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金沙江流域1957-2016年气温时空变化特征 被引量:9

Temporal and Spatial Characteristics of Distribution of Temperature in Chinsha River Basin from 1957 to 2016
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摘要 利用累积距平法、Mann-Kendall检验、Kriging插值及小波分析等方法,选取金沙江流域39个气象站点1957—2016年的平均气温数据进行了研究分析。结果表明:金沙江流域年及四季平均气温均表现为上升的趋势,且均呈现显著的增加趋势;金沙江流域年及四季年代距平的最高值均出现在2010—2016年,年代距平最低值春季出现在1980s,年及夏秋冬季均出现在1970s;流域年及四季气温变化均存在多个特征时间尺度,其中年平均气温具有6a,21a和28a左右的主周期,以28a左右周期相位变化最为显著;随着上游向下游海拔的降低,金沙江流域气温呈现逐渐增加的趋势,其中五道梁站气温最低,元谋站气温最高;除夏季外,年及其余季节39个气象站中均有87%以上站点均呈显著性增加趋势。 The average temperatures of the 39 meteorological stations were used to analyze the temporal and spatial distribution characteristics in Chinsha River Basin from 1957 to 2016 by employing the cumulative anomaly method,the Mann-Kendall method,the Kriging and the wavelet analysis method.The results indicated that the annual and the seasonal temperatures had an upward trend,and all showed a significant increase trend;the maximum values of interdecadal annual and seasonal mean temperature anomaly in the Chinsha River Basin occurred during the period of 2010-2016,and the minimum values of spring appeared in 1980s,while the minimum values of summer,autumn and winter occurred in 1970s;there were many multiple time-scale features of annual and seasonal mean temperature in the basin,with the principal periods of about 6,21 and 28 years,and the phase change of 28 years period was the most obvious;the mean temperature gradually increased with the altitude from the upstream to downstream of the basin,of which the Wudaoliang station temperature was the lowest,while the Yuanmou station temperature was the highest;except for the summer,the mean annual temperature and the average temperature of the rest seasons of more than 87%of 39 meteorological stations presented the significant increase trend.
作者 史雯雨 李增永 李娜 潘妮 SHI Wenyu;LI Zengyong;LI Na;PAN Ni(Sichuan Water Conservancy Vocational College,Chendu 611231,China)
出处 《水土保持研究》 CSCD 北大核心 2019年第1期162-167,共6页 Research of Soil and Water Conservation
关键词 金沙江 气温 趋势变化 周期 空间分布 Chinsha River Basin temperature tread variations period temporal and spatial distribution
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