ZHANG Shanhong,BAI Hongying,QI Guizeng,et al.Spatial Simulation of Active Accumulated Temperature≥10℃in Qinling-Daba Mountains Based on Anusplin and Multiple Linear Regression Model[J].Research of Soil and Water Conservation,2022,29(01):184-189+196.
基于多元线性回归模型和Anusplin的秦巴山区≥10℃积温空间模拟比较
- Title:
- Spatial Simulation of Active Accumulated Temperature≥10℃in Qinling-Daba Mountains Based on Anusplin and Multiple Linear Regression Model
- 文章编号:
- 1005-3409(2022)01-0184-06
- Keywords:
- Anusplin; active accumulated temperature; multiple linear regression model; spatial simulation; Qinling-Daba Mountains
- 分类号:
- P467
- 文献标志码:
- A
- 摘要:
- 为获取山区准确的高精度空间积温数据,采用高精度的气象插值软件Anusplin和多元线性回归模型两种方法,模拟山区≥10℃积温的空间分布,为山区积温空间模拟提供解决方法。以地形起伏较大的秦巴山区作为研究区,选用研究区内69个气象站点及其周边22个气象站点1960—2019年的逐日平均气温实测数据,采用Anusplin和多元线性回归模型两种方法,模拟了秦巴山区30 m分辨率≥10℃积温的空间分布。通过对预留气象站点实测数据进行验证,评价了两种方法在山区积温空间分布模拟复杂性问题中的适用性。结果表明:基于Anusplin的≥10℃积温的空间模拟方法较多元线性回归模型插值精度略高。即基于Anusplin的空间模拟方法能更真实地反映山区积温的空间分布情况,体现了海拔、经纬度对积温的影响,能更好地模拟复杂山区高精度的积温数据,为山区积温空间模拟提供了新的选择方法。
- Abstract:
- To obtain accurate and fast spatial accumulated temperature data in mountainous regions, two methods, high-precision meteorological interpolation software Anusplin and multiple linear regression model, were used to simulate the spatial distribution of accumulated temperature ≥10℃ in mountainous areas in order to provide solutions for the spatial distribution of accumulated temperature in mountainous areas. The Qinling-Daba Mountains with large topographic relief was taken as the study area. Based on Anusplin and multiple linear regression interpolation methods separately, 30 m resolution spatial distribution of actively accumulated temperature ≥10℃(AAT10)was simulated by combining with DEM and the daily meteorological observation data from 69 meteorological stations in the research and surrounding 22 meteorological stations during 1960—2019. The interpolation accuracy of Anusplin and multiple linear regression were compared, and the applicability of the two methods in complex mountainous areas is evaluated through verifying the measured data of reserved meteorological stations. The results show that both two interpolation methods are suitable for spatial simulation of active accumulated temperature ≥10℃(AAT10)in Qinling-Daba mountains, but the Anusplin has slightly higher accuracy than the multiple linear regression interpolation methods. In other words, the spatial interpolation method based on Anusplin can more realistically reflect the spatial distribution of the accumulated temperature, and can better simulate the high-precision accumulated temperature data of complex mountainous areas, which provides a new method for the spatial simulation of active accumulated temperature in the mountainous area.
参考文献/References:
[1] 秦大河.气候变化:区域应对与防灾减灾—气候变化背景下极端事件相关灾害影响及应对策略[M].北京:科学出版社,2009.[2] 宋佃星,延军平,马莉.近50年来秦岭南北气候分异研究[J].干旱区研究,2011,28(3):492-498.[3] 柏秦凤,霍治国,李世奎,等.1978年前、后中国≥10℃年积温对比[J].应用生态学报,2008,19(8):1810-1816.[4] 赵俊芳,郭建平,马玉平,等.气候变化背景下我国农业热量资源的变化趋势及适应对策[J].应用生态学报, 2010,21(11):2922-2930.[5] 李元华,刘学锋,刘莉,等.河北省近50年0℃界限温度积温变化特征分析[J].干旱区资源与环境,2006,20(4):12-15.[6] 王锡稳,王毅荣.黄土高原积温变化的敏感性研究[J].干旱区地理,2006,29(6):817-822.[7] 毛恒青,万晖.华北、东北地区积温的变化[J].中国农业气象,2000,21(3):1-5.[8] 邱新法,王喆,曾燕,等.1960—2013年中国≥10℃积温时空变化特征及其主导因素分析[J].江苏农业科学,2017,45(2):220-225.[9] 袁淑杰,谷晓平,向红琼,等.基于GIS的贵州高原复杂地形下积温的精细空间分布[J].资源科学,2010,32(12):2427-2432.[10] 梁敬,朱家龙.山区热量资源的估算方法[J].气象,1981(10):26-27.[11] 傅抱璞.山地气候[M].北京:科学出版社,1983.[12] 卢其尧,傅抱璞,虞静明.山区农业气候资源空间分布的推算方法及小地形的气候效应[J].自然资源学报,1988,3(2):101-112.[13] 邹立尧,赵秀兰.细网格点农业气象资源推算原理和方法[J].黑龙江气象,1996,2(3):3-5.[14] 刘新安,于贵瑞,范辽生,等.中国陆地生态信息空间化技术研究(Ⅲ)[J].自然资源报,2004,19(6):818-825.[15] 尹洪涛,刘新安,刘寿东,等.辽西地区热量资源分析与栅格化[J].资源科学,2006,28(1):169-173.[16] 戴声佩,李海亮,罗红霞,等.1960—2011年华南地区界限温度10℃积温时空变化分析[J].地理学报,2014,69(5):650-660.[17] 高蓓,邹继业,刘瑞芳.气候变暖背景下秦岭地区≥10℃热量的时空变化[J].中国农学通报,2016,32(2):155-162.[18] 陈嘉哲,赵彩杉,张学珍.21世纪气候变化情景下环北极地区植被生长季与活动积温变化[J].气候与环境研究,2020,25(5):543-554.[19] 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.[20] 戴声佩,李海亮,罗红霞,等.基于多元线性回归模型的华南地区≥10℃积温空间模拟研究[J].热带农业科学,2014,34(6):54-59.[21] 时光训,丁明军.近40 a来长江流域≥10℃积温的时空变化特征[J].热带地理,2016,36(4):682-691.[22] 李帅,张勃,马彬,等.基于格点数据的中国1961—2016年≥5℃、≥10℃有效积温时空演变[J].自然资源学报,2020,35(5):1216-1227.[23] 白红英.秦巴山区森林植被对环境变化的响应[M].北京:科学出版社,2014.[24] 章金城,周文佐.2006—2015年秦巴山区植被光合有效辐射吸引比例的时空变化特征[J].生态学杂志,2019,38(5):1453-1463.[25] 张雪芹,孙杨,郑度,等.中国干旱区温度带界线对气候变暖的响应[J].地理学报,2011,66(9):1166-1178.[26] 史本岩.辽宁省东部山区农业气候资源精细化模拟研究[D].沈阳:沈阳农业大学,2018.[27] Bates D, Lindstrom M, Wahba G, et al. Gcvpack-routines for generalized cross validation[J]. Communications in Statistics B-Simulation and Computation,1987,16(1):263-297.[28] 刘志红, Tim R McVicar, Li Lingtao,等.基于ANUSPLIN的时间序列气象要素空间插值[J].西北农林科技大学学报:自然科学版,2008,36(10):227-234.[29] 刘正佳,于兴修,王丝丝,等.薄盘光滑样条插值中3种协变量方法的降水量插值精度比较[J].地理科学进展,2012,31(1):56-62.[30] Hutchinson M F. ANUSPLIN version 4.2 user guide[Z]. Canberra:Australian National University, 2001.[31] 孟清,白红英,郭少壮.基于Anusplin秦岭地区近50多年来的降水时空变化[J].水土保持研究,2020,27(2):206-212.[32] 熊秋芬,黄玫,熊敏诠,等.基于国家气象观测站逐日降水格点数据的交叉检验误差分析[J].高原气象,2011,30(6):1615-1625.
备注/Memo
收稿日期:2020-12-16 修回日期:2021-02-16资助项目:国家自然科学基金(31570440); 商洛市气候适应型城市重点实验室开放研究(SLSYS2019019)第一作者:张善红(1983—),女,山东日照人,博士,研究方向为植被变化与水土保持研究。E-mail:feiyang84120@126.com通信作者:白红英(1962—),女,陕西宝鸡人,博士,教授,主要从事全球变化及自然地理学等方面的研究。E-mail:hongyingbai@163.com