[an error occurred while processing this directive]
暴雨灾害
       首页|  期刊介绍|  编 委 会|  征稿简则|  期刊订阅|  下载中心|  编辑部公告|  联系我们


暴雨灾害  2015, Vol. 34 Issue (01): 1-    DOI:
论文 最新目录 | 下期目录 | 过刊浏览 | 高级检索  |   
基于云团的分组Z-R关系拟合方案效果评估与误差分析
勾亚彬1,2 ,刘黎平2,王丹3, 仲凌志2,陈超4
(1.杭州市气象局,杭州 310051;2.中国气象科学研究院 灾害天气重点实验室,北京 100081; 3.国家气象中心,北京 100081;4.广东省气象台,广州 510080)
Evaluation and Analysis of the Z-R Storm-Grouping Relationships Fitting Scheme based on Storm Identification
GOU Yabin1, 2, LIU Liping2, WANG Dan3, ZHONG Lingzhi2, CHEN Chao4
(1. Hangzhou Meteorological Bureau , Hangzhou 310051;2.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Science, Beijing 100081;3.National meteorological center, Beijing 100081;4.Guangdong Meteorological Observatory Guangzhou,510080)
 全文: PDF (2785 KB)   HTML ( 输出: BibTeX | EndNote (RIS)      背景资料
摘要 为了降低因Z-R关系不确定导致的雷达定量降水估测(Quantitative Precipitation Estimation,简称QPE)误差,提出了基于云团的分组Z-R关系拟合方案,在风暴单体识别算法得到的不同降水云团或同一个云团内部的不同数据分组区域内,拟合并采用不同的Z-R关系反演地面降水信息。以2013年6月5—7日的梅雨锋过程为例,使用覆盖长江中下游地区的28部多普勒雷达和全国逐分钟雨量计的观测资料,对单一动态关系?简单分组Z-R关系以及基于云团的分组Z-R关系反演的雷达1 h QPE进行效果对比和误差分析,结果表明:(1)基于云团的分组Z-R关系可以有效识别降水云系的局部特征,这是基于云团的分组Z-R关系优于其他两种Z-R关系方案的重要原因。(2)雷达波束部分遮挡导致的偏弱反射率因子,对雷达QPE数据场的不连续性和Z-R关系的不确定性均有影响。(3)雷达硬件或雷达标定引入的偏强(弱)的反射率因子,与简单分组Z-R关系得到的雷达QPE局部高(低)估相关,这降低了简单分组Z-R关系在大范围降水过程中的适用性,但对基于云团的分组Z-R关系的影响较小。
服务
把本文推荐给朋友
加入我的书架
加入引用管理器
E-mail Alert
作者相关文章
勾亚彬
刘黎平
王丹
仲凌志
陈超
关键词风暴单体识别   分组Z-R关系   定量降水估测     
Abstract: A new grouping Z-R relationships fitting scheme is proposed based on the storm information derived by the storm-identification algorithm to reduce the error of quantitative precipitation estimation (QPE), by which different Z-R relationships are calculated and utilized respectively within separated storms identified by storm identification algorithm or data groups within the same storm to retrieve the surface rainfall information. Case study is presented by using the Meiyu front event between 05 and 07 June 2013, which covered the whole Middle-Lower Yangtze Plain. Using 28 S-band Doppler radar and 11623 minute-by-minute gauge observations, the unique dynamical Z-R relationship, simple grouping Z-R relationships and Z-R grouping relationships based on storm identifications are compared using radar 1-hour quantitative precipitation estimation derived respectively, the results show that (1) the storm-grouping relationships fitting scheme can effectively capture the local data characteristics which make it superior to the other two fitting scheme.(2) the weaker radar echoes introduced by radar beam shielding not only accounts for the discontinuity of radar QPE but affects the uncertainty of the Z-R relationships.(3) the stronger or weaker radar echoes resulted by radar hardware or the calibration associates with the overestimation or underestimation of radar QPE derived by the simple grouping Z-R relationships and make it unsuitable for the application in the large-scale rainfall event, but the impact on the storm-grouping relationships fitting scheme is relatively smaller.
Key wordsstorm-identification   grouping Z-R relationships   quantitative precipitation estimation   
引用本文:   
勾亚彬 , 刘黎平, 王丹,等 .2015. 基于云团的分组Z-R关系拟合方案效果评估与误差分析[J]. 暴雨灾害, 34(01): 1-.
GOU Yabin , LIU Liping, WANG Dan, et al .2015. Evaluation and Analysis of the Z-R Storm-Grouping Relationships Fitting Scheme based on Storm Identification[J]. Torrential Rain and Disasters, 34(01): 1-.
 
没有本文参考文献
[1] 张扬,刘黎平,何建新,文浩. 雨滴谱仪网数据在雷达定量降水估测中的应用[J]. 暴雨灾害, 2016, 35(2): 173-181.
[2] 殷志远,彭涛,杨芳, 沈铁元. 基于QPE 和QPF的遗传神经网络洪水预报试验[J]. 暴雨灾害, 2013, 32(4): 360-368.
[3] 吕晓娜,牛淑贞,袁春风,袁晓超. SWAN中定量降水估测和预报产品的检验与误差分析[J]. 暴雨灾害, 2013, 32(2): 142-150.
[4] 张亚萍,刘德,廖峻,周奇,田茂举. 一种基于水文模拟建立中小河流洪水气象风险等级指标的方法[J]. 暴雨灾害, 2012, 31(4): 351-357.
版权所有 © 2011《暴雨灾害》编辑部    鄂ICP备06018784号-3
地址: 湖北省武汉市东湖高新技术开发区金融港二路《暴雨灾害》编辑部
 邮编: 430205 Tel: 027-81804935   E-mail: byzh7939@163.com
技术支持: 北京玛格泰克科技发展有限公司