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DOI | 10.1007/s00382-018-4369-y |
Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center | |
Liu, Xiangwen1,2; Li, Weijing1,2; Wu, Tongwen1,2; Li, Tim3,4; Gu, Weizong5; Bo, Zongkai5; Yang, Beng6; Zhang, Li1,2; Jie, Weihua1,2 | |
2019-04-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 52页码:3823-3843 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA |
英文摘要 | Using the sub-seasonal to seasonal forecast model of Beijing Climate Center, several key physical parameters are perturbed by the Latin hypercube sampling method to find a better configuration for representation of Madden-Julian oscillation (MJO) in the free-run simulation. We find that although model simulation is especially sensitive to some parameters, there are overall no significant linear relationships between model skill and any one of the parameters, and the optimum performance can be obtained by combined perturbations of multiple parameters. By optimization, MJO's spectrum, intensity, spatial structure and propagation, as well as the mean state and variance, are all improved to some extent, suggesting the correspondence and interrelation of model's performances in simulating different characteristics of MJO. Further, several sets of initialized hindcasts using the optimized parameters are conducted, and their results are compared with the hindcasts using only improved initial conditions. We show that with an optimized model, the forecast of MJO beyond 3-week lead time is not improved, and the maximum useful skill is only slightly increased, implying that a decrease of model error does not always translate into an increase of forecast skill at all lead time. However, the skill is obviously enhanced during lead times of 2-3weeks for forecasts in most seasons and initial phases except for a few cases. Particularly, the deficiency in forecasting MJO's propagation from the Indian Ocean to the Pacific is relieved, further highlighting the positive contribution of reducing model error compared to previous work that only reduced initial condition error. In this study, we also show benefits of multi-scheme ensemble strategy in describing uncertainties of model error and initial condition error and thus improving MJO forecast. |
英文关键词 | Parameter optimization MJO simulation MJO forecast skill Improvement |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000467187600004 |
WOS关键词 | MADDEN-JULIAN OSCILLATION ; ASIAN SUMMER MONSOON ; INTRASEASONAL VARIABILITY ; CONVECTIVE PARAMETERIZATION ; CUMULUS CONVECTION ; MARITIME CONTINENT ; VERTICAL STRUCTURE ; PHYSICAL PROCESSES ; SENSITIVITY ; IMPACTS |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/181874 |
专题 | 气候变化 |
作者单位 | 1.China Meteorol Adm, Natl Climate Ctr, Climate Model Div, 46 Zhongguancun Nandajie, Beijing 100081, Peoples R China; 2.China Meteorol Adm, CMA NJU Joint Lab Climate Predict Studies, 46 Zhongguancun Nandajie, Beijing 100081, Peoples R China; 3.Univ Hawaii Manoa, Int Pacific Res Ctr, Honolulu, HI 96822 USA; 4.Univ Hawaii Manoa, Dept Meteorol, Honolulu, HI 96822 USA; 5.Shandong Meteorol Bur, Jinan, Shandong, Peoples R China; 6.Nanjing Univ, Nanjing, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Xiangwen,Li, Weijing,Wu, Tongwen,et al. Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center[J]. CLIMATE DYNAMICS,2019,52:3823-3843. |
APA | Liu, Xiangwen.,Li, Weijing.,Wu, Tongwen.,Li, Tim.,Gu, Weizong.,...&Jie, Weihua.(2019).Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center.CLIMATE DYNAMICS,52,3823-3843. |
MLA | Liu, Xiangwen,et al."Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center".CLIMATE DYNAMICS 52(2019):3823-3843. |
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