| 基于GIS的黔南州近31年降水时空分布特征分析 |
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| 作者姓名： | 陆莎莎 |
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| 作者单位： | 都匀市气象局 |
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| 摘 要： | 本文利用贵州省黔南州12个国家级自动气象站1989-2019年的地面降水观测资料,采用线性回归方法、Kriging法、反距离权重法、滑动t检验等方法,分析了黔南州近31年降水的时空变化规律及突变特征,主要得出以下结论：（1）黔南州年平均降水呈东西部偏多、北部和中南部偏少的“川”字型分布,降水量有明显的增加趋势;（2）季节降水高值区围绕都匀为中心南北摆动,其中春、夏、秋三个季节降水呈增多趋势,冬季呈减少趋势;（3）月降水主要集中在4-8月,其中11-4月降水为东多西少的东西向分布,5-9月为南多北少的南北向分布,10月为北多南少的南北向分布;（4）降水突变总体表现为2000年左右由减少趋势向增多趋势突变、21世纪10年代初由增多趋势向减少趋势突变。
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| 关 键 词： | 降水 时空分布 滑动t检验 克里金法 反距离权重法。 |
| 收稿时间： | 2020/8/21 0:00:00 |
| 修稿时间： | 2020/11/3 0:00:00 |
Analysis of Temporal and Spatial Distribution Characteristics of Precipitation in Qiannan Prefecture in the Past 31 Years Based on GIS |
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| Authors: | lushasha |
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| Institution: | Duyun Meteorological Bureau |
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| Abstract: | This paper uses the ground precipitation observation data from 12 national automatic meteorological observation stations?in Qiannan Prefecture, Guizhou Province from 1989 to 2019, and uses linear regression, Kriging?method, IDW (Inverse Distance Weighting), and moving t-test to analyze the nearly 31 the temporal and spatial variations of annual precipitation and the characteristics of abrupt changes mainly draw the following conclusions: (1) The annual average precipitation in Qiannan Prefecture is distributed in the shape of "Chuan" with more in the east and west and less in the north and south, and the amount of precipitation is obvious (2) The high-value area of seasonal precipitation oscillates north-south around Duyun. The three seasons of spring, summer and autumn show an increasing trend, and the winter shows a decreasing trend; (3) Monthly precipitation is mainly concentrated in 4-8 In January-April, the precipitation is more east-west and less west; May-September is north-south with more south and less north; October is north-south with more north and less south; (4) precipitation in general It shows a sudden change from a decreasing trend to an increasing trend around 2000, and a sudden change from an increasing trend to a decreasing trend in the early 2010s. |
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| Keywords: | precipitation temporal and spatial distribution Moving t test Kriging Inverse Distance Weighting |
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