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中文摘要：
结合全国317个气象站1956--2005年气象资料，分别利用普通Mann—Kendall、预置白Mann—Kendall、去趋势预置白Mann—Kendall趋势检验方法分析了年降水量、年平均气温和年蒸发皿蒸发量的趋势检验结果及自相关系数变化规律。其中，年降雨序列的自相关性不显著，3种趋势检验方法的分析结果差异不大；年平均气温和年蒸发皿蒸发量自相关性显著，其3种方法的检验结果差异性较大，需要剔除自相关性后进行趋势检验；空间特征上，北方站点气象要素的自相关显著性较高。数据分析和数学推导表明，序列正自相关性会放大序列趋势的显著性，序列的趋势项会增大计算的自相关系数。
英文摘要：
Trend test is an essential topic in climate change research. Three trend test methods, Mann-Kendall, Pre- Whitening Mann-Kendall and Trend-Free Pre-Whitening Mann-Kendall, are employed to analyze trends and autocorre- lations of annual precipitation, pan evaporation and average air temperature spatially and temporally across China. The meteorological variables are observed at 317 stations during the period 1956-2005. Specifically, the autocorrelation of annual precipitation is insignificant, resulting in the similar trend analysis results for the three methods. While both an- nual pan evaporation and average temperature exhibit significant autocorrelations, which result in distinct trend test re- suits using the three methods. Thus, the autocorrelation must be properly considered when conducting a trend test for both annual pan evaporation and average air temperature. In general, meteorological data from northern basins has a more significant autocorrelation than the southern one. In addition, the effects of trend on the estimated autocorrelation coefficient and correlation on the Mann-Kendall statistics are also investigated theoretically. Results indicate that the positive correlation magnifies the series trend significance and the trend existed in the series may contaminate the lag- 1 autocorrelation coefficient in turn.
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