京津冀地区潜在蒸散量时空演变特征及归因分析

为了深入认识京津冀地区潜在蒸散量的时空变化特征及其对气候变化的响应,该研究基于京津冀地区23个气象站57 a逐日气象观测资料,应用Penman-Monteith公式计算各站点日潜在蒸散量(ET0),剖析ET0的时空变化特征,运用敏感性分析法定量研究ET0对各气象要素的敏感性及其时空变化特征,定量识别各气象要素变化对ET0变化的贡献。研究结果表明:1)京津冀地区ET0空间分布整体呈由南向北递减趋势(除中部地区的塘沽站、黄烨站与保定站点ET0较高外)。ET0整体呈下降趋势,线性趋势率为-0.92 mm/a。ET0变化趋势空间分布由西北向东南递减,以春季减幅最为明显。2)京津冀地区ET0对相对湿度的最为敏感(-0.44),其次为风速(0.31)、日照时数(0.28)与平均气温(0.26)。随时间推移,ET0对平均风速与相对湿度敏感性整体呈下降趋势,而ET0对平均气温与日照时数的敏感性逐渐增强。敏感性系数空间分布从西北到东南:风速与平均气温敏感性系数逐渐递增,而日照时数与相对湿度敏感性系数逐渐递减。3)风速变化对京津冀地区ET0变化的贡献最大,平均气温次之。风速为主导因素的站点个数随时间呈下降趋势,平均气温与日照时数为主导的站点个数随时间呈上升趋势,说明近年来平均气温与日照时数对潜在蒸散量变化的影响愈加明显,这可能是由于近年来京津冀地区雾霾尤其是冬季雾霾对日照时数、气温与风速的产生一定影响,进而影响ET0。

Spatial-temporal variation characteristics and attribution analysis of potential evapotranspiration in Beijing-Tianjin-Hebei region

This paper aims to investigate the spatial and temporal variation characteristics of the potential evapotranspiration (ET0) and its response to climate change using the collected data from the daily weather observation of 23 meteorological stations in the Beijing-Tianjin-Hebei region for 57 years from 1960-2016. The specific parameters of dataset included the daily average air temperature, the maximum and minimum air temperature, relative humidity, wind speed and sunshine hours. We chose the Penman-Monteith formula to calculate the daily ET0 at each site, and then analyzed the spatial and temporal variation characteristics of the calculated ET0. A sensitivity coefficient was used to quantitatively study the sensitivity of ET0 to various meteorological elements and its spatial and temporal distribution. The contribution rate was set to evaluate the influence of meteorological elements changes on the variation of ET0 during the calculation. The results show that: (1) The spatial distribution of ET0 shows a decreasing trend from south to north across the Beijing-Tianjin-Hebei region, except a high ET0 in the central region, such as Tanggu, Huangye and Baoding stations. There was a linear decline rate of -0.92mm /a. e in the whole distribution of ET0. The spatial distribution of ET0 MK (Penman-Monteith) decreased from the northwest to southeast. In temporal characteristics, spring has the most obvious decrease, followed by autumn, summer, and winter. (2) The sensitivity coefficient of ET0 to the average air temperature, sunshine hours, relative humidity and wind speed are 0.26, 0.28, 0.31 and -044, respectively, indicating the most sensitive to the changes of relative humidity in the Beijing-Tianjin-Hebei region, followed by the wind speed and sunshine hours. The sensitivity coefficient of ET0 to meteorological elements presents in a fluctuating trend from1960-2016, the sensitivity coefficient of ET0 to the wind speed and relative humidity in a downward trend, while the sensitivity coefficient of ET0 to average temperature and sunshine hours in an upward trend. The spatial distribution of the sensitivity coefficient from northwest to southeast: the wind speed and average temperature gradually increased, while the sunshine hours and relative humidity gradually decreased. The spatial distribution characteristics of the sensitivity coefficient of ET0 to relative humidity and average temperature were the opposite situation, where the high sensitivity zone of average temperature belongs to the low sensitive zone of relative humidity. The opposite phenomenon also occurred in the spatial distribution characteristics of the sensitivity coefficient of ET0 to sunshine hours and wind speed sensitivity, i.e., the high sensitivity zone of sunshine hours belongs to the low sensitive zone of wind speed. (3) The contribution rate of meteorological elements to ET0 depends on the sensitivity coefficient and the relative change of meteorological elements. ET0 has the most sensitivity to the changes of relative humidity, but the change rate of the relative humidity was small. ET0 has the lower sensitive to the changes of wind speed, but the change rate of the wind speed was large, resulting the most contribution to ET0 in the whole region was the wind speed. However, the stations number of the wind speed as the dominant factor decreased with the measure time, whereas the stations number of the average temperature as the dominant factor increased with the measure time, especially in the period of 2010-2014 to 2010s, 12 stations with the average temperature as the dominant factor. The stations number of the sunshine hours as the dominant factor also increased with the measured time. It infers that the average temperature and sunshine hours have much significant influences on ET0 in recent years. From 2013 to 2016, the correlation coefficients of the winter average air temperature, sunshine hours, relative humidity, wind speed and PM2.5 concentration were -0.44, -0.53, 0.42 and -0.35, respectively, while the correlation coefficients of ET0 and PM2.5 concentration were -0.37. Therefore, it is possible that the haze, especially winter haze, has a certain impact on meteorological elements, and thereby on ET0 in the Beijing-Tianjin-Hebei region.