Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China （2007-2011） are briefly introduced in this article. Major achievements in the study of nonli...Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China （2007-2011） are briefly introduced in this article. Major achievements in the study of nonlinear atmospheric dynamics have been classified into two types： （1） progress based on the analysis of solutions of simplified control equations, such as the dynamics of NAO, the optimal precursors for blocking onset, and the behavior of nonlinear waves, and （2） progress based on data analyses, such as the nonlinear analyses of fluctuations and recording-breaking temperature events, the long-range correlation of extreme events, and new methods of detecting abrupt dynamical change. Major achievements in the study of predictability include the following： （1） the application of nonlinear local Lyapunov exponents （NLLE） to weather and climate predictability; （2） the application of condition nonlinear optimal perturbation （CNOP） to the studies of E1 Nifio-Southern Oscillation （ENSO） predictions, ensemble forecasting, targeted observation, and sensitivity analysis of the ecosystem; and （3） new strategies proposed for predictability studies. The results of these studies have provided greater understanding of the dynamics and nonlinear mecha- nisms of atmospheric motion, and they represent new ideas for developing numerical models and improving the forecast skill of weather and climate events.展开更多
Linear singular vector and linear singular value can only describe the evolution of sufficiently small perturbations during the period in which the tangent linear model is valid. With this in mind,the applications of ...Linear singular vector and linear singular value can only describe the evolution of sufficiently small perturbations during the period in which the tangent linear model is valid. With this in mind,the applications of nonlinear optimization methods to the atmospheric and oceanic sciences are introduced, which include nonlinear singular vector (NSV) and nonlinear singular value (NSVA), conditional nonlinear optimal perturbation (CNOP), and their applications to the studies of predictability in numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be explored by NSV and CNOP. Also attentions are paid to the introduction of the classification of predictability problems, which are related to the maximum predictable time, the maximum prediction error, and the maximum allowing error of initial value and the parameters. All the information has the background of application to the evaluation of products of numerical weather and climate prediction. Furthermore the nonlinear optimization methods of the sensitivity analysis with numerical model are also introduced, which can give a quantitative assessment whether a numerical model is able to simulate the observations and find the initial field that yield the optimal simulation. Finally, the difficulties in the lack of ripe algorithms are also discussed, which leave future work to both computational mathematics and scientists in geophysics.展开更多
In May 2008, ScienceWatch.com named Advances in Atmospheric Sciences a Rising Star among Geosciences journals. According to Essential Science IndicatorsSM from Thomson Reuters, the journal＇s cur-rent citation record ...In May 2008, ScienceWatch.com named Advances in Atmospheric Sciences a Rising Star among Geosciences journals. According to Essential Science IndicatorsSM from Thomson Reuters, the journal＇s cur-rent citation record includes 764 papers cited a total of 1,658 times between January 1, 1998 and February 29 2008.展开更多
利用1961—2015年国家气象信息中心沈阳站的日平均气温资料、美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)提供的多变量ENSO指数(multivariate ENSO index,MEI)资料等,在分析沈阳地区气温月际变化...利用1961—2015年国家气象信息中心沈阳站的日平均气温资料、美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)提供的多变量ENSO指数(multivariate ENSO index,MEI)资料等,在分析沈阳地区气温月际变化的基础上,结合厄尔尼诺/拉尼娜事件对其影响特征,利用线性倾向估计和非线性自回归(nonlinear auto regressive models with exogenous inputs,NARX)神经网络模型分别对沈阳地区2011—2015年的气温进行预测。结果表明,1961—2015年共计660个月中,沈阳地区11月—3月气温的变异系数在20%以上,远大于其他月份。1961—2015年的厄尔尼诺/拉尼娜事件往往在秋冬季达到最大强度,或为导致沈阳地区11月—3月气温变异增强的原因之一。厄尔尼诺事件结束之后的春季,沈阳地区气温偏低的概率逾70%。沈阳地区气温随MEI变化的线性倾向值为0.98,决定系数为0.98且通过了0.01的可信度检验。利用MEI对沈阳地区的气温进行同期和时滞预测,NARX的预测结果均优于一元线性回归模型。当气温滞后MEI16个月时,两者的相关系数达到最大且通过了0.01的显著性检验,此时回归模型预测的相关系数为0.59,较同期预测提升了79%;NARX预测的均方误差(mean-square error,MSE)为0.49,较同期预测降低了36%,相关系数为0.86,较同期预测提升了8%。展开更多
Systematic errors have recently been founded to be distinct in the zonal mean component forecasts, which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical m...Systematic errors have recently been founded to be distinct in the zonal mean component forecasts, which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-mean nonlinear dynamic regional prediction models of the zonal mean geopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data （NCEP/NCAR reanalysis data） were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996 indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction, and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 （averagely a relative change of 11.0% over the globe） by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model.展开更多
This article involves the study of atmospheric internal waves phenomenon,also referred to as gravity waves.This phenomenon occurs inside the fluid,not on the surface.The model is based on a shallow fluid hypothesis re...This article involves the study of atmospheric internal waves phenomenon,also referred to as gravity waves.This phenomenon occurs inside the fluid,not on the surface.The model is based on a shallow fluid hypothesis represented by a system of nonlinear partial differential equations.The basic assumption of the shallow flow model is that the horizontal size is much larger than the vertical size.Atmospheric internal waves can be perfectly represented by this model as the waves are spread over a large horizontal area.Here we used the Elzaki Adomian Decomposition Method(EADM)to obtain the solution for the considered model along with its convergence analysis.The Adomian decomposition method together with the Elzaki transform gives the solution in a convergent series without any linearization or perturbation.Comparisons are built between the results obtained by EADM and HAM to examine the accuracy of the proposed method.展开更多
基金sponsored by the Chinese Academy of Science (Grant No.KZCX3-SW-230)the National Basic Research Program of China (Grant Nos. 2012CB955202 and 2010CB950402)the National Natural Science Foundation of China (Grant Nos. 41176013 and 41105038)
文摘Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China （2007-2011） are briefly introduced in this article. Major achievements in the study of nonlinear atmospheric dynamics have been classified into two types： （1） progress based on the analysis of solutions of simplified control equations, such as the dynamics of NAO, the optimal precursors for blocking onset, and the behavior of nonlinear waves, and （2） progress based on data analyses, such as the nonlinear analyses of fluctuations and recording-breaking temperature events, the long-range correlation of extreme events, and new methods of detecting abrupt dynamical change. Major achievements in the study of predictability include the following： （1） the application of nonlinear local Lyapunov exponents （NLLE） to weather and climate predictability; （2） the application of condition nonlinear optimal perturbation （CNOP） to the studies of E1 Nifio-Southern Oscillation （ENSO） predictions, ensemble forecasting, targeted observation, and sensitivity analysis of the ecosystem; and （3） new strategies proposed for predictability studies. The results of these studies have provided greater understanding of the dynamics and nonlinear mecha- nisms of atmospheric motion, and they represent new ideas for developing numerical models and improving the forecast skill of weather and climate events.
文摘Linear singular vector and linear singular value can only describe the evolution of sufficiently small perturbations during the period in which the tangent linear model is valid. With this in mind,the applications of nonlinear optimization methods to the atmospheric and oceanic sciences are introduced, which include nonlinear singular vector (NSV) and nonlinear singular value (NSVA), conditional nonlinear optimal perturbation (CNOP), and their applications to the studies of predictability in numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be explored by NSV and CNOP. Also attentions are paid to the introduction of the classification of predictability problems, which are related to the maximum predictable time, the maximum prediction error, and the maximum allowing error of initial value and the parameters. All the information has the background of application to the evaluation of products of numerical weather and climate prediction. Furthermore the nonlinear optimization methods of the sensitivity analysis with numerical model are also introduced, which can give a quantitative assessment whether a numerical model is able to simulate the observations and find the initial field that yield the optimal simulation. Finally, the difficulties in the lack of ripe algorithms are also discussed, which leave future work to both computational mathematics and scientists in geophysics.
文摘In May 2008, ScienceWatch.com named Advances in Atmospheric Sciences a Rising Star among Geosciences journals. According to Essential Science IndicatorsSM from Thomson Reuters, the journal＇s cur-rent citation record includes 764 papers cited a total of 1,658 times between January 1, 1998 and February 29 2008.
文摘利用1961—2015年国家气象信息中心沈阳站的日平均气温资料、美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)提供的多变量ENSO指数(multivariate ENSO index,MEI)资料等,在分析沈阳地区气温月际变化的基础上,结合厄尔尼诺/拉尼娜事件对其影响特征,利用线性倾向估计和非线性自回归(nonlinear auto regressive models with exogenous inputs,NARX)神经网络模型分别对沈阳地区2011—2015年的气温进行预测。结果表明,1961—2015年共计660个月中,沈阳地区11月—3月气温的变异系数在20%以上,远大于其他月份。1961—2015年的厄尔尼诺/拉尼娜事件往往在秋冬季达到最大强度,或为导致沈阳地区11月—3月气温变异增强的原因之一。厄尔尼诺事件结束之后的春季,沈阳地区气温偏低的概率逾70%。沈阳地区气温随MEI变化的线性倾向值为0.98,决定系数为0.98且通过了0.01的可信度检验。利用MEI对沈阳地区的气温进行同期和时滞预测,NARX的预测结果均优于一元线性回归模型。当气温滞后MEI16个月时,两者的相关系数达到最大且通过了0.01的显著性检验,此时回归模型预测的相关系数为0.59,较同期预测提升了79%;NARX预测的均方误差(mean-square error,MSE)为0.49,较同期预测降低了36%,相关系数为0.86,较同期预测提升了8%。
基金Supported by the National Natural Science Foundation of China under Grant No. 40175013the National Key Project for Development of Science and Technology (96-908-02-01)the Project of Chinese Academy of Sciences (ZKCX2-SW-210).
文摘Systematic errors have recently been founded to be distinct in the zonal mean component forecasts, which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-mean nonlinear dynamic regional prediction models of the zonal mean geopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data （NCEP/NCAR reanalysis data） were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996 indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction, and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 （averagely a relative change of 11.0% over the globe） by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model.
文摘This article involves the study of atmospheric internal waves phenomenon,also referred to as gravity waves.This phenomenon occurs inside the fluid,not on the surface.The model is based on a shallow fluid hypothesis represented by a system of nonlinear partial differential equations.The basic assumption of the shallow flow model is that the horizontal size is much larger than the vertical size.Atmospheric internal waves can be perfectly represented by this model as the waves are spread over a large horizontal area.Here we used the Elzaki Adomian Decomposition Method(EADM)to obtain the solution for the considered model along with its convergence analysis.The Adomian decomposition method together with the Elzaki transform gives the solution in a convergent series without any linearization or perturbation.Comparisons are built between the results obtained by EADM and HAM to examine the accuracy of the proposed method.
