[1]陈思静,谢新乔,杨继周,等.地形复杂山区相对湿度空间插值方法对比研究[J].山地学报,2022,(5):778-786.[doi:10.16089/j.cnki.1008-2786.000711]
　CHEN Sijing,XIE Xinqiao,YANG Jizhou,et al.Comparison on Spatial Interpolation Methods of Relative Humidity in Complex Mountainous Terrain[J].Mountain Research,2022,(5):778-786.[doi:10.16089/j.cnki.1008-2786.000711]
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地形复杂山区相对湿度空间插值方法对比研究
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2022年第5期
页码:
778-786
栏目:
山地技术
出版日期:
2022-09-25

文章信息/Info

Title:
Comparison on Spatial Interpolation Methods of Relative Humidity in Complex Mountainous Terrain
文章编号:
1008-2786-(2022)5-778-9
作者:
陈思静1; 谢新乔2; 杨继周2; 景元书1*
(1. 南京信息工程大学 江苏省农业气象重点实验室,南京 210044; 2. 红塔集团原料部,云南 玉溪 653100)
Author(s):
CHEN Sijing1;  XIE Xinqiao2;  YANG Jizhou2;  JING Yuanshu1*
(1.Jiangsu Key Laboratory of AgroMeteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China; 2. Raw Material Department, Hongta Tobacco Co., Ltd., Yuxi 653100, Yunnan, China)
关键词:
ANUSPLIN;  多元线性回归;  空间插值;  相对湿度;  玉溪山区
Keywords:
ANUSPLIN;  multiple linear regression;  spatial interpolation;  relative humidity;  Yuxi hilly area
分类号:
P49
DOI:
10.16089/j.cnki.1008-2786.000711
文献标志码:
A
摘要:
在气象站点稀疏、气象数据少的山区,气象数据离散、精度低,不能满足山区开展精细化气象服务的需求。针对复杂地形条件的气象数据插值,不同插值方法显著影响相对湿度等气象数据精度及适用性。以玉溪山区为研究区域,选取2011—2019年10个训练站点的相对湿度实测数据,使用多元回归与残差分析相结合的AMMRR法与基于薄盘样条理论的ANUSPLIN插值软件进行空间插值处理,并模拟研究区域内相对湿度的空间分布,进行模拟精度检验,对比2种方法的插值结果。结果表明:(1)AMMRR中多元线性回归模型模拟效果可以满足建模精度要求,但插值结果仍存在部分地区与实际情况出入较大的问题。(2)ANUSPLIN的MAE为3.34、MRE为0.05、RMSE为3.91,3种精度评价指标均更低,空间插值结果更加稳定且精度更高,能更好地反映相对湿度在山区的分布情况。(3)玉溪山区相对湿度分布趋势总体表现为西南部与北部较高而中部较低。该研究可补充玉溪山区相对湿度的数据空缺,为市县区域经济作物病害防治及产量精准预测提供基础数据支持,并为站点较少的复杂山区选择空间插值方法提供参考。
Abstract:
In the mountainous areas with complex terrain, the meteorological data collected at sparse meteorological stations appears to be discrete with low accuracy, which cannot meet the demand for refined meteorological services in rural construction; therefore, it need proper mathematical treatment of interpolation for availability before utilization. Different interpolation methods significantly affect the accuracy and applicability of the discrete meteorological data, such as relative humidity. In this study, it took the Yuxi area of Yunnan province of China as a case study, where the distinctive feature of the landform is its steep terrain in low latitude plateau but equipped with very few of weather stations. Relative humidity data were collected at 10 training stations in Yuxi from 2011 to 2019; Both the AMMRR method, which combined with multiple regression and residual analysis, and the ANUSPLIN method based on the theory of Partial Thin Plate Smoothing Splines were separately used to conduct spatial interpolation fit; Then the spatial distribution of relative humidity in Yuxi was simulated, followed by accuracy inspection of the two methods and result comparison. The results show that:(1)Multiple linear regression model from AMMRR method could satisfy the expected accuracy for simulation, but the interpolation values still had distinct discrepancy as compared with field observations at some places.(2)MAE, MRE and RMSE obtained by ANUSPLIN method were 3.34, 0.05 and 3.91, respectively, achieving better precision indexes, with more stable and accurate spatial interpolation results, suggesting better reflection of the distribution of relative humidity in hilly areas.(3)The distribution trend of relative humidity in the Yuxi hilly area was generally higher in the southwest and north, and lower in the middle. This study could solve the shortage in the data of relative humidity in the Yuxi hilly area, which provides basic data support for the prevention and control of economic crop diseases and accurate prediction of yield in the region, and gives also a reference for choosing spatial interpolation methods in complex hilly areas with few weather stations.

参考文献/References:

[1] 张静文,张竞成,张雪雪,等. 耦合气象影响因素和Logistic方程的水稻纹枯病发病等级动态预测模型研究[J]. 植物保护,2022, 48(3): 172-180. [ZHANG Jingwen, ZHANG Jingcheng, ZHANG Xuexue, et al. A dynamic forecasting model for the severity of rice sheath blight by coupling meteorological factors with Logistic equation [J]. Plant Protection, 2022, 48(3): 172-180] DOI: 10.16688/j.zwbh.2021238
[2] 吕国华,白文波,武永峰,等. 北京地区温室大棚黄瓜生长期作物潜在病害的发生概率[J]. 中国农业气象,2014, 35(5): 556-560. [LYU Guohua, BAI Wenbo, WU Yongfeng, et al. Probability of cucumber potential disease incidence in sunlight greenhouse in Beijing [J]. Chinese Journal of Agrometeorology, 2014, 35(5): 556-560] DOI: 10.3969/j.issn.1000-6362.2014.05.012
[3] 曹哲铭,李北,赵昌洲,等. 烟草赤星病、靶斑病增长模型及预测模型研究[J/OL]. 吉林农业大学学报,2020: 1-8. [2022-10-30]. https: //kns.cnki.net/kcms/detail/22.1100.S.20200902.1601.012.html. [CAO Zheming, LI Bei, ZHAO Changzhou, et al. Study on runoff and sediment yield characteristics of topsoil, sandy soil, and hilly soil piles [J]. Journal of Jilin Agricultural University, 2020: 1-8. [2022-10-30]. https: //kns.cnki.net/kcms/detail/22.1100.S.20200902.1601.012.html. ] DOI: 10.13327/j.jjlau.2020.5721
[4] 刘玉洪,张克映,马友鑫,等. 哀牢山(西南季风山地)空气湿度资源的分布特征[J]. 自然资源学报,1996,11(4): 347-354. [LIU Yuhong, ZHANG Keying, MA Youxin, et al. Distribution characteristics of the air humidity resource of the Ailao Mountains(southwest monsoon mountainous area)[J]. Journal of Natural Resources,1996,11(4): 347-354]
[5] 马秀霞,黄领梅,沈冰. 陕西省月平均气温空间插值方法研究[J]. 水资源与水工程学报,2017,28(5): 100-105. [MA Xiuxia, HUANG Lingmei, SHEN Bing. Study on spatial interpolation method of monthly mean temperature in Shanxi province [J]. Journal of Water Resources and Water Engineering, 2017,28(5): 100-105] DOI: 10.11705/j.issn.1672-643X.2017.05.17
[6] BARTIER P M, KELLER C P. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting(IDW)[J]. Computers and Geosciences, 1996, 22(7): 795-799. DOI: 10.1016/0098-3004(96)00021-0
[7] TAIT A, HENDERSON R, TURNER R, et al. Thin plate smoothing spline interpolation of daily rainfall for New Zealand using a climatological rainfall surface [J]. International Journal of Climatology, 2006, 26(14): 2097-2115. DOI: 10.1002/joc.1350
[8] ADHIKARY S K, MUTTIL N, YILMAZ A G. Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments [J]. Hydrological Processes, 2017, 31(12): 2143-2161. DOI: 10.1002/hyp.11163
[9] 李叶,张艳红,陈子琦,等. 中高纬度山区气温空间化的方法比较研究——以大兴安岭北麓为例[J].山地学报,2021,39(2): 174-182. [LI Ye, ZHANG Yanhong, CHEN Ziqi, et al. Comparative study on spatialization methods of air temperature in middle and high latitude mountainous areas: A case study of northern foot of the Daxing'anling Mountains [J]. Mountain Research, 2021, 39(2): 174-182] DOI: 10.16089/j.cnki.1008-2786.000585
[10] 李月臣,何志明,刘春霞. 基于站点观测数据的气温空间化方法评述[J]. 地理科学进展,2014,33(8): 1019-1028. [LI Yuechen, HE Zhiming, LIU Chunxia. Review on spatial interpolation methods of temperature data from meteorological stations [J]. Progress in Geography, 2014,33(8): 1019-1028] DOI: 10.11820/dlkxjz.2014.08.002
[11] 柳小妮,郭婧,任正超,等. 基于气象要素空间分布模拟优化的中国草地综合顺序分类[J]. 农业工程学报,2012,28(9): 222-229. [LIU Xiaoni, GUO Jing, REN Zhengchao, et al. Chinese rangeland CSCS classification based on optimal simulation for spatial distribution of meteorological factors [J]. Transactions of the Chinese Society of Agricultural Engineering, 2012,28(9): 222-229] DOI: 10.3969/j.issn.1002-6819.2012.09.037
[12] 王红霞,柳小妮,郭婧,等. AMMRR插值法的改进及其在内蒙古草地综合顺序分类中的应用[J]. 中国生态农业学报,2013,21(7): 904-912. [WANG Hongxia, LIU Xiaoni, GUO Jing, et al. Improvement of AMMRR interpolation and application in CSCS classification of Inner Mongolia grassland [J]. Chinese Journal of Eco-Agriculture, 2013, 21(7): 904-912] DOI: 10.3724/SP.J.1011.2013.00904
[13] SAENZ-ROMERO C, REHFELDT G E, CROOKSTON N L, et al. Spline models of contemporary, 2030, 2060 and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation [J]. Climatic Change, 2010, 102(3-4): 595-623. DOI: 10.1007/s10584-009-9753-5
[14] 谭剑波,李爱农,雷光斌. 青藏高原东南缘气象要素Anusplin和Cokriging空间插值对比分析[J]. 高原气象,2016,35(4): 875-886. [TAN Jianbo, LI Ainong, LEI Guangbin. Contrast on Anusplin and Cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang Plateau [J]. Plateau Meteorology, 2016, 35(4): 875-886] DOI: 10.7522/j.issn.1000-0534.2015.00037
[15] 张仁平,张云玲,郭靖,等. 新疆地区降水分布的空间插值方法比较[J]. 草业科学,2018,35(3): 521-529. [ZHANG Renping, ZHANG Yunling, GUO Jing, et al. Comparison of spatial interpolation methods for precipitation distribution in Xinjiang region [J]. Pratacultural Science, 2018, 35(3): 521-529] DOI: 10.11829 /j.issn.1001-0629.2016-0608
[16] 朱求安,张万昌,余钧辉. 基于GIS的空间插值方法研究[J]. 江西师范大学学报(自然科学版),2004,28(2): 183-188. [ZHU Qiuan, ZHANG Wanchang, YU Junhui. The spatial interpolations in GIS [J]. Journal of Jiangxi Normal University(Natural Science), 2004,28(2): 183-188] DOI: 10.16357/j.cnki.issn1000-5862.2004.02.022
[17] 谢新乔,陆俊平,田育天,等. 玉溪市100 m级植烟土壤质地品质的区划研究[J/OL]. 土壤学报,2022: 1-11. [2022-10-30]. http: //kns.cnki.net/kcms/detail/32.1119.P.20220303.1905.006.html. [XIE Xinqiao, LU Junping, TIAN Yutian, et al. Soil texture grading and zoning for tobacco planting in Yuxi at 100 m spatial resolution [J]. Acta Pedologica Sinica, 2022: 1-11. [2022-10-30]. http: //kns.cnki.net/kcms/detail/32.1119.P.20220303.1905.006.html] DOI: 10.11766/trxb202109280526
[18] MARQUINEZ J, LASTRA J, GARCIA P. Estimation models for precipitation in mountainous regions: The use of GIS and multivariate analysis [J]. Journal of Hydrology, 2003, 270(1): 1-11. DOI: 10.1016/S0022-1694(02)00110-5
[19] 刘志红,LI Lingtao, MCVICAR T R, 等. 专用气候数据空间插值软件ANUSPLIN及其应用[J]. 气象,2008,34(2): 92-100. [LIU Zhihong, LI Lingtao, MCVICAR T R, et al. Introduction of the professional interpolation software for meteorology data: ANUSPLINN [J]. Meteorological Monthly, 2008, 34(2): 92-100]
[20] 莫跃爽,索惠英,焦树林,等. 喀斯特地区降水量空间插值方法对比——以贵州省为例[J]. 水土保持研究,2021,28(1): 164-170. [MO Yueshuang, SUO Huiying, JIAO Shulin, et al. Comparison of spatial interpolation methods of precipitation: A case of Karst area in Guizhou province [J]. Research of Soil and Water Conservation, 2021, 28(1): 164-170] DOI: 10.13869/j.cnki.rswc.2021.01.022
[21] 李海涛,邵泽东. 空间插值分析算法综述[J]. 计算机系统应用,2019,28(7): 1-8. [ LI Haitao, SHAO Zedong. Review of spatial interpolation analysis algorithm [J]. Computer Systems and Applications, 2019, 28(7): 1-8] DOI: 10.15888/j.cnki.csa.006988
[22] 刘勤,严昌荣,何文清,等. 黄河流域近40a积温动态变化研究[J]. 自然资源学报,2009,24(1): 147-153. [LIU Qin, YAN Changrong, HE Wenqing, et al. Dynamic variation of accumulated temperature data in recent 40 years in the Yellow River basin [J]. Journal of Natural Resources, 2009, 24(1): 147-153]
[23] DALY C. Guidelines for assessing the suitability of spatial climate data sets [J]. International Journal of Climatology, 2006, 26(6): 707-721. DOI: 10.1002/joc.1322
[24] 张锦明,郭丽萍,张小丹. 反距离加权插值算法中插值参数对DEM插值误差的影响[J]. 测绘科学技术学报,2012,29(1): 51-56. [ZHANG Jinming, GUO Liping, ZHANG Xiaodan. Effects of interpolation parameters in inverse distance weighted method on DEM accuracy [J]. Journal of Geomatics Science and Technology, 2012, 29(1): 51-56] DOI: 10.3969/j.issn.1673-6338.2012.01.013
[25] 赵冰雪,王雷,程东亚. 安徽省气象数据空间插值方法比较与分布特征[J]. 水土保持研究,2017,24(3): 141-145. [ZHAO Bingxue, WANG Lei, CHENG Dongya. Comparison of spatial interpolation method for meteorological data and distribution characteristic in Anhui province [J]. Research of Soil and Water Conservation, 2017, 24(3): 141-145] DOI: 10.13869/j.cnki.rswc.2017.03.026
[26] 艾葳,万继敏,崇元. 不同插值方法在海域气象参数估算中的可靠性评价[J]. 海洋技术学报,2019,38(2): 85-91. [AI Wei, WAN Jimin, CHONG Yuan. Evaluation of the reliability of offshore meteorological parameter estimates using different interpolation methods [J]. Journal of Ocean Technology, 2019, 38(2): 85-91] DOI: 10.3969/j.issn.1003-2029.2019.02.013
[27] 李月,齐实,程伯涵,等. 哀牢山山区降水时空分布的影响因素及插值方法比较[J]. 地球与环境, 2017,45(6): 600-611. [LI Yue, QI Shi, CHENG Bohan, et al. A study on factors of space-time distributions of precipitation in Ailao Mountain area and comparison of interpolation methods [J]. Earth and Environment, 2017,45(6): 600-611] DOI: 10.14050/j.cnki.1672-9250.2017.06.002
[28] 郭婧,柳小妮,任正超. 基于GIS模块的气象数据空间插值方法新改进——以甘肃省为例[J]. 草原与草坪,2011,31(4): 41-45+50. [GUO Jing, LIU Xiaoni, REN Zhengchao. An improved method for spatial interpolation of meteorological data based on GIS modules: A case study of Gansu province [J]. Grassland and Turf, 2011, 31(4): 41-45+50] DOI: 10.13817/j.cnki.cyycp.2011.04.002
[29] 周锁铨,缪启龙,吴战平,等. 山区平均气温细网格插值方法的比较[J]. 南京气象学院学报,1994,17(4): 488-492. [ZHOU Suoquan, MIAO Qilong, WU Zhanping, et al. Comparison of stepwise interpolation on small grids and multi-regression analysis for mountain mean temperature [J]. Journal of Nanjing Institute of Meteorology, 1994, 17(4): 488-492] DOI: 10.13878/j.cnki.dqkxxb.1994.04.015
[30] 韩梅,杨利民,王少江,等. 吉林省中西部半干旱地区近50年的降水与空气湿度变化[J]. 吉林农业大学学报,2003,25(4): 425-428. [HAN Mei, YANG Limin, WANG Shaojiang, et al. Changes of precipitation and air humidity of the recent 50 years in Changling county of Jilin province [J]. Journal of Jilin Agricultural University, 2003, 25(4): 425-428] DOI: 10.13327/j.jjlau.2003.04.020
[31] AULER A C, CASSARO F A M, DA SILVA V O, et al. Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: A case study for the most affected Brazilian cities [J]. Science of the Total Environment, 2020,729: 139090. DOI: 10.1016/j.scitotenv.2020.139090

相似文献/References:

[1]李 叶,张艳红,陈子琦,等.中高纬度山区气温空间化的方法比较研究——以大兴安岭北麓为例[J].山地学报,2021,(2):174.[doi:10.16089/j.cnki.1008-2786.000585]
　LI ye,ZHANG Yanhong,CHEN Ziqi,et al.Comparative Study on Spatialization Methods of Air Temperature in Middle and High Latitude Mountainous Areas: A Case Study of Northern Foot of the Daxing'anling Mountains[J].Mountain Research,2021,(5):174.[doi:10.16089/j.cnki.1008-2786.000585]

备注/Memo

备注/Memo:
收稿日期(Received date): 2022-04-14; 改回日期(Accepted date):2022-09-11
基金项目(Foundation item): 中国科学院数字地球重点实验室开放基金(2018LDE003); 云南红塔集团项目(S-6019001)。[Open Fund of Key Laboratory of Digital Earth, Chinese Academy of Sciences(2018LDE003); Yunnan Hongta Co. Project(S-6019001)]
作者简介(Biography): 陈思静(1997-),女,硕士研究生,主要研究方向:农业气象和生态环境。[CHEN Sijing(1997-), female, M.Sc. candidate, research on agrometeorology and ecological environment] E-mail:2097376991@qq.com
*通讯作者(Corresponding author): 景元书(1968-),男,博士,教授,主要研究方向:农业气象和小气候。[JING Yuanshu(1968-), Male, Ph.D., professor, research on agrometeorology and microclimate] E-mail: appmet@nuist.edu.cn
更新日期/Last Update: 2022-10-30