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ENSO Forecast: Initial Accuracy VS Model Uncertainties
Time:2023-09-13Keywords: Source of article:Pageviews:96

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ENSO Forecast: Initial Accuracy VS Model Uncertainties

 

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09:30-11:00 AM, September 22, 2023 (Friday)

 

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To improve the current ENSO forecast level, the “initial value” is still one of the major problems to be solved. Therefore, the main purpose of applying data assimilation in ENSO forecast is to provide an accurate and dynamically coordinated initial field for ENSO forecast model. Zheng Fei et al proposed a new method of ocean-atmosphere coupled data assimilation, which is one of the first ENSO forecast methods to be applied in practice internationally. This method breaks through the traditional understanding of initial error’s influence on El Nino forecast, by making full use of the high correlation between wind field and ocean current in the tropical Pacific. It significantly improves the accuracy of ocean flow field of coupled model by assimilating atmospheric wind stress observation, thus significantly improving the ENSO forecast level of climate model.

 

Model error is another key factor that limits and affects the accuracy of ENSO forecast. It is a great challenge to control the influence of model error and improve the forecast accuracy. To make up for the forecast deviation caused by stochastic process, Zheng Fei et al. developed a set of ensemble forecast methods for systematically analyzing, estimating and modeling the quantitative effects of stochastic process and used them in ENSO forecast. The results show that reasonable consideration of the influence and function of the whole effect of stochastic process can effectively make up for the forecast deviation caused by the stochastic process and extend the forecast timeliness of ENSO model, so as to improve the accuracy of ENSO model.

 

Guest Profile

Zhen Fei, a second-level researcher of the Institute of Atmospheric Physics, Chinese Academy of Sciences, and a leading scientific and technological innovation talent under the states “Major Talent Plan”, mainly involved in the research of ocean-atmosphere interaction, climate forecast and data assimilation. At present, he serves as an editorial board member of the SCI journals “Adv.Atmos.Sci.” and “J. Mar.Sci.Eng.”, a standing editorial member of Chinas core journal “Atmospheric Science”, and a member of the overall expert group of “Major Natural Disaster Prevention and Control and Public Security”, a national key R&D project of “14th Five-Year Plan”. He has published nearly 130 academic papers in core journals at home and abroad, including more than 60 SCI papers, won many awards, such as the “One Hundred Excellent Doctoral Dissertation”, the first prize of Meteorological Science and Technology Progress Achievement and “Zhao Jiuzhang” Outstanding Young and Middle-aged Science Award, and named to several national talent programs and the World’s 1,000 Most Influential Scientists in climate change research (Reuters 2021). 



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