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Application of the Conditional Nonlinear Local Lyapunov Exponent to Second-Kind Predictability

Advances in Atmospheric Sciences 2024年第9期41卷 1769-1786页

作者： Ming ZHANG ruiqiang ding Quanjia ZHONG Jianping LI Deyu LU State Key Laboratory of Earth Surface Processes and Resource Ecology(ESPRE)/Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of EducationBeijing Normal UniversityBeijing 100875China Department of Ocean Science Hong Kong University of Science and TechnologyHong KongChina College of Oceanic and Atmospheric Sciences/Frontiers Science Center for Deep Ocean Multispheres and Earth System(DOMES)/Key Laboratory of Physical Oceanography Ministry of Education/Academy of the Future Ocean/Center for Ocean Carbon NeutralityOcean University of ChinaQingdao 266100China Laoshan Laboratory Qingdao 266237China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth Science University of Chinese Academy of SciencesBeijing 100049China

In order to quantify the influence of external forcings on the predictability limit using observational data,the author introduced an algorithm of the conditional nonlinear local Lyapunov exponent(CNLLE)*** effectiveness of this algorithm is validated and compared with the nonlinear local Lyapunov exponent(NLLE)and signal-to-noise ratio methods using a coupled Lorenz *** results show that the CNLLE method is able to capture the slow error growth constrained by external forcings,therefore,it can quantify the predictability limit induced by the external *** this basis,a preliminary attempt was made to apply this method to measure the influence of ENSO on the predictability limit for both atmospheric and oceanic variable *** spatial distribution of the predictability limit induced by ENSO is similar to that arising from the initial conditions calculated by the NLLE *** similarity supports ENSO as the major predictable signal for weather and climate *** addition,a ratio of predictability limit(RPL)calculated by the CNLLE method to that calculated by the NLLE method was *** RPL larger than 1 indicates that the external forcings can significantly benefit the long-term predictability *** instance,ENSO can effectively extend the predictability limit arising from the initial conditions of sea surface temperature over the tropical Indian Ocean by approximately four months,as well as the predictability limit of sea level pressure over the eastern and western Pacific ***,the impact of ENSO on the geopotential height predictability limit is primarily confined to the troposphere.

关键词： conditional nonlinear local Lyapunov exponent second-kind predictability coupled Lorenz model ENSO

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The Predictability Limit of Oceanic Mesoscale Eddy Tracks in the South China Sea

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Advances in Atmospheric Sciences 2024年第9期41卷 1661-1679页

作者： Hailong LIU Pingxiang CHU Yao MENG Mengrong ding Pengfei LIN ruiqiang ding Pengfei WANG Weipeng ZHENG LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laoshan Laboratory Qingdao 266237China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Marine Science and Technology College Zhejiang Ocean UniversityZhoushan 316022China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100872China Center for Monsoon System Research(CMSR) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100190China

Employing the nonlinear local Lyapunov exponent (NLLE) technique, this study assesses the quantitative predictability limit of oceanic mesoscale eddy (OME) tracks utilizing three eddy datasets for both annual and seasonal means. Our findings reveal a discernible predictability limit of approximately 39 days for cyclonic eddies (CEs) and 44 days for anticyclonic eddies (AEs) within the South China Sea (SCS). The predictability limit is related to the OME properties and seasons. The long-lived, large-amplitude, and large-radius OMEs tend to have a higher predictability limit. The predictability limit of AE (CE) tracks is highest in autumn (winter) with 52 (53) days and lowest in spring (summer) with 40 (30) days. The spatial distribution of the predictability limit of OME tracks also has seasonal variations, further finding that the area of higher predictability limits often overlaps with periodic OMEs. Additionally, the predictability limit of periodic OME tracks is about 49 days for both CEs and AEs, which is 5-10 days higher than the mean values. Usually, in the SCS, OMEs characterized by high predictability limit values exhibit more extended and smoother trajectories and often move along the northern slope of the SCS.

关键词： predictability mesoscale eddy nonlinear local Lyapunov exponent South China Sea seasonal variability

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内部变率和全球变暖对春季北太平洋维多利亚模态增强的相对贡献

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广东海洋大学学报 2024年第1期44卷 84-92页

作者：刘宇豪丁瑞强李扬成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室四川成都610225 北京师范大学环境演变与自然灾害教育部重点实验室北京100875

【目的】讨论北太平洋维多利亚模态(Victoria mode,VM)在1900—2021年(122 a)内时空分布变化,研究内部变率和全球变暖对春季VM在122 a年际变率增强的相对贡献。【方法】利用英国Hadley海表温度资料和第六次国际耦合模式比较计划(CMIP6)... 详细信息

【目的】讨论北太平洋维多利亚模态(Victoria mode,VM)在1900—2021年(122 a)内时空分布变化,研究内部变率和全球变暖对春季VM在122 a年际变率增强的相对贡献。【方法】利用英国Hadley海表温度资料和第六次国际耦合模式比较计划(CMIP6)模式资料,采用多元线性回归方法分析内部变率和全球变暖对春季VM在122 a年际变率增强的相对贡献。【结果与结论】1)VM模态的解释方差从1900—1960年的9.3%增长到1961—2021年的13.1%,东北-西南方向的偶极子型结构变得更明显,且强VM事件年发生频率得到明显提高。2)定量分析得到全球变暖对1900—2014年春季VM的年际变率增强的相对贡献占46.67%,内部变率对1900—2014年春季VM的年际变率增强的相对贡献占34.38%。

关键词：北太平洋维多利亚模态 CMIP6 内部变率全球变暖多元线性回归

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北太平洋维多利亚模态对淮河流域夏季降水的影响

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气象科学 2024年第3期44卷 411-419页

作者：聂思源丁瑞强陈权亮成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室成都610225 北京师范大学环境演变与自然灾害教育部重点实验室北京100875

北太平洋维多利亚模态(Victoria Mode,VM)是北太平洋重要的气候模态,对全球降水和气候有着重要影响。本文使用CN05.1格点化观测数据集资料,研究了春季(2—4月)VM模态与我国淮河流域夏季(6—8月)降水的关系,揭示了其内在的可能机制,并在... 详细信息

北太平洋维多利亚模态(Victoria Mode,VM)是北太平洋重要的气候模态,对全球降水和气候有着重要影响。本文使用CN05.1格点化观测数据集资料,研究了春季(2—4月)VM模态与我国淮河流域夏季(6—8月)降水的关系,揭示了其内在的可能机制,并在此基础上建立了一个淮河流域夏季降水预测模型。结果表明,春季VM模态与淮河流域夏季降水存在较强的正相关关系,该相关受ENSO影响有限;春季VM模态可以通过海气相互作用在夏季增强赤道西太平洋上空的异常西风,导致影响淮河流域的气旋性环流异常。气旋性环流异常有利于淮河流域上空丰富的水汽供应和异常上升运动。因此,淮河流域夏季降水量增加。

关键词：维多利亚模态(VM) 淮河流域夏季降水

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Recent Advances in China on the Predictability of Weather and Climate

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Advances in Atmospheric Sciences 2023年第8期40卷 1521-1547页

作者： Wansuo DUAN Lichao YANG Mu MU Bin WANG Xueshun SHEN Zhiyong MENG ruiqiang ding LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China CMA Earth System Modeling and Prediction Center China Meteorological AdministrationBeijing 100081China CMA Tornado Key Laboratory Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China

This article summarizes the progress made in predictability studies of weather and climate in recent years in China,with a main focus on advances in methods to study error growth dynamics and reduce uncertainties in the forecasting of weather and ***,it covers(a)advances in methods to study weather and climate predictability dynamics,especially those in nonlinear optimal perturbation methods associated with initial errors and model errors and their applications to ensemble forecasting and target observations,(b)new data assimilation algorithms for initialization of predictions and novel assimilation approaches to neutralize the combined effects of initial and model errors for weather and climate,(c)applications of new statistical approaches to climate predictions,and(d)studies on meso-to small-scale weather system predictability *** of the major frontiers and challenges remaining in predictability studies are addressed in this context.

关键词： predictability target observation data assimilation ensemble forecasting

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Impact of Perturbation Schemes on the Ensemble Prediction in a Coupled Lorenz Model

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Advances in Atmospheric Sciences 2023年第3期40卷 501-513页

作者： Qian ZOU Quanjia ZHONG Jiangyu MAO ruiqiang ding Deyu LU Jianping LI Xuan LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth Science University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Frontiers Science Center for Deep Ocean Multispheres and Earth System(FDOMES)/Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies Ocean University of ChinaQingdao 266100China Laboratory for Ocean Dynamics and Climate Pilot Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China

Based on a simple coupled Lorenz model,we investigate how to assess a suitable initial perturbation scheme for ensemble forecasting in a multiscale system involving slow dynamics and fast *** initial perturbation approaches are used in the ensemble forecasting experiments:the random perturbation(RP),the bred vector(BV),the ensemble transform Kalman filter(ETKF),and the nonlinear local Lyapunov vector(NLLV)*** show that,regardless of the method used,the ensemble averages behave indistinguishably from the control forecasts during the first few time *** to different error growth in different time-scale systems,the ensemble averages perform better than the control forecast after very short lead times in a fast subsystem but after a relatively long period of time in a slow *** to the coupled dynamic processes,the addition of perturbations to fast variables or to slow variables can contribute to an improvement in the forecasting skill for fast variables and slow *** the initial perturbation approaches,the NLLVs show higher forecasting skill than the BVs or RPs *** NLLVs and ETKFs had nearly equivalent prediction skill,but NLLVs performed best by a narrow *** particular,when adding perturbations to slow variables,the independent perturbations(NLLVs and ETKFs)perform much better in ensemble *** results are simply implied in a real coupled air–sea *** the prediction of oceanic variables,using independent perturbations(NLLVs)and adding perturbations to oceanic variables are expected to result in better performance in the ensemble prediction.

关键词： ensemble prediction nonlinear local Lyapunov vector(NLLV) ensemble transform Kalman filter(ETKF) coupled air-sea models

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Influence of the NAO on Wintertime Surface Air Temperature over East Asia:Multidecadal Variability and Decadal Prediction

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Advances in Atmospheric Sciences 2022年第4期39卷 625-642页

作者： Jianping LI Tiejun XIE Xinxin TANG Hao WANG Cheng SUN Juan FENG Fei ZHENG ruiqiang ding Frontiers Science Center for Deep Ocean Multispheres and Earth System-Key Laboratory of Physical Oceanography-Institute for Advanced Ocean Studies-Academy of the Future Ocean Ocean University of ChinaQingdao 266100China Laboratory for Ocean Dynamics and Climate Pilot Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Global Change and Earth System Sciences Beijing Normal UniversityBeijing 100875China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China

In this paper,we investigate the influence of the winter NAO on the multidecadal variability of winter East Asian surface air temperature(EASAT)and EASAT decadal *** observational analysis shows that the winter EASAT and East Asian minimum SAT(EAmSAT)display strong in-phase fluctuations and a significant 60-80-year multidecadal variability,apart from a long-term warming *** winter EASAT experienced a decreasing trend in the last two decades,which is consistent with the occurrence of extremely cold events in East Asia winters in recent *** winter NAO leads the detrended winter EASAT by 12-18 years with the greatest significant positive correlation at the lead time of 15 *** analysis shows that ENSO may affect winter EASAT interannual variability,but does not affect the robust lead relationship between the winter NAO and *** present the coupled oceanic-atmospheric bridge(COAB)mechanism of the NAO influences on winter EASAT multidecadal variability through its accumulated delayed effect of~15 years on the Atlantic Multidecadal Oscillation(AMO)and Africa-Asia multidecadal teleconnection(AAMT)*** NAO-based linear model for predicting winter decadal EASAT is constructed on the principle of the COAB mechanism,with good hindcast *** winter EASAT for 2020-34 is predicted to keep on fluctuating downward until~2025,implying a high probability of occurrence of extremely cold events in coming winters in East Asia,followed by a sudden turn towards sharp *** predicted 2020/21 winter EASAT is almost the same as the 2019/20 winter.

关键词： winter East Asian surface air temperature North Atlantic Oscillation Atlantic Multidecadal Oscillation Africa-Asia multidecadal teleconnection pattern coupled oceanic-atmospheric bridge multidecadal variability

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Comparisons of Two Ensemble Mean Methods in Measuring the Average Error Growth and the Predictability

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Acta meteorologica Sinica 2011年第4期25卷 395-404页

作者： ding ruiqiang LI Jianping State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029

In this paper, taking the Lorenz system as an example, we compare the influences of the arithmetic mean and the geometric mean on measuring the global and local average error growth. The results show that the geometric mean error （GME） has a smoother growth than the arithmetic mean error （AME） for the global average error growth, and the GME is directly related to the maximal Lyapunov exponent, but the AME is not, as already noted by Krishnamurthy in 1993. Besides these, the GME is shown to be more appropriate than the AME in measuring the mean error growth in terms of the probability distribution of errors. The physical meanings of the saturation levels of the AME and the GME are also shown to be different. However, there is no obvious difference between the local average error growth with the arithmetic mean and the geometric mean, indicating that the choices of the AME or the GME have no influence on the measure of local average predictability.

关键词： predictability arithmetic mean geometric mean Lorenz system

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Quantitative Comparison of Predictabilities of Warm and Cold Events Using the Backward Nonlinear Local Lyapunov Exponent Method

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Advances in Atmospheric Sciences 2020年第9期37卷 951-958页

作者： Xuan LI ruiqiang ding Jianping LI Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China Key Laboratory of Physical Oceanography Institute for Advanced Ocean StudiesOcean University of China and Qingdao National Laboratory for Marine Science and TechnologyQingdao 266100China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies Ocean University of China and Qingdao National Laboratory for Marine Science and TechnologyQingdao 266100China

The backward nonlinear local Lyapunov exponent method(BNLLE)is applied to quantify the predictability of warm and cold events in the Lorenz *** show that the maximum prediction lead times of warm and cold events present obvious layered structures in phase *** maximum prediction lead times of each warm(cold)event on individual circles concentric with the distribution of warm(cold)regime events are roughly the same,whereas the maximum prediction lead time of events on other circles are *** results show that warm events are more predictable than cold events.

关键词： backward nonlinear local Lyapunov exponent maximum prediction lead time layered structure statistical result

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Influence of the Preceding Austral Summer Southern Hemisphere Annular Mode on the Amplitude of ENSO Decay

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Advances in Atmospheric Sciences 2017年第11期34卷 1358-1379页

作者： Fei ZHENG Jianping LI ruiqiang ding State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Global Change and Earth System Science Beijing Normal UniversityBeijing 100875China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and Technologyqingdao 266237China Plateau Atmosphere and Environment Key Laboratory of Sichuan Province Chengdu University of Information Technologychengdu 610103China

There is increasing evidence of the possible role of extratropical forcing in the evolution of ENSO. The Southern Hemi- sphere Annular Mode （SAM） is the dominant mode of atmospheric circulation in the Southern Hemisphere extratropics. This study shows that the austral summer （December-January-February; DJF） SAM may also influence the amplitude of ENSO decay during austral autumn （March-April-May; MAM）. The mechanisms associated with this SAM-ENSO relationship can be briefly summarized as follows： The SAM is positively （negatively） correlated with SST in the Southern Hemisphere middle （high） latitudes. This dipole-like SST anomaly pattern is referred to as the Southern Ocean Dipole （SOD）. The DJF SOD, caused by the DJF SAM, could persist until MAM and then influence atmospheric circulation, including trade winds, over the Nifio3.4 area. Anomalous trade winds and SST anomalies over the Nifio3.4 area related to the DJF SAM are further developed through the Bjerkness feedback, which eventually results in a cooling （warming） over the Nifio3.4 area followed by the positive （negative） DJF SAM.

关键词： Southern Hemisphere Annular Mode ENSO Southern Ocean Dipole

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