4.6 Article

Changes in annual and seasonal temperature extremes in the arid region of China, 1960-2010

期刊

NATURAL HAZARDS
卷 65, 期 3, 页码 1913-1930

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SPRINGER
DOI: 10.1007/s11069-012-0454-4

关键词

Temperature extremes; Mann-Kendall test; Sen's slope estimates; The arid region

资金

  1. National Basic Research Program of China (973 Program) [2010CB951003]

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Daily data of minimum and maximum temperature from 76 meteorological stations for 1960-2010 are used to detect the annual and seasonal variations of temperature extremes in the arid region, China. The Mann-Kendall test and Sen estimator are used to assess the significance of the trend and amount of change, respectively. Fifteen temperature indices are examined. The temperature extremes show patterns consistent with warming, with a large proportion of stations showing statistically significant trends. Warming trends in indices derived from daily minimum temperature are of greater magnitudes than those from maximum temperature, and stations along the Tianshan Mountains have larger trend magnitudes. The decreases in frequency for cold extremes mainly occur in summer and autumn, while warm extremes show significant increases in frequency in autumn and winter. For the arid region as a whole, the occurrence of cold nights and cold days has decreased by -1.89 and -0.89 days/decade, respectively, and warm nights and warm days has increased by 2.85 and 1.37 days/decade, respectively. The number of frost days and ice days exhibit significant decreasing trends at the rates of -3.84 and -2.07 days/decade. The threshold indices also show statistically significant increasing trends, with the extreme lowest temperatures faster than highest temperatures. The diurnal temperature range has decreased by 0.23 A degrees C/decade, which is in accordance with the more rapid increases in minimum temperature than in maximum temperature. The results of this study will be useful for local human mitigation to alterations in water resources and ecological environment in the arid region of China due to the changes of temperature extremes.

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