大气折射率湍流结构系数C2n的观测试验

以美国NOAA波传播实验室估算大气折射率湍流结构系数的模式为基础，经过数值试验和观测对比调试，给出了一个得到我国雷达测值验证的实用的C2_n估算模式。     

用常规探空资料估算C^2n和ε垂直变化初探

用南京，射阳的常规探空资料建立了估算折射率结构常数Ｃ＾２ｎ的湍能耗散率ε垂直变化理论模式。结果表明：用该理论模式计算的ε值与用天气脉冲多普勒雷达探测的速度谱宽σ＾２ｒ再估算得到的ε值有较好的一致性。     

用常规探空资料估算C_n~2和ε垂直变化初探

用南京、射阳的常规探空资料建立了估算折射率结构常数Ｃ２ｎ和湍能耗散率ε垂直变化理论模式。结果表明：用该理论模式计算的ε值与用天气脉冲多普勒雷达探测的速度谱宽σ２ｒ再估算得到的ε值有较好的一致性     

用常规探空资料估算Cn2和ε垂直变化初探

用南京、射阳的常规探空资料建立了估算折射率结构常数C_n²和湍能耗散率ε垂直变化理论模式。结果表明:用该理论模式计算的ε值与用天气脉冲多普勒雷达探测的速度谱宽σ_r²再估算得到的ε值有较好的一致性。     

西太平洋热带海域强对流天气过程湍流通量输送的某些特征

本根据“实验３号”科学考察船在ＴＯＧＡ－ＣＯＡＲＥ（１９９２年１１月－１９９３年２月）定点（２°１５＇Ｓ，１５８°００＇Ｅ）连续观测的大气，海洋资料，利用考虑风速和大气层结影响的整体输送动力学公式，计算给出了在西太平洋热带海域强对流天气过程中动量、感热和潜热等湍流通量垂直交换和水平输送的一些特性，并与该海域其它天气过程湍流通量交换和输送的特性作了比较，此外，中还讨论了更接近实际的曳力系数，感热     

碘化银人工冰核在云中的扩散及飞机播撒航线的设计

为在飞机播撒碘化银进行人工增雨中科学设计飞行航线。本文推导并求解了湍流扩散方程，得出了过冷层状云中ＡｇＩ人工冰核的扩散规律。为此为根据给出了飞行航线间距满足的方程和ＡｇＩ的空间浓度。     

VSAT天线压重估算

针对ＶＳＡＴ天线产生的压重对房顶的影响，指出了其压重产生的３个因素，并重点介绍了压重的估算方法，该方法也适用于其它卫星天线压重的估算。     

气象卫星遥感洪涝面积估算

本文介绍了应用ＮＯＡＡ极轨气象卫星ＡＶＨＲＲ资料估算洪涝面积的原理和技术方法。应用气象卫星遥感资料，结合地理信息和实陆调查资料，通过计算分析和图像处理，可以实时、客观地判断洪涝灾害范围，区分洪涝程度，计算受灾面积。     

表面气温内部变率估算方法的比较研究

本文利用37个CMIP5模式和CESM（Community Earth System Model）包含40个成员的超级集合试验的表面气温预估数据，比较了工业革命前气候参照试验、多项式拟合法和方差分析方法这三种目前在国际上运用较多的方法所估算的表面气温内部变率的异同，分析了内部变率的估算对气候预估中信号萌芽时间（TOE）的影响。结果表明:若采用CMIP5多模式集合，则工业革命前气候参照试验和多项式拟合法都是估算内部变率的合理方法，而方差分析方法则由于包含模式性能自身的影响会夸大内部变率故不推荐使用。内部变率的全球分布呈现出极向强化的现象，中高纬度地区的内部变率幅度远大于热带、副热带地区。内部变率受不同排放情景的影响较小，且随时间无显著变化，但方差分析方法估算的内部变率在热带地区容易受到排放情景的影响。若基于类似CESM这样的单个气候模式的超级集合模拟试验来估算内部变率，三种方法估算的结果相似。不同方法估算的内部变率对TOE的影响主要位于北大西洋拉布拉多海、南大洋威德尔海和罗斯海等邻近海洋深对流区。对于中国区域平均来说，基于CESM超级集合模拟试验，三种方法估算的内部变率与强迫信号之比都小于15%；对CMIP5多模式集合，采用工业革命前气候参照试验和多项式拟合法得到的结果与此接近，但若采用方差分析方法则显著高估内部变率的作用。     

光合有效量子通量密度的气侯学计算

讨论了光合有效辐射（ＰＡＲ）的两种计量系统，提出了利用太阳总辐射照度估算光合有效量子通量密度的气候学公式。根据国外对昼光的观测资料，得到了ＰＡＲ能量的量子转换系数，即太阳总辐射中，ＰＡＲ每１Ｊ的能量含有４．５５μｍｏｌ的量子。在气候学计算中，可利用这个值进行ＰＡＲ的能量和量子的换算。     

基于VDRAS的快速更新雷达四维变分分析系统

基于雷达资料快速更新四维变分同化 (RR4DVar) 技术和三维数值云模式,初步研发了一个针对对流尺度数值模拟的快速更新雷达四维变分分析系统。系统通过对京津冀6部多普勒天气雷达资料进行RR4DVar同化,并融合5 min自动气象站观测和中尺度数值模式结果,可快速分析得到12~18 min更新的低层大气三维动力、热力场的对流尺度结构特征。针对2009年7月22日发生在京津冀的一次强风暴个例,通过一系列敏感性试验,并利用局地加密资料进行检验对比,表明有效的雷达资料RR4DVar同化及自动气象站和中尺度模式资料融合方案、恰当的中尺度背景场设置和动力约束方法是获得合理结果的关键。研究也表明:恰当的系统配置能够模拟出与对流生消发展密切相关的近风暴环境特征,包括低层入流、垂直风切变、低层辐合上升和暖舌等,以及风暴自身形成的冷池、出流等与风暴演变密切相关的对流尺度结构。     

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.     

基于生成对抗网络GAN的人工智能临近预报方法研究

研究设计了基于生成对抗网络(Generative Adversarial Networks,GAN)的人工智能临近预报方法,并进行了业务试验。该方法利用广东12部S波段天气雷达2015—2017年海量雷达拼图资料进行人工智能学习来做临近预报。GAN方法从一系列雷达观测资料中,运用卷积法提取回波图像信息建立预报模型,并通过损失函数训练模型,得到基于人工智能技术的临近预报。对2018年发生在广东地区的4个天气过程的外推预报试验表明,GAN方法对对流天气过程的回波位置、形状及强度的临近预报多数情况下与实况基本一致,具有较好的预报效果。但是该方法预报的回波范围偏大,对层状云降水的预报效果较差。对西风带系统引起的降水,西南季风降水,东风系统引起的降水以及台风降水的18个个例1 h预报的3个级别的回波强度检验发现,GAN方法对中等强度回波的预报较好,但对强回波的预报效果仍有待提高。     

Relationship between radar reflectivity and the time scale of warm rain formation in a global cloud-resolving model

The connections between radar reflectivity and the time scale of warm rain formation are examined within a global cloud-resolving model. The parameterizations formulae of auto-conversion and accretion processes in the model reveal specific relationships between the time scale for auto-conversion and radar reflectivity of cloud water as well as between the time scale for accretion and radar reflectivity of rain water. The overall time scale for warm rain formation, determined by combined contributions from these processes, is found to relate with total radar reflectivity in the manner that varies with cloud-rain composition between auto-conversion and accretion limits. The global statistics from the model output reveals that the time scale is closely related with the total radar reflectivity, thus suggesting that the radar reflectivity is a gross measure of the warm rain time scale. The relationship developed is applied to both model-simulated and CloudSat-observed radar reflectivities to compare the time scales of warm rain formation between observation and the model. Comparison of the time scale so derived reveals significant differences between the model and CloudSat observations. These differences suggest that the simulated cloud-rain composition in the model is biased toward larger rain water contents and smaller content of cloud water compared to reality due to an accelerated cloud-to-rain water conversion in the model.     

华中区域LRUC系统的构建与试验

如何将区域观测资料在中尺度模式中快速有效同化是提高区域精细化数值预报准确率和时效性的关键所在。本文简单介绍了基于LAPS和WRF建立的快速循环同化预报系统LRUC,以一次影响长江中游的典型梅雨锋暴雨过程为例,设计几种试验方案,结合实况降水分布,对比分析华中区域多普勒雷达资料循环同化对改善暴雨预报的作用;根据个例试验结果,设计批量后报试验方案,对比分析雷达资料同化对华中区域2007年主汛期(6—8月)多个时效降水预报评分。暴雨个例试验结果表明,华中区域多普勒雷达资料在LAPS中的同化,能为WRF提供更优初值场;同化华中区域地面资料和雷达资料后,比仅同化地面资料更能改进模式初值,改善模式降水预报,且降雨量级越大,24 h降水预报TS评分越高。批量后报试验结果表明,建立的快速循环同化预报系统LRUC,能对区域多源观测资料进行多时次循环同化分析,为模式初值增加观测资料的时间演变信息,提高模式对暴雨量级降水的预报水平;系统具有稳定性和一定的评分水平。     

Application of a Three-dimensional Variational Method for Radar Reflectivity Data Correction in a Mudslide-inducing Rainstorm Simulation

Various types of radars with different horizontal and vertical detection ranges are deployed in China, particularly over complex terrain where radar blind zones are common. In this study, a new variational method is developed to correct threedimensional radar reflectivity data based on hourly ground precipitation observations. The aim of this method is to improve the quality of observations of various types of radar and effectively assimilate operational Doppler radar observations. A mudslide-inducing local rainstorm is simulated by the WRF model with assimilation of radar reflectivity and radial velocity data using LAPS(Local Analysis and Prediction System). Experiments with different radar data assimilated by LAPS are performed. It is found that when radar reflectivity data are corrected using this variational method and assimilated by LAPS,the atmospheric conditions and cloud physics processes are reasonably described. The temporal evolution of radar reflectivity corrected by the variational method corresponds well to observed rainfall. It can better describe the cloud water distribution over the rainfall area and improve the cloud water analysis results over the central rainfall region. The LAPS cloud analysis system can update cloud microphysical variables and represent the hydrometeors associated with strong convective activities over the rainfall area well. Model performance is improved and the simulation of the dynamical processes and moisture transport is more consistent with observation.     

集合卡尔曼滤波同化中雷达位置的敏感性研究

针对对流尺度集合卡尔曼滤波（EnKF）雷达资料同化中雷达位置对同化的影响进行研究。为了考察强对流出现在雷达不同方位时集合卡尔曼滤波同化雷达资料的能力,以一个理想风暴为例,设计了8个均匀分布在模拟区域周围的模拟雷达进行试验。单雷达同化试验中,初期同化对雷达位置较敏感,而十几个循环后对雷达方位的敏感性降低。造成初期同化效果较差的雷达观测位于模拟区域正南和正北方向,这两部雷达与模拟区域中心的连线垂直于风暴移动方向（即环境气流的方向）。双雷达试验的结果表明,正东、正南、正西和正北方向的雷达组合观测会使同化初期误差较大,这说明并不是所有与风暴连线成90°的雷达组合都能在短时同化中得到合理的分析结果,还需要都处于模拟区域对角线上（即与环境气流成45°夹角）,同化效果才较好。短时同化后的确定性预报结果表明,较大分析误差也会导致较大预报误差。这些分析误差主要是由于同化初期不准确的集合平均场驱动出的不合理的背景误差协方差造成的。当背景场随着同化循环得到改进后,驱动出的合理的背景误差协方差使得不同位置雷达同化造成的差异逐步减小。基于上述结果,引入迭代集合均方根滤波（iEnSRF）算法,结果显示使用该算法后,雷达位置对同化效果的影响减小,同化不同位置的雷达资料均能有效降低分析和预报误差。      

Raindrop Size Distribution Parameters Retrieved from Xinfeng C-Band Polarimetric Radar Observations

The objective of this research was to acquire a raindrop size distribution (DSDs) retrieved from C-band polarimetric radar observations scheme for the first time in south China.An observation period of the precipitation process was selected,and the shape-slope (μ-Λ) relationship of this region was statistically analyzed using the raindrop sample observations from the two-dimensional video disdrometer (2DVD) at Xinfeng Station,Guangdong Province.Simulated data of the C-band polarimetric radar reflectivity Z_(HH)and differential reflectivity Z_(DR)were obtained through scattering simulation.The simulation data were combined with DSD fitting to determine the Z_(DR)-Λand log_(10)(Z_(HH)/N_0)-Λrelationships.Using Xinfeng C-band polarimetric radar observations Z_(DR)and Z_(HH),the raindrop Gamma size distribution parametersμ,Λ,and N_0were retrieved.A scheme for using C-band polarimetric radar to retrieve the DSDs was developed.This research revealed that during precipitation process,the DSDs obtained using the C-band polarimetric radar retrieval scheme are similar to the 2DVD observations,the precipitation characteristics of rainfall intensity (R),mass-weighted mean diameter (D_m) and intercept parameter (N_w) with time obtained by radar retrieval are basically consistent with the observational results of the 2DVD.This scheme establishes the relationship between the observations of the C-band polarimetric radar and the physical quantities of the numerical model.This method not only can test the prediction of the model data assimilation system on the convective scale and determine error sources,but also can improve the microphysical precipitation processes analysis and radar quantitative precipitation estimation.The present research will facilitate radar data assimilation in the future.     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.