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1.
高分辨率η模式的数值试验   总被引:12,自引:0,他引:12  
针对中尺度地形对我国天气影响的重要性,本文先后提高了REM的水平和垂直分辨率,并采用包络地形方法处理模式中尺度地形。运用常规报文资料得到初始场,对1993年8月4~5日,1994年7月12~13日的两次大暴雨个例分别进行了数值试验。结果表明,仅提高REM的水平分辨率,对降水预报有一定的改善,但多报出了几个大暴雨中心;而对模式水平及垂直分辨率同时提高后,其降水场、形势场的预报有明显的改进和提高,虚假降水中心消失。  相似文献   

2.
王铁  穆穆 《气象学报》2008,66(6):955-967
Regional-Eta-Coordinate-Model(REM)中尺度模式对中国区域性降水显示出公认的较高预报能力,建立其四维变分资料同化系统是完善该模式,进一步提高其预报效果的重要工作。本研究编写了REM模式的切线性模式和伴随模式,介绍了建立REM模式伴随系统的过程,并利用实际天气个例资料,分别对REM模式的切线性模式、伴随模式及定义的目标函数梯度进行了正确性检验,检验结果表明对REM模式的切线性模式及伴随模式编写是成功的。利用REM模式的伴随系统,对1998年06月08日00时到09日00时和2000年08月01日00时到02日00时两个实际天气个例进行了四维变分资料同化试验。从数值试验的结果分析可以看到,进行四维变分资料同化后,两个天气个例在预报结束时刻其预报结果对风场和湿度场的预报都有明显改善,对温度场和高度场的预报也有所改善。对于累积降水的预报,两个个例利用四维变分资料同化后得到的初始场进行的预报结果则有较大不同,在个例1中,变分同化后对降水中心的位置和降水强度的预报都有明显改善,预报结果更接近于观测场;个例2中,变分同化后对降水中心位置和强度的预报则没有改善,产生这种现象的原因可能是由于定义的目标函数中没有加进背景场项,也可能是由于采用的观测资料时次比较少,还需要进一步进行研究和试验。  相似文献   

3.
对区域数值模式(REM)的改进及数值试验   总被引:6,自引:2,他引:4  
针对中尺度地形对我国天气影响的重要性,对REM先后进行水平、垂直分辨率的提高,并运用常规报文资料获得初始场,运用包络地形方法获得模式所需的地形资料,对1994年7月12─13目的大暴雨个例进行了数值试验,结果表明,仅提高REM的水平分辨率,对降水预报有一定的改进和提高,但多报出了几个大暴雨中心。而对模式水平及垂直分辨率均提高后(称此模式为C模式),其降水场、形势场的预报有明显的改进和提高,虚假降水中心消失,C模式的水平、垂直分辨率基本上是协调的。  相似文献   

4.
杨燕  纪立人 《大气科学》1997,21(5):533-544
用数字滤波方法对观测资料序列进行处理,得到初始场用于T42L9全球谱模式的月预报,以去除误差增长较快的高频扰动对低频过程的影响,并且利用多时刻的观测资料提取低频过程的信息。对冬季和夏季两个不同个例进行了实验,并比较了取不同长度的观测序列,截取不同周期的过程作为初值对预报效果的影响。结果说明,经过滤波后对低频分量和平均场的预报都有较显著的改进。而且对于较长时效的预报,应保留更低频的过程(比如10 d以上周期)。最显著的改进是在第2旬。冬季个例经过滤波的初始场在第2旬对北太平洋阻塞形势的预报能力有较明显提高。  相似文献   

5.
区域初始分析误差对梅雨锋中尺度低压数值预报的影响   总被引:6,自引:0,他引:6  
以梅雨锋中尺度低压个例为研究对象,根据目标观测的思想,采用NCEP和T106再分析资料分析了区域初始分析误差对梅雨锋中尺度低压数值预报误差的影响。结果表明:区域初始分析误差对数值预报误差有重要影响,改善某些特定区域初始场质量有可能改善随后数值预报的效果。但是,区域初始分析误差对数值预报误差的影响较为复杂,它与天气类型、不同个例和区域间误差相互作用等因素密切相关。对梅雨锋中尺度低压短期数值预报有较大影响的初始分析误差与梅雨锋锋区及其附近地区的要素场关系密切,相比较而言,风场似乎更加重要一些。如果对梅雨锋带中低层风切变区及相伴低空急流区有更好的描述,这将对梅雨锋中尺度低压系统数值预报效果的改善有着积极的作用。在此基础上,就相关的目标观测设计问题作了简要讨论。  相似文献   

6.
为了提高长江中下游地区高影响天气的数值预报,利用条件非线性最优扰动(CNOP)方法,对一次长江中下游地区冬季降水个例(高影响天气事件)进行目标观测研究,并通过观测系统模拟试验(OSSE)检验了该方法确定敏感区的有效性和可行性。试验结果表明,CNOP方法可有效识别对应于高影响天气事件的敏感区。通过对敏感区进行初始场修正后,可明显改善验证区内24 h累积降水预报误差和总能量预报误差。进一步分析发现,通过改善敏感区内的初始场信息(如水汽通量场和低层冷空气活动等),使得数值模式不仅能更真实刻画该天气系统的初始结构,还能更好模拟出该天气系统随时间的演变特征,因而减少了验证区内对该天气系统的预报误差。这一结果表明可以把CNOP方法应用于长江中下游地区高影响天气事件的目标观测研究或实践中。   相似文献   

7.
杨燕  纪立人 《大气科学》1997,21(5):533-534
用数字滤波方法对观测资料序列进行处理,得到初始场用于T42L9全球谱模式的月预报,以去除误差增长较快的高频扰动对低频过程的影响,并且利用多时刻的观测资料提取低频过程的信息。对冬季和夏季两个不同个例进行了实例,并比较了取不同长度的观测序列,截取不同周期的过程作为初值对预报效果的影响。结果说明,经过滤波后对低频分量和平均场的预报都有显著的改进。而且对于较长时效的预报,应保留更低频的过程(比如10d以上  相似文献   

8.
"93.8"鲁西南大暴雨的数值试验   总被引:9,自引:9,他引:0  
针对中尺度地形对我国天气影响的重要性,对REM先后进行水平、垂直分辨率的提高,并运用常规报文资料获得初始场,采用包络地形等方法获得模式所需的地形资料,对1993年8月4 ̄5日的大暴雨个例进行了数值试验。结果表明,仅提高REM的水平分辨率,对降水预报有一定的改进和提高,但多报出了几个大暴雨中心。而模式水平及垂直分辨率均提高后(下称C模式),其降水场、形势场的预报有明显的改进和提高,虚假降水中心消失,  相似文献   

9.
GRAPES区域集合预报尺度混合初始扰动构造的新方案   总被引:3,自引:0,他引:3       下载免费PDF全文
集合预报初始扰动能否准确反映预报误差的结构特征是决定区域集合预报质量的关键因素之一。本文针对GRAPES区域数值预报模式,发展设计了一种基于资料同化思想的混合尺度初始扰动构造新方案。该方案以全球大尺度信息为背景场,区域模式预报作为观测资料,借助GRAPES三维变分同化系统,将高质量的全球大尺度信息与区域模式预报中质量较高的中小尺度信息有效融合,构造混合尺度区域集合预报初始扰动,并通过个例试验和批量试验,比较分析了新方案和原区域集合预报的性能。试验结果表明,基于资料同化构造的初始扰动能够有效融合全球大尺度信息和中小尺度天气系统的信息,其降水概率预报更具参考价值。总体上看,区域集合预报混合初始扰动新方案能够较好地改进区域集合预报质量,尤其是对高度场和温度场效果更为显著,但对风场的集合预报性能影响略小。  相似文献   

10.
针对中尺度对形对我国天气影响的重要性,对REM先后进行水平,垂直分辨率的提高,并运用常规报文资料获得初始场,运用包络地形方法获得模式所需的地形资料,对1994年7月12-13日的大暴雨个例进行了数值试验,结果表明,仅提高REM的水平分辨率,对降水预报有一定的改进和提高,但多报出了几个大暴雨中心。  相似文献   

11.
基于WRF四维变分伴随模式建立数值预报敏感初始误差计算流程并对台风北冕 (0809) 进行了分析。结果表明:基于线性化近似的伴随敏感分析方法对台风系统在24 h内适用。构造敏感初始误差的参考系数存在一个合理的取值范围,参考系数取为0.08效果最好。在初始场中去除敏感初始误差能够有效减少预报误差,改善台风路径预报效果,依据24 h预报误差计算出的敏感初始误差订正对24 h后台风数值预报效果也有明显影响。另外,敏感初始误差分布在台风中心附近,伴随台风系统环流且各物理量分布形态相似。对流层下层和中上层的敏感初始误差均对数值预报效果有所影响,对流层中上层的作用略大于对流层下层。敏感初始误差中各物理量对数值预报改善的贡献各不相同,相对而言,风场的贡献最大。  相似文献   

12.
The Regional Eta-coordinate Model(REM) has performed well in forecasting heavy rainfalls in China in recent years.A four-dimensional variational assimilation system(4DVar) is developed to improve the forecast skill of the REM.The tangent linear model and adjoint model codes are written according to thecode to coderule,and the establishment of the REM adjoint modeling system is introduced in detail in this paper.The tangent linear and adjoint models of the REM are validated against the observational data,...  相似文献   

13.
There are three common types of predictability problems in weather and climate, which each involve different constrained nonlinear optimization problems: the lower bound of maximum predictable time, the upper bound of maximum prediction error, and the lower bound of maximum allowable initial error and parameter error. Highly efficient algorithms have been developed to solve the second optimization problem. And this optimization problem can be used in realistic models for weather and climate to study the upper bound of the maximum prediction error. Although a filtering strategy has been adopted to solve the other two problems, direct solutions are very time-consuming even for a very simple model, which therefore limits the applicability of these two predictability problems in realistic models. In this paper, a new strategy is designed to solve these problems, involving the use of the existing highly efficient algorithms for the second predictability problem in particular. Furthermore, a series of comparisons between the older filtering strategy and the new method are performed. It is demonstrated that the new strategy not only outputs the same results as the old one, but is also more computationally efficient. This would suggest that it is possible to study the predictability problems associated with these two nonlinear optimization problems in realistic forecast models of weather or climate.  相似文献   

14.
Ensemble Forecast: A New Approach to Uncertainty and Predictability   总被引:8,自引:0,他引:8  
Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ensemble forecasts is to try to assimilate the initial uncertainty (initial error) and the forecast uncertainty (forecast error) by applying either the initial perturbation method or the multi-model/multiphysics method. In fact, the mean of an ensemble forecast offers a better forecast than a deterministic (or control) forecast after a short lead time (3-5 days) for global modelling applications. There is about a 1-2-day improvement in the forecast skill when using an ensemble mean instead of a single forecast for longer lead-time. The skillful forecast (65% and above of an anomaly correlation) could be extended to 8 days (or longer) by present-day ensemble forecast systems. Furthermore, ensemble forecasts can deliver a probabilistic forecast to the users, which is based on the probability density function (PDF) instead of a single-value forecast from a traditional deterministic system. It has long been recognized that the ensemble forecast not only improves our weather forecast predictability but also offers a remarkable forecast for the future uncertainty, such as the relative measure of predictability (RMOP) and probabilistic quantitative precipitation forecast (PQPF). Not surprisingly, the success of the ensemble forecast and its wide application greatly increase the confidence of model developers and research communities.  相似文献   

15.
In south China, warm-sector rainstorms are significantly different from the traditional frontal rainstorms due to complex mechanism, which brings great challenges to their forecast. In this study, based on ensemble forecasting, the high-resolution mesoscale numerical forecast model WRF was used to investigate the effect of initial errors on a warmsector rainstorm and a frontal rainstorm under the same circulation in south China, respectively. We analyzed the sensitivity of forecast errors to the...  相似文献   

16.
利用1998~2002年4~7月间欧洲、日本,2002年5~7月我国数值预报产品进行统计分析,总结出以数值预报产品为主的暴雨预报模式指标。这一模式指标,为日常预报工作中以天气学预报为主转向以数值预报为主奠定良好基础,也为预报员提供客观简捷的预报方法。通过一年的试报探索和一年的实际业务应用,其预报准确率较为理想。  相似文献   

17.
The nonlinear local Lyapunov exponent (NLLE) method is adopted to quantitatively determine the predictability limit of East Asian summer monsoon (EASM) intensity indices on a synoptic timescale. The predictability limit of EASM indices varies widely according to the definitions of indices. EASM indices defined by zonal shear have a limit of around 7 days, which is higher than the predictability limit of EASM indices defined by sea level pressure (SLP) difference and meridional wind shear (about 5 days). The initial error of EASM indices defined by SLP difference and meridional wind shear shows a faster growth than indices defined by zonal wind shear. Furthermore, the indices defined by zonal wind shear appear to fluctuate at lower frequencies, whereas the indices defined by SLP difference and meridional wind shear generally fluctuate at higher frequencies. This result may explain why the daily variability of the EASM indices defined by zonal wind shear tends be more predictable than those defined by SLP difference and meridional wind shear. Analysis of the temporal correlation coefficient (TCC) skill for EASM indices obtained from observations and from NCEP’s Global Ensemble Forecasting System (GEFS) historical weather forecast dataset shows that GEFS has a higher forecast skill for the EASM indices defined by zonal wind shear than for indices defined by SLP difference and meridional wind shear. The predictability limit estimated by the NLLE method is shorter than that in GEFS. In addition, the June-September average TCC skill for different daily EASM indices shows significant interannual variations from 1985 to 2015 in GEFS. However, the TCC for different types of EASM indices does not show coherent interannual fluctuations.  相似文献   

18.
Numerical experiments of adjoint variational assimilation have been performed using the knownLorenz system.With the increase of sensitivity of model's initial values,it is more and more difficultto use the adjoint method to get the initial values which are consistent with the dynamics of the fore-cast model.Under some circumstances the algorithm completely fails.This shows that four-dimen-sional assimilation is related to the limit of predictability.On the other hand.with the increase ofmodel equation's error,the result of variational assimilation may become worse and worse so that theprediction has no meaning.But if the model parameters are corrected when variational assimilation ismade,the forecast results can be greatly improved based on Lorenz model.  相似文献   

19.
为了提供有价值且可靠的概率(或者不确定性)预报,最新的全球集合预报系统已在美国国家环境预报中心日常业务运行,以满足社会需求。通过对各个关键要素的概率预报统计检验,可为广大用户提供这些概率预报的信心指数。但是预报(或集合预报)能力不仅取决于我们使用的预测要素,而且与时间和空间分辨率,极端事件或者高影响天气,以及预报时效有关。以大尺度天气系统预报为例,通常选择北半球500 hPa位势高度距平相关指数或概率指数表征模式的预报能力。如参照北半球500 hPa位势高度的距平相关指数(60%AC)或概率预报技巧指数(25%CRPSS),美国全球集合预报系统能够提供大约10 d的技巧预报。从全球集合预报系统输出的各预报要素,满足不同时空尺度需求的角度进行讨论,其可预报性(或预报极限)能够为模式研发人员、一线预报员和用户提供参考。尤其是对大气可预报性的深入研究,对于从科学与技术角度全面提升数值预报系统水平非常重要。当能够确定可预报性(或是预报误差)的真实来源时,科学家(包括模式研发人员)就能够有针对性地修改与完善。将传统的可预报性研究与改进的能够更客观地表述预报不确定性的集合预报相结合,所得可预报性将提供另一种有价值的参考。可预报性研究总体表明,全球集合预报系统对行星波、大尺度和天气尺度的系统(或者过程)可能分别具备约15、12、10 d的预报能力。对于热带天气过程的预报,如果进一步改善模式偏差和物理参数化过程,其MJO(Madden-Julian Oscillation)预报技巧可以延长至32.5 d。  相似文献   

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