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Modified climate with long term memory in tree ring proxies

机译:树木环代理中具有长期记忆的改良气候

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Long term memory (LTM) scaling behavior in worldwide tree-ring proxies and subsequent climate reconstructions is analyzed for and compared with the memory structure inherent to instrumental temperature and precipitation data. Detrended fluctuation analysis is employed to detect LTM, and its scaling exponent α is used to evaluate LTM. The results show that temperature and precipitation reconstructions based on ring width measurements (mean ) contain more memory than records based on maximum latewood density (mean ). Both exceed the memory inherent to regional instrumental data ( for temperature, for precipitation) in the time scales ranging from 1 year up to 50 years. We compare memory-free () pseudo-instrumental precipitation data with pseudo-reconstructed precipitation data with LTM (), and demonstrate the biasing influences of LTM on climate reconstructions. We call for attention to statistical analysis with regard to the variability of proxy-based chronologies or reconstructions, particularly with respect to the contained (i) trends, (ii) past warm/cold period and wet/dry periods; and (iii) extreme events.
机译:分析并比较了全球树木年轮代理和随后的气候重建中的长期记忆(LTM)缩放行为,并将其与仪器温度和降水数据固有的记忆结构进行了比较。使用去趋势波动分析来检测LTM,并使用其缩放指数α来评估LTM。结果表明,基于环宽度测量(均值)的温度和降水重建比基于最大晚木密度(均值)的记录包含更多的内存。在1年到50年的时间范围内,两者都超出了区域仪器数据(温度,降水)固有的存储能力。我们比较了无记忆()伪仪器降水数据与LTM()的伪重建降水数据,并证明了LTM对气候重建的偏见影响。我们呼吁注意基于代理的年代或重构的可变性的统计分析,特别是所包含的(i)趋势,(ii)过去的暖/冷期和湿/干期; (iii)极端事件。

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