水汽场初值调整及其对华南降水预报贡献的研究

该文利用GMS多通道气象卫星资料推导得到的降水资料估算出的加热率, 作为非绝热的非线性正规模初始化过程中的非绝热强迫项, 进行风压场的初值调整, 再采用一个与模式中的对流参数化方案相反的逆运算方案, 进行水汽场的初值调整.以保证初始时刻按模式的物理参数化方案计算得到的加热率与由卫星推导的加热率一致. 这一方法在非绝热的非线性正规模初值化的框架中, 使初始时刻的水汽场得到调整.既实现了传统的初始化目标, 又提高了模式对降水的短时预报效果.对华南的两个个例的试验结果表明该文的方法是有效的.     

有限区域非线性正规波初值化方法实验与比较

本文以一个有限区域六层斜压原始方程模式为基础，实现了非线性正规波初值化方案，并做了２４小时积分预报实验，将非线性正规波初值化方案和平衡初值及实测风初值方案积分结果进行了比较。结果表明；非线性正规波初值化方案和对初始场个性较小，初值化后风压场配置合理；积分初期能迅速抑制重力波高频振荡，使模式计算稳定；２４小时形势预报较实测初值预报结果好得多，高层形势预报比平衡初值有改进，降水落区远比另外两种方案好。     

南海热带气旋路径集合预报试验

利用3种不同模式的初始资料，通过它们生成得到16个不同的初始场，分别对2004年南海及其周边地区9个热带气旋个例进行集合预报试验，最后筛选得到了7个南海热带气旋初值集合成员，由此初步探讨了南海热带气旋初值集合成员的生成方法。结果表明，采用不同模式的初始资料生成得到初值集合成员的方法用于集合预报，对南海热带气旋路径预报有一些明显的改进。     

卫星资料在模式初值中的初步应用研究

运用物理初值化方法,将气象卫星资料引入模式初始场,使初始场向观测场逼近,试图改进由于初始资料不完善而造成的模式积分前期降水量偏少的现象。应用ARPS中尺度模式对天津地区的一次强降水天气过程进行了数值模拟对比试验,结果表明,加入卫星观测资料后,部分卫星观测为对流云区,水汽和云水物质的水平和垂直分布进行了较为明显的调整,模式的临近短时降水预报也有明显增强的趋势。可判断出模式的初始状况更接近观测实际,对提高中小尺度天气系统的短期和临近预报的准确率有积极作用。     

GRAPES业务全球集合控制预报初值的动力升尺度方法

以生成GRAPES全球集合预报业务系统的控制预报初值为目的,基于GRAPES全球模式,开展了控制预报初值生成方法研究,发展了高分辨率初值动力升尺度方法,并检验了不同方法的可行性。通过对比不同方法产生的初始场形态,证实了仅仅对高分辨率初始场进行二维水平插值存在不足,基于静力学方程对Exner气压变量进行三维插值至关重要。结果表明,动力升尺度方法利用静力平衡关系,对全场的温压场进行调整,使之协调平衡,可以改善二维水平插值方法导致的初始位势高度场和温度场的噪音问题,产生适用于GRAPES全球集合预报业务系统的控制预报初值。     

数字滤波初值化方案的数值实验

本文以一个有限区域16层斜压原始方程模式为基础,对数字滤波初值化方案进行了数值试验,并与平衡初值及实测风初值等方案的积分结果进行了比较、结果表明：数字滤波初值化能有效地滤掉初始场中的高频重力波和小尺度扰动,使客观分析质量得到明显改进;该方法易于引入非绝热过程,能有效抑制积分初期的Spinup现象;形势预报和降水预报均较其它方案有所改进。     

物理初值化在台风数值天气预报中的应用试验

根据P.R.Julian(1984)的物理初值化方法，利用有限区数值预报模式，针对台风系统的预报做了物理初值化试验。结果表明，物理初值化不但可以改善台风、低压和副高区域的初始流场形势以及初始降水率，而且可以改善台风强度的发展变化过程和路径的预报，是一种有效可行的方法。     

华南暖区暴雨预报的模式初始场质量敏感性分析北大核心

本文利用高分辨率中尺度数值预报模式WRF和两组再分析资料,在研究不同模式初值对华南暖区暴雨预报质量差异明显的基础上,利用合成初值方法进行了模式初值对暖区暴雨预报的敏感性数值试验研究,讨论了模式初始场关键物理量对暖区暴雨预报质量的影响,重点开展了模式初值湿度场质量对华南暖区暴雨降水预报的敏感性分析。结果表明:模式初始场质量的较小差异,可显著影响本次华南暖区暴雨预报的降水强度、降水落区以及降水发生时间等的质量。初始水汽场对暖区暴雨预报影响最大,也最为敏感,是准确预报对流单体的发生发展以及地面强降水的基础。风场和温度场对暖区暴雨预报的影响相对较小。对流层低层较强的风速辐合是本次暖区暴雨强对流单体触发、生成和加强发展以至产生暖区强降水的物理基础。     

地形作用对月际长期数值预报效果的影响

利用改进的Ｔ４２Ｌ１０月长期数值预报谱模式，以１９９２年８月３１日国家气象中心日常客观分析资料为初始场，在模式中分别就考虑和不考虑地形两种情形对当所９月北半球环流形势进行了模拟预报，并对比分析研究了地形作用对月际长期数值预报效果的影响。改进的Ｔ４２Ｌ１０谱模式考虑了较完整的物理过程，同时具有以下特点：（１）非线性平衡方程初值化和σ面上模式初值精度的提高；（２）改进了模诊断云和模式水汽场方法；（３）     

牛顿松弛方法的初值化与试验比较

本文采用一个有限区域数值预报模式，在平衡风和实测风初值的基础上引进和试验了牛顿松弛方法，并同单纯的平衡风初值及实测风初值作了比较，结果发现方法对初始场及总体预报结果均有明显改进。     

Organization of convection and monsoon forecasts

Summary In this paper we address the issue of monsoon forecasts in relation to the organization of convection. Given a physical initialization procedure, within a data assimilation, it is possible to use the detailed distribution of rainfall from mesoconvective precipitating elements to define the initial state of a global model. If that is carried out using a very high resolution model then the initial state can carry within it an organization of convection within the resolvable scales. Then the impact of physical initialization on the maintenance and prediction of tropical weather such as the monsoon can be determined. Lacking such an initialization, one can expect the convectively driven energetics to be biased, and a slow degradation of the forecasts can follow. Several examples of forecasts at different resolutions are discussed here. The main findings of this study are that improved forecast results are obtained when physical initialization is invoked where the observed rain and the model resolution are comparable, i.e. the footprint of the highest resolutions rainfall estimates obtained from satellite based data sets (principally we use the SSM/I instrument over the oceans). At this resolution, we note that the model is able to carry an organization of convection in the initialization and in the forecasts through the medium-range time scale.We have compared our results of monsoon studies at a resolution T255 with those at resolution T62. The transform grid separation at the resolution T255 is approximately 50 km and at the resolution T62, it is approximately 200 km. We find that the model at the higher resolution (T255) performs better and has more realistic energy conversions for the convectively driven synoptic scale monsoon.An organization of convection, at the synoptic scales, is not seen in the forecasts at lower resolutions, T62, where the rainfall patterns are generally much broader and tend to be more zonal. Such organization appears more realistic at the resolution T255. Variances of the energy conversion, calculated in the two-dimensional spectral space, from physically initialized short range forecasts at the higher resolution are seen to be largest on the scales of the monsoon. Similar calculations for the reanalyzed fields at lower resolutions show the spectral distribution of variances to be biased towards local Hadley scale overturnings.With 12 Figures     

A Multivariate Empirical Orthogonal Function-Based Scheme for the Balanced Initial Ensemble Generation of an Ensemble Kalman Filter

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.     

ON USE OF LHN METHOD TO ASSIMILATE THE INTENSIFIED SURFACE PRECIPITATIONS FOR GRAPES_MESO MODEL INITIALIZATION

The quantitative precipitation forecast (QPF) in very-short range (0-12 hours) has been investigated in this paper by using a convective-scale (3km) GRAPES_Meso model. At first, a latent heat nudging (LHN) scheme to assimilate the hourly intensified surface precipitation data was set up to enhance the initialization of GRAPES_Meso integration. And then based on the LHN scheme, a convective-scale prediction system was built up in considering the initial “triggering” uncertainties by means of multi-scale initial analysis (MSIA), such as the three-dimensional variational data assimilation (3DVAR), the traditional LHN method (VAR0LHN3), the cycling LHN method (CYCLING), the spatial filtering (SS) and the temporal filtering (DFI) LHN methods. Furthermore, the probability matching (PM) method was used to generate the QPF in very-short range by combining the precipitation forecasts of the five runs. The experiments for one month were carried out to validate the MSIA and PM method for QPF in very-short range. The numerical simulation results showed that: (1) in comparison with the control run, the CYCLING run could generate the smaller-scale initial moist increments and was better for reducing the spin-up time and triggering the convection in a very-short time; (2) the DFI runs could generate the initial analysis fields with relatively larger-scale initial increments and trigger the weaker convections at the beginning time (0-3h) of integration, but enhance them at latter time (6-12h); (3) by combining the five runs with different convection triggering features, the PM method could significantly improve the QPF in very-short range in comparison to any single run. Therefore, the QPF with a small size of combining members proposed here is quite prospective in operation for its lower computation cost and better performance.     

Cyclone track prediction by a quasi-Lagrangian limited area model

Summary. ?Cyclone track predictions in the Indian seas (Bay of Bengal and Arabian Sea) with a quasi-Lagrangian model (QLM) have been attempted. QLM has a horizontal resolution of 40 km and 16 sigma levels in the vertical. It is integrated in a domain of about 4400 × 4400 km². A new initialization procedure to provide initial fields for running the model has been designed. The initialization procedure consists of updating the global model forecasts, used as first guess, provided by the National Center for Medium Range Weather Forecasting (NCMRWF), New Delhi. A new version of IMD’s operational optimum interpolation scheme has been created to suit the QLM grid structure. Lateral boundary conditions are computed from the extended forecasts of NCMRWF. The track forecasts in each case show a reasonable skill of the forecast model in predicting the direction of movement within acceptable limits of forecast errors, which are comparable to some of the best models operated by advanced NWP centers of the world. Even the recurving storms are well predicted. Evolution of the vertical motion fields are also studied which reveal some interesting features, which are described in detail in the text. The composited vertical motion fields are projected against observed rainfall distribution, which show a good spatial correspondence. Received August 9, 2001; revised March 12, 2002; accepted June 17, 2002 Published online: May 8, 2003     

云物理初始化对一次强对流天气数值预报的影响研究

基于第二代华东快速更新循环同化预报模式系统,针对2015年4月28日华东强对流天气,分析了云初始化对强对流数值预报的作用和影响。有无云初始化试验对比结果表明,在循环系统中使用云初始化,能够显著提高0~6 h的降水预报评分,强降水的位置预报更接近实况。云初始化能较好地改善初始场水凝物的质量分布,提供较准确的相关对流系统的初始信息,改进强对流区域内水凝物的预报效果,有效避免了模式初始阶段的降水滞后现象,缩短了模式由于初始微物理信息缺失引起的“spin-up”时间。而积分6 h以后的结果与无云初始化的结果差别不大。      

Impact of physical initialization on cloud forecasts

Summary The impact of initial data on cloud forecasts by the Florida State University Global Spectral Model (FSUGSM) has been investigated. This work has shown that improving the information content of the initial data by physical initialization has a very strong, positive impact on cloud forecasts. Model spin-up of clouds is considerably reduced. There is an overall better representation of high, middle, low, and total clouds over the tropics and there is a discernible improvement in the prediction of clouds. A strong correlation between cloud shortwave forcing and longwave forcing has been noted in model forecasts with the physically initialized data. This result compares very well with observations from the Earth Radiation Budget Experiment (ERBE).With 10 Figures     

A Bogus Typhoon Scheme and Its Application to a Movable Nested Mesh Model

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数字滤波初始化(DFI)在高水平分辨率模式中的应用

数字滤波初始化应用的前提假设之一是不平衡重力惯性波在频率谱上与有天气意义的波动不重叠。随着水平分辨率的不断提高,数值模式能够解析的重力波具有波长更短、频率更高的性质,模式中有天气意义的波动与高频噪声的界线更加模糊,因此,数字滤波初始化在高分辨率模式中的应用性能尚未明确。以一次深对流过程为例,在3 km水平分辨率条件下采用不同滤波参数配置进行数字滤波初始化试验,试图对高水平分辨率预报初始场中高频噪声特征、如何区分具有天气意义的高频信号和虚假噪声、数字滤波初始化在数值预报模式(WRF)高水平分辨率条件下的应用性能等一系列相关问题给出初步的认识。试验结果表明,在针对高分辨率模式进行数字滤波初始化时,原有应用于低分辨率模式的初始化配置参数已不适用,必须根据高分辨率噪声的特点重新设计相应的滤波方案。即使在"无噪声"状态下,有天气意义的信息在模式中也具有与虚假高频噪声一致的表现形式,即大的地面气压变化倾向。数字滤波初始化的确能对特定切断频率的高频振荡进行滤波,但无法区分其性质究竟是具有天气意义的高频信号,还仅仅只是虚假的高频噪声。如果要达到滤除初始场中高频噪声的理想效果、并且消除积分过程中的高频振荡,必须延长滤波时间窗,但这是以增加额外的积分时间、以及有可能损害气象上有意义的波动为代价的。滤波效果越显著,滤波结果对初始场的改变越大,这两个方面实质上是有冲突的,因此,在应用数字滤波初始化时必须在滤波效果可接受和保证预报性能两方面之间进行妥协。最后就数字滤波初始化在高分辨率有限区域数值模式中的可能应用提出了具体的建议。     

Assimilation and Simulation of Typhoon Rusa （2002） Using the WRF System

Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002).The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-km horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa‘s track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation.