Roles of initial ocean surface and subsurface states on successfully predicting 2006–2007 El Niño with an intermediate coupled model
Roles of initial ocean surface and subsurface states on successfully predicting 2006–2007 El Niño with an intermediate coupled model
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DOI：
10.5194/os-11-187-2015
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发表时间：
2015-02
期刊：
影响因子：
3.2
通讯作者：
F. Zheng;Jiang Zhu
中科院分区：
文献类型：
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作者：
F. Zheng;Jiang Zhu
抽象的。2006-2007年的厄尔尼诺事件是一个异常微弱的事件，大多数模型只是在东太平洋开始变暖之后才预测到的。在这项研究中，厄尔尼诺预测系统的基础上，预测2006-2007年厄尔尼诺事件的初始海洋表面和次表层状态的作用进行了研究，以确定预测厄尔尼诺增长的有利条件，并隔离在三组后报实验。通过仅同化海表面温度（SST）观测值以优化初始表面条件，仅同化海平面（SL）数据以更新初始次表面状态，或同时同化SST和SL数据来初始化后报。结果表明，三种不同初始状态的后报都能成功地提前1年预报2006-2007年厄尔尼诺事件，其中以SST和SL初始的后报预报效果最好。各组后报结果之间的比较进一步表明，成功的预测是更显着的影响，由初始地下状态比由初始表面条件。准确的初始地表状态可以触发对2006-2007年厄尔尼诺事件的较容易的预测，而更合理的初始次表层状态可以有助于改善对暖事件发展的预测。
Abstract. The 2006–2007 El Nino event, an unusually weak event, was predicted by most models only after the warming in the eastern Pacific had commenced. In this study, on the basis of an El Nino prediction system, roles of the initial ocean surface and subsurface states on predicting the 2006–2007 El Nino event are investigated to determine conditions favorable for predicting El Nino growth and are isolated in three sets of hindcast experiments. The hindcast is initialized through assimilation of only the sea surface temperature (SST) observations to optimize the initial surface condition, only the sea level (SL) data to update the initial subsurface state, or both the SST and SL data. Results highlight that the hindcasts with three different initial states can all successfully predict the 2006–2007 El Nino event 1 year in advance and that the hindcast initialized by both the SST and SL data performs best. A comparison between the various sets of hindcast results further demonstrates that successful prediction is more significantly affected by the initial subsurface state than by the initial surface condition. The accurate initial surface state can trigger the easier prediction of the 2006–2007 El Nino, whereas a more reasonable initial subsurface state can contribute to improving the prediction in the growth of the warm event.