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The accuracy of quantitative precipitation estimation (QPE) for dual-polarization radars can be improved by using a localized rainfall estimation algorithm derived from the raindrop size distribution (DSD). In the present study, DSDs observed at Suzhou City, Jiangsu province; Yangjiang City, Guangdong province; and Naqu City, Tibet are analyzed during the rainy season together with the corresponding polarimetric variables for the above three regions. Most importantly, these DSD data are used to develop optimal “synthetic” QPE algorithms for S-, C-, and X-band dual-polarization radars, which will be built or upgraded in the three regions. Meanwhile, a new piecewise fitting method (PFM) is proposed. It has been found that the number concentration N(D) of small raindrops (D<1mm) is the highest in Suzhou, while that of larger raindrops (D>1mm) is the highest in Yangjiang. The characteristics of the differential reflectivity (ZDR) and specific differential phase (KDP) are significantly different in the three locations, suggesting that different rainfall estimators are needed for different locations. Further performance assessment of the QPE based on DSD data indicates that the PFM QPE algorithm (LDSD) performs better than the conventional fitting method (CFM), and the localized QPE algorithm can improve the QPE accuracy. Observations from S-band dual-polarization radars and rain gauges in the Southern China Monsoon Rainfall Experiment are implemented to verify the performances of the QPE algorithms proposed in the present study. It is found that compared with non-localized algorithms, the localized LDSD algorithm yields the best results with at least 7.66% and 8.43% reductions in the RMSE and NE, respectively, which implies that while polarimetric variables can reflect DSD characteristics, the localized QPE algorithm remains necessary. 相似文献
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为了提高雷达定量降水估测的精度,建立一套高精度的双偏振雷达定量降水估测方法,并对其在业务应用中的表现进行评估。本文利用雨滴谱仪数据使用非球形粒子的散射模型（T-Matrix模型）进行不同偏振量的模拟计算,根据计算结果对实测雨滴谱数据（DSD）进行分类拟合,实现对CSU-HIDRO（Colorado State University-Hydrometeor Identification Rainfall Optimization）优化降水估测算法的改进。为了评估改进后CSU-HIDRO优化算法（简称CSU-HIDRO_I）的应用效果,本文选取2016～2017年两年汛期发生于中国华南地区的6次大范围强降水过程为评估对象,分别采用单偏振雷达定量降水估测的R(ZH)关系法（WSR-88D Precipitation Processing System,简称PPS法）和CSU-HIDRO_I法进行小时降水量估测。按照不同降水率大小以及距离雷达20～60 km和60~100 km范围分别对两种降水估测方法进行评估,并将雷达估测的小时降水量同地面雨量计小时降水量资料进行对比,结果表明:（1）CSU-HIDRO_I法在应用评估过程中取得了较好的评估效果,其估测精度及稳定性均较好。（2）PPS法对小雨（降水率R<2.5 mm/h）存在一定的高估,对大雨及暴雨（R>8 mm/h）存在明显低估,而CSU-HIDRO_I法能够有效的降低强降水的低估情况,同时提高了小雨的估测精度。与PPS法相比,CSU-HIDRO_I法对小雨、中雨、大雨及暴雨的估测偏差分别降低了38%、24%、17%、15%。（3）PPS法在降水估测中对离雷达的距离更为敏感,相同降水率下不同距离处的相对误差波动较大,CSU-HIDRO_I法对距离敏感性较弱,相同降水率强度下,相对误差随距离的变化波动较小。 相似文献
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基于比差分传播相移(KDP)的降水估计算法R(KDP)相较于传统基于水平反射率因子(ZH)的算法R(ZH)的表现更优。在雷达实际运行中,由于随机误差和后向散射相位(backscattering phase)的影响,可能出现负的KDP。运用一种基于变分的雷达定量降水估计混合算法(V-RQPE)。该算法用变分拟合方法重构差分相位(ΦDP),用一种新的稳健的边界条件求解方法,在消除随机误差的同时获得非负的KDP,进而进行降水估计。随后我们使用2017年5月7日广州S波段雷达的回波数据和地面雨量站观测数据进行验证,同时使用了六种不同的算法进行对比,结果显示,在1小时累计降水估计中,V-RQPE表现最好,在24小时累计降水估计中,V-RQPE和基于变分拟合的KDP的降水估计算法(R-VKDP)表现最好,实验结果表明变分拟合方法对雷达降水估计能力有显著提升。 相似文献
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利用房山X波段双偏振雷达观测资料，分析2017年6月18日北京门头沟泥石流的强降水过程，重点研究了泥石流发生地上空10 km×10 km区域内雷达反射率因子时空变化特征，并结合雷达定量降水估测（Quantitative Precipitation Estimation，QPE）讨论该类雷达探测设备在复杂地形区域的适用性。结果表明，在山区常规自动气象站布网稀疏的条件下，X波段双偏振雷达能够有效捕捉此次强降水的发生发展过程，同时，雷达定量降水估测得到的高分辨率降水场可以把握山区强降水中心，进而弥补山区雨量站匮乏的不足。此次过程中影响泥石流事件发生的降水时间发生在6月18日12—16时，其中，15时事发区域小时QPE最大值达到53.9 mm·h-1，上游来水和局地突发性强降水共同作用是本次泥石流事件的主要成因。 相似文献
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利用2013年8月北京C波段双偏振多普勒天气雷达体扫数据、探空资料和地面雨量站资料,获得反射率因子垂直廓线（vertical profile of reflectivity,VPR）识别零度层亮带,比较平均反射率因子垂直廓线（mean VPR,MVPR）、显著反射率因子垂直廓线（apparent VPR,AVPR）和显著相关系数垂直廓线（apparent vertical profile of correlation coefficient,AVPCC）3种零度层亮带订正方法的效果,并利用地面雨量站资料进行定量降水估计（quantity precipitation estimation,QPE）验证订正效果。结果表明:采用MVPR和0℃层高度能有效识别零度层亮带,零度层亮带厚度为0.8~1.5 km;经3种方法订正后,零度层亮带影响区得到了不同程度的抑制,其中MVPR法订正效果最差,基本未能减弱零度层亮带的影响,AVPR法和AVPCC法的订正效果较好,明显减弱了零度层亮带影响区的回波强度,订正后回波更均匀。利用地面雨量站数据进行QPE验证表明:经零度层亮带订正后雷达估测的降水与地面雨量站实测降水更接近,也表明AVPR法和AVPCC法效果更好。 相似文献
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A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter, chaff, clear air echoes etc. In this study, a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek. For selected precipitation and non-meteorological events, the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values. The membership functions and weights are then determined by these density functions. Finally, the non-meteorological echoes are identified by combining the membership functions and weights. The performance is qualitatively evaluated by long-term rain accumulation. The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection (POD), false alarm rate (FAR), and clutter-signal ratio (CSR). In addition, the issues in using filtered dual-polarization data are alleviated. 相似文献
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The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation(QPE) based on the Z–R(reflectivity factor–rain rate) relationship.The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity(VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands(S-, C-and X-band) of dual-polarized radars and to reduce overestimation errors in Z–R relationship–based QPEs. After the reflectivity was corrected by the algorithms using average VPR(AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient(AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z–R relationship–based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE(root-mean-square error), RMAE(relative mean absolute error) and RMB(relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28,0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively.The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars. 相似文献
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Kun ZHAO Hao HUANG Mingjun WANG Wen-Chau LEE Gang CHEN Long WEN Jing WEN Guifu ZHANG Ming XUE Zhengwei YANG Liping LIU Chong WU Zhiqun HU Sheng CHEN 《大气科学进展》2019,36(9):961-974
Dual-polarization(dual-pol)radar can measure additional parameters that provide more microphysical information of precipitation systems than those provided by conventional Doppler radar.The dual-pol parameters have been successfully utilized to investigate precipitation microphysics and improve radar quantitative precipitation estimation(QPE).The recent progress in dual-pol radar research and applications in China is summarized in four aspects.Firstly,the characteristics of several representative dual-pol radars are reviewed.Various approaches have been developed for radar data quality control,including calibration,attenuation correction,calculation of specific differential phase shift,and identification and removal of non-meteorological echoes.Using dual-pol radar measurements,the microphysical characteristics derived from raindrop size distribution retrieval,hydrometeor classification,and QPE is better understood in China.The limited number of studies in China that have sought to use dual-pol radar data to validate the microphysical parameterization and initialization of numerical models and assimilate dual-pol data into numerical models are summarized.The challenges of applying dual-pol data in numerical models and emerging technologies that may make significant impacts on the field of radar meteorology are discussed. 相似文献
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《Atmospheric Research》2010,95(4):579-595
In this work the capability of reliable rainfall measurements with small weather radars in complex terrain for flood forecasting purposes is examined. Rain measurements were carried out during winter–spring 2007 with a mobile X-band dual-polarization radar in the northwestern mountainous part of the island of Crete in Greece. In this area a 2D-video disdrometer and a network of raingauges was installed for radar calibration and evaluation of rainfall measurements, respectively. The complex terrain of the experimental site may significantly reduce the performance of rain measurements due to ground clutter and partial or total beam blockage. A beam blockage algorithm using high resolution terrain data was applied in order to find areas with significant terrain effects and estimate correction of the radar measurements. Rain attenuation correction was based on modern sophisticated algorithms using differential phase measurements. The accuracy of rainfall estimation from standard or polarimetric algorithms at plan position indicator (PPI) scans was examined for high-temporal resolution (1 min) rainfall rates and accumulated rainfall values for winter and spring time rain events. For high elevation measurements, which were required in order to avoid terrain effects in large areas of interest, a correction for the vertical-profile-of-reflectivity (VPR) was also applied to the radar data. An average VPR model used in the corresponding correction of reflectivity was constructed based on range–height indicator (RHI) scans. It was concluded that quantitative high resolution X-band radar observations of rainfall in complex terrain is possible after careful application of all the above processing steps. 相似文献
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雷达定量降水估测（QPE）是短时临近预报的关键部分,在定量降水预报（QPF）、强降水预警、城市积水内涝、地质山洪灾害、精细化天气服务等方面具有重要作用。利用京津冀地区雷达定量降水估测资料和逐时自动气象站降水观测数据,分析了2011—2016年夏季京津冀地区雷达定量降水估测的误差空间分布特征,并重点提出了一种新的雷达本地化定量气候校准算法。结果表明,京津冀地区雷达定量降水估测较好地反映了总降水量东北—西南带状分布特征,但西北部山区、东北部山区及西南部山区估计偏弱,东北部山前地带估计偏强,西北部存在虚假降水估计,而北京市城区估计最为准确。利用雷达本地化定量气候校准算法对1 h雷达定量降水估测进行气候尺度上的约束订正,检验结果表明,经过校准后的雷达定量降水估测偏差（BIAS）、平均绝对误差（MAE）、均方根误差（RMSE）和均方根相对误差（RRMSE）均减小。绝大部分站点偏差减小幅度超过50%,京津冀东部及南部平原地带平均绝对误差、均方根误差和均方根相对误差减小幅度在20%左右,而北部及西南部山区误差减小幅度相对较小。降水个例检验结果表明,经过雷达定量气候校准后的雷达定量降水估测强度更接近自动气象站观测的降水量级,且降水结构细致,偏差、平均绝对误差和均方根误差均减小,与自动气象站观测降水的相关系数增大,因此该算法有助于改进雷达定量降水估测的准确度。 相似文献
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雷达定量降水估计技术及效果评估 总被引：13，自引：2，他引：11
为提高雷达定量估测降水的精度,利用广东省6部新一代多普勒天气雷达(CINRAD/SA)回波资料和雨量计降水量观测资料,采用概率配对法(PFT,Probability-fitting technique)建立Z-I关系进行单部雷达降水估测,并采用最优插值法(OI,Optimum Interpolation)对降水估计进行订正;为扩大降水估测的范围,对多部雷达的降水估计进行拼接,采取重叠区域以各部雷达的均方根误差平方的倒数作为权重系数(iω==1/RMSE(K)2/n∑i-1/RMSE(i)2)进行加权平均,并分别分析比较上述方法得到的降水估计与单纯OI雨量计及与雷达拼图回波强度得到的降水估计的优劣。以上各环节误差分析表明,对于单部雷达,雨量计降水强度与其上空9点平均的雷达回波强度关系最为密切;6部相同型号的雷达估测降水精度各异。交叉检验表明,OI雷达法对单部和多部雷达估测降水均可取得较好的校准效果;对于多部雷达的降水估测,单部雷达先分别进行OI订正后拼接,然后对重叠区再次OI订正的结果比直接对未订正的单部雷达降水估计拼接后统一做一次OI订正的效果好。多部雷达降水估计拼接时,前期对于单部雷达降水估计的订正尤为重要;多部雷达降水估计的拼接值精度要明显高于OI雨量计,而相比由雷达拼图回波强度得到的降水估计而言,前者也优于后者。因此,多部雷达降水估计的拼接方法,对雷达资料的应用有较好的参考价值,在业务上也有一定的应用前景。 相似文献
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高时空分辨率、高精度的降水产品对于极端降水的监测以及防灾减灾具有重要意义。地面雨量计提供点尺度降水精确观测,但无法精细化捕捉对流性强降水的空间分布。雷达观测可以精细地刻画降水的空间分布特征,但雷达定量估计降水（QPE,quantitative precipitation estimation）产品估测精度易受雷达观测偏差和Z–R（雷达反射率—降水率）关系等因素影响。因此,本文开展高时空分辨率的雷达—雨量计降水融合算法研究,集成雨量计观测和雷达定量估计降水产品各自的优点。该算法主要步骤包括:雨量站观测数据格点化、局地雨量计订正雷达QPE和雷达—雨量计降水融合三个部分。首先利用克里金插值方法,对雨量站观测的降水进行插值,得到格点降水信息;再通过局地雨量计订正方法系统性地订正雷达QPE产品,以提高雷达QPE产品精度;最后,结合降水类型,通过雷达—雨量计降水融合算法,产生高时空分辨率、高精度的雷达—雨量计降水融合产品。通过郑州“21·7”暴雨、台风“烟花”和2021年8月随州暴雨三个典型的极端降水个例,对雷达—雨量计降水融合算法产生的雷达—雨量计降水融合产品进行了系统地评估和分析。结果表明,在不同的极端降水个例和不同的降水时段,雷达—雨量计降水融合产品精度上优于雷达QPE产品,且在降水的空间分布上较雨量站观测格点插值产品更能精细地刻画降水的结构特征。表明算法得到的雷达—雨量计降水融合产品的准确性较高,对极端降水有较好地捕捉和监测能力。 相似文献
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复杂地形下C波段雷达定量降水估计算法 总被引：1，自引：0，他引：1
C波段雷达定量降水估计（QPE）精度受到很多因素的影响,主要包括:（1）雷达标定,（2）非气象回波的干扰,（3）降水物垂直空间变化,（4）地形或地物的严重遮挡,（5）Z-R关系的代表性,（6）雷达拼图的质量,（7）雷达观测回波衰减等。文中雷达定量降水估计算法基于陕西省C波段天气雷达展开,从雷达探测数据质量控制、地形遮挡、Z-R关系和雷达拼图等方面提高C波段天气雷达定量降水估计的精度,产生降水类型产品和1 h定量降水估计产品,产品空间分辨率为0.01°×0.01°,时间分辨率为6 min。通过对7次降水过程进行评估,结果表明:基于混合仰角反射率因子处理模块和降水类型分类模块进行雷达定量降水估计,得到的结果与地面雨量站观测降水接近,1 h累计降水量的统计评分指标均方根误差稳定在3 mm以下,相对误差稳定在50%左右,相对偏差保持在?30%以内,雷达定量降水估计产品的离散度和绝对偏差都较低,表明该算法得到的雷达定量降水估计稳定可靠。 相似文献
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本文针对南京溧水S波段双偏振多普勒天气雷达获取的回波I/Q信号,采用FFT算法处理水平和垂直通道I/Q数据,分别得到水平和垂直通道回波的强度、速度值,定性分析了两通道回波强度、速度数据差异,引入平均差及均方根误差参数做定量分析。对比结果表明:两通道I/Q数据处理得到的回波层次分布基本一致;两通道速度数据差异较小,强度数据差异较大。以水平通道回波数据为基准,当回波强度小于16 dBz时,水平通道强度偏小,这可能是由云系边缘较小的针状冰晶所致;当回波强度大于32 dBz时,水平通道强度值偏大,且随回波强度的增加两通道强度差值增大,这反映了强降水中大粒子较多,而粒子越大,降落过程中扁平程度越大;两通道回波强度的差值与回波强度大小呈现一定相关性,这可能反映了单偏振天气雷达在定量测量降水中精度不高,通过双偏振雷达联合利用两通道数据有望改善雷达定量测量降水精度,提升雷达定量估测降水能力。 相似文献
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利用对流许可尺度集合预报系统,针对2015年4月28日夜间移动到江苏南部和上海地区,伴随短时强降水和冰雹的一次强对流过程,使用初始多源融合分析场对集合预报结果影响进行了分析。结合上海南汇双偏振雷达基数据观测,对12～14 h预报时效的反射率因子、差分反射率及冰雹集合预报结果进行了定性和定量的评估,分析了改进初始水物质分布,同时增加小尺度信息对于模式预报结果的影响。主要结果为:(1)对反射率因子预报的评估显示,初始场调整了水物质分布且增加了小尺度信息的试验(以下简称ADAS试验),对降水的范围、分布特征及评分都有明显改进(2)由于差分反射率在较小的距离内变化剧烈,对其准确预报难度较大,ADAS试验虽然预报强度偏强,但整体的位置和强度与实况更为接近,特别在大粒子预报方面具有更高的技巧,能够对微物理过程相关特征更好地进行描述;(3)使用地面人工观测和双偏振雷达观测对冰雹概率预报评估的结果显示,ADAS试验预报的高概率降雹区与观测落区接近,对冰雹落区预报具有一定的指示意义。通过多源融合分析调整初始水物质分布并增加小尺度信息的集合预报试验改善了较长预报时效的强降水和冰雹概率预报,具有更高的可信度,双偏振变量预报具有区分强降水与冰雹的优势,通过与观测的对比可以更好地评估模式对微物理过程描述的准确性。 相似文献
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地形的起伏使雷达波束受到严重的遮挡,使回波数据质量受到很大干扰。本文使用SRTM任务的DEM数据和谷歌公司的DEM数据分别计算了位于北京南郊的S波段雷达低仰角的波束遮挡率,建立了部分遮挡区域的回波反射率订正关系,并在2018年5月19日北京一次大范围层状云降水过程中,对波束遮挡订正前后的雷达定量估测雨量与地面3个雨量计观测结果进行了定性与定量化对比分析。结果表明:①波束遮挡订正有助于改善反射率因子的空间连续性。波束遮挡订正后的仰角0.5°的反射率与1.5°的反射率之间的差值整体呈现缩小特征,符合层状云降水垂直廓线特点。②09:00—11:00,相比波束遮挡订正前的雷达定量估测雨量(QPE),波束订正后的QPE准确性得到改善,使用分级标准误差与归一化平均偏差评价波束遮挡订正前后QPE与雨量计实测值之间的误差,波束订正后的反射率估测雨量与雨量计实测雨量一致性更好。 相似文献
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“灾害天气短时临近预报系统”(SWAN)在我国气象预报业务中已得到广泛应用。文章介绍其中雷达定量降水估算QPE算法 (RASIM方法)的技术与特点,选取湖北省6部S波段多普勒天气雷达在2012年探测的暴雨天气过程资料,系统性评估了SWAN系统中QPE产品实用性,初步分析了产生估算误差的原因。评估表明：整体而言该方法在湖北省使用效果较好,平均绝对误差率小于30%;探测距离的增加对S波段雷达QPE精度影响不大;各雷达对30 mm以上降水的估算平均绝对误差率较小,但估算结果较实况偏弱,随着雨量（雨强）增大,低估的比例也增大。就单部雷达而言,宜昌雷达估算降水误差最大,武汉雷达受附近建筑遮挡影响次之,恩施雷达估算降水误差最小。 相似文献