共查询到20条相似文献，搜索用时 390 毫秒
1.
An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result. 相似文献
2.
Focusing on the role of initial condition uncertainty,we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC)Rammasun(1409),which is the strongest TC to have made landfall in China during the past 50 years.Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty,particularly for TC intensity.This uncertainty increases with forecast time,with a more rapid and significant increase after 24 h.The predicted TC develops slowly before 24 h,and at this stage the TC in the member forecasting the strongest final TC is not the strongest among all members.However,after 24 h,the TC in this member strengthens much more than that the TC in other members.The variations in convective instability,precipitation,surface upward heat flux,and surface upward water vapor flux show similar characteristics to the variation in TC intensity,and there is a strong correlation between TC intensity and both the surface upward heat flux and the surface upward water vapor flux.The initial condition differences that result in the maximum intensity difference are smaller than the errors in the analysis system.Differences in initial humidity,and to a lesser extent initial temperature differences,at the surface and at lower heights are the key factors leading to differences in the forecasted TC intensity.These differences in initial humidity and temperature relate to both the overall values and distribution of these parameters. 相似文献
3.
Improving multi-model ensemble probabilistic prediction of Yangtze River valley summer rainfall 总被引：1，自引：0，他引：1
Seasonal prediction of summer rainfall over the Yangtze River valley(YRV) is valuable for agricultural and industrial production and freshwater resource management in China, but remains a major challenge. Earlier multi-model ensemble(MME) prediction schemes for summer rainfall over China focus on single-value prediction, which cannot provide the necessary uncertainty information, while commonly-used ensemble schemes for probability density function(PDF) prediction are not adapted to YRV summer rainfall prediction. In the present study, an MME PDF prediction scheme is proposed based on the ENSEMBLES hindcasts. It is similar to the earlier Bayesian ensemble prediction scheme, but with optimization of ensemble members and a revision of the variance modeling of the likelihood function. The optimized ensemble members are regressed YRV summer rainfall with factors selected from model outputs of synchronous 500-h Pa geopotential height as predictors. The revised variance modeling of the likelihood function is a simple linear regression with ensemble spread as the predictor. The cross-validation skill of 1960–2002 YRV summer rainfall prediction shows that the new scheme produces a skillful PDF prediction, and is much better-calibrated, sharper, and more accurate than the earlier Bayesian ensemble and raw ensemble. 相似文献
4.
A Multivariate Empirical Orthogonal Function-Based Scheme for the Balanced Initial Ensemble Generation of an Ensemble Kalman Filter 
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下载免费PDF全文 The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly. 相似文献
5.
Extreme rainfall is common from May to October in south China. This study investigates the key deviation ofinitial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22, 2020 in Guangdong Province, south China by comparing ensemble members with different performances. Based on the rainfall distribution and pattern, two types are selected for analysis compared with the observed precipitation. Through the comparison of the thermal and dynamic fields in the middle and lower layers, it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution. The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case. Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion. This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts. 相似文献
6.
Sun et al., (1983) have given some favourable environmental conditions and have shown that there are four common features in convective rainstorms. In this paper, an important process of evolution of cloud systems was revealed when heavy rainfall occurred based on the diagnostic analysis of heavy rainfall cases. When the different cloud systems merge into a large one, the mesoscale heavy rainfall occurs and enhances. In other words, the process of evolution of cloud systems emphasized in this paper is the process of interaction between two cloud systems when the heavy rainfall occurs. The favourable environmental condition is also investigated. 相似文献
7.
Soil moisture retrieval from satellite images and its application to heavy rainfall simulation in eastern China 总被引：7，自引：4，他引：3
The soil water index (SWI) from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient (CORR), root-mean-square-error (RMSE) and bias (BIAS) shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture (NCEP) in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13–14 June, 18–22 June, and 21–26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21–26 July shows that the update of soil moisture initial conditions can improve the model’s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13–14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy rainfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI. 相似文献
8.
Application of ATOVS microwave radiance assimilation to rainfall prediction in Summer 2004 总被引：3，自引：0，他引：3
Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A （AMSU-A） and Unit B （AMSU-B） radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder （ATOVS） microwave radiance assimilation, is employed to simulate some heavy rainfall cases. The experiment results show that the assimilation of AMSU-A （B） microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A （B） microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China. 相似文献
9.
A Diagnostic and Numerical Study on a Rainstorm in South China Induced by a Northward-Propagating Tropical System 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 A strong cyclonic wind perturbation generated in the northern South China Sea （SCS） moved northward quickly and developed into a mesoscale vortex in southwest Guangdong Province, and then merged with a southward-moving shear line from mid latitudes in the period of 21-22 May 2006, during which three strong mesoscale convective systems （MCSs） formed and brought about torrential rain or even cloudburst in South China. With the 1° ×1° NCEP （National Centers for Environment Prediction） reanalysis data and the Weather and Research Forecast （WRF） mesoscale model, a numerical simulation, a potential vorticity inversion analysis, and some sensitivity experiments are carried out to reveal the formation mechanism of this rainfall event. In the meantime, conventional observations, satellite images, and the WRF model outputs are also utilized to perform a preliminary dynamic and thermodynamic diagnostic analysis of the rainstorm systems. It is found that the torrential rain occurred in favorable synoptic conditions such as warm and moist environment, low lifting condensation level, and high convective instability. The moisture transport by strong southerly winds associated with the rapid northward advance of the cyclonic wind perturbation over the northern SCS provided the warm and moist condition for the formation of the excessive rain. Under the dynamic steering of a southwesterly flow ahead of a north trough and that on the southwest side of the West Pacific subtropical high, the mesoscale vortex （or the cyclonic wind perturbation）, after its genesis, moved northward and brought about enormous rain in most parts of Guangdong Province through providing certain lifting forcing for the triggering of mesoscale convection. During the development of the mesoscale vortex, heavy rainfall was to a certain extent enhanced by the mesoscale topography of the Yunwu Mountain in Guangdong. The effect of the Yunwu Mountain is found to vary under different prevailing wind directions and intensities. The location o 相似文献
10.
An Analysis of a Meso-β System in a Mei-yu Front Using the Intensive Observation Data During CHeRES 2002 总被引：3，自引：0，他引：3
The conventional and intensive observational data of the China Heavy Rain Experiment and Study (CHeRES) are used to specially analyze the heavy rainfall process in the mei-yu front that occurred during 20-21 June 2002, focusing on the meso-β system. A mesoscale convective system (MCS) formed in the warm-moist southwesterly to the south of the shear line over the Dabie Mountains and over the gorge between the Dabie and Jiuhua Mountains. The mei-yu front and shear line provide a favorable synoptic condition for the development of convection. The GPS observation indicates that the precipitable water increased obviously about 2-3h earlier than the occurrence of rainfall and decreased after that. The abundant moisture transportation by southwesterly wind was favorable to the maintenance of convective instability and the accumulation of convective available potential energy (CAPE). Radar detection reveals that meso-β and -γ systems were very active in the MαCS. Several convection lines developed during the evolution of the MαCS, and these are associated with surface convergence lines. The boundary outflow of the convection line may have triggered another convection line. The convection line moved with the mesoscale surface convergence line, but the convective cells embedded in the convergence line propagated along the line. On the basis of the analyses of the intensive observation data, a multi-scale conceptual model of heavy rainfall in the mei-yu front for this particular case is proposed. 相似文献
11.
北京“7.21”暴雨的不稳定性及其触发机制分析 总被引：10，自引：3，他引：7
本文利用WRF模拟的高分辨率资料对2012年7月21日北京特大暴雨过程的对流不稳定和条件对称不稳定性及其触发和维持机制进行了诊断分析。分析结果表明:(1)在临近暴雨发生时刻及暴雨初期, 大气低层主要以对流不稳定为主, 随后对流触发, 不稳定性减弱, 而低空急流和湿斜压性的增强, 使得条件性对称不稳定加强, 维持和加强了暴雨的不稳定性。(2)分析表明, 在暴雨过程中主要由于较强的水平风的垂直切变造成湿位涡的斜压分量异常, 从而导致条件性对称不稳定的产生。(3)本文分别对暴雨发生过程中的对流不稳定与条件对称不稳定的触发机制进行了分析, 主要结论如下:暴雨初期对流性降水阶段, 切变线上有利的垂直上升环境与地形的强迫抬升相互配合, 触发了对流性降水。另外, 北京上空的干冷空气入侵, 也增强了大气的对流不稳定性, 更易触发对流;对称不稳定导致的降水阶段, 主要是由于北京上空冷暖空气的长期对峙, 冷空气逐渐深入到暖湿空气下方, 使得暖湿气团沿冷气团爬升, 从而触发对称不稳定, 造成持续性降水。此次暴雨过程中0900～1300 UTC时刻暴雨增幅的重要原因是0900 UTC北京风向突变, 转为偏东风, 且风速骤增, 北京西北侧的喇叭口状的地形的强迫抬升作用, 与上空750 hPa移来的切变线上的垂直运动相互叠加, 形成中尺度涡旋, 产生了强烈的上升运动, 触发不稳定, 产生大暴雨。 相似文献
12.
Mesoscale predictability of mei-yu heavy rainfall 总被引：1，自引：0，他引：1
Recently reported results indicate that small amplitude and small scale initial errors grow rapidly and subsequently contaminate short-term deterministic mesoscale forecasts. This rapid error growth is dependent on not only moist convection but also the flow regime. In this study, the mesoscale predictability and error growth of mei-yu heavy rainfall is investigated by simulating a particular precipitation event along the mei-yu front on 4-6 July 2003 in eastern China. Due to the multi-scale character of th... 相似文献
13.
Sensitivity simulations are conducted in AREM (Advanced Regional Eta-Coordinate numerical heavy-rain prediction Model) for a torrential precipitation in June 2008 along South China to investigate the effect of initial uncertainty on precipitation predictability. It is found that the strong initial-condition sensitivity for precipitation prediction can be attributed to the upscale evolution of error growth. However, different modality of error growth can be observed in lower and upper layers. Compared with lower-level, significant error growth in the upper-layer appears over both convective area and high jet stream. It thus indicates that the error growth depends on both moist convection due to convective instability and the wind shear associated with dynamic instability. As heavy rainfall process can be described as a series of energy conversion, it reveals that the advection-term and latent heating serve as significant energy sources. Moreover, the dominant source terms of error-energy growth are nonlinearity advection (ADVT) and difference in latent heating (DLHT), with the latter being largely responsible for the rapid error growth in the initial stage. In this sense, the occurrence of precipitation and error-growth share the energy source, which implies the inherent predictability of heavy rainfall. In addition, a decomposition of ADVT further indicates that the flow-dependent error growth is closely related to the atmospheric instability. Thus the system growing from unstable flow regime has its intrinsic predictability. 相似文献
14.
以GRAPES中尺度有限区模式作为试验模式, 从模式的不确定性方面来构造中尺度的集合预报, 重点考虑物理因子与初始条件的扰动作用。针对2004年7月10日北京城区的突发性暴雨过程进行了36 h的集合预报试验。结果表明:GRAPES模式可有效地捕捉到中尺度过程的信息; 中尺度集合预报是可行的, 可改进中尺度暴雨过程落区、强度的预报; 不同集合方案的预报结果各不相同, 同一方案各个成员的预报结果也有差异, 即存在适宜的离散度; 在离散度分析中发现在北京附近存在一个明显大值区, 且在大气中低层的垂直结构表现出一致性, 表明这一区域的预报不确定性很大。从集合检验结果中得到:单纯考虑模式物理扰动来构造中尺度集合预报系统有一定难度, 当加入初始场不确定信息后, 同时考虑模式的不确定性和初始场的不确定性, 有助于捕捉更多的中尺度系统的不确定信息, 有助于构造更为有效的中尺度集合预报系统。 相似文献
15.
引起舟曲特大泥石流灾害的"8·8"暴雨过程中尺度特征分析 总被引：3，自引：3，他引：0
利用常规气象资料以及FY-2E气象卫星云图、多普勒天气雷达资料和NCEP每6h一次的1°×1°格点资料,采用天气学诊断分析的方法,对2010年8月7—8日出现在甘肃省舟曲县的一次局地突发性致泥石流暴雨进行了诊断分析。结果表明:此次暴雨是在高空短波槽、东风倒槽、低涡切变线、副热带高压和地面冷空气的共同作用下发生的。对流云团发展生成MCS是暴雨发生的直接原因。对流云降水回波的发展和增强与降水强度的变化有很好的对应关系。来自孟加拉湾和东海的暖湿空气是此次暴雨的主要水汽来源。中低层辐合,高层辐散的配置和垂直涡度的显著增大,为本次暴雨的发生提供了必要的动力条件。暴雨中心位于700 hPa等假相当位温线密集带的西南侧边缘,暴雨是伴随着对流有效位能和大量不稳定能量的有效释放而发生的。倾斜涡度的活跃发展,条件性对称不稳定机制的形成可能是导致此次暴雨发生的主要触发机制。 相似文献
16.
从天气系统背景、FY-2C卫星产品、水汽通量分布特征和大气稳定度特征等方面,分析了受台风低压倒槽与东移锋面云系的共同影响,于2005年7月21日夜间到23日邯郸市出现的大范围的暴雨天气,结果发现:500hPa槽前中尺度切变线是直接影响产生暴雨的重要系统;地形作用使迎风坡降水增强;中尺度对流云团和雨团关系密切,暴雨中心位于OLR和TBB低值区下面;西部山区的暴雨区水汽主要来源于南海、东海,东部平原大暴雨水汽主要来源于南海;暴雨区上空低层为对流不稳定,高层为对称不稳定。 相似文献
17.
新疆位于半干旱地区,2007年7月13—18日新疆沿天山一带多站出现暴雨。利用每分钟与小时降水资料、常规地面与高空观测资料、NCEP 1°×1°再分析资料、静止卫星云图资料与雷达资料进行分析,重点考察2007年7月16—17日乌鲁木齐暴雨过程 (7·17暴雨) 的天气尺度及中尺度特征,并与1996年同期暴雨过程以及我国东部暴雨过程进行对比。结果表明:该降水是一次大尺度斜压过程,中亚低涡是该暴雨过程的主要影响系统,但其位置、形态与强度均不同于1996年过程;干冷空气侵入加强了大气的对流性不稳定,对暴雨的加强和发展起重要作用;该暴雨过程的水汽主要来自于青藏高原东部—甘肃西部一线以及南疆北部;该暴雨过程中有明显的γ-中尺度对流雨团发生,径向速度辐合可能是γ-中尺度对流雨团的重要触发机制。 相似文献
18.
2016年7月31日至8月1日新疆伊犁河谷发生了一次极端强降水事件,多站突破降水极值。利用NCEP/NCAR 0.25°×0.25°再分析资料、中国地面卫星雷达三源融合逐小时降水产品及国家基本地面观测站逐时降水资料,通过天气研究和预报（WRF）数值模拟和诊断分析强降水期间大气的不稳定性及其触发机制,证实了不同尺度系统相互作用以及复杂地形的影响是干旱、半干旱地区极端暴雨形成的重要因子,并得出以下结论:（1）降水前河谷低层高对流有效位能积累,低层锋面东移触发对流有效位能释放,造成河谷第一阶段短时强降水天气;前期对流性降水释放湿对流不稳定能量,低层大气对称不稳定性逐渐增强,在对称不稳定作用下维持和加强了伊犁河谷第二阶段强降水天气。（2）第一强降水阶段期间大气低层为对流不稳定性层结,降水初期和第二阶段强降水期间大气均为条件对称不稳定性层结,对称不稳定的产生主要来自于湿位涡斜压分量（Mpv2）,其中降水初期低层Mpv2变化由大气的湿斜压性和低层水平风的垂直切变所造成,第二阶段强降水低层Mpv2变化主要由大气湿斜压性造成。（3）第一阶段强降水期间,低层锋面和地形抬升,垂直运动迅速发展,造成河谷南、北部山前降水;河谷东侧中尺度气旋在地形阻挡下稳定少动,是东部地区短时强降水天气发生的直接启动机制。第二阶段强降水期间,中、低层锋区叠加爬坡,冷锋锋生,中、低层风场辐合区叠加,河谷东北部形成垂直环流圈,上升运动进一步发展,是造成河谷第二阶段暴雨的重要原因。 相似文献
19.
利用NCEP 1°×1°再分析资料,应用能量天气学方法对发生在2015年8月14日的川西平原暖区暴雨进行了分析。结果表明,总能量在8月14日经历了在上午积聚和午后释放的过程,并且随着时间由北向南增加,这和雨带从成都往眉山、乐山移动一致。总能量极大值14时出现在30°N附近,这和强降雨中心午间出现在眉山吻合。14日白天潜热能和总能量变化趋势一致,且不同时段变化值接近,潜热能的变化是导致总能量变化的主要因子,潜热能是此次川西平原暖区暴雨的主要贡献者。川西平原潜热能明显增大,有利于出现降水,潜在不稳定区和雨区有较好的对应关系。饱和能差较小,对流不稳定能量增加,有利于出现降水。14日14时对流不稳定能量和潜在不稳定能量显著增大,能量平衡高度达到200h Pa附近,导致成片暴雨区的出现。 相似文献
20.
两次暴雨过程模拟对陆面参数化方案的敏感性研究 总被引：1，自引：0，他引：1
选取发生在江西和福建境内的两次暴雨个例,利用NCEP再分析资料在对暴雨发生前、后的环境场和物理量场进行诊断和对比分析的基础上,采用中尺度模式WRF V3.3,通过数值模拟探讨了陆面过程对两次暴雨过程的可能影响及其相关的物理过程。结果表明,2012年5月12日江西大暴雨主要受大尺度环流和中尺度天气系统影响,具有范围大、持续时间长等特点,属于大尺度降水为主的暴雨;而2011年8月23日福建暴雨发生在副热带高压控制下的午后,局地下垫面强烈的感热和潜热通量使低层大气不稳定性增强,触发了此次对流性降水为主的暴雨。通过资料诊断分析,可以判断陆面过程对福建暴雨个例的影响程度明显强于江西暴雨个例。通过关闭地表通量试验发现,陆面过程对暴雨模拟十分重要,尤其是对于该个例中对流性降水的发生起到关键性的作用。通过陆面参数化方案的敏感性试验发现,两次暴雨过程对陆面参数化方案均较为敏感。江西暴雨对陆面过程的敏感性主要体现在对流降水的模拟上,而福建暴雨则体现在大尺度降水的模拟方面,即福建暴雨对陆面参数化方案的敏感性强于江西暴雨。敏感性产生机制与降水类型关系紧密,大尺度降水对陆面过程的敏感性主要来源于不同参数化模拟的中高空对流系统的差异,而对流降水的敏感性则与不同参数化模拟的地表通量的差异有关。通过陆面参数的扰动试验进一步发现,相比于地表粗糙度和最小叶孔阻抗,土壤孔隙度和地表反照率则是影响对流降水对陆面过程敏感的关键因子,这在本质上与地表通量是否受到扰动有关。地表通量较风场而言,受扰动引起变化的空间范围广、时间响应快,变化具有明显规律性。所得结果可为深入理解陆面过程影响暴雨等天气过程和改进数值模式对暴雨的模拟能力提供一定的参考。 相似文献