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Quantitative Estimates of the Impact of the Most Important Factors on Global Climate Change over the Past 150 Years

机译:过去150年来全球气候变化对全球气候变化影响的影响的定量估计

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We propose using multiple regression to create a statistical model for describing climate change under the influence of specified climate-forming factors. This model provides not only estimates of the temporal evolution of global temperature, but also a set of corresponding confidence intervals with a high level of statistical significance (probability). Eliminating the linear trend of climatic temperature series (CRUTEM) and atmospheric CO2 concentration allows an objective quantitative assessment of the impact of natural factors on climate change. The global CRUTEM temperature responds quasi-synchronously to the fluctuations in the average surface temperature of the North Atlantic (AMO index); however, to changes in solar activity (Wolf numbers), it does so with a delay of approximately 15 years. The linear trend of increasing CO2 concentration in the atmosphere explains almost all the interannual variability and reflects the linear trend of global temperature, but covers only part of its interannual variability.
机译:我们建议使用多元回归来创建统计模型,用于描述规定的气候形成因素的影响下的气候变化。该模型不仅提供了全球温度的时间演变的估计,而且还提供了一组具有高统计显着性(概率)的相应置信区间。消除气候温度系列(Crutem)和大气二氧化碳浓度的线性趋势允许客观定量评估自然因素对气候变化的影响。全球Crutem温度对北大西洋(AMO指数)平均表面温度的波动进行了响应。然而,为了变化太阳能活动(狼号码),它会延迟大约15年。增加大气中CO2浓度的线性趋势几乎解释了所有续际变异性,并反映了全球温度的线性趋势,但仅涵盖其持续可变性的一部分。

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