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An initial perturbation Method for the Multiscale Singular Vector in Global Ensemble Prediction

Advances in Atmospheric Sciences 2024年第3期41卷 545-563页

作者： Xin LIU Jing CHEN Yongzhu LIU Zhenhua HUO Zhizhen XU Fajing CHEN Jing WANG Yanan MA Yumeng HAN School of Atmospheric Sciences Nanjing University of Information Science&TechnologyNanjing 210044China Chinese Academy of Meteorological Sciences Beijing 100081China CMA Earth System Modeling and Prediction Centre(CEMC) Beijing 100081China Key Laboratory of Earth System Modeling and Prediction of China Meteorological Administration Beijing 100081China Tianjin Meteorological Observatory Tianjin 300074China China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory Hebei 071799China

Ensemble prediction is widely used to represent the uncertainty of single deterministic Numerical Weather Prediction(NWP) caused by errors in initial conditions(ICs). The traditional Singular Vector(SV) initial perturbation method tends only to capture synoptic scale initial uncertainty rather than mesoscale uncertainty in global ensemble prediction. To address this issue, a multiscale SV initial perturbation method based on the China Meteorological Administration Global Ensemble Prediction System(CMA-GEPS) is proposed to quantify multiscale initial uncertainty. The multiscale SV initial perturbation approach entails calculating multiscale SVs at different resolutions with multiple linearized physical processes to capture fast-growing perturbations from mesoscale to synoptic scale in target areas and combining these SVs by using a Gaussian sampling method with amplitude coefficients to generate initial perturbations. Following that, the energy norm,energy spectrum, and structure of multiscale SVs and their impact on GEPS are analyzed based on a batch experiment in different seasons. The results show that the multiscale SV initial perturbations can possess more energy and capture more mesoscale uncertainties than the traditional single-SV method. Meanwhile, multiscale SV initial perturbations can reflect the strongest dynamical instability in target areas. Their performances in global ensemble prediction when compared to single-scale SVs are shown to(i) improve the relationship between the ensemble spread and the root-mean-square error and(ii) provide a better probability forecast skill for atmospheric circulation during the late forecast period and for short-to medium-range precipitation. This study provides scientific evidence and application foundations for the design and development of a multiscale SV initial perturbation method for the GEPS.

关键词： multiscale uncertainty singular vector initial perturbation global ensemble prediction system

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Study on ETKF-Based initial perturbation Scheme for GRAPES Global Ensemble Prediction

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Acta meteorologica Sinica 2009年第5期23卷 562-574页

作者：马旭林薛纪善陆维松 Key Laboratory of Meteorological Disasters of Ministry of Education NUIST Chinese Academy of Meteorological Sciences

initial perturbation scheme is one of the important problems for ensemble prediction. In this paper, ensemble initial perturbation scheme for Global/Regional Assimilation and PrEdiction System （GRAPES） global ensemble prediction is developed in terms of the ensemble transform Kalman filter （ETKF） method. A new GRAPES global ensemble prediction system （GEPS） is also constructed. The spherical simplex 14-member ensemble prediction experiments, using the simulated observation network and error characteristics of simulated observations and innovation-based inflation, are carried out for about two months. The structure characters and perturbation amplitudes of the ETKF initial perturbations and the perturbation growth characters are analyzed, and their qualities and abilities for the ensemble initial perturbations are given. The preliminary experimental results indicate that the ETKF-based GRAPES ensemble initial perturbations could identify main normal structures of analysis error variance and reflect the perturbation amplitudes. The initial perturbations and the spread are reasonable. The initial perturbation variance, which is approximately equal to the forecast error variance, is found to respond to changes in the observational spatial variations with simulated observational network density. The perturbations generated through the simplex method are also shown to exhibit a very high degree of consistency between initial analysis and short-range forecast perturbations. The appropriate growth and spread of ensemble perturbations can be maintained up to 96-h lead time. The statistical results for 52-day ensemble forecasts show that the forecast scores of ensemble average for the Northern Hemisphere are higher than that of the control forecast. Provided that using more ensemble members, a real-time observational network and a more appropriate inflation factor, better effects of the ETKF-based initial scheme should be shown.

关键词： GRAPES ensemble transform Kalman filter (ETKF) initial perturbation ensemble prediction

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Effects of the initial perturbations on the Rayleigh–Taylor–Kelvin–Helmholtz instability system

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Frontiers of physics 2022年第3期17卷 77-89页

作者：陈峰许爱国张玉东甘延标刘冰冰王爽 School of Aeronautics Shan Dong Jiaotong UniversityJinan 250357China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsP.O.Box 8009-26Beijing 100088China HEDPS Center for Applied Physics and Technologyand College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Mechanics and Safety Engineering Zhengzhou UniversityZhengzhou 450001China Hebei Key Laboratory of Trans-Media Aerial Underwater Vehicle North China Institute of Aerospace EngineeringLangfang 065000China Naval Architecture and Port Engineering College Shan Dong Jiaotong UniversityWeihai 264200China School of Science Shandong Jianzhu UniversityJinan 250101China

The effects of initial perturbations on the Rayleigh–Taylor instability (RTI), Kelvin–Helmholtz instability (KHI), and the coupled Rayleigh–Taylor–Kelvin–Helmholtz instability (RTKHI) systems are investigated using a multiple-relaxation-time discrete Boltzmann model. Six different perturbation interfaces are designed to study the effects of the initial perturbations on the instability systems. It is found that the initial perturbation has a significant influence on the evolution of RTI. The sharper the interface, the faster the growth of bubble or spike. While the influence of initial interface shape on KHI evolution can be ignored. Based on the mean heat flux strength D3,1, the effects of initial interfaces on the coupled RTKHI are examined in detail. The research is focused on two aspects: (i) the main mechanism in the early stage of the RTKHI, (ii) the transition point from KHI-like to RTI-like for the case where the KHI dominates at earlier time and the RTI dominates at later time. It is found that the early main mechanism is related to the shape of the initial interface, which is represented by both the bilateral contact angle θ_(1) and the middle contact angle θ_(2). The increase of θ_(1) and the decrease of θ_(2) have opposite effects on the critical velocity. When θ_(2) remains roughly unchanged at 90 degrees, if θ_(1) is greater than 90 degrees (such as the parabolic interface), the critical shear velocity increases with the increase of θ_(1), and the ellipse perturbation is its limiting case;If θ_(1) is less than 90 degrees (such as the inverted parabolic and the inverted ellipse disturbances), the critical shear velocities are basically the same, which is less than that of the sinusoidal and sawtooth disturbances. The influence of inverted parabolic and inverted ellipse perturbations on the transition point of the RTKHI system is greater than that of other interfaces: (i) For the same amplitude, the smaller the contact angle θ_(1), the later the transitio

关键词： discrete Boltzmann method hydrodynamic instability non-equilibrium characteristic initial perturbation

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Using the Lund-Potsdam-Jena Model to Understand the Different Responses of Three Woody Plants to Land Use in China

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Advances in Atmospheric Sciences 2013年第2期30卷 515-524页

作者： SUN Guodong MU Mu State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 Key Laboratory of Ocean Circulation and Wave Institute of Oceanology Chinese Academy of Sciences Qingdao 266071

In this study, the approach of conditional nonlinear optimal perturbation related to initial perturbation （CNOP-I） was employed to investigate the maximum variations in plant amount for three main woody plants （a temperate broadleaved evergreen, a temperate broadleaved summergreen, and a boreal needleleaved evergreen） in China. The investigation was conducted within a certain range of land use intensity using a state-of-the-art Lund-Potsdam-Jena dynamic global vegetation model （LPJ DGVM）. CNOP-I represents a class of deforestation and can be considered a type of land use with respect to the initial perturbation. When deforestation denoted by the CNOP-I has the same intensity for all three plants, the variation in plant amount of the boreal needleleaved evergreen in northern China is greater than the variation in plant amount of both the temperate broadleaved evergreen and temperate broadleaved summergreen in southern China. As deforestation intensity increases, the plant amount variation in the three woody plant functional types carbon changes, in a nonlinear fashion. The impact of land use on plant functional types is minor because the interaction between climate condition and land use is not considered in the LPJ model. Finally, the different impacts of deforestation on net primary production of the three plant functional types were analyzed by modeling gross primary production and autotrophic respiration. Our results suggest that the CNOP-I approach is a useful tool for exploring the nonlinear and different responses of terrestrial ecosystems to land use.

关键词： conditional nonlinear optimal perturbation initial perturbation CNOP-I terrestrial ecosys-tem land use

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Inducing Unstable Grassland Equilibrium States Due to Nonlinear Optimal Patterns of initial and Parameter perturbations:Theoretical Models

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Advances in Atmospheric Sciences 2012年第1期29卷 79-90页

作者：孙国栋穆穆 The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 Key Laboratory of Ocean Circulation and Wave Institute of OceanologyChinese Academy of SciencesQingdao 266071

Due to uncertainties in initial conditions and parameters, the stability and uncertainty of grassland ecosystem simulations using ecosystem models are issues of concern. Our objective is to determine the types and patterns of initial and parameter perturbations that yield the greatest instability and uncertainty in simulated grassland ecosystems using theoretical models. We used a nonlinear optimization approach, i.e., a conditional nonlinear optimal perturbation related to initial and parameter perturbations （CNOP） approach, in our work. Numerical results indicated that the CNOP showed a special and nonlinear optimal pattern when the initial state variables and multiple parameters were considered simultaneously. A visibly different complex optimal pattern characterizing the CNOPs was obtained by choosing different combinations of initial state variables and multiple parameters in different physical processes. We propose that the grassland modeled ecosystem caused by the CNOP-type perturbation is unstable and exhibits two aspects： abrupt change and the time needed for the abrupt change from a grassland equilibrium state to a desert equilibrium state when the initial state variables and multiple parameters are considered simultaneously. We compared these findings with results affected by the CNOPs obtained by considering only uncertainties in initial state variables and in a single parameter. The numerical results imply that the nonlinear optimal pattern of initial perturbations and parameter perturbations, especially for more parameters or when special parameters are involved, plays a key role in determining stabilities and uncertainties associated with a simulated or predicted grassland ecosystem.

关键词： conditional nonlinear optimal perturbation initial perturbation parameter perturbation grass-land ecosystem

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Analysis Study on perturbation Energy and Predictability of Heavy Precipitation in South China

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Advances in Atmospheric Sciences 2010年第2期27卷 382-392页

作者：朱本璐林万涛张云 State Key Laboratory of Numerical Modeling for Atmospheric and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences Institute of Meteorology PLA University of Science and Technology

The AREMv2.3 mesoscale numerical model is used to explore storm processes in South China during the pre-rainy season in 2006 by imposing perturbations on the initial fields of physical variables （temperature, humidity, and wind fields）. Sensitivity experiments are performed to examine the impacts of initial uncertainties on precipitation, on the error growth, and on the predictability of mesoscale precipitation in South China. The primary conclusion is that inherent initial condition uncertainties can significantly limit the predictability of storm. The 24-h accumulated precipitation is most sensitive to temperature perturbations. Larger-amplitude initial uncertainties generally lead to larger perturbation energies than those with smaller amplitude, but these kinds of differences decrease with time monotonically so the mechanism for the growth of perturbation energy is nonlinear. The power spectra of precipitation differences indicate that predictability increases with accumulated time. This also indicates the difficulties faced for short-term, small-scale precipitation forecasting.

关键词： initial perturbation error growth DTE predictability

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