基于去趋势波动分析的中国气温变化趋势研究
首发时间:2018-10-31
摘要:在全球暖化的大背景下进行气温趋势分析有着十分重要的现实意义。然而,传统的趋势分析继续直接利用线性回归并忽略了气温序列中可能的自相关性,因此可能对结果产生影响。本文选取了我国590个气象观测站的近46年的气温数据作为研究对象,应用去趋势波动分析法(detrended fluctuation analysis) 来分析序列的长程相关性以及其对气温的变化趋势的影响:590个站点中有555个站点的趋势是不显著的。然而,线性回归方法则只有49个站点估计出来的趋势是不显著的。两者之间的差异源于线性回归法没有考虑长程相关性的影响。我们进一步推测了在长程相关性存在时的最可能趋势并发现,如果不考虑长程相关性而仅使用线性回归估计趋势会显著高估趋势。考虑到长程相关性在现实数据中的普遍性,趋势研究时必须将其考虑在内。我们的分析为这类情况提供了一般研究框架。
关键词: 长程相关性 去趋势波动分析 气温序列 趋势 显著性。
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trend analysis of the temperature variation in china based on detrending fluctuation analysis
abstract:as globing warming has raised increasing concern in these years, research on trends in climate has become a hot topic. usually, the linear regression is employed for trend analysis. this detection method works on the basis of an assumption that the series is just first-order correlated or uncorrelated at all. however, in the real-life data, especially in the climatic data, e.g. the temperature data, there generally exists long-term correlation. therefore, the direct application of the linear regression analysis is inappropriate. this study employs detrended fluctuation analysis to investigate trends in temperature data in 590 meteorological stations of china in recent 46 years. the result shows that 555 stations out of 590 have insignificant trends. in contrast, only 49 stations display insignificant trends if using the traditional linear regression. such difference should be due to the effect of long-term correlation. furthermore, we try to calculate the most possible trend in the long-term correlated temperature data. our anlaysis demonstrates that the traditional linear regression method, which does not take long-term correlations into account, would significantly overestimate the trend in observed data. therefore, the effect of long-term correlation has to be taken into consideration in trend analysis of the real-life data. our analysis provides a general framework for the trend analysis of long-term correlated data.
keywords: long-term correlation ~detrended fluctuation analysis ~temperature series ~trend ~significance.
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