Homogeneity test of extreme temperature in Xinjiang and analysis of its temporal and spatial characteristics

doi:10.11755/j.issn.1006-7639-2025-03-0394

Abstract

Abstract:

Under the background of global warming, Xinjiang has frequently experienced extreme weather and climate events. An in-depth study on the homogenization of extreme temperature will help to accurately analyze climate change characteristics and provide a basis for formulating effective climate change response strategies. Utilizing the Penalized Maximum T Test (PMT) method included in the RHtestsV5 software package, the paper selected homogenized monthly average maximum and minimum temperatures as reference sequences to conduct homogeneity tests on monthly extreme maximum and minimum temperature series from 1951 to 2022 at 105 national surface meteorological stations in Xinjiang. This analysis aimed to identify the primary causes of inhomogeneity in the monthly extreme maximum and minimum temperature series in Xinjiang, and the Quantile-Matching (QM) method was employed to adjust the inhomogeneous series. The results are as follows: 1) Among the 105 national surface meteorological stations, 26 stations exhibited breakpoints in monthly extreme minimum temperature, and 8 stations exhibited breakpoints in monthly extreme maximum temperature. Extreme minimum temperature are more susceptible to non-natural factors than extreme maximum temperatures. 2) Relocation of meteorological stations is the primary cause of breakpoints in extreme maximum and minimum temperature series. Environmental changes act as the secondary factor for extreme maximum temperature, while the causes of breakpoints in extreme minimum temperature also include instrument type replacement, environmental changes and changes in observation times. 3) The trends of annual extreme maximum and minimum temperatures throughout Xinjiang showed little difference before and after the adjustments. However, stations such as Moyu exhibited a shift from a cooling trend to a warming trend in both monthly extreme maximum and minimum temperatures. The adjusted extreme maximum and minimum temperatures in Xinjiang are more in line with the climate warming characteristics of the northwest region, and the spatial consistency of climate change has been significantly improved. 4) The changing trends of the corrected data sequences of the extreme maximum temperature at Moyu Station and the extreme minimum temperature at Korla Station are consistent with the data of the old sites, and have a better consistency with the research results of the climate warming characteristics in Xinjiang, indicating that the correction method is reliable and scientific.

Key words: Xinjiang, monthly extreme maximum temperature, monthly extreme minimum temperature, PMT method, homogeneity

摘要： 全球变暖背景下，新疆极端天气气候事件频发，深入研究气温极值的均一化，将有助于准确分析气候变化特征，为制定有效的气候变化应对策略提供参考。利用RHtestsV5软件中惩罚最大T检验方法（Penalized Maximal T Test，PMT），选用均一化的月平均最高气温和月平均最低气温作为参考序列，对新疆105个国家级地面气象站1951—2022年月极端最高、极端最低气温序列进行均一性检验，分析造成新疆月极端最高、最低气温序列非均一的主要原因，采用分位数匹配（Quantile-Matching，QM）方法对非均一序列进行订正。结果表明：1）105个国家级地面气象站中26站月极端最低气温、8站月极端最高气温序列存在断点，极端最低气温比极端最高气温更易受非自然因素影响；2）台站迁移是极端最高、最低气温序列产生断点的主要原因，极端最高气温产生断点的次要原因是环境变化，而极端最低气温产生断点的原因还包括仪器换型、环境变化和观测时次改变；3）订正前、后全疆年极端最高气温和极端最低气温趋势变化差异不大，但墨玉站等月极端最高、最低气温订正后由降温趋势变为增温趋势，订正后新疆极端最高、最低气温更符合西北地区气候变暖特征，气候变化的空间一致性得到明显改善；4）墨玉极端最高气温和库尔勒极端最低气温订正后的数据序列变化趋势与旧址数据保持一致，且与新疆气候变暖特征的研究结果吻合度更好，说明订正方法具有可靠性和科学性。

关键词: 新疆, 月极端最高气温, 月极端最低气温, PMT方法, 均一性

CLC Number:

P468

LIU Weiping, CAO Lijuan, ZHANG Pu, LI Zhen, YUAN Fang, FEI Ye, WANG Qiwen, LI Qinglei. Homogeneity test of extreme temperature in Xinjiang and analysis of its temporal and spatial characteristics[J]. Journal of Arid Meteorology, 2025, 43(3): 394-402.

刘卫平, 曹丽娟, 张璞, 李珍, 远芳, 费烨, 王琪雯, 李庆雷. 新疆极端气温均一性检验及变化趋势时空特征[J]. 干旱气象, 2025, 43(3): 394-402.

Figures/Tables 6

Fig.1 The spatial distribution of national surface meteorological stations in Xinjiang

Fig.2 Series of annually relocated stations in Xinjiang from 1951 to 2022

Fig.3 Spatial distribution of homogeneous and inhomogeneous stations for monthly extreme maximum and minimum temperature series in Xinjiang from 1951 to 2022

Fig.4 The annual extreme maximum (a) and minimum (b) temperature series before and after correction of 105 stations in Xinjiang from 1961 to 2022, as well as the spatial distribution of the trends (Unit: ℃·(10 a)-1) of annual extreme maximum (c, d) and minimum (e, f) temperatures before (c, e) and after (d, f) correction

Fig.5 The annual mean extreme maximum (a, c) and extreme minimum (b, d) temperature series at Moyu (a), Fuyun (b), Shisanjianfang (c), and Tazhong (d) stations

Fig.6 The parallel observation series of annual extreme maximum temperature at the old site of Moyu Station (a) and annual extreme minimum temperature at Korla Station (b), as well as the observation series of them before and after homogenization at the new sites

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