摘要
基于2008—2016年昆山市自动气象站逐分钟降水观测数据,分别利用芝加哥雨型法和Pilgrim&Cordery雨型法,推求昆山市不同生态系统在不同重现期下60 min和120 min短历时设计暴雨雨型,并对比分析两种雨型推求方法的结果以及不同生态系统的雨型计算结果。结果表明:推求昆山市60 min历时设计暴雨雨型分布时,芝加哥雨型法和Pilgrim&Cordery雨型法的结果基本一致,为单峰型雨型,雨峰位置位于中间偏前;推求120 min历时设计暴雨雨型分布时,芝加哥雨型法结果为单峰型,Pilgrim&Cordery雨型法为多峰型,但两种方法求得的雨峰位置都位于中间偏前。在历时60 min和120 min时,芝加哥雨型法计算出的平均最大分段降水量显著大于Pilgrim&Cordery法和实际雨样的结果,Pilgrim&Cordery法的结果略小于实际雨样。昆山市不同地区的降水会受到生态系统类型的影响,以农田生态系统的影响最为明显,两种雨型推求方法的结果均表示,农田生态系统的最大分段降水量是5种生态系统中最大的。
Based on the minute-by-minute precipitation observation data of Kunshan automatic meteorological stations from 2008 to 2016,designed rainstorm pattern of different ecosystems in Kunshan City for the durations of 60 minutes and 120 minutes were deduced with the Chicago method and the Pilgrim&Cordery method,meanwhile,the two methods and the results of rain pattern calculation in different ecosystems were compared and analyzed.Results show that when inferring the designed rainstorm distribution of 60 minutes in Kunshan,the results of the Chicago method and the Pilgrim&Cordery method are basically the same.Both of them are unimodal rain patterns,and the rain peaks are located in the front.When inferring the design rainstorm distribution of 120 minutes,the Chicago method is unimodal and the Pilgrim&Cordery method is multimodal,but the rain peak positions obtained by the two methods are located in front of the middle.During 60 minutes and 120 minutes,the average maximum segmental precipitation calculated by the Chicago method is significantly larger than those of the Pilgrim&Cordery method and actual rain samples,and the results of the Pilgrim&Cordery method are slightly smaller than the actual rain samples.Precipitation in different areas of Kunshan will be affected by ecosystem type,in which,the farmland ecosystem is the most obvious.The results of the two rain type estimation methods indicate that the maximum segmental precipitation of farmland ecosystems is the largest of the five ecosystems.
作者
汪婷
包云轩
陈粲
唐倩
吴俊梅
夏蕴玉
WANG Ting;BAO Yunxuan;CHEN Can;TANG Qian;WU Junmei;XIA Yunyu(Meteorological Bureau of Kunshan City,Jiangsu Kunshan 215337,China;Meteorological Disaster Forecast and Evaluation Collaborative Innovation Center,Nanjing University of Information Science&Technology,Nanjing 210044,China)
出处
《气象科学》
北大核心
2021年第2期259-269,共11页
Journal of the Meteorological Sciences
基金
昆山市社会发展科技计划项目(KS1459)
江苏省大学生科技创新训练项目(201610300081X)。