Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation
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  • 英文篇名:Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation
  • 作者:Yiding ; Zhao ; Xunqiang ; Yin ; Yajuan ; Song ; Fangli ; Qiao
  • 英文作者:Yiding Zhao;Xunqiang Yin;Yajuan Song;Fangli Qiao;College of Oceanic and Atmospheric Sciences, Ocean University of China;First Institute of Oceanography, Ministry of Natural Resources;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao);Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources;
  • 英文关键词:seasonal prediction;;North Pacific;;sea surface temperature;;precipitation;;FIO-ESM climate model
  • 中文刊名:SEAE
  • 英文刊名:海洋学报(英文版)
  • 机构:College of Oceanic and Atmospheric Sciences, Ocean University of China;First Institute of Oceanography, Ministry of Natural Resources;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao);Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources;
  • 出版日期:2019-01-15
  • 出版单位:Acta Oceanologica Sinica
  • 年:2019
  • 期:v.38
  • 基金:The National Natural Science Foundation of China(NSFC)-Shandong Joint Fund for Marine Science Research Centers under contract No.U1606405;; the National Programme on Global Change and Air-Sea Interaction under contract Nos GASIIPOVAI-05 and GASI-IPOVAI-06;; the International Cooperation Project on the China-Australia Research Centre for Maritime Engineering of Ministry of Science and Technology,China under contract No.2016YFE0101400;; the Qingdao National Laboratory for Marine Science and Technology through the AoShan Talents Program under contract No.2015ASTP;; the Transparency Program of Pacific Ocean-South China Sea-Indian Ocean under contract No.2015ASKJ01;; the Scientific and Technological Innovation Project of Qingdao National Laboratory for Marine Science and Technology under contract No.2016ASKJ16;; the Public Science and Technology Research Funds Projects of Ocean under contract No.201505013;; the China-Korea Cooperation Project on the Trend of North-West Pacific Climate Change
  • 语种:英文;
  • 页:SEAE201901003
  • 页数:8
  • CN:01
  • ISSN:11-2056/P
  • 分类号:9-16
摘要
The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.
        The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.
引文
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