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利用PSU／NCAR中尺度非静力有限区域MM5及其伴随模式，以T106分析资料为背景场，设计两种台风Bogus方案对台风的初始场进行优化，并进行了数值模拟试验。对9608号台风个例的数值模拟试验研究表明，经过优化的台风初始场较好地改进了由于海洋上资料缺乏所造成的台风中心位置不准、台风环流偏弱和台风内部结构不完整等问题，提高了台风路径预报的准确率。通过试验对比发现，BDA方案优化的初始场更合理，其台风路径预报效果优于GFDL方案。 相似文献
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非对称Bogus台风与QuikSCAT风场资料的三维变分同化应用对台风数值模拟影响研究 总被引：1，自引：0，他引：1
针对台风Bogus三维变分同化现有方法所存在的不足,引入台风移向、移速等客观因素构造出非对称台风风场模型,并与QuikSCAT风场产品相结合共同改善模式初始场。通过对比初始场增量发现,同化台风Bogus资料能较好地订正出包括高空反气旋环流在内的整层大气环流特征,而QuikSCAT风场资料则主要改善了底层环流特征,修正了台风中心位置,并且部分弥补了Bogus资料影响范围有限这一不足。接着通过设计试验方案对“云娜”台风加强阶段进行了模拟研究,结果表明：在变分同化系统的约束下,背景场、Bogus资料与QuikSCAT风场资料较协调地结合在一起,提高了台风路径及强度模拟水平,尤其是底层内外物理量的共同改进,对台风的模拟效果有明显的正效应。 相似文献
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应用ATOVS资料和非对称Bogus资料对登陆台风韦帕的4DVAR数值模拟分析 总被引：3，自引：1，他引：2
前人研究中BDA方法采用的轴对称Bogus台风不能反映个别台风具体特征并弃掉了背景场的合理成分,也没有考虑大环境场的影响及湿热要素的同化。因此,提出一种充分融合分析场信息和实际观测信息并考虑副高影响的精细非对称台风Bogus方法,并在MM5的伴随同化系统中引入快速辐射传输模式RTTOV8,通过四维变分同化(4DVAR)技术,加入海面风场和气压场Bogus资料及多颗卫星多条轨道上的ATOVS红外和微波卫星辐射亮温资料并考虑Noah陆面过程方案来对登陆台风韦帕进行数值模拟,结果表明,单独同化海面Bogus资料的BDA方案可间接产生初始场非对称三维环流结构和暖心结构,但对湿度场及台风周围大环境场的调整不足,台风登陆后的路径预报改善也不明显;引入陆面过程方案弥补了Bogus资料对台风登陆后路径预报的不足;加入ATOVS资料能对湿度场及台风周围环境场做出调整,重构了大量中尺度结构信息,取得更为精细的初始台风环流和温压湿场结构,保持BDA方案路径及强度预报的优势的同时,使预报的降水强度增加,降水落区发生改变。 相似文献
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基于模式约束三维变分技术的连续循环同化试验研究 总被引：3，自引：1，他引：2
由于模式约束三维变分同化技术中考虑了模式的动力和物理过程,因此能保证各物理量间的平衡关系,从而滤除由于观测资料引入导致的高频波动,减小模式与初始场的协调时间.由于能在较短时间调整到稳定状态,采用模式约束三维变分同化进行连续循环同化可用较少的计算量达到同化多时次的多种观测资料的目的.该研究利用模式约束三维变分技术,针对2006年"桑美"台风个例,进行了连续循环同化卫星云导风、QuikSCAT海面风、Bogus海平面气压的试验.在台风数值预报中往往需要使用经验构造的台风信息(如Bogus海平面气压,Bogus风场等),该研究采用了模式约束三维变分同化技术同化Bogus海平面气压.由于模式约束三维变分同化技术充分考虑了各物理量间的约束,因此通过同化Bogus海平面气压也调整了初始场中相应的高度场、温度场、风场等变量,使得初始场中的台风涡旋具有较强的协调性,提高了对台风的模拟能力.采用AVN模式6小时间隔的分析场作为侧边界,2006年8月8日20时的分析场作为初估场,文中对8月8日20时到9日05时"桑美"台风的观测资料进行了连续循环同化.采用连续循环同化后台风路径的模拟精度得到了显著提高,对台风降水结构等的模拟也得到了改善. 相似文献
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非对称台风风场的动力初始化应用研究 总被引：2，自引：2，他引：0
在对比NCAR-AFWA三维Bogus(虚拟)风场及风压场方案的基础上,虚拟台风模型中的水平风场采用考虑台风移速、移向、摩擦等客观因素的非对称方案,垂直风场采用考虑高空反气旋环流的风廓线方案,然后利用Nudging动力初始化技术形成新的模式初始场.最后对"云娜"台风进行数值模拟,结果表明:通过合理引入客观因子及观测事实对台风Bogus模型进行构建,并利用同化方法使各个物理量相互协调,可以使初始场与实况更加接近,从而在一定程度上提高台风路径及强度的预报水平,并对降水分布的预报效果也有所改善. 相似文献
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改进的台风初值化方案及四维变分同化的个例试验 总被引：4，自引：4，他引：0
由于洋面上常规观测资料严重不足,使得客观分析的结果难以准确地描写初始台风的热力结构和环流特征,这是造成台风数值预报误差较大的重要原因.传统的Bogus方案虽然对台风预报有很大改进,但是仍有许多不足.文中在前人研究工作的基础上,对Bogus方案进行了改进,提高了对台风强度的描述能力,并结合四维变分资料同化的方法,利用模式动力学约束,自动生成具有非对称环流结构的台风初值,最后进行了四维变分同化试验和数值模拟试验.数值结果表明:这种结合Bogus方法和四维变分同化方法的台风初值化方案对于台风的路径模拟和强度模拟均有较好的改进. 相似文献
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广州地Ⅸ的高温天气主要是受副热带高压和台风外围下沉气流的影响所致.文中采用BDA(Bogus Data Assimila-tion)方法,探讨BDA方案对广州地区台风背景条件下高温预报的改进能力.选取2005年7月中旬广州地区出现的高温天气进行研究.这是比较典型的受副热带高压和台风(海棠)共同影响造成高温的天气过程.分析有无采用BDA方案的模式初始场.结果表明:采用BDA方案同化Bogus模型可以调整台风中心位置和强度,使所得到的初始场中心位置与观测更为接近,台风强度(气压梯度力、风速)比末用Bogus的情况强,与观测值更为接近.数值模拟的结果表明,采用了BDA方案的敏感试验可以更好地预撤台风路径和台风中心强度变化,从而更好地预报高温天气,对高温区分布、日平均温度大小等的预报都有改进.文中对引起这种预报差异的原因进行了讨论,并探讨高温预报改进的可能机制.大气下沉运动的增强是高温预报改进的主要原因.敏感试验由于广州中低层大气的水汽减少,大气的下沉增强,致使天空的云量减少,对太阳短波辐射的阻挡减小,从而地面吸收热量增多,温度升高,输送给大气的感热增加,大气气温升高.采用BDA方案可以改进模式在台风"海棠"过程对广州高温的预报. 相似文献
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利用一简单的湿度发展方程，尝试用非线性最优化方法讨论降水预报中的最优初值场的获得。试验结果表明，通过非线性最优化分析方法，可以找到一最优初始场，使得模式预报结果与实际观测场一致，这为将来在实际应用中如何改善更复杂模式的初始场，提高预报准确率提供了一个很有意义的思路。 相似文献
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Based on the high-resolution Regional Ocean Modeling System(ROMS) and the conditional nonlinear optimal perturbation(CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kuroshio large meander(LM) path, and the growth mechanism of optimal initial errors was revealed. For each LM event, two types of initial error(denoted as CNOP1 and CNOP2) were obtained. Their large amplitudes were found located mainly in the upper 2500 m in the upstream region of the LM, i.e., southeast of Kyushu. Furthermore, we analyzed the patterns and nonlinear evolution of the two types of CNOP. We found CNOP1 tends to strengthen the LM path through southwestward extension. Conversely,CNOP2 has almost the opposite pattern to CNOP1, and it tends to weaken the LM path through northeastward contraction.The growth mechanism of optimal initial errors was clarified through eddy-energetics analysis. The results indicated that energy from the background field is transferred to the error field because of barotropic and baroclinic instabilities. Thus, it is inferred that both barotropic and baroclinic processes play important roles in the growth of CNOP-type optimal initial errors. 相似文献
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Jong-Seong Kug Yoo-Geun Ham Masahide Kimoto Fei-Fei Jin In-Sik Kang 《Climate Dynamics》2010,35(2-3):331-340
In this study, a new method is developed to generate optimal perturbations in ensemble climate prediction. In this method, the optimal perturbation in initial conditions is the 1st leading singular vector, calculated from an empirical linear operator based on a historical model integration. To verify this concept, this method is applied to a hybrid coupled model. It is demonstrated that the 1st leading singular vector from the empirical linear operator, to a large extent, represents the fast-growing mode in the nonlinear integration. Therefore, the forecast skill with the optimal perturbations is improved over most lead times and regions. In particular, the improvement of the forecast skill is significant where the signal-to-noise ratio is small, indicating that the optimal perturbation method is effective when the initial uncertainty is large. Therefore, the new optimal perturbation method has the potential to improve current seasonal prediction with state-of-the-art coupled GCMs. 相似文献
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ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model. 相似文献
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In this study, singular vector analysis was performed for the period from 1856 to 2003 using the latest Zebiak–Cane model
version LDEO5. The singular vector, representing the optimal growth pattern of initial perturbations/errors, was obtained
by perturbing the constructed tangent linear model of the Zebiak–Cane model. Variations in the singular vector and singular
value, as a function of initial time, season, ENSO states, and optimal period, were investigated. Emphasis was placed on exploring
relative roles of linear and nonlinear processes in the optimal perturbation growth of ENSO, and deriving statistically robust
conclusions using long-term singular vector analysis. It was found that the first singular vector is dominated by a west–east
dipole spanning most of the equatorial Pacific, with one center located in the east and the other in the central Pacific.
Singular vectors are less sensitive to initial conditions, i.e., independence of seasons and decades; while singular values
exhibit a strong sensitivity to initial conditions. The dynamical diagnosis shows that the total linear and nonlinear heating
terms play opposite roles in controlling the optimal perturbation growth, and that the linear optimal perturbation is more
than twice as large as the nonlinear one. The total linear heating causes a warming effect and controls two positive perturbation
growth regions: one in the central Pacific and the other in the eastern Pacific; whereas the total linearized nonlinear advection
brings a cooling effect controlling the negative perturbation growth in the central Pacific. 相似文献
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Study of the Optimal Precursors for Blocking Events 总被引：2，自引：0，他引：2
The precursors of dipole blocking are obtained by a numerical approach based upon a quasi-geostrophic barotropie planetary- to synoptic-scale interaction model without topography and with a localized synopticscale wave-maker. The optimization problem related to the precursors of blocking is formulated and the nonlinear optimization method is used to examine the optimal synoptic-scale initial field successfully. The results show that the prominent characteristics of the optimal synoptic-scale initial field are that the synoptic-scale wave train structures exist upstream of the incipient blocking. In addition, the large-scale low/high eddy-forcing pattern upstream of the incipient blocking is an essential precondition for the onset of dipole blocking. 相似文献
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The Combined Effect of Initial Error and Model Error on ENSO Prediction Uncertainty Generated by the Zebiak-Cane Model 
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下载免费PDF全文 Initial errors and model errors are the source of prediction errors. In this study, the authors compute the conditional nonlinear optimal perturbation （CNOP）-type initial errors and nonlinear forcing singular vector （NFSV）- type tendency errors of the Zebiak-Cane model with respect to El Nifio events and analyze their combined effect on the prediction errors for E1 Nino events. The CNOP- type initial error （NFSV-type tendency error） represents the initial errors （model errors） that have the largest effect on prediction uncertainties for E1 Nifio events under the perfect model （perfect initial conditions） scenario. How- ever, when the CNOP-type initial errors and the NFSV- type tendency errors are simultaneously considered in the model, the prediction errors caused by them are not am- plified as the authors expected. Specifically, the predic- tion errors caused by the combined mode of CNOP-type initial errors and NFSV-type tendency errors are a little larger than those caused by the NFSV-type tendency er- rors. This fact emphasizes a need to investigate the opti- mal combined mode of initial errors and tendency errors that cause the largest prediction error for E1 Nifio events. 相似文献
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Optimal Perturbations Triggering Weather Regime Transitions: Onset of Blocking and Strong Zonal Flow 总被引：1，自引：0，他引：1
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
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运用流体力学软件FloEFD对沽源单个建筑物周围的风场进行数值模拟。通过不断改变模型中计算参数的设置进行一系列模拟试验,对比模拟试验结果,并与观测资料进行比较,分析不同计算参数对模拟结果的影响,并获得适用于该模型的最佳参数。主要研究的计算参数包括计算域高度,初始网格等级,局部初始网格等级和不同平均风速剖面形式。结果表明:计算域高度从3倍建筑物高度开始,空腔区的长度、漩涡中心位置以及再发展区的边界位置基本保持稳定。随着初始网格等级的增加,空腔区的长度、再发展区的边界位置及计算时间逐渐增大。局部初始网格等级对模拟结果影响不显著。以两种不同平均风速剖面形式进行模拟,迎风漩涡长度不同,背风面影响不大。与观测资料比较显示,最优参数组合为:计算域高度为3倍建筑物高度,初始网格等级为4、局部初始网格等级为4、平均风速剖面形式为指数律。 相似文献
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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