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Study of atmospheric predictability Based on Periphery Theory

Meteorological and Environmental Research 2015年第3期6卷 1-4页

作者： Niu Jinqi Cao Hongxing Niu Baoshan Wu Yongping Shangshui Meteorological Station in Henan Province Chinese Academy of Meteorological Sciences College of Physical Sciences and Technology Yangzhou University

The system periphery （＂jieke＂ in Chinese） is defined as a part of the system and is adjacent to its environment. The periphery is an in- termediary agent between the system and its environment, and has two functions： defending system itself and exchanging with the environment. Generally, the periphery is defined on space dimension. We will investigate the periphery from the time dimension, and study a time jieke based on set theory viewpoint; initial values and forecast lead in weather forecast are clarified. Further predictability of weather forecast on the basis of periph- ery theory is defined; its calculation formulae are given, with which computing for day-to-day forecast were carded out. The results have been com- pared with present researches of atmospheric predictability, and it shows advancing the predictability study. Most interesting is that atmospheric pre- dictability possesses rule of gold ratio 0.618, and it is found firstly in research of weather and climate predictability.

关键词： Periphery (jieke) Time periphery atmospheric predictability Gold ratio China

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The importance of data assimilation components for initial conditions and subsequent error growth

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Science China Earth Sciences 2024年第1期67卷 105-116页

作者： Zhongrui WANG Haohao SUN Lili LEI Zhe-Min TAN Yi ZHANG Key Laboratory of Mesoscale Severe Weather Ministry of Educationand School of Atmospheric SciencesNanjing UniversityNanjing 210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjing 210023China

Despite a specific data assimilation method,data assimilation(DA)in general can be decomposed into components of the prior information,observation forward operator that is given by the observation type,observation error covariances,and background error *** a classic Lorenz model,the influences of the DA components on the initial conditions(ICs)and subsequent forecasts are systematically investigated,which could provide a theoretical basis for the design of DA for different scales of *** forecast errors undergo three typical stages:a slow growth stage from 0 h to 5 d,a fast growth stage from 5 d to around 15 d with significantly different error growth rates for ensemble and deterministic forecasts,and a saturation stage after 15 *** strategies that provide more accurate ICs can improve the *** assimilation is superior to offline assimilation,and a flow-dependent background error covariance matrix(Pf)provides better analyses than a static background error covariance matrix(B)for instantaneous observations and frequent time-averaged observations;but the opposite is true for infrequent time-averaged observations,since cycling simulation cannot construct informative priors when the model lacks predictive skills and the flow-dependent Pf cannot effectively extract information from low-informative observations as the static *** observations contain more information than time-averaged observations,thus the former is preferred,especially for infrequent observing ***,ensemble forecasts have advantages over deterministic forecasts,and the advantages are enlarged with less informative observations and lower predictive-skill model priors.

关键词： Data assimilation atmospheric predictability Background error covariances Ensemble forecasts

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Nonlinear Local Lyapunov Exponent and Quantification of Local predictability

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Chinese Physics Letters 2008年第5期25卷 1919-1922页

作者：丁瑞强李建平 HA Kyung-Ja State Key Laboratory of Numerical Modeling for atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 Division of Earth Environmental ~System Pusan National University Busan 609- 735 Korea

Nonlinear local Lyapunov exponent （NLLE） is applied to quantitatively determine the local predictability limit of chaotic systems. As an example, we find that the local predictability limit of Henon attractor varies considerably with time, and some underlying phase-spatial structure does not appear. The local predictability limit of initially adjacent points in phase space may be completely different. This will cause difficulties in making the long-time analogue forecast.

关键词： atmospheric predictability

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