A Method for Identifying the Dominant Meteorological Factors of Atmospheric Evaporative Demand in Mid‐Long Term
A Method for Identifying the Dominant Meteorological Factors of Atmospheric Evaporative Demand in Mid‐Long Term
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DOI：
10.1029/2022wr033321
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发表时间：
2023-07
影响因子：
5.4
通讯作者：
Saiyan Liu;Yangyang Xie;Hongyuan Fang;Pengcheng Xu;Huihua Du
中科院分区：
文献类型：
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作者：
Saiyan Liu;Yangyang Xie;Hongyuan Fang;Pengcheng Xu;Huihua Du
为了更好地了解全球变暖背景下大气蒸发需求(AED)的变化，提出了异常贡献分析来估计气象因素对AED的中长期贡献。用气象要素总贡献率(ψ)和相对变化量(ϕ)之间的皮尔逊相关系数(RP)和散射体(β)的森趋势斜率(βS)来评价该方法的适用性。|1−RP|和|1−βS|的值越小，该方法越适用。为了验证该方法的有效性，采用参考作物蒸散量作为AED的替代方法。采用多年贡献分析作为比较分析的方法，只能研究长期内AED的主导气象因子。并以中国所在的淮河流域为例进行了实证研究。结果表明：(A)在应用异常贡献分析时，中长期的|1−Rp|和|1−βS|的值大多小于0.1，清楚地展示了气象因子对大气降水的中长期贡献过程；(B)在长期内，风速和日照时数是两个最主要的因子(总的绝对贡献率超过60%)，但在中长期(如夏季风速和冬季日照时数)它们并不总是占主导地位。因此，异常贡献分析是一种合理有效的方法，有助于洞察AED的变化。
To better understand the changes in the atmospheric evaporative demand (AED) in the context of global warming, the anomaly contribution analysis is presented to estimate mid‐long term contributions of meteorological factors to the AED. The Pearson correlation coefficient (RP) between the total contribution (ψ) of meteorological factors and the relative variation (ϕ) of the AED, and the Sen's trend slope (βS) of (ϕ, ψ) scatters are used to evaluate the applicability of the method. The smaller the values of |1 − RP| and |1 − βS|, the more applicable the method is. To validate the method, the reference crop evapotranspiration is employed as a proxy for the AED. The multi‐year contribution analysis is used as a comparison approach, which can only investigate the dominant meteorological factors of the AED in long term. Moreover, the Huaihe River basin of China is taken as a case study. Results show that (a) the values of |1 − RP| and |1 − βS| in mid‐long term are less than 0.1 in most cases when applying the anomaly contribution analysis, and the mid‐long term contribution processes of meteorological factors to the AED are clearly demonstrated; and (b) the wind speed and sunshine hours are the two most dominant factors (the total absolute contribution exceeds 60%) in long term, but they are not always the dominant factors in mid‐long term (e.g., wind speed in summer, and sunshine hours in winter). Therefore, the anomaly contribution analysis is a reasonable and effective method, which can help to gain insights into the changes in the AED.