摘要
Based on daily maximum and minimum temperature observed by the China Mete- orological Administration at 115 meteorological stations in the Yangtze River Basin from 1962 to 2011, the methods of linear regression, principal component analysis and correlation analysis are employed to investigate the temporal variability and spatial distribution of tem- perature extremes. Sixteen indices of extreme temperature are selected. The results are as follows： （1） The occurrence of cold days, cold nights, ice days, frost days and cold spell du- ration indicator has significantly decreased by -0.84, -2.78, -0.48, -3.29 and -0.67 days per decade, respectively. While the occurrence of warm days, warm nights, summer days, tropi- cal nights, warm spell duration indicator and growing season length shows statistically sig- nificant increasing trends at rates of 2.24, 2.86, 2.93, 1.80, 0.83 and 2.30 days per decade, respectively. The tendency rate of the coldest day, coldest night, warmest day, warmest night and diurnal temperature range is 0.33, 0.47, 0.16, 0.19 and -0.07~C per decade, respectively （2） The magnitudes of changes in cold indices （cold nights, coldest day and coldest night） are obviously greater than those of warm indices （warm nights, warmest day and warmest night）. The change ranges of night indices （warm nights and cold nights） are larger than those of day indices （warm days and cold days）, which indicates that the change of day and night tem- perature is asymmetrical. （3） Spatially, the regionally averaged values of cold indices in the upper reaches of the Yangtze River Basin are larger than those in the middle and lower reaches. However, the regionally averaged values of most warm indices （except warm spell duration indicator） and growing season length in the middle and lower reaches are larger than those in the upper reaches. （4） The extreme temperature indices are well correlated with each other except diurnal temperature range.
Based on daily maximum and minimum temperature observed by the China Mete- orological Administration at 115 meteorological stations in the Yangtze River Basin from 1962 to 2011, the methods of linear regression, principal component analysis and correlation analysis are employed to investigate the temporal variability and spatial distribution of tem- perature extremes. Sixteen indices of extreme temperature are selected. The results are as follows： （1） The occurrence of cold days, cold nights, ice days, frost days and cold spell du- ration indicator has significantly decreased by -0.84, -2.78, -0.48, -3.29 and -0.67 days per decade, respectively. While the occurrence of warm days, warm nights, summer days, tropi- cal nights, warm spell duration indicator and growing season length shows statistically sig- nificant increasing trends at rates of 2.24, 2.86, 2.93, 1.80, 0.83 and 2.30 days per decade, respectively. The tendency rate of the coldest day, coldest night, warmest day, warmest night and diurnal temperature range is 0.33, 0.47, 0.16, 0.19 and -0.07~C per decade, respectively （2） The magnitudes of changes in cold indices （cold nights, coldest day and coldest night） are obviously greater than those of warm indices （warm nights, warmest day and warmest night）. The change ranges of night indices （warm nights and cold nights） are larger than those of day indices （warm days and cold days）, which indicates that the change of day and night tem- perature is asymmetrical. （3） Spatially, the regionally averaged values of cold indices in the upper reaches of the Yangtze River Basin are larger than those in the middle and lower reaches. However, the regionally averaged values of most warm indices （except warm spell duration indicator） and growing season length in the middle and lower reaches are larger than those in the upper reaches. （4） The extreme temperature indices are well correlated with each other except diurnal temperature range.
基金
l National Basic Research Program of China （973 Program）, No.2013CBA01801
National Natural Science Foundation of China, No.41161012, No.41240001
Basic Scientific Research Foundation in University of Gansu Province
