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1.
A two-layer quasi-geostrophic model is used to study the stability and sensitivity of motions on smallscale vortices in Jupiter’s atmosphere. Conditional nonlinear optimal perturbations (CNOPs) and linear singular vectors (LSVs) are both obtained numerically and compared in this paper. The results show that CNOPs can capture the nonlinear characteristics of motions in small-scale vortices in Jupiter’s atmosphere and show great difference from LSVs under the condition that the initial constraint condition is large or the optimization time is not very short or both. Besides, in some basic states, local CNOPs are found. The pattern of LSV is more similar to local CNOP than global CNOP in some cases. The elementary application of the method of CNOP to the Jovian atmosphere helps us to explore the stability of variousscale motions of Jupiter’s atmosphere and to compare the stability of motions in Jupiter’s atmosphere and Earth’s atmosphere further.  相似文献   

2.
In the present paper, we explore the manner in which nonlinearities modulate El Niño events by investigating the optimal precursory disturbance for El Niño events in the Zebiak-Cane model. The initial anomalies of conditional nonlinear optimal perturbations (CNOPs) and linear singular vectors (LSVs) are investigated. The CNOPs evolve into stronger El Niño events than the LSVs and act as the optimal precursor for El Niño events. By examining the role of nonlinearities in El Niño events induced by CNOPs and LSVs, we determined that, when the initial anomalies of the CNOP and LSV structures are large, the nonlinearities enhance CNOP-El Niño events but suppress LSV-El Niño events. Nonlinearities in the Zebiak-Cane model arise from nonlinear temperature advection (NTA), sub-surface temperature parameterization (STP), and wind stress anomalies (WSA). Using these types of nonlinearities, we trace the approach of the nonlinearities modulating the CNOP- and LSV-El Niño events. The results demonstrate that nonlinearities that originate from NTA enhance both CNOP-El Niño events and LSV-El Niño events, while nonlinearities originating from STP and WSA suppress these events. For the CNOP-El Niño events, the enhancement effect of NTA is larger than the suppression effect of STP and WSA, resulting in the combined effect of the nonlinearities in the Zebiak-Cane model being an enhancement of the CNOP-El Niño events. However, for the LSV-El Niño events, the enhancement effect of NTA is smaller than the suppression effect of WSA and STP. Consequently, the combined effect of the nonlinearities in the Zebiak-Cane model suppresses the LSV-El Niño events.  相似文献   

3.
This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations(CNOPs)–based ensemble forecast technique in MM5(Fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model). The results show that the ensemble forecast members generated by the orthogonal CNOPs present large spreads but tend to be located on the two sides of real tropical cyclone(TC) tracks and have good agreements between ensemble spreads and ensemble-mean forecast errors for TC tracks. Subsequently, these members reflect more reasonable forecast uncertainties and enhance the orthogonal CNOPs–based ensemble-mean forecasts to obtain higher skill for TC tracks than the orthogonal SVs(singular vectors)–, BVs(bred vectors)– and RPs(random perturbations)–based ones. The results indicate that orthogonal CNOPs of smaller magnitudes should be adopted to construct the initial ensemble perturbations for short lead–time forecasts, but those of larger magnitudes should be used for longer lead–time forecasts due to the effects of nonlinearities. The performance of the orthogonal CNOPs–based ensemble-mean forecasts is case-dependent,which encourages evaluating statistically the forecast skill with more TC cases. Finally, the results show that the ensemble forecasts with only initial perturbations in this work do not increase the forecast skill of TC intensity, which may be related with both the coarse model horizontal resolution and the model error.  相似文献   

4.
The authors apply the technique of conditional nonlinear optimal perturbations (CNOPs) as a means of providing initial perturbations for ensemble forecasting by using a barotropic quasi-geostrophic (QG) model in a perfect-model scenario. Ensemble forecasts for the medium range (14 days) are made from the initial states perturbed by CNOPs and singular vectors (SVs). 13 different cases have been chosen when analysis error is a kind of fast growing error. Our experiments show that the introduction of CNOP provides better forecast skill than the SV method. Moreover, the spread-skill relationship reveals that the ensemble samples in which the first SV is replaced by CNOP appear superior to those obtained by SVs from day 6 to day 14. Rank diagrams are adopted to compare the new method with the SV approach. The results illustrate that the introduction of CNOP has higher reliability for medium-range ensemble forecasts.  相似文献   

5.
基于五变量草原生态系统理论模式,应用与参数有关的条件非线性最优扰动(CNOP-P)方法,探讨了由参数不确定性导致的草原生态系统模式模拟结果的不确定性问题。参数的不确定性可能来源于观测和（或）对物理过程描述等的不确定性。选取了五变量草原生态系统模式中具有物理意义的32个模式参数进行数值试验。试验结果表明,对所考察的32个模式参数,在一定的不确定性和给定的优化时刻范围内,单独优化每个参数所得CNOP-Ps的联合模态与同时优化32个参数所得CNOP-P的模态并不相同。比较了上述两类参数误差以及随机参数误差对草原生态系统模拟的差异。随机参数误差与上述优化方法所得参数误差的不确定性范围大小相同。数值结果表明,同时优化32个参数所得 CNOP-P 类型参数误差使得草原生态系统模拟的不确定性程度最大。这种影响表现在使得草原生态系统转变为沙漠生态系统,或者使得草原生态系统转变为具有更多生草量的草原生态系统。上述数值结果不依赖于优化时间和参数不确定性程度的大小。这些数值结果建议我们应当考虑多参数的非线性相互作用来研究草原生态系统模式模拟的不确定性问题,并且揭示出CNOP-P方法是讨论上述问题的一个有用的工具。  相似文献   

6.
条件非线性最优扰动方法在适应性观测研究中的初步应用   总被引：12，自引：3，他引：12  
穆穆  王洪利  周菲凡 《大气科学》2007,31(6):1102-1112
针对适应性观测中敏感性区域的确定问题，考虑初始误差对预报结果的影响, 比较了条件非线性最优扰动(CNOP)与第一线性奇异向量(FSV)在两个降水个例中的空间结构的差异，考察了它们总能量范数随时间发展演变的异同。结合敏感性试验的分析，揭示了预报结果对CNOP类型的初始误差的敏感性要大于对FSV类型的初始误差的敏感性，因而减少初值中CNOP类型误差的振幅比减少FSV类型的收益要大。这一结果表明可以把CNOP方法应用于适应性观测来识别大气的敏感区。关于将CNOP方法有效地应用于适应性观测所面临的挑战及需要采取的对策等也进行了讨论。  相似文献   

7.
The initial errors constitute one of the main limiting factors in the ability to predict the El Nio–Southern Oscillation(ENSO) in ocean–atmosphere coupled models. The conditional nonlinear optimal perturbation(CNOP) approach was employed to study the largest initial error growth in the El Nio predictions of an intermediate coupled model(ICM). The optimal initial errors(as represented by CNOPs) in sea surface temperature anomalies(SSTAs) and sea level anomalies(SLAs) were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of El Nio, the El Nio event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier(SPB) phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly,weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events.  相似文献   

8.
A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has ＂on off＂ switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method （ADJ）, and a GA using tournament selection operation and the niching technique （GA-DEB） were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared.  相似文献   

9.
SUN Guodong  MU Mu 《大气科学进展》2011,28(6):1266-1278
The response of a grassland ecosystem to climate change is discussed within the context of a theoretical model.An optimization approach,a conditional nonlinear optimal perturbation related to parameter(CNOP-P) approach,was employed in this study.The CNOP-P,a perturbation of moisture index in the theoretical model,represents a nonlinear climate perturbation.Two kinds of linear climate perturbations were also used to study the response of the grassland ecosystem to different types of climate changes.The results show that the extent of grassland ecosystem variation caused by the CNOP-P-type climate change is greater than that caused by the two linear types of climate change.In addition,the grassland ecosystem affected by the CNOP-P-type climate change evolved into a desert ecosystem,and the two linear types of climate changes failed within a specific amplitude range when the moisture index recovered to its reference state.Therefore,the grassland ecosystem response to climate change was nonlinear.This study yielded similar results for a desert ecosystem seeded with both living and wilted biomass litter.The quantitative analysis performed in this study also accounted for the role of soil moisture in the root zone and the shading effect of wilted biomass on the grassland ecosystem through nonlinear interactions between soil and vegetation.The results of this study imply that the CNOP-P approach is a potentially effective tool for assessing the impact of nonlinear climate change on grassland ecosystems.  相似文献   

10.
A projected skill is adopted by use of the differential evolution （DE） algorithm to calculate a conditional nonlinear optimal perturbation （CNOP）. The CNOP is the maximal value of a constrained optimization problem with a constraint condition, such as a ball constraint. The success of the DE algorithm lies in its ability to handle a non-differentiable and nonlinear cost function. In this study, the DE algorithm and the traditional optimization algorithms used to obtain the CNOPs are compared by analyzing a theoretical grassland ecosystem model and a dynamic global vegetation model. This study shows that the CNOPs generated by the DE algorithm are similar to those by the sequential quadratic programming （SQP） algorithm and the spectral projected gradients （SPG2） algorithm. If the cost function is non-differentiable, the CNOPs could also be caught with the DE algorithm. The numerical results suggest the DE algorithm can be employed to calculate the CNOP, especially when the cost function is non-differentiable.  相似文献   

11.
The sensitive regions of conditional nonlinear optimal perturbations (CNOPs) and the first singular vector (FSV) for a northwest Pacific typhoon case are reported in this paper. A large number of probes have been designed in the above regions and the ensemble transform Kalman filter (ETKF) techniques are utilized to examine which approach can locate more appropriate regions for typhoon adaptive observations. The results show that, in general, the majority of the probes in the sensitive regions of CNOPs can reduce more forecast error variance than the probes in the sensitive regions of FSV. This implies that adaptive observations in the sensitive regions of CNOPs are more effective than in the sensitive regions of FSV. Furthermore, the reduction of the forecast error variance obtained by the best probe identified by CNOPs is twice the reduction of the forecast error variance obtained by FSV. This implies that dropping sondes, which is the best probe identified by CNOPs, can improve the forecast more than the best probe identified by FSV. These results indicate that the sensitive regions identified by CNOPs are more appropriate for adaptive observations than those identified by FSV.  相似文献   

12.
In this paper,a nonlinear optimization method is used to explore the finite-time instability of the atmospheric circulation with a three-level quasigeostrophic model under the framework of the conditional nonlinear optimal perturbation (CNOP).As a natural generalization of linear singular vector (SV),CNOP is defined as an initial perturbation that makes the cost function the maximum at a prescribed forecast time under certain physical constraint conditions.Special attentions are paid to the different structures and energy evolutions of the optimal perturbations.The results show that the most instable region of the global atmospheric circulation lies in the midlatitude Eurasian continent.More specially,SV and CNOP in the total energy norm with an optimization time of 2 days both present localness:they are mainly located in the midlatitude Asian continent and its east coast.With extension of the optimization time,SVs are more upstream and less localized in the zonal direction,and CNOPs differ essentially from SVs with broader zonal and meridional coverages; as a result,CNOPs acquire larger kinetic and available potential energy amplifications than SVs in the nonlinear model at the corresponding optimization time.For the climatological wintertime flow,it is seen that the baroclinic terms remain small over the entire time evolution,and the energy production comes essentially from the eddy kinetic energy,which is induced by the horizontal shear of the basic flow.In addition,the effects of SVs and CNOPs on the Eurasian atmospheric circulation are explored.The results show that the weather systems over the Eurasian continent in the perturbed fields by CNOPs are stronger than those by SVs at the optimization time.This reveals that the CNOP method is better in evaluating the instability of the atmospheric circulation while the SV method underestimates the possibility of extreme weather events.  相似文献   

13.
Simulations and predictions using numerical models show considerable uncertainties, and parameter uncertainty is one of the most important sources. It is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all parameters. Therefore, identifying the sensitive parameters or parameter combinations is crucial. This study proposes a novel approach: conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA) method. The CNOPSA method fully consi...  相似文献   

14.
In this paper, the approach proposed by Mu and Jiang (2008) to obtain the optimal perturbations for triggering blocking (BL) onset is generalized to seek the optimal perturbations triggering onset of the strong zonal flow (SZF) regime. The BL and SZF regimes are characterized by the same dipole-like anomaly pattern superposed on the climatological flow, but with opposite sign. The results show that this method is also superior at finding the initial optimal perturbations triggering onset of the SZF regime, especially in the medium range. Furthermore, by comparing the two kinds of conditional nonlinear optimal perturbations (CNOPs) trig-gering onset of BL and SZF regimes, we find that in the linear approximation, there is symmetry in the sensitivities for BL and SZF onset, and the perturbations that optimally trigger onset of BL and SZF regimes at times when linear approximation is valid are also characterized by the same spatial pattern but with opposite sign. Whereas when the optimization time is extended to 6 days, the two kinds of CNOPs lose their out-of-phase behavior. The nonlinearity results in an asymmetry between the sensitivity for BL and SZF onset. Additionally, we find that the optimal perturbations have one common property, which is that the second baroclinic mode contributes more to the initial perturbations while the barotropic mode dominates the final structures.  相似文献   

15.
In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.  相似文献   

16.
谭晓伟  王斌  王栋梁 《气象学报》2011,69(3):400-411
基于GRAPES区域业务预报模式,采用一种快速算法计算出来的条件非线性最优扰动对实际台风个例麦莎(No.0509)开展了目标观测研究,应用数值模式,进行一系列的敏感性试验,讨论了与目标观测设计相关的一些问题,包括确定瞄准区时使用不同的引导性变量对目标观测效果的影响、及瞄准区范围变化对预报效果的影响。文中分别以提高麦莎在检验区(20.125°—35.3125°N,116.8125°—129.75°E)内的24 h海平面气压预报和24 h累积降水量预报为目的,基于条件非线性最优扰动使用了3种不同的引导性变量寻找敏感区(又称瞄准区),对这些敏感区的分布特点和有效性进行了比较和讨论。试验结果表明,在使用的3种引导性变量中,用不同的引导性变量识别的敏感区是有差别的,总体上说,文中使用的3种引导性变量识别的瞄准区对提高预报都是有效的,特别是第2和第3种的效果更好些,且两者识别的瞄准区常显示出类似的特点。文中进一步针对检验区内24 h累积降水量预报误差问题,将前面确定的瞄准区范围扩大相同的幅度,讨论瞄准区范围变化对改进预报的影响。试验结果表明,增加瞄准格点数,有可能使预报效果得到改善,但是试验结果同时也暗示了单纯靠扩大瞄准...  相似文献   

17.
汪叶  段晚锁 《大气科学》2019,43(4):915-929
初始扰动振幅的大小和集合样本数对于集合预报取得更高预报技巧具有重要意义。本文将正交条件非线性最优扰动方法（orthogonal conditional nonlinear optimal perturbations,简称CNOPs）应用于概念模型Lorenz-96模式探讨了初始扰动振幅和集合样本数对集合预报技巧的影响,从而为使用更复杂模式进行集合预报提供指导。结果表明,由于CNOPs扮演了非线性系统中的最优初始扰动,从而使得当初始扰动振幅小于初始分析误差的大小时,CNOPs集合预报获得更高的预报技巧,并且CNOPs集合预报的最高预报技巧总是高于奇异向量法（singular vectors,简称SVs）集合预报的最高预报技巧。结果还表明,CNOPs集合预报倾向于具有一个合适的样本数时,达到最高技巧。更好的集合离散度——预报误差关系和更为平坦的Talagrand图（Talagrand diagram）进一步证明了CNOPs集合预报系统的可靠性,从而夯实了上述结果的合理性。因此,针对CNOPs集合预报,本文认为采用一个适当小于初始分析误差的初始扰动振幅和一个合适的集合样本数,有利于CNOPs集合预报达到最高预报技巧。  相似文献   

18.
张星  穆穆  王强  张坤 《山东气象》2018,38(1):1-9
对近年来利用条件非线性最优扰动（Conditional Nonlinear Optimal Perturbation,CNOP）方法开展的黑潮目标观测研究进行了总结,主要包括日本南部黑潮路径变异的目标观测研究、黑潮延伸体模态转变的目标观测研究和源区黑潮流量变化的目标观测研究。通过计算这些事件的CNOP型扰动,发现这些事件的CNOP型扰动具有局地特征,可以作为实施目标观测的敏感区。理想回报试验结果表明,如果在由CNOP方法识别的敏感区内实施目标观测,则会大幅度提高上述事件的预报技巧。  相似文献   

19.
基于GIMMS（global inventory modeling and mapping studies）NDVI 3g数据,在提取北半球荒漠草原过渡带每年植被物候期的基础上,研究了1982-2012年物候期的时间演化趋势及空间分异特征,并结合全球气候再分析资料,探讨了物候变化的气候驱动因素。结果表明：在1998年之前,荒漠草原过渡带植被物候期变化地区间差异较大,而在1998年之后,北半球荒漠草原过渡带生长季结束期整体提前,平均提前0.41 d/a;同时,除萨赫勒以外的各地区植被生长季长度普遍缩短,平均缩短0.88 d/a。植被物候期与气候因子的相关分析发现,荒漠草原过渡带植被物候变化受气候变化影响显著,且空间差异明显。在中高纬度地区,气温是限制植被活动的关键因子,温度升高可以促进生长季开始期的提前,而降水增加则会妨碍植被生长;在较低纬度地区,水分是影响植被活动的关键因素,高温造成的水分亏缺会导致植被生长季缩短。从植被物候期对各气候因子响应的时滞性来看,荒漠草原过渡带植被的物候期对气温变化的响应最迅速,对蒸散的响应存在一定的滞后性,而对降水的响应不存在时滞差异。  相似文献   

20.
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.  相似文献   

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