| 基于聚类分析的兰州地区自动站降水特征分析 |
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| 引用本文： | 苟浩锋.基于聚类分析的兰州地区自动站降水特征分析[J].新疆气象,2020,14(1):108-114. |
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| 作者姓名： | 苟浩锋 |
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| 作者单位： | 兰州市气象局 |
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| 基金项目： | 兰州市科技局“兰州市强对流天气短时临近预报集成系统”（2018-4-57）、甘肃省气象局科研项目（GSMAZd2017-08）和中国气象局预报员专项项目(CMAYBY2019-129)共同资助 |
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| 摘 要： | 利用兰州地区2013—2018年4—10月139个自动气象站逐时累积降水量和降水小时数资料,通过K均值聚类分析方法进行二维聚类分区,分析不同区域降水精细化时空分布特征。结果表明:(1)K均值聚类方法将兰州地区降水划分为3个区域,年平均降水量分别为246、317和427 mm,降水小时数分别为306、404和454 h。分区结果同地理位置、地形高度相适应,与主观分区结果较一致但更加科学精细;(2)3个区域降水分布特征相似,但也存在较明显的地域性差异,降水量集中在7—8月,分别占46%、45%、44%,降水小时数集中在6—9月,分别占55%、53%和53%;(3)从日变化特征看,降水量、降水小时数、降水强度的高值分别集中在7—8月的午后至前半夜、7月的16—17时、8月的00—04时和16—23时。
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| 关 键 词： | 兰州地区 聚类分析 自动站分类 降水特征 |
| 收稿时间： | 2019/5/5 0:00:00 |
| 修稿时间： | 2019/9/17 0:00:00 |
Analysis of AWS Precipitation Characteristics Based on K-Means Clustering Method in Lanzhou Area |
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| gouhaofeng.Analysis of AWS Precipitation Characteristics Based on K-Means Clustering Method in Lanzhou Area[J].Bimonthly of Xinjiang Meteorology,2020,14(1):108-114. |
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| Authors: | gouhaofeng |
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| Abstract: | Through K-means clustering analysis method, two-dimensional clustering partition is conducted with hourly cumulative precipitation and hours of precipitation at 139 automatic weather stations in Lanzhou area from April to October of the year from 2013 to 2018, and spatial and temporal distribution characteristics of precipitation refinement in different regions are analyzed. The results show that: (1) K-means clustering method divides the precipitation in Lanzhou area into three precipitation regions with annual average precipitation of 246, 317 and 427 mm respectively and precipitation hours of 306, 404 and 454h respectively. The results of partition agree with geographical location and topographic height, and the results are quite in accordance with the subjective partition results but are more scientific; (2) The precipitation distribution characteristics in the three regions are similar, but the regional differences are quite clear, too. The amount of precipitation is concentrated in July and August, accounting for 46%, 45% and 44% respectively, and hours of precipitation are concentrated from June to September, accounting for 55%, 53% and 53% respectively; (3) According to the diurnal variation characteristics, precipitation, hours of precipitation, and precipitation intensity are concentrated in the afternoon to the first half of the night of July to August, from 4 to 5 p.m. in July, and from 0 to 4 a.m. and 16-23:00 in August respectively. |
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| Keywords: | Lanzhou Area Clustering Analysis AWS Classification Precipitation Characteristics |
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