Cloud-Type-Dependent 1DVAR Algorithm for Retrieving Hydrometeors and Precipitation in Tropical Cyclone Nanmadol from GMI Data

Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.

Numerical Study on the Impacts of Hydrometeor Processes on the“21·7”Extreme Rainfall in Zhengzhou Area of China

The impacts of hydrometeor-related processes on the development and evolution of the“21·7”extremely heavy rainfall in Zhengzhou were investigated using WRF simulations.Surface precipitation was determined by the hydrometeor microphysical processes(all microphysical source sink terms of hydrometeors)and macrophysical processes(local change and flux convergence of hydrometeors).The contribution of hydrometeor macrophysical processes was commonly less than 10%,but could reach 30%–50%in the early stage of precipitation,which was largely dependent on the size of the study area.The macrophysical processes of liquid-phase hydrometeors always presented a promotional effect on rainfall,while the ice-phase hydrometeors played a negative role in the middle and later stages of precipitation.The distributions of microphysical latent heat corresponded well with those of buoyancy and vertical velocity(tendency),indicating that the phase-change heating was the major driver for convective development.Reasonable diagnostic buoyancy was obtained by choosing an area close to the convective size for getting the reference state of air.In addition,a new dynamic equilibrium involving hydrometeors with a tilted airflow was formed during the heavy precipitation period(updraft was not the strongest).The heaviest instantaneous precipitation was mainly produced by the warm-rain processes.Sensitivity experiments further pointed out that the uncertainty of latent heat parameterization(±20%)did not significantly affect the convective rainfall.While when the phase-change heating only altered the temperature tendency,its impact on precipitation was remarkable.The results of this study help to deepen our understanding of heavy rainfall mechanisms from the perspective of hydrometeor processes.

Possibility of Solid Hydrometeor Growth Zone Identification Using Radar Spectrum Width

In this study,the correlation between simulated and measured radar velocity spectrum width(σ_(v))is investigated.The results show that the dendrites growth zones(DGZs)and needles growth zones(NGZs)mostly contain dendrites(DN)and needles(NE),respectively.Clearσ_(v) zones(1.1<σ_(v)(m s^(-1))<1.3 and 0.3<σ_(v)(m s^(-1))<0.7 for the DGZ and NGZ,respectively)could be identified in the case studies(27 and 28 February 2016)near altitudes corresponding to temperatures of–15°C and–5°C,according to the Japan Meteorological Agency and mesoscale model reanalysis data.Oblate particles with diverse particle shapes were observed in the DGZ withσ_(v)>1.2 m s^(-1),a differential reflectivity(ZDR)higher than 0 dB,and a cross-correlation coefficient(ρhv)less than 0.96.In contrast,prolate particles with relatively uniform shapes were observed in the NGZ withσ_(v)<0.6 m s^(-1),a ZDR less than 0 dB,andρhv higher than 0.97.The simulation results show that the DN exhibited a largerσ_(v) compared to the NE,and this observedσ_(v) was strongly dependent on the wind fluctuations(v’)due to turbulence or wind shear.In contrast,the NE exhibited a significantly smallσ_(v)~0.55 m s^(-1),which converges irrespective of v’.In addition,a strong correlation between the measuredσ_(v) values at five radar elevation angles(θ=6.2°,9.1°,13.1°,19°,and 80°)and those simulated in this study confirmed the significance of the analysis results.

基于ECOC平衡随机森林的雷达降水粒子分类

针对数据不平衡情况下的降水粒子分类问题,提出了一种基于纠错输出码(error correcting output code,ECOC)平衡随机森林的双偏振气象雷达降水粒子分类方法。首先,将多类别降水粒子数据集编码为多个二分类数据集;然后,对二分类数据集进行有放回的平衡重采样,构建多棵分类回归树;最后,利用所有的分类回归树联合进行降水粒子分类。对实测数据的处理结果表明,所提方法能够在保证总体准确率较高的情况下,大幅提高少数类的分类效果。

热带地区雹暴的闪电活动-动力-微物理特征研究

基于低频电场变化探测阵列三维闪电定位系统和S波段双偏振天气雷达数据, 对海南岛2021年6月24日一次雹暴过程的闪电活动和云内动力与微物理特征进行了详细的分析.结果显示: 该雹暴闪电活动以云闪为主, 占总闪的85.38%.降雹前发生的地闪以正地闪为主, 在降雹前25 min内, 正地闪频数占总地闪频数的60%, 高于一般雷暴正地闪活动比例.在雹暴成熟阶段, 上升气流出现两次增强, 而闪电频数的增加均滞后于上升气流增强的时段, 同时, 闪电频数的增加也可能与对流单体的合并有关.结合模糊逻辑判断法对云内降水粒子的识别, 计算了总闪与冰相粒子的相关系数, 其中霰和冰晶粒子与总闪相关性较高, 相关系数分别为0.76和0.83.根据闪电辐射源的空间分布特征, 推测该雹暴降雹前为反三极性电荷结构, 正电荷区位于约7~9.5 km(~-10 ℃至-25 ℃).

Flood Forecasting Experiment Based on EC and WRF in the Bailian River Basin

In order to extend the forecasting period of flood and improve the accuracy of flood forecasting,this paper took Bailian River Reservoir which located in Huanggang City of Hubei Province as an example and carried out basin flood simulation and forecasting by coupling the quantitative precipitation forecasting products of numerical forecast operation model of Institute of Heavy Rain in Wuhan(WRF)and the European Center for Medium-range Weather Forecasts(ECMWF)with the three water sources Xin an River model.The experimental results showed that the spatiotemporal distribution of rainfall predicted by EC is closer to the actual situation compared to WRF;the efficiency coefficient and peak time difference of EC used for flood forecasting are comparable to WRF,but the average relative error of flood peaks is about 14%smaller than WRF.Overall,the precipitation forecasting products of the two numerical models can be used for flood forecasting in the Bailian River basin.Some forecasting indicators have certain reference value,and there is still significant room for improvement in the forecasting effects of the two models.

Statistics-based Optimization of the Polarimetric Radar Hydrometeor Classification Algorithm and Its Application for a Squall Line in South China

A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results---especially in the mixed rain-hail region--can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar- detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

Evaluation of WRF Model Hydrometeors Based on TMI Observations Using an Indirect Method

Using a microwave radiative transfer （MWRT） model with microwave brightness temperatures （TBs） observed from the Tropical Rainfall Measuring Mission （TRMM） Microwave Imager （TMI）, an indirect approach evaluated hydrometeors generated from the Weather Research and Forecasting （WRY） model in the process of CHABA typhoon in August 2004. This study compares the simulated TBs generated from the microwave radioactive transfer model connected to the WRF model with the observed TBs derived from TMI and analyzes the differences between these TBs. The results indicate that the WRF model underestimates the amount and area of liquid and ice hydrometeors inside the typhoon center. The results also indicate relatively better agreement between the simulated and the observed TBs in the vertical polarization than in the horizontal polarization.

Evaluation of the WDM6 scheme in the simulation of number concentrations and drop size distributions of warm-rain hydrometeors: comparisons with the observations and other schemes

The number concentrations and drop size distributions(DSDs)of warm-rain hydrometeors play an important role in the simulation of microphysical processes.To evaluate the performance of the WDM6 scheme,which predicts the cloud number concentration(Nc)explicitly in aspects of warm-rain hydrometeors number concentrations and DSDs,the simulation of the WDM6 scheme is compared with airborne observations of a flight trial,as well as with the simulations of the Thompson scheme and Morrison scheme.Results show that the WDM6 scheme produces smaller(larger)cloud(rain)number concentrations and wider cloud DSDs compared to the observations,with the largest biases at upper levels of stratiform cloud(SC).The Thompson scheme and the Morrison scheme,both of which set the Nc as a constant,compare better to the observations than the WDM6 scheme in aspects of Nc and DSD.Sensitivity tests of the initial cloud condensation nuclei(CCN)number concentration(CCN0)of the WDM6 scheme show that a better choice of the initial CCN0 may improve the simulation of convective cloud but helps little in terms of SC.The simulation of rain number concentration and DSD is not sensitive to the CCN0 in the WDM6 scheme.

Background Error Covariance Statistics of Hydrometeor Control Variables Based on Gaussian Transform

Use of data assimilation to initialize hydrometeors plays a vital role in numerical weather prediction(NWP).To directly analyze hydrometeors in data assimilation systems from cloud-sensitive observations,hydrometeor control variables are necessary.Common data assimilation systems theoretically require that the probability density functions(PDFs)of analysis,background,and observation errors should satisfy the Gaussian unbiased assumptions.In this study,a Gaussian transform method is proposed to transform hydrometeors to more Gaussian variables,which is modified from the Softmax function and renamed as Quasi-Softmax transform.The Quasi-Softmax transform method then is compared to the original hydrometeor mixing ratios and their logarithmic transform and Softmax transform.The spatial distribution,the non-Gaussian nature of the background errors,and the characteristics of the background errors of hydrometeors in each method are studied.Compared to the logarithmic and Softmax transform,the Quasi-Softmax method keeps the vertical distribution of the original hydrometeor mixing ratios to the greatest extent.The results of the D′Agostino test show that the hydrometeors transformed by the Quasi-Softmax method are more Gaussian when compared to the other methods.The Gaussian transform has been added to the control variable transform to estimate the background error covariances.Results show that the characteristics of the hydrometeor background errors are reasonable for the Quasi-Softmax method.The transformed hydrometeors using the Quasi-Softmax transform meet the Gaussian unbiased assumptions of the data assimilation system,and are promising control variables for data assimilation systems.

Impact of Long-range Desert Dust Transport on Hydrometeor Formation over Coastal East Asia

Model simulations and hydrological reanalysis data for 2007 are applied to investigate the impact of long-range desert dust transport on hydrometeor formation over coastal East Asia. Results are analyzed from Hong Kong and Shanghai, which are two representative coastal cities of East Asia. Long-range desert dust transport impacts mainly spring and summer clouds and precipitation over coastal East Asia. In spring, clouds and precipitation come mainly from large-scale condensation and are impacted mainly by dust from the Gobi, Sahara, and Thar deserts. These desert dusts can participate in the precipitation within and below the clouds. At lower latitudes, the dust particles act mainly as water nuclei. At higher latitudes, they act as both water nuclei and ice nuclei. The effect of Gobi, Sahara, and Thar dust on large-scale clouds and precipitation becomes stronger at higher latitudes. In summer, clouds and precipitation over coastal East Asia come mainly from convection and are impacted mainly by dust from the Taklamakan, Arabian, and Karakum-Kavir deserts. Most Taklamakan dust particles can participate in precipitation within convective clouds as ice nuclei, while Arabian and Karakum-Kavir dust particles participate only as water nuclei in precipitation below the clouds. The effect of Taklamakan dust on convective clouds and precipitation becomes stronger at lower latitudes. Of all the desert dusts, that from the Gobi and Taklamakan deserts has the relatively largest impact. Gobi dust impacts climate change in coastal East Asia by affecting spring water clouds at higher latitudes.

Influence of Mass and Radius of Ice Crystals on Hydrometeors,Internal Energy,and Kinetic Energy:A Numeric Model Study

Two cloud-scale experiments with two different ice-phase schemes were carried out for a precipitation event that occurred in eastern China in 2005.The results were analyzed to examine the influences of the change of ice-particle mass and radius on hydrometeors,internal energy,and kinetic energy,as well as the primary factors responsible.It was found that the ice content increases notably and the snow content decreases due to the change.This is the consequence of the modulation of cloud microphysical processes.In particular,the Bergeron process and the accretion of snow and cloud ice are markedly influenced.The differences of internal energy and kinetic energy between the two experiments are caused by adjustments to pressure-flux divergence,the coupling of temperature and divergence,and gravitational work,and the reason is that these three factors result in differences of local changes of internal and kinetic energy.

Parameterizations of different hydrometeor spectral relative dispersion in the convective clouds

Spectral relative dispersion of different hydrometeors is vital to accurately describe sedimentation.Here,the Weather Research and Forecasting model with spectral bin microphysics is used to simulate convective clouds in Shouxian of Anhui province in China to study the spectral relative dispersion of different hydrometeors.Firstly,regardless of clean or polluted conditions,the relative dispersion of ice crystal spectra and its volume-mean diameter are negatively correlated,while the relative dispersion of other hydrometeor spectra is positively related to their respective volume-mean diameter.The correlations for cloud droplets and raindrops are affected by the process of collision-coalescence;the correlations for ice crystals,graupel particles,and snow particles could be affected by the deposition,riming,and aggregation processes,respectively.Secondly,relative dispersion parameterizations are developed based on a comprehensive consideration of the relationships between the relative dispersion and volume-mean diameter under both polluted and clean conditions.Finally,the relative dispersion parameterizations are applied to terminal velocity parameterizations.The results show that for cloud droplets,ice crystals,graupel particles,and snow particles,assuming the shape parameter in the Gamma distribution is equal to 0 underestimates the shape parameter and overestimates the relative dispersion;and for raindrops,assuming the shape parameter is equal to 0 is close to the relative dispersion parameterizations.The most appropriate constant shape parameters are recommended for different hydrometeors.The relative dispersion parameterizations developed here shed new light for further optimizing the terminal velocity parameterizations in models.

A Recognition Method of Hydrometeor in Tropical Cyclones by Using the GPM Dual-Frequency Precipitation Radar

In this paper,we propose a fuzzy logic algorithm to recognize the types of hydrometeors by using Ka and Ku reflectivity factors,temperature thresholds and an asymmetric t-form membership function.The identifiable types of hydrometeors include snow,graupel,mixed-phase particles,large raindrops,and small raindrops.The reflectivity detection data of Ka and Ku with attenuation correction is from dual-frequency precipitation radar onboard the global precipitation measurement satellite.The temperature data from the European Centre for Medium-range Weather Forecasts are used to identify the hydrometeors,and the identified hydrometeors are compared with the vertical profiles of phase from official level-2 DPR products.The results show that the identified hydrometeors are reasonable and reveal the evolution process of tropical cyclones,which can be further applied to the study of precipitation microphysical process and artificial precipitation.

扩展水凝物控制变量的雷达资料同化对台风“天鸽”数值模拟的影响

利用WRF(Weather Research and Forecast)模式及WRFDA(WRF model data assimilation system)系统,针对2017年台风“天鸽”个例通过同化雷达径向速度(Vr)和反射率因子(RF),研究水凝物控制变量的雷达资料同化对台风分析预报的影响。研究表明:雷达径向速度的直接同化有效地改进了模式初始场中台风涡旋区的中小尺度信息,分析场中产生了气旋性的风场增量,对模式背景场中的台风有显著增强作用。通过在传统控制变量中扩展针对水凝物的控制变量可有效地同化雷达反射率因子资料,对初始场的水物质进行调整,并对随后确定性预报的台风路径和强度都有一定的正效果。此外,相比没有水凝物控制变量的雷达同化试验,加入了水凝物控制变量的雷达资料同化试验降水预报效果更好。这为将我国近海的地基多普勒天气雷达用于台风初始化分析和预报提供了一定的技术支撑和保障。

双偏振雷达水凝物分类算法优化及在雹暴云的应用分析

为提升我国多普勒双偏振雷达水凝物分类的应用水平,在美国强风暴实验室(NSSL)研发的水凝物分类算法(HCA)基础上,通过增加冰雹区与三体散射区水凝物类型的订正识别、选用数值模式温度分析场识别融化层、引入水凝物类型垂直分布限制条件等,建立了优化方法(HCA-Opt)。利用HCA-Opt分析了2021年7月9日济南市章丘区一次雹暴云的水凝物分布特征,对冰雹落区与水凝物分类结果进行比对检验,得到如下主要结论:HCA-Opt可以正确识别冰雹与三体散射区的水凝物类型,修正了HCA将其识别为地物的问题;HCA-Opt利用模式温度分析场可准确识别融化层高度,解决了强对流天气下HCA使用的融化层自动识别算法(MLDA)无法有效识别融化层的缺陷;与HCA相比,HCA-Opt识别的水凝物在垂直分布上更加合理。HCA-Opt给出的水凝物分类结果较好描述了雹暴初生、降雹不同阶段的水凝物空间分布,初步揭示了不同高度水凝物粒子相态转化特征。HCA-Opt识别的水凝物分类中,中(小)雨与霰的可信度最高,冰晶与湿雪的可信度较低,且容易与干雪混淆;总体而言,HCA-Opt提高了水凝物分类识别技巧,对冰雹预警和落区判别具有较好的指示作用和业务应用前景。

一次东北冷涡天气过程双偏振雷达降水粒子相态识别

利用辽宁省S波段双偏振天气雷达资料,对2019年6月7—9日辽宁地区一次东北冷涡强对流天气过程及双偏振雷达的偏振参量在降水粒子相态识别中的作用进行分析,并对模糊逻辑算法中的判别规则进行改进和分析。结果表明:双偏振雷达的偏振参量可以对水凝物的种类、空间分布、物理形态进行大致判断,但水凝物相态识别结果仍需细化。采用非均匀权重相加的判别规则能够有效地对两次天气过程中的降水粒子相态进行识别。不同的判别规则得到的水凝物分类结果在弱回波区虽存在一定差异,但在大部分观测区域的分类结果基本一致,符合天气演变规律,能够为气象预报预警提供鉴别参考。具有广泛时间、空间适配性的模糊逻辑算法,仍需大量实测案例数据的验证与仿真。

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

The characteristics of the raindrop size distribution(DSD)during regional freezing rain(FR)events that occur throughout the phase change(from liquid to solid)are poorly understood due to limited observations.We investigate the evolution of microphysical parameters and the key formation mechanisms of regional FR using the DSDs from five disdrometer sites in January 2018 in the Jianghan Plain(JHP)of Central China.FR is identified via the size and velocity distribution measured from a disdrometer,the discrete Fréchet distancemethod,surface temperature,human observations,and sounding data.With the persistence of precipitation,the emergence of graupel or snowflakes significantly reduces the proportion of FR.The enhancement of this regional FR event is mainly dominated by the increase in the number concentration of raindrops but weakly affected by the diameters.To improve the accuracy of quantitative precipitation estimation for the FR event,a modified second-degree polynomial relation between the shapeμand slopeΛof gamma DSDs is derived,and a new Z-R(radar reflectivity to rain rate)relationship is developed.The mean values of mass-weighted mean diameters(D_(m))and generalized intercepts(lgN_(w))in FR are close to the stratiform results in the northern region of China.Both the melting of tiny-rimed graupels and large-dry snowflakes are a response to the formation of this regional FR process in the JHP,dominated by the joint influence of the physical mechanism of warm rain,vapor deposition,and aggregation/riming coupled with the effect of weak convective motion in some periods.

冀西北地区一次大冰雹过程的双偏振雷达特征分析

利用常规气象资料、ERA5再分析资料以及雷达资料,对2022年6月10日发生在冀西北地区的一次大冰雹天气过程进行分析。结果表明:(1)此次冰雹天气发生在冷涡的东南象限、低空切变线前侧暖区,对流由局地的热力作用触发并在辐合线附近发展加强。(2)降雹过程可分为3个阶段,前2个阶段为2个不同的超级单体分别影响而形成,粒子相态识别结果主要为干冰雹粒子,雷达回波具有高反射率因子、低差分反射率因子、高相关系数和低差分相移率的特点;第3个阶段为2个超级单体合并后形成,除冰雹外还出现了局地的短时强降水,直径较大且数密度较多的大雨滴造成了短时强降水。(3)利用雷达反演的风场可以分析对流单体的动力结构,通过分析不同阶段单体的动力结构得到单体未来的移动方向与发展趋势,特别是垂直剖面中上升气流的强度对单体的发展趋势有重要指示意义。