善海表温度和上层海洋热含量的模拟,30°S~30°N纬度带内年平均SST的绝均差降低60%.同化后大气模式模拟的赤道两侧信风得到明显改善,上升气流在赤道以北热带地区增强而在赤道以南热带地区减弱,热带降水模拟的动力结构更为合理,水汽和云量分布也更切合实际.热带年平均降水的空间分布和强度在同化后均得到改善,赤道以南的纬向年平均降水峰值显著降低,降水偏差明显减小,同化后30°S~30°N纬度带内年平均降水绝均差降低35%.
- 气候模式 /
- 海洋数据同化 /
- 集合调整卡尔曼滤波 /
- 降水
Abstract: Using the Ensemble Adjustment Kalman Filter (EAKF),two kinds of oceanic satellite observations,namely sea surface temperature (SST) and sea level anomaly (SLA),had been assimilated into the ocean model component of the FIO-ESM (First Institute of Oceanography Earth System Model version 1.0). We analyzed the differences of the atmospheric circulation,specific humidity,cloud fraction,and precipitation in tropical between the assimilation and no assimilation experiment,to investigate the impacts of ocean data assimilation on tropical precipitation simulation in a climate model. The results showed that ocean data assimilation can effectively improve the sea surface temperature and ocean heat content in the upper layer of the ocean,the absolute mean error of annual mean SST in the area of 30°S~30°N were reduced by 60%. Sea level pressure and atmospheric circulation such as lower winds had been significantly improved. The atmospheric vertical motion turns to be more reasonable,which provide reliable dynamic conditions for precipitation simulation. Improvements of SST and atmospheric circulation would further influence the spatial distribution of the specific humidity and cloud fraction,giving more reasonable moisture conditions for precipitation simulation. Finally,the spatial distribution and intensity of zonal mean were significantly improved,the peak value of precipitation in the south of the equator were obviously reduced,and the absolute mean error of annual mean precipitation in the oceanic area of 30°S~30°N were reduced by 35%.
- climate model /
- data assimilation /
- EAKF /
- precipitation

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