1981—2023年雅鲁藏布江流域大气饱和水汽压差变化及影响因素

doi:10.12006/j.issn.1673-1719.2024.097

摘要/Abstract

摘要：

饱和水汽压差（vapor pressure deficit，VPD）可反映大气对水分的需求，厘清VPD时空变化特征有助于了解区域大气干湿程度对气候变化的响应。基于近43年（1981—2023年）雅鲁藏布江流域（简称雅江流域）34个气象站点逐月日照时数、平均气温、平均最高气温、平均最低气温、降水量（P_r)、相对湿度、水汽压和平均风速等资料，采用线性倾向估计、R/S分析、Mann-Kendall法、Morlet小波分析和逐步回归等方法，分析近43年雅江流域VPD时空变化特征及影响因子。结果表明：(1)雅江流域年、季VPD总体上呈东西部低、中部高分布特征；月际变化呈双峰型，第1、2峰值分别在6、10月，1月最小；VPD夏季最大，春季次之，冬季最小。(2)年VPD以0.030 kPa/(10 a)的速率显著增加，主要表现在夏秋季，尤其近23年（2001—2023年）增速明显。年、季VPD在21世纪前10年中后期发生了突变，且未来持续增大的可能性很高。20世纪80和90年代年、季VPD均偏低，以90年代最明显；21世纪前10年因夏、冬两季VPD偏高，年VPD偏高；21世纪10年代年、季VPD均偏高，主要表现在夏、秋两季。VPD在春、夏、秋3季都存在3~4 a显著周期，冬季有2~3 a周期，年VPD无显著周期。(3)四季和年VPD与地理因子的线性关系不显著，但存在极显著的二次曲线关系。(4)年、季平均气温升高是致使VPD增加的主导因子；2004年以后，年平均气温、水汽压对VPD贡献率有所降低，P_r的作用明显增大。

关键词: 雅鲁藏布江, 饱和水汽压差（VPD）, 线性趋势, 年代际变化, 突变, 周期

Abstract:

Vapor pressure deficit (VPD) reflects the atmospheric water demand, and clarifying the spatial and temporal characteristics of VPD is helpful to understand the response of regional atmospheric dryness and wetness to climate change. Based on the data of monthly sunshine duration, average temperature (T_m), average maximum temperature, average minimum temperature, precipitation (P_r), relative humidity, vapour pressure (e) and wind speed of 34 meteorological stations in the Yalung Zangbo River basin (YZRB) from 1981 to 2023, the spatio-temporal characteristics and influencing factors of VPD in YZRB during recent 43 years were analyzed by linear trend estimate, R/S analysis, Mann-Kendall method, Morlet wavelet analysis and stepwise regression method. The results show that: (1) The annual and seasonal VPD in YZRB were generally lower in the east and west, and higher in the middle. The monthly variation showed a bimodal pattern, with the 1st and 2nd peaks in June and October, respectively, and the minimum in January. VPD was the largest in summer, followed by spring, and the smallest in winter. (2) The annual VPD increased significantly with a rate of 0.030 kPa/(10 a), mainly in summer and autumn, especially in the last 23 years (2001-2023). The annual and seasonal VPD mutation occurred in the mid-to-late 2000s, and the possibility of continuous increase in the future is very high. The annual and seasonal VPD were lower in the 1980s and 1990s, especially in the 1990s. In the 2000s, due to the higher VPD in summer and winter, the annual VPD was higher. Annual and seasonal VPD were higher in the 2010s, mainly in summer and autumn. VPD had a significant 3-4 a cycle in spring, summer and autumn, 2-3 a cycle in winter, and annual VPD had no significant cycle. (3) Seasonal/annual VPD had no significant linear relationship with geographical factors, but there was a very significant quadratic curve relationship between them. (4) The increase of annual and seasonal T_m was the dominant factor causing the increase of VPD. After 2004, the contribution of annual T_m and e to VPD decreased, and the role of P_r increased significantly.

Key words: Yalung Zangbo River basin (YZRB), Vapor pressure deficit (VPD), Linear trend, Inter-decadal change, Climate mutation, Cycle

杜军, 高佳佳, 陈涛, 次旺, 巴果卓玛. 1981—2023年雅鲁藏布江流域大气饱和水汽压差变化及影响因素[J]. 气候变化研究进展, 2024, 20(5): 544-557.

DU Jun, GAO Jia-Jia, CHEN Tao, Tsewang , Pakgordolma . Spatio-temporal variation of vapor pressure deficit and impact factors in the Yalung Zangbo River basin from 1981 to 2023[J]. Climate Change Research, 2024, 20(5): 544-557.

图/表 14

图1 雅鲁藏布江流域气象站点分布注：该图基于西藏自治区自然资源厅服务网站下载的标准地图[审图号为藏S(2022)004号]绘制，底图边界无修改，下同。图中数字序号含义如下：A类站为4拉孜、7日喀则、8南木林、10江孜、13尼木、14浪卡子、17拉萨、20墨竹工卡、21贡嘎、23泽当、27加查、29米林、31林芝、33波密、34嘉黎；B类站为1仲巴、2萨嘎、3昂仁、5萨迦、6谢通门、9白朗、11康马、12仁布、15曲水、16堆龙德庆、18林周、19达孜、22扎囊、24琼结、25桑日、26曲松、28朗县、30工布江达、32墨脱。

Fig. 1 Distribution of meteorological stations in the Yalung Zangbo River basin (YZRB)

表1 H指数分级

Table 1 H index classification

图2 雅江流域年、季VPD多年平均值空间分布

Fig. 2 Spatial distribution of perennial average value for annual and seasonal vapor pressure deficit (VPD) in YZRB

图3 1981—2023年雅江流域15站年、季VPD变化趋势及其显著性分布注：加粗数字1、2、3分别表示P<0.05，P<0.01，P<0.001，未标数字的站点表示未通过显著性检验；LTR为变化趋势，下同。

Fig. 3 Spatial distribution of linear trend (LTR) and its significance for annual and seasonal VPD at 15 stations in YZRB from 1981 to 2023

图4 雅江流域VPD月际变化和季变化

Fig. 4 Monthly and seasonal variations of VPD in YZRB

图5 1981—2023年雅江流域平均年、季VPD变化注：ORV为历年值；y1,y2,y3分别为不同时段的线性方程；*、**、***分别表示P<0.05，P<0.01，P<0.001，下同。

Fig. 5 Change of average annual and seasonal VPD in YZRB from 1981 to 2023

表2 1981—2020年雅江流域平均年、季VPD距平的年代际变化

Table 2 The decadal anomaly of annual and seasonal VPD in YZRB from 1981 to 2020 kPa

表3 1981—2023年雅江流域平均年、季VPD的H指数

Table 3 H index of annual and seasonal VPD in YZRB from 1981 to 2023

图6 1981—2023年雅江流域平均年、季VPD的M-K检验

Fig. 6 The M-K test results of average annual and seasonal VPD in YZRB from 1981 to 2023

图7 1981—2023年雅江流域平均年、季VPD的小波能量谱及小波全域能量谱注：黑虚线表示头部影响的临界线，黑实线内的区域表示通过0.05显著性检验；蓝色实线表示能量谱，超过虚线的部分表示通过0.05显著性检验。

Fig. 7 Wavelet analysis of average annual and seasonal VPD in YZRB from 1981 to 2023 and the global wavelet power spectra

表4 雅江流域平均年、季VPD与地理因子之间的相关系数以及贡献率

Table 4 Correlations and contribution rates of geographic factors to average annual and seasonal VPD in YZRB

图8 雅江流域年VPD与地理因子的点聚图

Fig. 8 The relationship between annual VPD and geographic factors in YZRB

表5 雅江流域四季VPD与地理因子的二次曲线方程

Table 5 Quadratic curve equation of seasonal VPD and geographic factors in YZRB

表6 雅江流域主要气象因子对VPD贡献率

Table 6 Contribution rates of main meteorological factors to VPD in YZRB

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