基于武汉MST雷达的降雨物理过程观测与研究

利用武汉MST(Mesosphere-Stratosphere-Troposphere)雷达对降雨事件的观测, 建立了二阶高斯谱模型, 基于最小二乘法拟合得到相应的大气湍流谱与降雨谱信息.从大气湍流谱和降雨谱中可以分别提取大气及降雨粒子的回波能量及径向运动状态, 从而反演大气背景三维风场和讨论降雨形成机制.同时, 基于雨滴粒径伽马分布特征, 根据降雨回波谱反演得到不同高度的雨滴粒径分布, 从而研究对流层区域降雨的微物理过程.     

雨滴谱参数估计优化方案及其微物理资料检验

提出一种新的雨滴谱参数估计优化方案。其最大优点就是：对于任意几束相邻的测雨雷达观测资料,从任意的雨滴谱模型（如Marshall-Palmer经验公式）决定的积分雨参数之间的关系（如k-Z关系）出发,利用雷达视反向率资料并借助雷达海平面或地表面回波信号,可以获取束向上的比较接近实际降雨场的雨滴谱;然后利用校正的雨滴谱参数决定的积分雨参数之间的关系,降雨量反演长法就可以提供较准确的降雨量分布。这个方案可行性被同区域机载2D－P雨滴谱仪实测的微物理资料很好地验证。     

基于雨滴谱分布数据库的近红外辐射衰减研究

为了研究降雨对近红外辐射的衰减,定量评估降雨对近红外设备的影响,在雨滴谱分布二元函数模型建立的基础上,提出了一种雨滴谱分布数据库的建立方法,对LAWS和PARSONS在美国华盛顿地区测量的雨滴谱分布数据进行拟合,建立雨滴谱分布数据库。基于雨滴谱分布数据库,结合米散射理论和衰减系数公式,得到了1μm,2μm和3μm波长近红外辐射的消光效率因子与雨滴直径的关系曲线,并计算了在降雨量分别为0.25mm/h,1.25mm/h,2.5mm/h,12.5mm/h,25mm/h和50mm/h条件下的近红外辐射衰减系数。结果表明,不同降雨量条件下,对于雨滴谱分布的函数关系式,正态分布具有更好的拟合效果;消光效率曲线的包络线随波长的增大而增大;拟合衰减系数和降雨强度的函数关系发现,指数函数具有很好的拟合效果。该计算结果对研究降雨对近红外辐射的衰减具有重要意义。     

反卷积算法在风廓线雷达探测降水中的应用

大气垂直运动的不均匀性展宽了降水信号谱,影响了雷达探测反演的雨滴谱分布。为了消除大气运动不均匀性对雨滴谱反演精度的影响,需要对雷达接收到的降水谱进行反卷积处理。文章通过一种改进的反卷积算法对实际雷达探测降水信号进行了处理,比较分析了反卷积处理对雨滴谱反演的影响。     

气溶胶影响测云雷达反射率阈值

大量观测研究表明,降水云与非降水云的雷达反射率存在阈值（Threshold radar reflectivity）,当云的雷达反射率大于该阈值时,就可以形成降水;相反,云的雷达反射率小于该阈值,则不能形成降水。     

基于BP神经网络的雨滴谱仪设计

为了减小传统雨滴谱观测仪器的体积、重量、成本,并提高雨滴谱的测量精度,提出一种基于等距导电圆环结构的新型雨滴谱探头、Cortex-M3 ARM处理器及高精度低噪声测量电路的雨滴谱仪。雨滴谱仪利用不同直径雨滴引起输出电压的差异进行测量。以Sigmoid函数作为传递函数,利用梯度下降法建立雨滴谱仪的输出电压和雨滴直径的BP神经网络模型,并将基于该模型的算法嵌入ARM处理器,求出雨滴直径。该雨滴谱仪实现了对直径为2.67～5.56 mm雨滴的观测,测量误差小于±0.1 mm。     

风廓线雷达探测降水反演雨滴谱中的反卷积算法

大气垂直运动的不均匀性展宽了降水返回信号谱,影响了雷达探测反演的雨滴谱分布。为了消除大气运动不均匀性对雨滴谱反演精度的影响,需要对雷达接收到的降水谱进行反卷积处理。研究文章提出一种改进的迭代反卷积方法,方法通过对雷达接收信号设置阈值约束条件,迭代中采用逐次逼近的方法,减小了雷达噪声扰动对反卷积的干扰。     

卫星资料在云顶粒子尺度特征分析中的应用

选取NOAA卫星AVHRR通道3（3.55-3.93μm）观测资料，分析云顶粒子的物理性质，并用地面雨量和雷达观测资料对卫星反演分析结果进行验证，分析结果显示通道3反射率小，云顶粒子尺度大时易产生降水，当云层为单一层次时，通道3的反射率小值区与雷达回波区间具有良好的对应关系，证实了在降水过程中卫星分析云顶粒子尺度结果与雷达观测一致。     

雨滴成像中的散焦模糊复原方法及应用

针对自主研制的降水微物理特征测量仪存在的成像质量问题,重点考虑与光源相关的散焦模糊,提出了基于点扩散函数的雨滴图像复原方法,利用圆盘函数对雨滴图像进行复原,消除噪声和模糊,得到具有清晰轮廓的雨滴图像。利用与雨滴光学性质相近的玻璃球进行了定标实验,确定了成像系统散焦模糊的半径和图像二值化的阈值。外场实测结果表明,图像复原可以有效修正雨滴尺度及其谱分布,测量得到的雨滴谱和降雨强度与激光雨滴谱仪的结果具有很好的一致性。该方法应用于降水微物理特征测量仪,可以显著提高雨滴谱及其他微物理特征的测量性能。     

基于线阵图像传感器的降水测量技术研究

降水现象是全球水循环和气候变化的重要研究对象.降水粒子谱资料在天气现象的自动观测、云微物理过程研究和气象雷达回波订正等领域有重要应用.基于线阵图像传感器的降水观测系统可获取降水粒子图像信息,为雨滴的微物理特性研究提供原始资料.在简述基于线阵图像传感器的降水测量系统工作原理基础上,分析了线阵降水测量关键技术及线阵数据处理相关问题,分别从光学系统参数需求、线阵传感器高速扫描和线阵数据处理等方面进行了讨论,以期线阵图像采集技术能更好地应用于降水测量.     

Raindrop size distribution using method of moments for terrestrial and satellite communication applications in Singapore

As communication services using higher frequencies are growing rapidly in the tropics, there is an increasing need for a finer model to predict the attenuation due to rain. The raindrop size distribution (DSD) is one of the major sources of error in any prediction model, mainly because of its variability in both space and time. The DSD parameters are computed from distrometer data that are classified into stratiform and convective types using S-band radar data. The method of moments is employed to estimate the parameters of lognormal DSD. The modeled DSD parameters are optimized by examining the root mean square (RMS) error and the average probability ratio (APR) in estimation of the rain rate, rain attenuation, and radar reflectivity factor simultaneously. The proposed model gives maximum (close to unity) APR and minimum RMS error when compared to any other set of DSD parameters.     

雨衰减的解析近似

本文对Ｌａｗｓ－Ｐａｒｓｏｎｓ和广州雨滴尺寸分布雨衰减和降雨经之间的指数关系中的ａ和ｂ值＾「１」「２」进行了分析和解析回归，给出其与频率的解析近似关系，利用其计算的雨衰减和数值计算结果有很好的一致性。     

Rain Attenuation Ratios on Short Microwave and Millimeter Wave Bands Earth-Space Paths

The knowledge of the ratio of rain attenuation at one frequency to that at another on slant paths is useful for the design of satellite-to-Earth communication links and up-link power control systems. It is well known that the rain attenuation is influenced by parameters of precipitation along the slant path such as DSD (raindrop size distribution), raindrop temperature, rainfall rate, and so on. In this paper, based on several DSDs applied to various climate zones, at short microwave and long millimeter wave bands, the attenuation ratios are estimated on Earth-space paths. A comparison of the prediction results with the experiment data in Boston and Kashima areas is carried out. It is shown that the M-P and Weibull DSD applied to rain attenuation ratios estimation are better DSD at higher latitude regions. The Guangzhou DSD applied to rain attenuation ratios prediction is better in tropical and subtropical areas in China. The lognormal DSD may be a appropriate DSD applied to predict rain attenuation ratios in tropical areas at A_down>1dB or R>15mm/h. However, the attenuation ratios predicted by the Guangzhou DSD disagree with by the lognormal DSD, it requires that the DSD applied to predict rain attenuation ratios are further studied in tropical areas.     

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.     

A soft computing approach for rainfall retrieval from the TRMM microwave imager

A neural network model for rainfall retrieval over ocean from remotely sensed microwave (MW) brightness temperature (BT) is proposed. BT data are obtained from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The BT values from different channels of TMI over the Pacific Ocean (163/spl deg/ to 177/spl deg/W and 18/spl deg/ to 34/spl deg/S) are the input features. The near-surface rainfall rate from the Precipitation Radar (PR) are considered as a target. The proposed model consists of a neural network with online feature selection (FS) and clustering techniques. A K-means clustering algorithm is applied to cluster the selected features. Different networks have been trained to give an instantaneous rainfall rate with all input features as well as with selected features obtained by applying the FS algorithm. It is found that the hybrid network utilizing FS and clustering techniques performs better. The developed network is also validated with two independent datasets on March 14, 2000 over the Atlantic Ocean having stratiform rain and on March 21, 2000 over the Pacific Ocean having both stratiform and convective rain. In both cases, the hybrid network performs well with correlation coefficient improving to 0.78 and 0.81, respectively, in contrast to 0.70 and 0.75 for the network with all features. The rainfall rate retrieved from the hybrid network is also compared with the TMI surface rain rate, and a correlation of 0.84 and 0.75 is found for the two events. The proposed hybrid model is validated with a Doppler Weather Radar, and correlation of 0.52 is observed.     

A New Prediction Model of Rain Attenuation That Separately Accounts for Stratiform and Convective Rain

An improved version of the exponential cell (EXCELL) rain attenuation model is presented here. Analogously to the original one, it predicts attenuation through a cellular representation of precipitation, but, in addition, is able to discriminate between stratiform and convective rain by means of an embedded algorithm. Accordingly, two separate physical rain heights, derived from the ERA-15 database, are used to calculate stratiform and convective rain attenuation and, when considering stratiform precipitation, the melting layer contribution to attenuation is added. Eventually, the predicted cumulative distribution function (CDF) of excess attenuation is the combination of the contributions due to stratiform and convective precipitation types. Some input parameters of the prediction model, such as those defining the melting layer process or the rain plateau embedding rain cells, can be modified in order to account for the local meteorological characteristics.      

Modeling and measurement of rainfall by ground-based multispectral microwave radiometry

The potential of ground-based multispectral microwave radiometers in retrieving rainfall parameters is investigated by coupling physically oriented models and retrieval methods with a large set of experimental data. Measured data come from rain events that occurred in the USA at Boulder, Colorado, and at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site in Lamont, OK. Rain cloud models are specified to characterize both nonraining clouds, stratiform and convective rainfall. Brightness temperature numerical simulations are performed for a set of frequencies from 20 to 60 GHz at zenith angle, representing the channels currently deployed on a commercially available ground-based radiometric system. Results are illustrated in terms of comparisons between measurements and model data in order to show that the observed radiometric signatures can be attributed to rainfall scattering and absorption. A new statistical inversion algorithm, trained by synthetic data and based on principal component analysis is also developed to classify the meteorological background, to identify the rain regime, and to retrieve rain rate from passive radiometric observations. Rain rate estimate comparisons with simultaneous rain gauge data and rain effect mitigation methods are also discussed.     

Microwave link dual-wavelength measurements of path-averageattenuation for the estimation of drop size distributions and rainfall

Microwave attenuation measurements at 25 and 38 GHz made on a 2.3-km microwave link are employed to estimate drop size distributions (DSD), rainfall rate, and rainfall accumulation. A theoretical model for the propagation of microwaves in a link system sets forth the basis for the development of a dual-wavelength analytical technique to invert two parameters of a path-average gamma DSD. The DSDs obtained from the technique are evaluated in conjunction with point measurements performed with a 2-D video disdrometer. Additionally, the DSDs yield path-average rainfall rates and rainfall accumulation which are compared with path-average measurements from a network of optical and tipping bucket rain gauges located beneath the link path, and with estimates based on empirical power law relations     

Effect of raindrop size distribution and rain rate inhomogeneity on the relationship between attenuation and depolarization

In addition to attenuation, depolarization due to rain is another factor that degrades satellite propagation signals, especially in the higher frequency bands and in places that have high rates of rainfall. A formula to predict cross‐polarization as a function of attenuation has been proposed, and it is derived by a theoretical calculation using frequency, the forward scattering amplitude of raindrops, rainfall rates, the raindrop size distribution (DSD), and various other propagation parameters. In this paper, a formula for predicting cross‐polarization is derived on the basis of the assumption of a gamma‐type DSD up to 100 GHz. These results are compared with conventional exponential‐type DSDs, such as the Marshall‐and‐Palmer DSD. Moreover, for a more realistic propagation situation, we consider the effect on the aforementioned relationship of rainfall rate inhomogeneity along the propagation path. It is shown that, for practical purposes, this inhomogeneity does not have a significant effect on satellite propagation. Copyright © 2017 John Wiley & Sons, Ltd.     

A method for estimating rain rate and drop size distribution frompolarimetric radar measurements

Polarimetric radar measurements are sensitive to the size, shape and orientation of raindrops and provide information about drop size distribution (DSD), canting angle distribution and rain rate. The authors propose and demonstrate a method for retrieving DSD parameters for calculating rain rate and the characteristic particle size. The DSD is assumed to be a gamma distribution and the governing parameters are retrieved from radar measurements: reflectivity (Z_HH), differential reflectivity (ZDR), and a constrained relation between the shape (CL) and slope (Λ) parameters derived from video disdrometer observations. The estimated rain rate is compared with that obtained from more traditional methods and the calculated characteristic size is compared with the measured values. The calculated K_DP based on the retrieved Gamma DSD is also compared with measurements. The proposed method shows improvement over the existing models and techniques because it can retrieve all three parameters of the gamma distribution. For maintaining the continuity of earlier published results, raindrop shape is assumed to be equilibrium