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基于AI指数的新疆干湿时空变化及其影响因素分析

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  • 西北师范大学地理与环境科学学院,兰州 730070
张彦龙(1989- ),男,甘肃通渭人,硕士研究生,主要研究干旱区域环境与绿洲建设。E-mail:zhangylsunshine@163.com

收稿日期: 2015-04-03

  修回日期: 2015-09-24

  网络出版日期: 2016-04-28

基金资助

国家自然科学基金项目(40961035); 甘肃省科技计划基金项目(0803RJZA094); 甘肃省级重点学科自然地理学项目

Study on Temporal and Spatial Variation of the Dry-wet and Its Influence Factors in Xinjiang Based on Aridity Index

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  • College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, China

Received date: 2015-04-03

  Revised date: 2015-09-24

  Online published: 2016-04-28

Supported by

National Natural Science Foundation of China, No.40961035; Science and Technology Project of Gansu Province, No.0803RJZA094; Provincial Key Disciplines of Natural Geography Project of Gansu

摘要

论文基于新疆53个气象站点1961—2013年逐日气温、降水、风速、日照时数、相对湿度、大气环流指数和太阳黑子数据,应用Penman-Monteith模型、ArcGIS反距离加权插值、Mann-Kendall(M-K)检验、Morlet小波和主成分分析方法,分析其降水量、潜在蒸散量和AI指数时空变化及影响因素。结果表明:近53 a来,新疆降水量呈上升趋势,潜在蒸散量在波动中呈下降趋势,倾向率分别为8.81 mm/10 a和-28.73 mm/10 a,AI指数在波动中呈下降趋势,倾向率为 -0.05/10 a,多年平均值为0.5,表明新疆气候有变湿趋势。从年内分布看,降水量和潜在蒸散量呈单峰型分布,峰值分别出现在7月和8月,分别为24.58和137.12 mm;AI指数最大值滞后于降水量(7月)和潜在蒸散量(8月),出现在9月,为0.9,最小值出现在1月,为0.46。新疆潜在蒸散量空间分布为南疆大于北疆,东部大于西部;降水量北疆大于南疆;AI指数的空间分布与降水量相反,总体表现为南疆大于北疆,盆地大于山区,M-K趋势介于0~-0.02/a之间,且北疆AI指数减小趋势较南疆更显著,与北疆比南疆更湿润的事实相符。新疆降水量和潜在蒸散量分别在1987和1981年发生突变,AI指数在1981和1984年存在两个明显的突变点。Morlet小波及其功率谱分析表明,降水量存在6.49、5.71和4.35 a(p≤0.05)的周期,蒸散量存在21.37 a(p≤0.2)的周期,AI指数存在6.62、3.45 a(p≤0.1)的周期,表明AI指数可能受大气环流和厄尔尼诺的影响。主成分分析表明,AI指数与气温呈正相关,与降水量呈负相关,且南疆比北疆对降水更敏感。此外,AI指数与维尔霍扬斯克-奥伊米亚康(WYMI)、ENSO关系密切,相关系数分别为0.46(p≤0.05)和-0.34(p≤0.05)。

本文引用格式

张彦龙, 刘普幸 . 基于AI指数的新疆干湿时空变化及其影响因素分析[J]. 自然资源学报, 2016 , 31(4) : 658 -671 . DOI: 10.11849/zrzyxb.20150345

Abstract

Based on the collected climate data regarding daily temperature, precipitation, wind speed, sunshine hour as well as related humidity from 53 meteorological stations, and atmospheric circulation index and sunspot in the study region during 1961-2013, evapotrans-piration (ET0) was estimated by applying Penman-Monteith model. Additionally, Inverse Dis-tance Weighted was applied to comprehensively investigate the temporal-spatial variations of ET0, precipitation and aridity index (AI). The abrupt change and period of ET0, precipitation and AI were characterized using comprehensive time series analysis conducted with moving M-K test and Morlet wavelet. Principal component analysis was employed to analyze the factors that influenced the AI. The results showed that: In recent 53 years, precipitation displayed an increasing trend (8.81 mm/10 a), ET0 and AI presented decreasing trend on the whole at the rates of -28.73 mm/10 a and -0.05/10 a, suggesting that the regional climate trended to be wetter in Xinjiang. As for annual distribution, ET0 and precipitation both exhibited unimodal distributions with peaks appeared in August (137.12 mm) and July (24.58 mm), the maximum in September (0.9), and the minimum in January (0.46). Spatially, the ET0 in southern Xinjiang was greater than that in northern Xinjiang, and that of east was greater than that of west; the precipitation in northern was greater than that in southern. The spatial patterns of AI and precipitation were opposite. Overall, the AI in south was greater than that in north, and that in basin was greater than that in the mountains. The M-K trend of AI was between 0 - -0.02/a, and the decreasing trend of AI in north was more extraordinary than that in south, consistent with the facts that the north of Xinjiang was wetter than the south. The abrupt changes for ET0 and precipitation occurred in 1987 and 1981, respectively. There were two distinct point mutations of AI in 1981 and 1984. Morlet wavelet and its power spectrum analysis showed: Precipitation exhibited periods of 6.49 a, 5.71 a and 4.35 a (p≤0.05), ET0 showed the period of 21.37 a (p≤0.2), and AI had periods of 6.62 a and 3.45 a (p≤0.1), indicating that it was related to atmospheric circumfluence and El Niño events to some extent. Principal component analysis demonstrated: AI was positively correlated with temperature and negatively correlated with precipitation, and the southern part of Xinjiang was more sensitive to precipitation than the northern part. Correlation coefficient between AI and WYMI, and ENSO were 0.46 (p≤0.05) and -0.34 (p≤0.05), respectively.

参考文献

[1] KEYANTASH J, DRACUP J A. The quantification of drought: An evaluation of drought indices [J]. Bulletin of the American Meteorological Society, 2002, 83(8): 1167-1180.
[2] SCHUBERT S D, SUAREZ M J, PEGION P J, et al. On the cause of the 1930s Dust Bowl [J]. Science, 2004, 303(5665) : 1855-1859.
[3] WILHITE D A. Drought as a natural hazard: Concepts and definitions [M]// WILHITE D A. Drought: A Global Assessment. London: Routledge, 2000: 3-18.
[4] 王劲松, 郭江勇, 倾继祖. 一种K干旱指数在西北地区春旱分析中的应用 [J]. 自然资源学报, 2007, 22(5): 709-717.[WANG J S, GUO J Y, QING J Z. Application of a kind of K drought index in the spring drought analysis in Northwest China. Journal of Natural Resources, 2007, 22(5): 709-717. ]
[5] UMMENHOFER C C, SEN GUPTA A, BRIGGS P R, et al. Indian and Pacific Ocean influences on southeast Australian drought and soil moisture [J]. Journal of Climate, 2011, 24(5): 1313-1336.
[6] 郑广芬, 陈晓光, 赵光平, 等. 宁夏地表湿润状况及极端干湿事件演变规律 [J]. 中国沙漠, 2007, 27(2): 326-330.

[7] 李泽明, 陈皎, 董新宁. 重庆2011年和2006年夏季严重干旱及环流特征的对比分析 [J]. 西南大学学报(自然科学版), 2014, 36(8): 113-121.

[8] 王允, 刘普幸, 曹立国, 等. 基于湿润指数的1960—2011年中国西南地区地表干湿变化特征 [J]. 自然资源学报, 2014, 29(5): 830-838.

[9] 江 东, 付晶莹, 庄大方, 等. 2008—2009年中国北方干旱遥感动态监测 [J]. 自然灾害学报, 2012, 21(3): 92-100.

[10] 段海霞, 王劲松, 刘芸芸, 等. 2009/2010年我国西南秋冬春连旱特征及其大气环流异常分析 [J]. 冰川冻土, 2013, 35(4): 1022-1034.

[11] 姚 萍, 黄小梅, 陈菲菲, 等. 2011年春季长江中下游严重干旱的异常环流分析 [J]. 农业灾害研究, 2013, 3(4): 55-61.

[12] 赵志平, 吴晓莆, 李果, 等. 2009—2011年我国西南地区旱灾程度及其对植被净初级生产力的影响 [J]. 生态学报, 2015, 35(2): 350-360.

[13] 王素艳, 郑广芬, 杨洁, 等. 几种干旱评估指标在宁夏的应用对比分析 [J]. 中国沙漠, 2012, 32(2): 517-524.

[14] 卫捷, 马柱国. Palmer干旱指数、地表湿润指数与降水距平的比较 [J]. 地理学报, 2003, 58(S1): 117-124.

[15] 张存杰, 王宝灵, 刘德祥, 等. 西北地区旱涝指标的研究 [J]. 高原气象, 1998, 17(4): 381-389.

[16] 王玲玲, 康玲玲, 王云璋. 气象、水文干旱指标计算方法研究概述 [J]. 水资源与水工程学报, 2004, 15(3): 15-18.

[17] 袁文平, 周广胜. 干旱指标的理论分析与研究展望 [J]. 地球科学进展, 2004, 19(1): 80-85.

[18] 姚玉璧, 张存杰, 邓振镛, 等. 气象、农业干旱指标综述 [J]. 干旱地区农业研究, 2007, 25(1): 185-189.

[19] HUO Z L, DAI X Q , FENG S Y, et al. Effect of climate change on reference evapotransspiration and aridity index in a-rid region of China [J]. Journal of Hydrology, 2013, 492: 24-34.
[20] 王智, 师庆三, 王涛, 等. 1982—2006年新疆山地-绿洲-荒漠系统植被覆盖变化时空特征 [J]. 自然资源学报, 2011, 26(4): 609-618.

[21] 高歌, 陈德亮, 任国玉, 等. 1956—2000年中国潜在蒸发量变化趋势 [J]. 地理研究, 2006, 25(3): 378-387.

[22] 祝昌汉. 再论总辐射的气候学计算方法(二) [J]. 南京气象学院学报, 1982(2): 196-206.

[23] 施雅风, 沈永平, 胡汝骥. 西北气候由暖干向暖湿转型的信号、影响和前景初步探讨 [J]. 冰川冻土, 2002, 24(3): 219-226.

[24] 陈洪武, 王旭, 马禹. 大风对新疆沙尘暴的影响 [J]. 北京大学学报(自然科学版), 2003, 39(2): 187-193.

[25] 施雅风, 沈永平, 李栋梁, 等. 中国西北气候由暖干向暖湿转型的特征和趋势探讨 [J]. 第四纪研究, 2003, 23(2): 152-163.

[26] 普宗朝, 张山清, 王胜兰, 等. 近36年天山山区潜在蒸散量变化特征及其与南、北疆的比较 [J]. 干旱区研究, 2009, 26(3): 424-432.

[27] 普宗朝, 张山清, 王胜兰, 等. 近48 a新疆干湿气候变化特征 [J]. 中国沙漠, 2012, 31(6): 1563-1572.

[28] 蓝永超, 沈永平, 苏宏超, 等. 全球变暖情景下新疆降水的变化 [J]. 干旱区资源与环境, 2008, 22(10): 66-71.

[29] 刘普幸. 近54年民勤绿洲气候变化趋势与周期分析 [J]. 干旱区研究, 2009, 7(4): 471-476.

[30] 卢爱刚, 葛建平, 庞德谦, 等. 40 a来中国旱灾对ENSO事件的区域差异响应研究 [J]. 冰川冻土, 2006, 28(4): 535-542.

[31] 赵佩章, 陈健, 赵文桐. 太阳黑子对厄尔尼诺、拉尼娜的影响 [J]. 地球物理学进展, 2001, 16(3): 85-90.

[32] 马柱国, 邵丽娟. 中国北方近百年干湿变化与太平洋年代际振荡的关系 [J]. 大气科学, 2006, 30(3): 464-474.

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