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.

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.

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.

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.

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.

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(WRF) 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

暖云粒子数浓度及粒子谱对微物理过程的模拟有着重要影响,不同于许多微物理方案,WDM6方案显示预报云滴数浓度。为评估其模拟效果,本文对比了WDM6方案与Thompson方案、Morrison方案在一次飞机观测试验中的模拟结果。结果表明:相比于观测结果,WDM6方案模拟云(雨)滴数浓度偏小(大),云滴谱较宽,特别是对于层状云中上部的模拟偏差较大。尽管Thompson方案和Morrison方案将云滴数浓度设置为常数,但这两种方案的云滴数浓度及云滴谱却更接近于观测。对于WDM6方案初始云凝结核数目(CCN0)的敏感性试验表明,改变CCN0能够改进WDM6方案对于对流云的模拟,但对于层状云的模拟结果影响较小。

Parameterizations of different hydrometeor spectral relative dispersion in the convective clouds

离散度的诊断对模式中沉降过程的准确描述至关重要.本文利用WRF模式结合谱分档方案模拟安徽寿县地区的对流云,研究不同水成物的离散度.首先,无论在清洁还是污染条件下,除冰晶谱的离散度与体积平均直径间呈现负相关关系外,云滴,雨滴,霰粒子与雪粒子谱离散度与体积平均直径呈现正相关关系;云滴和雨滴受碰并过程影响,冰晶,霰粒子和雪粒子分别受凝华过程,淞附过程和聚并增长影响.其次,综合考虑污染与清洁条件下离散度和体积平均直径之间的相关关系,建立了离散度的参数化方案.最后,把该离散度方案应用到下落末速度的参数化方案中,结果表明,对于云滴,冰晶,霰粒子和雪粒子,在Gamma分布中假设谱形参数等于0会低估谱形参数而高估离散度.对于雨滴而言,假设谱形参数等于0与参数化方案结果接近.针对不同的水成物,给出了最合适的谱形参数定值.本文发展的离散度方案为进一步优化模式中下落末速度参数化方案提供参考.

Characteristics of Cloud Water Resource and Precipitation Efficiency of Hydrometeors over Northwest China

Understanding the characteristics of cloud water resource(CWR)and precipitation efficiency of hydrometeors(PEh)is imperative for the application of CWR in Northwest China.The atmospheric precipitable water(PW)in all four seasons and clouds and PEh in summer were studied with ERA-5 and CloudSat data in this region.The results show that topography,especially in the Tibetan Plateau,exerts significant impacts on the precipitation and PW in summer,since large amounts of clouds are distributed along the mountain ranges.The study region is divided into four typical areas:the monsoon area in eastern Northwest China(NWE),the Qilian Mountains area(QM),the Tianshan Mountains area(TM),and the Source of Three Rivers area(STR).Over the four areas,cloud top height(6.3 km)and cloud base height(3.3 km)over NWE are higher,and precipitating clouds are thicker(7 km)in the single-layer clouds.Liquid water content decreases with increasing altitude,while the ice water content first increases and then decreases.Liquid water path is higher over NWE(0.11 kg m^(−2))than over TM and STR(0.05 kg m^(−2)),and the ice water path is mainly concentrated within the range of 0.025–0.055 kg m^(−2).The PEh values are distributed unevenly and affected evidently by the terrain.Although the PEh values in the four typical areas(0.3–0.6)are higher than those in other regions,the CWR is relatively abundant and has a higher exploitation potential.Therefore,it is well-founded to exploit CWR for alleviating water shortages in these areas of Northwest China in summer.

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。

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。

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.

Effect of Different Microphysical Parameterizations on the Simulations of a South China Heavy Rainfall

A heavy rainfall event in south China was simulated by the Weather Research and Forecasting(WRF) model with three microphysics schemes, including the Morrison scheme, Thompson scheme, and Milbrandt and Yau scheme(MY), which aim to evaluate the capability to reproduce the precipitation and radar echo reflectivity features, and to evaluate evaluate their differences in microphysics and the associated thermodynamical and dynamical feedback. Results show that all simulations reproduce the main features crucial for rainfall formation. Compared with the observation, the MY scheme performed better than the other two schemes in terms of intensity and spatial distribution of rainfall. Due to abundant water vapor, the accretion of cloud droplets by raindrops was the dominant process in the growth of raindrops while the contribution of melting was a secondary effect. Riming processes, in which frozen hydrometeors collect cloud droplets mainly, contributed more to the growth of frozen hydrometeors than the Bergeron process. Extremely abundant snow and ice were produced in the Thompson and MY schemes respectively by a deposition process. The MY scheme has the highest condensation and evaporation, but the lowest deposition. As a result, in the MY scheme, the enhanced vertical gradient of condensation heating and evaporation cooling at low levels produces strong positive and weak negative potential vorticity in Guangdong, and may favor the formation of the enhanced rainfall center over there.

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。

卷积神经网络联合SVM的降水粒子分类

针对传统模糊逻辑降水粒子识别算法存在过度依赖专家经验来设置参数的缺陷,提出一种基于卷积神经网络(Convolutional Neural Network,CNN)和支持向量机(Support Vector Machine,SVM)联合结构的降水粒子分类方法。本文首先搭建了适用于双偏振雷达数据矩阵传播结构的4种卷积神经网络模型,通过对KOHX雷达各极化参数进行分块和堆叠操作,制作模型所需数据集并训练模型。然后根据各CNN模型对目标块的分类特点,结合SVM分类器,搭建能够识别5类目标粒子的联合结构。最后,对KOHX雷达0.5°仰角扫描数据进行测试,得到该联合结构模型的分类准确率达94.92%。并且对于不同仰角、不同雷达的扫描数据均能进行有效分类,表现出较好的鲁棒性。

不同云微物理方案对台风“安比”降雨模拟的影响

利用WRF3.9.1模式对台风“安比”于2018年7月23日至24日北上至37°N以北造成的河北东北部、天津等地的大暴雨过程进行模拟,并对比了不同云微物理方案模拟的台风路径、结构、降雨分布,分析了云内水成物混合比差异与垂直运动的关系。结果表明:①各方案均能较好模拟出台风北上时的结构和强度,其中Morrsion 2-moment方案对强降雨的时段、区域、中心雨量把握最准确。②台风主雨区云体内的云水粒子分布于0~8 km,0℃高度在4~5 km,说明云体内存在大量过冷水。③强降雨时段,各方案模拟的垂直上升速度与小时雨强有较好的对应关系。同时雨区云顶高达10~15 km,配合云团内的强上升运动,云中出现大量过冷水及固态水成物。④Thompson方案与Morrsion 2-moment方案的云霰混合比明显大于其他方案,并且云霰粒子、云水粒子在0℃以上有大量重合,二者是云中贝吉龙过程的关键因素,对降雨量有着直接影响。⑤各微物理方案模拟的云体内部垂直上升运动区强弱与小时雨强大小相关性较好。本研究可以为改进适用于台风的云微物理方案提供方向,还加深了云微物理过程对台风降雨的认识。