Advanced Search
Impact Factor: 5.8

Volume 23 Issue 4

Jul.  2006

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2006 >  23(4): 615-624

Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model

  • 1.

    International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, Maryland, USA,International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029


doi: 10.1007/s00376-006-0615-z

  • A simple method for initializing intermediate coupled models (ICMs) using only sea surface temperature (SST) anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984–2003 and the period 1997–2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.
  • [1] Chuan GAO, Xinrong WU, Rong-Hua ZHANG, 2016: Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 875-888.  doi: 10.1007/s00376-016-5249-1
    [2] Bin MU, Juhui REN, Shijin YUAN, Rong-Hua ZHANG, Lei CHEN, Chuan GAO, 2019: The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1381-1392.  doi: 10.1007/s00376-019-9040-y
    [3] Chuan GAO, Rong-Hua ZHANG, Xinrong WU, Jichang SUN, 2018: Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 410-422.  doi: 10.1007/s00376-017-7109-z
    [4] Daquan ZHANG, Lijuan CHEN, Gill M. MARTIN, Zongjian KE, 2023: Seasonal Prediction Skill and Biases in GloSea5 Relating to the East Asia Winter Monsoon, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 2013-2028.  doi: 10.1007/s00376-023-2258-8
    [5] Fei ZHENG, Jin-Yi YU, 2017: Contrasting the Skills and Biases of Deterministic Predictions for the Two Types of El Niño, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1395-1403.  doi: 10.1007/s00376-017-6324-y
    [6] ZHENG Fei, ZHU Jiang, WANG Hui, Rong-Hua ZHANG, 2009: Ensemble Hindcasts of ENSO Events over the Past 120 Years Using a Large Number of Ensembles, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 359-372.  doi: 10.1007/s00376-009-0359-7
    [7] KANG Xianbiao, HUANG Ronghui, WANG Zhanggui, ZHANG Rong-Hua, 2014: Sensitivity of ENSO Variability to Pacific Freshwater Flux Adjustment in the Community Earth System Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1009-1021.  doi: 10.1007/s00376-014-3232-2
    [8] Se-Hwan YANG, LI Chaofan, and LU Riyu, 2014: Predictability of Winter Rainfall in South China as Demonstrated by the Coupled Models of ENSEMBLES, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 779-786.  doi: 10.1007/s00376-013-3172-2
    [9] Yawen DUAN, Peili WU, Xiaolong CHEN, Zhuguo MA, 2018: Assessing Global Warming Induced Changes in Summer Rainfall Variability over Eastern China Using the Latest Hadley Centre Climate Model HadGEM3-GC2, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1077-1093.  doi: 10.1007/s00376-018-7264-x
    [10] DING Yihui, LIU Yiming, SHI Xueli, LI Qingquan, LI Qiaoping, LIU Yan, 2006: Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons inChina byUsing a Nested Regional ClimateModel (RegCM NCC) Part II: The Experimental Seasonal Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 487-503.  doi: 10.1007/s00376-006-0323-8
    [11] WANG Zhiren, WU Dexing, CHEN Xue'en, QIAO Ran, 2013: ENSO Indices and Analyses, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1491-1506.  doi: 10.1007/s00376-012-2238-x
    [12] Xinyi XING, Xianghui FANG, Da PANG, Chaopeng JI, 2024: Seasonal Variation of the Sea Surface Temperature Growth Rate of ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 465-477.  doi: 10.1007/s00376-023-3005-x
    [13] Zhou Tianjun, Yu Rucong, Li Zhaoxin, 2002: ENSO-Dependent and ENSO-Independent Variability over the Mid-Latitude North Pacific: Observation and Air-Sea Coupled Model Simulation, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 1127-1147.  doi: 10.1007/s00376-002-0070-4
    [14] LI Gang*, LI Chongyin, TAN Yanke, and BAI Tao, 2014: The Interdecadal Changes of South Pacific Sea Surface Temperature in the Mid-1990s and Their Connections with ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 66-84.  doi: 10.1007/s00376-013-2280-3
    [15] Xiaofei WU, Jiangyu MAO, 2019: Decadal Changes in Interannual Dependence of the Bay of Bengal Summer Monsoon Onset on ENSO Modulated by the Pacific Decadal Oscillation, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1404-1416.  doi: 10.1007/s00376-019-9043-8
    [16] Yuanhai FU, Zhongda LIN, Tao WANG, 2021: Simulated Relationship between Wintertime ENSO and East Asian Summer Rainfall: From CMIP3 to CMIP6, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 221-236.  doi: 10.1007/s00376-020-0147-y
    [17] Yadi LI, Xichen LI, Juan FENG, Yi ZHOU, Wenzhu WANG, Yurong HOU, 2024: Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 115-140.  doi: 10.1007/s00376-023-3047-0
    [18] Jingrui YAN, Wenjun ZHANG, Suqiong HU, Feng JIANG, 2024: Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies, ADVANCES IN ATMOSPHERIC SCIENCES.  doi: 10.1007/s00376-023-3196-1
    [19] Junchen YAO, Xiangwen LIU, Tongwen WU, Jinghui YAN, Qiaoping LI, Weihua JIE, 2023: Progress of MJO Prediction at CMA from Phase I to Phase II of the Sub-Seasonal to Seasonal Prediction Project, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1799-1815.  doi: 10.1007/s00376-023-2351-z
    [20] Yu NIE, Jie WU, Jinqing ZUO, Hong-Li REN, Adam A. SCAIFE, Nick DUNSTONE, Steven C. HARDIMAN, 2023: Subseasonal Prediction of Early-summer Northeast Asian Cut-off Lows by BCC-CSM2-HR and GloSea5, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 2127-2134.  doi: 10.1007/s00376-022-2197-9
PDF

Get Citation+

shu
Export:  

Share Article

Article Metrics

Article Views: 1625 Times

PDF downloads: 1091 Times

Cited by: Times
  • 加载中

    • Manuscript History

    Manuscript received: 10 July 2006
    Manuscript revised: 10 July 2006
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model

    • 1. International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, Maryland, USA,International Center for Climate and Environment Science (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
    • Manuscript received: 2006-07-10
    • Manuscript revised: 2006-07-10

    Abstract: A simple method for initializing intermediate coupled models (ICMs) using only sea surface temperature (SST) anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984–2003 and the period 1997–2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.

      HTML

    Catalog

      Publish with AAS

      Contact us

      Links

      Copyright © 2018-2028 ADVANCES IN ATMOSPHERIC SCIENCES 京ICP备14024088号-7

      Supported by: Beijing Renhe Information Technology Co. Ltd  support: info@rhhz.net  

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return