首页|基于重标极差分析和非周期循环分析的气候变化趋势预测——以兰州市为例

基于重标极差分析和非周期循环分析的气候变化趋势预测——以兰州市为例

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
  • 维普
利用兰州市区及周边5个气象站的气象数据,通过重标极差分析(R/S)和非周期循环分析,计算兰州市气温、降水和城市热岛强度时间序列的Hurst指数、分维数和非周期循环的平均循环长度,分析气温、降水和城市热岛强度时间序列的变化趋势、长期记忆效应和记忆周期.结果表明:兰州市四季和年平均气温呈现上升趋势,变化趋势具有持续性特征.年均、春、夏、秋、冬季气温序列的平均循环长度分别为9a、4a、8a、5 a和6a.兰州市春、冬季降水量仍将持续递减,夏季降水持续递增；年平均和秋季降水量变化过程具有反持续性,未来的年平均和秋季降水量将出现增加的趋势,年均、春、夏、秋、冬季降水量序列的平均循环长度分别为9 a、7 a、10 a、12 a和13 a.兰州热岛强度冬季最强,夏季最弱,春秋居中；1月平均热岛强度为1.6℃,7月平均热岛强度为0.1℃.近50 a兰州市热岛强度逐渐增强,线性趋势达到0.46℃·(10a)-1,未来兰州市热岛强度的变化趋势将以目前的速率持续增强.将定量描述长程依赖性的重标极差分析和非周期循环分析二者结合起来,应用于气候变化的趋势预测研究,是一种新颖、科学、可行的非线性研究方法.
Prediction of Climate Change Trend Based on Rescaled Range Analysis and Non-periodic Cycle Analysis——A Case Study in Lanzhou City
Based on two methods of R/S and non-periodic cycle analysis, the values of Hurst parameter H, fractal dimension D and non-cycle average cycle length of temperature and precipitation at time series in Lanzhou City were calculated, and then the variation trends, long-term memory effects and memory cycles of temperature and precipitation at the time series were analyzed. The results show that the values of H and D of average seasonal and annual temperature varied in ranges of 0. 5 - 1 and 1-1.5 respectively, there was a fractal structure, and average seasonal and annual temperature was in a continuous increase trend. Average cycle lengths of average annual and spring, summer, autumn and winter temperature at time series were 9 years, 4 years, 8 years, 5 years and 6 years respectively. Precipitation in spring and winter will continuously decrease but increase in summer. H and D of average annual and autumn precipitation series with long-term negative correlation will vary in ranges of 0 -0.5 and 1.5-2 respectively, the change process has an anti-persistent character, the average annual and autumn precipitation in the future will in an increase trend, average cycle lengths of average annual, spring, summer, autumn and winter precipitation at time series will be 9 years, 7 years, 10 years, 12 years and 13 years respectively. Precipitation in the past will affect that in the future for a long time. The study revealed that the methods of R/S and non-periodic cycle analysis are new, scientific and reliable in predicting regional climate change.

rescaled range analysisnon-periodic cycle analysistemperatureprecipitationheat island effectclimate changetrend predictionLanzhou

李国栋、张俊华、王乃昂、程弘毅、赵丽萍

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河南大学环境与规划学院,河南开封475000

兰州大学资源环境学院,甘肃兰州730000

广东商学院,广东广州510320

重标极差分析(R/S) 非周期循环分析 气温 降水 热岛效应 气候变化 趋势预测 兰州

国家自然科学基金国家自然科学基金河南省教育厅科学技术研究重点项目广东高校优秀青年创新人才培育项目河南大学自然科学基金

411010884090102112A170002LYM100802011YBZR034

2013

干旱区研究
中国科学院新疆生态与地理研究所 中国土壤学会

干旱区研究

CSTPCDCSCD北大核心
影响因子：1.157
ISSN：1001-4675
年,卷(期)：2013.30(2)
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