{"title":"Drop size distribution retrieval using dual-polarization radar at C-band and S-band","authors":"Daniel Durbin, Yadong Wang, Pao-Liang Chang","doi":"10.5194/amt-17-5397-2024","DOIUrl":null,"url":null,"abstract":"Abstract. Having knowledge of the drop size distribution (DSD) is of particular interest to researchers as it is widely applied to quantitative precipitation estimation (QPE) methods. Polarimetric radar measurements have previously been utilized to derive DSD curve characteristics frequently modeled as a gamma distribution. Likewise, approaches using dual-frequency measurements have shown positive results. Both cases have relied on the need to constrain the relationship between the DSD parameters based on location or assumed weather conditions. This paper presents a methodology for retrieving the DSD parameters using the dual-frequency and polarimetric nature of measurements from a unique data set taken at co-located S-band and C-band dual-polarization radars. Using the reflectivity and differential-phase measurements from each radar, an optimization routine employing particle swarm optimization (PSO) and T-matrix computation of radar parameters is able to accurately retrieve the gamma distribution parameters without the constraints required in previous methods. Retrieved results are compared to known truth data collected using a network of OTT Parsivel disdrometers in Taiwan in order to assess the success of this procedure.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"63 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Measurement Techniques","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/amt-17-5397-2024","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Having knowledge of the drop size distribution (DSD) is of particular interest to researchers as it is widely applied to quantitative precipitation estimation (QPE) methods. Polarimetric radar measurements have previously been utilized to derive DSD curve characteristics frequently modeled as a gamma distribution. Likewise, approaches using dual-frequency measurements have shown positive results. Both cases have relied on the need to constrain the relationship between the DSD parameters based on location or assumed weather conditions. This paper presents a methodology for retrieving the DSD parameters using the dual-frequency and polarimetric nature of measurements from a unique data set taken at co-located S-band and C-band dual-polarization radars. Using the reflectivity and differential-phase measurements from each radar, an optimization routine employing particle swarm optimization (PSO) and T-matrix computation of radar parameters is able to accurately retrieve the gamma distribution parameters without the constraints required in previous methods. Retrieved results are compared to known truth data collected using a network of OTT Parsivel disdrometers in Taiwan in order to assess the success of this procedure.
摘要研究人员对水滴大小分布(DSD)的了解特别感兴趣,因为它被广泛应用于定量降水估算(QPE)方法。以前曾利用偏振雷达测量来推导水滴大小分布曲线特征,通常将其建模为伽马分布。同样,使用双频测量的方法也取得了积极成果。这两种方法都需要根据地点或假定的天气条件来限制 DSD 参数之间的关系。本文介绍了一种利用双频和偏振测量性质检索 DSD 参数的方法,这些测量数据来自在共址 S 波段和 C 波段双偏振雷达上获取的独特数据集。利用每部雷达的反射率和差分相位测量数据,采用粒子群优化(PSO)和雷达参数 T 矩阵计算的优化程序,能够准确地检索伽马分布参数,而无需以往方法所需的限制条件。检索结果与利用台湾 OTT Parsivel 测距仪网络收集的已知真实数据进行了比较,以评估该程序的成功与否。
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.