卫星资料反演湿度场改变模式初值对降水预报的影响

为探讨初始场资料在数值预报中的重要性，用高分辨率卫星T_BB资料反演的云内湿度场来改进模式初值，初步研究分析了改进的模式初值对降水预报的影响。以湿绝热过程的变态方程为积分方程，由卫星T_BB资料反演出大气中各等压面层湿度场。通过对比分析反演的湿度场与客观分析 (T106) 的水汽场，发现两者有较大区别，前者更加合理地反映出降水区域高空湿度场的分布。利用中尺度模式MM5将有限区域的常规探空资料和非常规资料进行同化，并对暴雨个例进行预报对比试验。不同初值的对比试验表明，在模式的初始场中引入卫星资料反演的湿度场后，明显地改善了模式降水预报的强度和落区，比仅使用常规探空资料更接近于实况。     

TOVS卫星反演资料变分分析的试验研究与应用

为弥补海洋、高原等地带常规资料的不足,分析使用非常规卫星资料得到越来越多的重视,其中TOVS资料的精度及与常规资料的误差减少的研究尤为重要。本文采用变分分析技术对TOVS卫星反演资料进行同化分析研究,结果表明,变分结果分析场能充分体现常规与非常规资料的优势,使得天气系统能得到更精确的表示。     

登陆台风对安阳降水的影响及其预报

在分析1966－1995年安阳区域夏季登陆台风的不同环流形势基础上，利用历史天气图资料及安阳区域实况要素资料，找出台风登陆后安阳区域产生的不同天气的预防指标，并分类建立了预报方程。     

寒潮暴风雪天气的动力和热力特征分析

普查了1960－1997年3－5月历史实况天气图资料，计算了寒潮暴风雪天气过程中的动能、变压、潜热能等动力和热力物理量，着重分析了它们在寒潮暴风雪天气过程中的作用及其变化特征。     

飞机报资料在0506华南致灾暴雨过程模拟中的应用

利用常规和非常规观测资料,对2005年6月18～24日华南地区的一次致灾暴雨过程进行了分析,并对18～19日的过程进行了模拟研究。由于常规观测资料的分析对于描述暴雨的系统结构等方面尚显不足,因此利用GRAPES模式对此次暴雨过程进行了模拟研究。采用不同资料,利用模式同化系统经过12小时的同化,将得出的不同的同化分析场作为模式的初始场,对此次过程进行24小时的数值模拟做对比模拟试验,来对比分析飞机报同化场对于模式预报的改进作用。试验证明,利用有飞机报加入的同化分析场做初始场的模拟结果不仅能够模拟出主要的降水区域,而且降水强度与实况更加吻合,比未加入飞机报的控制试验结果的准确率提高了。飞机报资料的使用对于提高此次暴雨过程模拟效果是可行的、必要的,而且也为该资料用于华南暴雨的预报奠定了基础。     

卫星云图反演资料质量控制方案在暴雨模拟中的对比研究

本文以2003年7月9～10日发生在江淮流域的暴雨过程为例,应用FY-2B卫星红外云图灰度资料,利用统计回归的反演方法求出高分辨率的温度和湿度的反演场用于改进预报的初始场。设计和对比了几种质量控制方案,再将控制后的反演场与常规资料进行同化,最后用MM5模式进行了模拟对比试验。结果表明：在模式的初始场中引入卫星云图反演场能反映出更为细致的中尺度结构,有效地增强了对降水有重要影响的高湿区;锋生函数质量控制方案改善模式的初始场,从而改善了MM5模式降水预报的落区和强度,提高了降水预报准确性及Ts评分。     

实时资料物理量场诊断分析系统及应用

该系统通过报文自理客观分析、物理量计算，图形处理等工作能迅速从省－地网实时常规资料中获取有关物理量场数据或图形资料。使用方便，效果较好，可作为天气图的辅助工具投入日常业务化应用，增加预报信息量，也可应用于历史天气过程的研究。     

中尺度模式的四维伴随同化系统及其同化试验

以中尺度模式MM4为基础，利用伴随码技术改进、完善了MM4伴随模式同化系统，并利用该系统进行了常规资料和非常规资料的伴随模式同化试验，例如加入了可降水量资料等。试验表明：在伴随模式同化系统中加入常规和非常规资料，可以改进初始场，从而改善预报场。     

一种新型西南低涡逐步订正识别方法

西南低涡是形成于青藏高原东侧的特殊天气系统,国内学者目前对于西南低涡的识别没有统一的标准。通过分析西南低涡的主要特征,结合高度场、涡度场、风场,设计了一种适应于西南低涡的HVW识别方法,将其应用于2014年6—8月GRAPES-MESO高分辨率格点分析资料,对比与西南低涡天气图实况的差异。通过对西南低涡的识别、低涡生成和消亡时间、低涡中心位置以及低涡中心强度这几方面的具体分析,得到以下几点结论:1)HVW识别方法能够有效识别出高精度格点资料中的西南低涡过程,与格点实况的吻合率达到87.5%;对于天气图和格点资料都能够再现的西南低涡个例,HVW识别方法的准确度能够达到90.9%,说明HVW识别方法能够有效捕捉西南低涡。2)以天气图实况资料为西南低涡生命时长检验标准,HVW识别方法能够合理分析低涡的生成和消亡时间。3)对西南低涡中心位置偏差进行分析发现,HVW识别的西南低涡中心位置不仅位于西南低涡气压低值附近,更位于风场辐合中心。4)对西南低涡中心强度的评估发现,格点实况与HVW识别方法分析的西南低涡强度差异几乎可以忽略,充分说明了HVW识别方法包含了格点实况的高度场信息,也说明该识别方法的西南低涡中心强度可以用来代替格点实况结果。通过对2014年6—8月西南低涡过程的具体分析,验证了HVW逐步循环定位方法的可行性、合理性以及准确性。     

基于MICAPS系统的数字化天气图及常规气象资料检索分析系统

介绍了基于“9210工程”和MICAPS系统的资料自动存储、整理、检索和历史天气图分析业务系统——基于MICAPS系统的数字化天气图及常规气象资料检索分析系统，较全面地介绍了该系统高度自动化、设计友好的功能和在业务中的应用。     

时间加密探空观测对分析和预报质量的敏感性研究

探空观测是气象资料同化中最基本的常规观测资料,对同化分析和预报的有效改善具有重要作用。由于现有探空观测站的空间分辨率较低,分布不均匀,且每日仅有两次观测,数量偏少,限制了其分析场对中小尺度大气状态的准确再现能力。自我国L波段雷达-数字探空仪更新换代以来,探空观测具备了获取每日4次、垂直分辨为秒级和分钟级的大气廓线资料。本文利用WRF中尺度数值模式,通过06时（世界时,下同）加密探空资料和12时常规探空资料的有效同化,研究分析了时间加密探空观测资料对同化分析和预报质量的敏感性影响。结果表明：同化06时的时间加密探空资料的午后暴雨预报质量优于12时常规探空观测。具体而言,同化06时的时间加密探空资料预报的大雨和暴雨的预报技巧高于12时常规探空资料;位势高度、温度和风场等预报场的均方根误差在高层的改进效果更加明显;06时的时间加密探空资料的同化对高层的高空急流和低层的水汽通量散度的预报质量贡献更大。批量试验进一步证实了有效同化时间加密探空资料对分析和数值预报效果改进的积极意义。     

变分分析技术在城市气象资料分析中的应用

随着城市气象研究和城市气象服务的深入开展,越工需要分辨率更高、精度更高的观测资料,同时,随着城市气象观测网的不断完善,已能提供较多的常规和非常规观测资料。为了得到更完善的气象要素分布场,首先应对这些常规和非常规观测资料进行客观分析。使用上海市的气象哨、常规气象观测站的观测资料和非常规观测资料进行客观分析。使用上海市的气象哨、常规气象观测站的观测资料和上海市的地表分类信息,对变分分析技术进行了实验。     

Numerical Assessing Experiments on the Individual Component Impact of the Meteorological Observation Network on the ＂July 2000＂ Torrential Rain in Beijing

In an effort to assess the impact of the individual component of meteorological observations (ground-based GPS precipitable water vapor,automatic and conventional meteorological observations) on the torrential rain event in 4-5 July 2000 in Beijing (with the 24-h accumulated precipitation reaching 240 mm),24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model.Results indicate that,because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system,better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills.3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation,and automatic and conventional surface meteorological observations rank second.After acquiring the supplement information from the other meteorological observations,the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast.By incorporating the ground- based GPS precipitable water vapor data into the 3DVAR analyses at the initial time,the threat scores (TS) with thresholds of 1,5,10,and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations,respectively.This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.     

System of Multigrid Nonlinear Least-squares Four-dimensional Variational Data Assimilation for Numerical Weather Prediction (SNAP): System Formulation and Preliminary Evaluation

A new forecasting system—the System of Multigrid Nonlinear Least-squares Four-dimensional Variational (NLS-4DVar) Data Assimilation for Numerical Weather Prediction (SNAP)—was established by building upon the multigrid NLS-4DVar data assimilation scheme, the operational Gridpoint Statistical Interpolation (GSI)?based data-processing and observation operators, and the widely used Weather Research and Forecasting numerical model. Drawing upon lessons learned from the superiority of the operational GSI analysis system, for its various observation operators and the ability to assimilate multiple-source observations, SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations. The multigrid NLS-4DVar assimilation framework is used for the analysis, which can adequately correct errors from large to small scales and accelerate iteration solutions. The analysis variables are model state variables, rather than the control variables adopted in the conventional 4DVar system. Currently, we have achieved the assimilation of conventional observations, and we will continue to improve the assimilation of radar and satellite observations in the future. SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments. In the case evaluation experiments, two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites. This showed that SNAP can absorb observations and improve the initial field, thereby improving the precipitation forecast. In the one-week cycling assimilation experiments, six-hourly assimilation cycles were run in one week. SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar (Four-dimensional Ensemble Variational) as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.     

往返式探空观测资料的质量控制及不确定性分析

为了推动新型探测资料在数值预报模式中的应用,本文进行了往返式探空资料同化应用前重要的基础性研究工作。基于国内首次往返式探空观测资料,首先建立了面向业务化应用的往返式探空资料质量控制方案,通过对比和分析质量控制前后观测样本的统计特征,论证了质量控制方案的合理性,质量控制后探测要素抽样分布更为合理,要素间一致性得到提高。进而以数值天气预报高时间分辨率的模式预报场和同站址业务常规探空观测资料为参考,分析质量控制后资料的不确定性,结果表明往返探空探测精度达到了世界气象组织WMO（World Meteorological Center）规定的突破目标,部分探测要素甚至实现了理想目标,探测资料具有可用性。最后结合数值模式背景场探讨往返探空资料的可同化性,研究表明往返探空的风场观测和夜间温度观测满足变分同化系统的高斯、无偏假定,可直接同化;气压、湿度和日间温度观测在资料同化前需要开展偏差订正工作,从而更有效的发挥资料价值。本文的研究工作为今后往返探空资料在模式中的同化应用奠定了基础。     

ASSIMILATION OF REAL OBSERVATIONAL DATA WITH THE GSI-HYBRID DATA ASSIMILATION SYSTEM TO IMPROVE TYPHOON FORECAST

A hybrid GSI (Grid-point Statistical Interpolation)-ETKF (Ensemble Transform Kalman Filter) data assimilation system has been recently developed for the WRF (Weather Research and Forecasting) model and tested with simulated observations for tropical cyclone (TC) forecast. This system is based on the existing GSI but with ensemble background information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution (27 km) is used. A case study of typhoon Muifa (2011) is performed to assimilate real observations including conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble covariance shows significant improvements with respect to track forecast compared to the standard GSI system which in theory is three dimensional variational analysis (3DVAR). By comparing the analyses, analysis increments and forecasts, the hybrid system is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better describe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon initial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is tested and similar results are revealed with those from cycled GSI-ETKF approach.     

Assimilating surface observations in a four-dimensional variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case

This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System(VDRAS).Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational(4DVAR) data assimilation system.A squall-line case observed during a field campaign is selected to investigate the performance of the technique.A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions.The surface-based cold pool,divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation.Three experiments—assimilating radar data only,assimilating radar data with surface data blended in a mesoscale background,and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation.Independent surface and wind profiler observations are used for verification.The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations.It is also shown that the additional surface data can help improve the analysis and forecast at low levels.Surface and low-level features of the squall line—including the surface warm inflow,cold pool,gust front,and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS.     

中尺度分析系统LAPS应用雷达资料的个例研究

武汉暴雨所引进国际先进的中尺度分析系统LAPS, 经成功本地移植后, 该系统能融合华中区域多种非常规观测资料, 提供包含丰富中尺度信息的高分辨率中尺度分析场。针对一次梅雨期强降水过程, 利用LAPS系统进行中尺度分析, 通过对比该系统融合多普勒雷达资料前后各种物理量场的差异, 研究了多普勒雷达资料在该系统中的作用。结果表明, LAPS融合雷达径向风后, 对风场的改善比较明显, 能揭示流场的中尺度信息。融合多种资料后的LAPS中尺度分析场比NCEP再分析场更接近实况, 能清楚地反映中尺度特征, 可作为分析此次强降水过程发生\, 发展的工具。融合雷达资料反射率后, LAPS云分析能提供与实况接近的较细致的云信息, 有利于了解暴雨过程中云参数的演变, 同时也为数值模式热启动提供条件。