doi:  10.3878/j.issn.1006-9895.1808.18149
近期气候预测系统IAP-DecPreS对印度洋偶极子的回报技巧: 全场同化和异常场同化的比较

Predictive skill of the near-term climate prediction system IAP-DecPreS for the Indian Ocean dipole: A comparison of full-field and anomaly initializations
摘要点击 210  全文点击 30  投稿时间:2018-04-12  修订日期:2018-07-14
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基金:  国家自然科学基金 41675089, 41775091, 公益性行业(气象) 科研专项 GYHY201506012
中文关键词:  气候预测  印度洋偶极子  全场同化  异常场同化
英文关键词:  Climate prediction, Indian Ocean dipole mode, Anomaly initialization, Full-field initialization
        
作者中文名作者英文名单位
胡帅hushuai中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室LASG
吴波wubo中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室LASG
周天军zhoutianjun中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室LASG
引用:胡帅,吴波,周天军.2019.近期气候预测系统IAP-DecPreS对印度洋偶极子的回报技巧: 全场同化和异常场同化的比较[J].大气科学
Citation:hushuai,wubo,zhoutianjun.2019.Predictive skill of the near-term climate prediction system IAP-DecPreS for the Indian Ocean dipole: A comparison of full-field and anomaly initializations[J].Chinese Journal of Atmospheric Sciences (in Chinese)
中文摘要:
      印度洋偶极子(IOD)是热带印度洋年际变率主导模态之一,对于区域乃至全球气候有重要影响。准确预报IOD对于短期气候预测具有重要意义。中国科学院大气物理研究所最近建立了近期气候预测系统IAP-DecPreS,其初始化方案采用“集合最优插值-分析增量更新”(EnOI-IAU)方案,能够同化观测的海洋次表层温度廓线资料。本文分析了IAP-DecPreS季节回报试验对IOD的回报技巧,重点比较了全场同化和异常场同化两种初始化策略下预测系统对IOD的回报技巧。分析表明,8月起报秋季IOD,无论从确定性预报还是概率性预报的角度,基于全场同化的回报试验技巧均高于异常场同化的回报试验。对于5月起报的秋季IOD,基于两种初始化策略的回报试验技巧相当。研究发现,全场同化策略相对于异常场的优势主要源于它提高了对伴随ENSO发生的IOD的预报技巧。ENSO遥强迫触发的热带东印度洋风-蒸发-SST正反馈过程是IOD发展和维持的关键。采用全场同化策略的回报结果能够更好地模拟出IOD发展过程中ENSO遥强迫产生的异常降水场和异常风场的空间分布特征;而采用异常场同化策略,模拟的异常降水场和风场偏差较大。导致两种初始化策略预测结果技巧差异的主要原因是,全场同化能够减小模式对热带印度洋气候平均态降水固有的模拟偏差,从而提升了热带印度洋对ENSO遥强迫响应的模拟能力。而异常场同化由于在同化过程中保持了模式固有的气候平均态,因此模拟的热带印度洋对ENSO强迫的响应存在与模式自由积分类似的模拟偏差。
Abstract:
      Indian Ocean dipole (IOD) is one of the dominant interannual variability modes of sea surface temperature (SST) in the tropical Indian Ocean, which has striking impacts on regional and global climate. It is very meaningful to predict the IOD skillfully for short-term climate predictions. Recently, a near-term climate prediction system named as IAP-DecPreS was constructed by the Institute of Atmospheric Physics (IAP), based on a newly developed initialization scheme (EnOI-IAU). The EnOI-IAU scheme can assimilate observed ocean temperature profile records.In this paper, we compare the differences in skill of the IAP-DecPreS for the IOD in fall (September-November) between two distinct initialization approaches-anomaly and full-field initializations. It is found that, for predictions started from August, the hindcast runs based on the full-field initialization have higher skill for both deterministic and probabilistic predictions, compared to those based on the anomaly initialization. For predictions started from May, the predictive skill of the hindcasts based on the two initialization approaches are similar. Compared with the anomaly initialization, the superiority of the full-field initialization is that it improves the predictive skill for the IOD events occurring together with ENSO. The wind-evaporation-SST positive feedback over the tropical eastern Indian Ocean excited by the ENSO remote forcing is the key for the development and maintenance of the IOD. The hindcasts based on the full-field initialization can reproduce the spatial distributions of precipitation and wind anomalies associated with the ENSO during the IOD developing stage. In contrast, for the hindcasts based on the anomaly initialization, the biases of precipitation and wind anomalies are much larger. The full-field initialization can reduce the initial errors of the climatological precipitation over the tropical Indian Ocean, thus improved the accuracies in simulating the response of precipitation and wind anomalies over the tropical Indian Ocean to the ENSO remote forcing. However, the anomaly initialization nearly does not change the model inherent climatology, so the ENSO-related precipitation and wind anomalies over the tropical Indian Ocean simulated by the anomaly hindicates show similar biases with the model historical runs.
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