| 江西省降水空间插值方法适用性分析 |
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| 引用本文： | 占龙飞,陈佳义,李婕,赵冠男,胡菊芳.江西省降水空间插值方法适用性分析[J].气象与减灾研究,2021,44(3):215-221. |
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| 作者姓名： | 占龙飞 陈佳义 李婕 赵冠男 胡菊芳 |
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| 作者单位： | 江西省气候中心,江西 南昌 360096;淮安市淮阴区气象局,江苏 淮安 223300;江西省气象台,江西 南昌 360096 |
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| 基金项目： | 2021年华东区域气象科技协同创新基金合作项目（编号：QYHZ202106）；2019年江西省气象局面上项目“南昌城市通风廊道建设——风、热环境特征研究”；2021年江西省气象局指导性科研计划项目（编号: ZDX2021004）；2020年江西省气象局重点项目（编号：JX2020Z14；JX2020Z18）. |
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| 摘 要： | 文中基于数字高程模型,建立了多元线性回归插值模型(MLR)和PRISM空间插值方法,并与传统的反距离权重法(IDW)和普通克里金插值法(OK)进行比较.结果表明:1)江西省5月、7—10月降水量与海拔高度存在显著的相关性,与坡度、坡向无明显相关.2)从插值精度来看,3—9月PRISM和MLR空间插值精度明显优于IDW和OK,冬半年IDW和OK插值精度略高于MLR和PRISM;4种插值方法的年降水量插值精度排序为PRISM>MLR>OK>IDW;PRISM和MLR在高海拔地区的插值精度远高于IDW和OK.3)从插值效果来看,4种插值方法的降水空间分布具有一致性,MLR和PRISM优于IDW和OK.
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| 关 键 词： | PRISM MLR 克里金插值 IDW 降水空间插值 |
| 收稿时间： | 2021/5/23 0:00:00 |
| 修稿时间： | 2021/6/28 0:00:00 |
Applicability analysis of spatial interpolation method for precipitation in Jiangxi province |
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| Zhan Longfei,Chen Jiayi,Li Jie,Zhao Guannan and Hu Jufang.Applicability analysis of spatial interpolation method for precipitation in Jiangxi province[J].Meteorology and Disaster Reduction Research,2021,44(3):215-221. |
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| Authors: | Zhan Longfei Chen Jiayi Li Jie Zhao Guannan and Hu Jufang |
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| Institution: | Jiangxi Climate Center,Meteorological Bureau of Huaiyin District,Jiangxi Meteorological Observation,Jiangxi Climate Center and Jiangxi Climate Center |
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| Abstract: | The multiple linear regression interpolation model (MLR) and PRISM (Parameter elevation Regression on Independent Slopes Model) spatial interpolation method on monthly and annual time scales were established in this paper. Based on the accuracy and effect of interpolation, the two aforementioned methods were compared with the traditional inverse distance weighting method (IDW) and the ordinary Kriging interpolation method (OK). The results showed that: 1) the monthly precipitation presented a significant correlation with height above sea level in May and from July to October in Jiangxi province, but exhibited no obvious correlation with the slope and aspect of the terrain. 2) In terms of the interpolation accuracy, the spatial interpolation accuracy of PRISM and MLR from March to September was significantly better than that of IDW and OK, and the interpolation accuracy of IDW and OK in the winter half year was slightly higher than that of MLR and PRISM; the annual precipitation interpolation accuracies ranking of the four interpolation methods were PRISM> MLR> OK> IDW; the interpolation accuracies of PRISM and MLR for high altitude areas were much higher than those of IDW and OK. 3) In terms of the interpolation effect, the precipitation distribution of the four interpolation results was consistent, and MLR and PRISM were better than IDW and OK. |
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| Keywords: | PRISM MLR Kriging interpolation IDW precipitation interpolation |
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