秦岭—大巴山高分辨率气温和降水格点数据集的建立及其对区域气候的指示
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摘要
本文建立了秦岭—大巴山高分辨率(～29 m×29 m)的气候格点数据集,包括逐月气温和降水、年均温和年降水、春夏秋冬气温和降水。空间插值方法采用国际上较为先进的ANUSPLIN软件内置的薄盘光滑样条函数,以经度、纬度和海拔为独立变量。空间插值结果与流行的WorldClim 2.0气候格点数据集具有一致性,但是比后者更精确、分辨率更高、细节更突出。本文揭示和证实:秦岭南麓是最冷月气温的0℃分界线。秦岭—大巴山气温具有明显的垂直地带性。6月气温直减率最大,为0.61℃/100 m;12月气温直减率最小,为0.38℃/100 m;年均气温直减率为0.51℃/100 m。夏季和秋季降水从西南向东北递减,强降水中心出现在大巴山西南坡。冬季降水从东南向西北递减。大巴山是年降水1000 mm分界线,夏季降水500mm分界线;秦岭是年降水800 mm分界线,夏季降水400 mm分界线。与大尺度大气环流对比揭示:秦岭—大巴山气温和降水空间分布主要受到东亚季风和地形因子的控制。本文进一步明确了秦岭和大巴山的气候意义:大巴山主要阻挡夏季风北上,影响降水空间分布;秦岭主要阻挡冬季风南下,影响冬季气温空间分布。本文建立的高分辨率气候格点数据集,加深了对区域气候的认识,并将有多方面的用途。
In this study, we developed a high-resolution grid dataset of air temperature and precipitation for the Qinling-Daba Mountains in central China, which includes monthly precipitation and temperature, seasonal precipitation and temperature, annual precipitation and temperature. Spatial interpolation was performed using thin-plate smoothing spline in the software ANUSPLIN, with latitude, longitude and elevation as independent variables. Our dataset is consistent with the widely-used WorldClim 2.0 dataset, but has more accuracy,because it is based on a larger number of meteorological stations and higher-resolution elevation data. Our results show that the southern foot of Qinling Mountains is the 0 ℃isothermal line in the coldest month(January). The Qinling-Daba Mountains has obvious vertical temperature zones. The maximum temperature lapse rate occurs in June, which is0.61 ℃ per 100 m, while the minimum temperature lapse rate is 0.38 ℃ per 100 m, occurring in December. The annual mean temperature lapse rate is 0.51 ℃ per 100 m. Both summer and autumn precipitations decrease from southwest to northeast, with heavy rainfall center located on the southwestern slope of the Daba Mountains, while winter precipitation decreases from southeast to northwest. The Daba Mountains is the 1000 mm isohyetal line of annual precipitation and 500 mm isohyetal line of summer precipitation, while the Qinling Mountains is the 800 mm isohyetal line of annual precipitation and 400 mm isohyetal line of summer precipitation. Comparison with large-scale atmospheric circulation indicates that the spatial distributions of air temperature and precipitation in the Qinling-Daba Mountains are mainly controlled by the East Asian monsoon and topography. In summer, the Daba Mountains prevents the northward penetration of East Asian summer monsoon and therefore influences the spatial distribution of precipitation. In winter, the Qinling Mountains prevents the southward penetration of East Asian winter monsoon and therefore influences the spatial distribution of air temperature. In summary, our high-resolution grid dataset contributes to a better understanding of regional climate and will have many applications in future researches.
In this study, we developed a high-resolution grid dataset of air temperature and precipitation for the Qinling-Daba Mountains in central China, which includes monthly precipitation and temperature, seasonal precipitation and temperature, annual precipitation and temperature. Spatial interpolation was performed using thin-plate smoothing spline in the software ANUSPLIN, with latitude, longitude and elevation as independent variables. Our dataset is consistent with the widely-used WorldClim 2.0 dataset, but has more accuracy,because it is based on a larger number of meteorological stations and higher-resolution elevation data. Our results show that the southern foot of Qinling Mountains is the 0 ℃isothermal line in the coldest month(January). The Qinling-Daba Mountains has obvious vertical temperature zones. The maximum temperature lapse rate occurs in June, which is0.61 ℃ per 100 m, while the minimum temperature lapse rate is 0.38 ℃ per 100 m, occurring in December. The annual mean temperature lapse rate is 0.51 ℃ per 100 m. Both summer and autumn precipitations decrease from southwest to northeast, with heavy rainfall center located on the southwestern slope of the Daba Mountains, while winter precipitation decreases from southeast to northwest. The Daba Mountains is the 1000 mm isohyetal line of annual precipitation and 500 mm isohyetal line of summer precipitation, while the Qinling Mountains is the 800 mm isohyetal line of annual precipitation and 400 mm isohyetal line of summer precipitation. Comparison with large-scale atmospheric circulation indicates that the spatial distributions of air temperature and precipitation in the Qinling-Daba Mountains are mainly controlled by the East Asian monsoon and topography. In summer, the Daba Mountains prevents the northward penetration of East Asian summer monsoon and therefore influences the spatial distribution of precipitation. In winter, the Qinling Mountains prevents the southward penetration of East Asian winter monsoon and therefore influences the spatial distribution of air temperature. In summary, our high-resolution grid dataset contributes to a better understanding of regional climate and will have many applications in future researches.
引文
[1] Hijmans R, Cameron S, Parra J, et al. Very high resolution interpolated climate surfaces for global land areas.International Journal of Climatology, 2005, 25(15):1965-1978.
[2] Fick S, Hijmans R. WorldClim 2:New 1‐km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 2017, 37(12):4302-4315.
[3] New M, Lister D, Hulme M, et al. A high-resolution data set of surface climate over global land areas. Climate research,2002, 21(1):1-25.
[4] Harris I, Jones P, Osborn T, et al. Updated high‐resolution grids of monthly climatic observations:The CRU TS3.10Dataset. International Journal of Climatology, 2014, 34(3):623-642.
[5] Wu Jia, Gao Xuejie. A gridded daily observation dataset over China region and comparison with the other datasets.Chinese Journal of Geophysics, 2013, 56(4):1102-1111.[吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比.地球物理学报, 2013, 56(4):1102-1111.]
[6] Wu Xian, Huang Wei, Chen Fahu. Construction and application of monthly air temperature and precipitation gridded datasets with high resolution(0.025°×0.025°)over China during 1951-2012. Journal of Lanzhou University(Natural Sciences), 2014, 50(2):213-220.[吴娴,黄伟,陈发虎. 1951-2012年中国大陆0.025°×0.025°高分辨率月气温和降水量格点数据集的建立及其初步应用.兰州大学学报(自然科学版), 2014, 50(2):213-220.]
[7] Chen Mingrong, Tang Haibin, Tian Lianshu, et al. Geography of Shaanxi Province. Xi'an:Shaanxi People's Publishing House, 1996.[陈明荣,唐海彬,田连恕,等.陕西省地理.西安:陕西人民出版社, 1996.]
[8] Feng Shengwu, Xu Defu, Lei Xinyan. Physical Geography of China. Beijing:Higher Education Press, 1989.[冯绳武,徐德馥,雷新彦.中国自然地理.北京:高等教育出版社, 1989.]
[9] Zhang Qiang, Ruan Xin, Xiong Anyuan. Establishment and assessment of the grid air temperature data sets in China for the past 57 years. Journal of Applied Meteorological Science, 2009, 20(4):385-393.[张强,阮新,熊安元.近57年我国气温格点数据集的建立和质量评估.应用气象学报, 2009, 20(4):385-393.]
[10] Zhuo Jing, Zhu Yannian. Spatial interpolation methods of annual average precipitation on Qinling Mountains. Arid Land Geography, 2017, 40(3):555-563.[卓静,朱延年.秦岭主脊区年降水量空间插值最优方法研究.干旱区地理, 2017,40(3):555-563.]
[11] Sun Weihong, Chang Zhiyang. Discussion on spatial interpolation method of precipitation in West Qinling Mountains based on GIS. Soil and Water Conservation in China, 2017, 38(6):54-56.[孙伟红,常直杨.基于GIS的西秦岭地区降水量空间插值方法探讨.中国水土保持, 2017, 38(6):54-56.]
[12] Mo Shenguo, Zhang Baiping. Simulation of temperature fields based on DEM in Qinling Mts. Mountain Research,2007, 25(4):406-411.[莫申国,张百平.基于DEM的秦岭温度场模拟.山地学报, 2007, 25(4):406-411.]
[13] Bai Hongying, Ma Xinping, Gao Xiang, et al. Variations in January temperature and 0℃isothermal curve in Qinling Mountains based on DEM. Acta Geographica Sinica, 2012, 67(11):1443-1450.[白红英,马新萍,高翔,等.基于DEM的秦岭山地1月气温及0℃等温线变化.地理学报, 2012, 67(11):1443-1450.]
[14] Liu Zhihong, Li Lingtao, Tim R, et al. Introduction of the professional interpolation software for meteorology data:ANUSPLIN. Meteorological Monthly, 2008, 34(2):92-100.[刘志红, Li Lingtao, Tim R,等.专用气候数据空间插值软件ANUSPLIN及其应用.气象, 2008, 34(2):92-100.]
[15] Tachikawa T, Kaku M, Iwasaki A, et al. ASTER global digital elevation model version 2:Summary of validation results.NASA Land Processes Distributed Active Archive Center and the Joint Japan-US ASTER Science Team, 2011:1-26.
[16] Kanamitsu M, Ebisuzaki W, Woollen J, et al. NCEP-DOE AMIP-II Reanalysis(R-2). Bulletin of the American Meteorological Society, 2002, 83(11):1631-1643.
[17] Hutchinson M, Xu Tingbao. Anusplin version 4.4 user guide. Canberra:Fenner School of Environment and Society,Australian National University, 2013:1-52.
[18] Hutchinson M. Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems, 1995, 9(4):385-403.
[19] Tan Jianbo, Li Ainong, Lei Guangbin. Contrast on Anusplin and Cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang Plateau. Plateau Meteorology, 2016, 35(4):875-886.[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.高原气象, 2016, 35(4):875-886.]
[20] Liao Rongwei, Cao Lijuan, Zhang Dongbin, et al. Validation of gridded precipitation and temperature data over China.Meteorological Science and Technology, 2017, 45(2):364-374.[廖荣伟,曹丽娟,张冬斌,等.中国地面气温和降水网格化数据精度比较.气象科技, 2017, 45(2):364-374.]
[21] Qian Yonglan, Lv Houquan, Zhang Yanhong. Application and assessment of spatial interpolation method on daily meteorological elements based on ANUSPLIN software. Journal of Meteorology and Environment, 2010, 26(2):7-15.[钱永兰,吕厚荃,张艳红.基于ANUSPLIN软件的逐日气象要素插值方法应用与评估.气象与环境学报, 2010, 26(2):7-15.]
[22] Hutchinson M. The application of thin plate smoothing splines to continent-wide data assimilation//Jasper J(Ed.)Data Assimilation Systems:BMRC Research Report No.27. Melbourne:Bureau of Meteorology, 1991:104-113.
[23] Jones D, Wang W, Fawcett R. High-quality spatial climate data-sets for Australia. Australian Meteorological and Oceanographic Journal, 2009, 58(4):233-248.
[24] Xiong Qiufen, Huang Mei, Xiong Minquan, et al. Cross-validation error analysis of daily gridded precipitation based on China meteorological observation. Plateau Meteorology, 2011, 30(6):1615-1625.[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.高原气象, 2011, 30(6):1615-1625.]
[25] Liu Zhengjia, Yu Xingxiu, Wang Sisi, et al. Comparative analysis of three covariates methods in thin plate smoothing splines for interpolating precipitation. Progress in Geography, 2012, 31(1):56-62.[刘正佳,于兴修,王丝丝,等.薄盘光滑样条插值中三种协变量方法的降水量插值精度比较.地理科学进展, 2012, 31(1):56-62.]
[26] Ma Xinping, Bai Hongying, Guo Shuai, et al. Verification of temperature vertical lapse rate and mountain climate characteristics of Taibai Mountains in Qinling Mountains. Journal of Arid Land Resources and Environment, 2017, 31(7):139-144.[马新萍,白红英,郭帅,等.秦岭太白山气温垂直递减率研究.干旱区资源与环境, 2017, 31(7):139-144.]
[27] Zhai Danping, Bai Hongying, Qin Jin, et al. Temporal and spatial variability of air temperature lapse rates in Mt. Taibai,Central Qinling Mountains. Acta Geographica Sinica, 2016, 71(9):1587-1595.[翟丹平,白红英,秦进,等.秦岭太白山气温直减率时空差异性研究.地理学报, 2016, 71(9):1587-1595.]
[28] Li Shuangshuang, Lu Jiayu, Yan Junping, et al. Spatiotemporal variability of temperature in northern and southern Qinling Mountains and its influence on climatic boundary. Acta Geographica Sinica, 2018, 73(1):13-24.[李双双,芦佳玉,延军平,等. 1970-2015年秦岭南北气温时空变化及其气候分界意义.地理学报, 2018, 73(1):13-24.]
[29] Bi Baogui. The influence of mesoscale topography on torrential rain in southern Shaanxi Province. Nanjing:Nanjing Institute of Meteorology, 2004.[毕宝贵.中尺度地形对陕南暴雨的影响研究.南京:南京气象学院, 2004.]
[2] Fick S, Hijmans R. WorldClim 2:New 1‐km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 2017, 37(12):4302-4315.
[3] New M, Lister D, Hulme M, et al. A high-resolution data set of surface climate over global land areas. Climate research,2002, 21(1):1-25.
[4] Harris I, Jones P, Osborn T, et al. Updated high‐resolution grids of monthly climatic observations:The CRU TS3.10Dataset. International Journal of Climatology, 2014, 34(3):623-642.
[5] Wu Jia, Gao Xuejie. A gridded daily observation dataset over China region and comparison with the other datasets.Chinese Journal of Geophysics, 2013, 56(4):1102-1111.[吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比.地球物理学报, 2013, 56(4):1102-1111.]
[6] Wu Xian, Huang Wei, Chen Fahu. Construction and application of monthly air temperature and precipitation gridded datasets with high resolution(0.025°×0.025°)over China during 1951-2012. Journal of Lanzhou University(Natural Sciences), 2014, 50(2):213-220.[吴娴,黄伟,陈发虎. 1951-2012年中国大陆0.025°×0.025°高分辨率月气温和降水量格点数据集的建立及其初步应用.兰州大学学报(自然科学版), 2014, 50(2):213-220.]
[7] Chen Mingrong, Tang Haibin, Tian Lianshu, et al. Geography of Shaanxi Province. Xi'an:Shaanxi People's Publishing House, 1996.[陈明荣,唐海彬,田连恕,等.陕西省地理.西安:陕西人民出版社, 1996.]
[8] Feng Shengwu, Xu Defu, Lei Xinyan. Physical Geography of China. Beijing:Higher Education Press, 1989.[冯绳武,徐德馥,雷新彦.中国自然地理.北京:高等教育出版社, 1989.]
[9] Zhang Qiang, Ruan Xin, Xiong Anyuan. Establishment and assessment of the grid air temperature data sets in China for the past 57 years. Journal of Applied Meteorological Science, 2009, 20(4):385-393.[张强,阮新,熊安元.近57年我国气温格点数据集的建立和质量评估.应用气象学报, 2009, 20(4):385-393.]
[10] Zhuo Jing, Zhu Yannian. Spatial interpolation methods of annual average precipitation on Qinling Mountains. Arid Land Geography, 2017, 40(3):555-563.[卓静,朱延年.秦岭主脊区年降水量空间插值最优方法研究.干旱区地理, 2017,40(3):555-563.]
[11] Sun Weihong, Chang Zhiyang. Discussion on spatial interpolation method of precipitation in West Qinling Mountains based on GIS. Soil and Water Conservation in China, 2017, 38(6):54-56.[孙伟红,常直杨.基于GIS的西秦岭地区降水量空间插值方法探讨.中国水土保持, 2017, 38(6):54-56.]
[12] Mo Shenguo, Zhang Baiping. Simulation of temperature fields based on DEM in Qinling Mts. Mountain Research,2007, 25(4):406-411.[莫申国,张百平.基于DEM的秦岭温度场模拟.山地学报, 2007, 25(4):406-411.]
[13] Bai Hongying, Ma Xinping, Gao Xiang, et al. Variations in January temperature and 0℃isothermal curve in Qinling Mountains based on DEM. Acta Geographica Sinica, 2012, 67(11):1443-1450.[白红英,马新萍,高翔,等.基于DEM的秦岭山地1月气温及0℃等温线变化.地理学报, 2012, 67(11):1443-1450.]
[14] Liu Zhihong, Li Lingtao, Tim R, et al. Introduction of the professional interpolation software for meteorology data:ANUSPLIN. Meteorological Monthly, 2008, 34(2):92-100.[刘志红, Li Lingtao, Tim R,等.专用气候数据空间插值软件ANUSPLIN及其应用.气象, 2008, 34(2):92-100.]
[15] Tachikawa T, Kaku M, Iwasaki A, et al. ASTER global digital elevation model version 2:Summary of validation results.NASA Land Processes Distributed Active Archive Center and the Joint Japan-US ASTER Science Team, 2011:1-26.
[16] Kanamitsu M, Ebisuzaki W, Woollen J, et al. NCEP-DOE AMIP-II Reanalysis(R-2). Bulletin of the American Meteorological Society, 2002, 83(11):1631-1643.
[17] Hutchinson M, Xu Tingbao. Anusplin version 4.4 user guide. Canberra:Fenner School of Environment and Society,Australian National University, 2013:1-52.
[18] Hutchinson M. Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems, 1995, 9(4):385-403.
[19] Tan Jianbo, Li Ainong, Lei Guangbin. Contrast on Anusplin and Cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang Plateau. Plateau Meteorology, 2016, 35(4):875-886.[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.高原气象, 2016, 35(4):875-886.]
[20] Liao Rongwei, Cao Lijuan, Zhang Dongbin, et al. Validation of gridded precipitation and temperature data over China.Meteorological Science and Technology, 2017, 45(2):364-374.[廖荣伟,曹丽娟,张冬斌,等.中国地面气温和降水网格化数据精度比较.气象科技, 2017, 45(2):364-374.]
[21] Qian Yonglan, Lv Houquan, Zhang Yanhong. Application and assessment of spatial interpolation method on daily meteorological elements based on ANUSPLIN software. Journal of Meteorology and Environment, 2010, 26(2):7-15.[钱永兰,吕厚荃,张艳红.基于ANUSPLIN软件的逐日气象要素插值方法应用与评估.气象与环境学报, 2010, 26(2):7-15.]
[22] Hutchinson M. The application of thin plate smoothing splines to continent-wide data assimilation//Jasper J(Ed.)Data Assimilation Systems:BMRC Research Report No.27. Melbourne:Bureau of Meteorology, 1991:104-113.
[23] Jones D, Wang W, Fawcett R. High-quality spatial climate data-sets for Australia. Australian Meteorological and Oceanographic Journal, 2009, 58(4):233-248.
[24] Xiong Qiufen, Huang Mei, Xiong Minquan, et al. Cross-validation error analysis of daily gridded precipitation based on China meteorological observation. Plateau Meteorology, 2011, 30(6):1615-1625.[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.高原气象, 2011, 30(6):1615-1625.]
[25] Liu Zhengjia, Yu Xingxiu, Wang Sisi, et al. Comparative analysis of three covariates methods in thin plate smoothing splines for interpolating precipitation. Progress in Geography, 2012, 31(1):56-62.[刘正佳,于兴修,王丝丝,等.薄盘光滑样条插值中三种协变量方法的降水量插值精度比较.地理科学进展, 2012, 31(1):56-62.]
[26] Ma Xinping, Bai Hongying, Guo Shuai, et al. Verification of temperature vertical lapse rate and mountain climate characteristics of Taibai Mountains in Qinling Mountains. Journal of Arid Land Resources and Environment, 2017, 31(7):139-144.[马新萍,白红英,郭帅,等.秦岭太白山气温垂直递减率研究.干旱区资源与环境, 2017, 31(7):139-144.]
[27] Zhai Danping, Bai Hongying, Qin Jin, et al. Temporal and spatial variability of air temperature lapse rates in Mt. Taibai,Central Qinling Mountains. Acta Geographica Sinica, 2016, 71(9):1587-1595.[翟丹平,白红英,秦进,等.秦岭太白山气温直减率时空差异性研究.地理学报, 2016, 71(9):1587-1595.]
[28] Li Shuangshuang, Lu Jiayu, Yan Junping, et al. Spatiotemporal variability of temperature in northern and southern Qinling Mountains and its influence on climatic boundary. Acta Geographica Sinica, 2018, 73(1):13-24.[李双双,芦佳玉,延军平,等. 1970-2015年秦岭南北气温时空变化及其气候分界意义.地理学报, 2018, 73(1):13-24.]
[29] Bi Baogui. The influence of mesoscale topography on torrential rain in southern Shaanxi Province. Nanjing:Nanjing Institute of Meteorology, 2004.[毕宝贵.中尺度地形对陕南暴雨的影响研究.南京:南京气象学院, 2004.]