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A mathematical model of atmospheric retention of man-made CO_2 emissions

机译:人为CO_2排放在大气中保留的数学模型

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Rust and Thijsse have previously shown that changes in global annual average temperature anomalies T(ti) compiled by the Climatic Research Unit vary linearly with atmospheric CO_2 concentrations c(ti). The c(ti) can be related to man-made CO_2 emissions F(ti) by a linear regression model whose solution vector gives the unknown retention fractions γ(ti) of the F(ti) in the atmosphere. Gaps in the c(ti) record make the system underdetermined, but the constraints 0 ≤ γ(ti) ≤ 1 make estimation tractable. The γ(ti) are estimated by two methods: (1) assuming a finite harmonic expansion for γ(t), and (2) using a constrained least squares algorithm to compute average values of γ{t) on suitably chosen time subintervals. The final result is an estimate of γ(t) with enough accuracy to establish the connection between emissions from fossil fuel use and land use changes and increases in global average annual temperature anomalies.
机译:Rust和Thijsse之前已经表明,由气候研究部门编制的全球年平均温度距平T(ti)的变化随大气CO_2浓度c(ti)线性变化。可通过线性回归模型将c(ti)与人为CO_2排放量F(ti)相关,该线性回归模型的解矢量给出了F(ti)在大气中的未知保留分数γ(ti)。 c(ti)记录中的间隙使系统不确定,但是约束0≤γ(ti)≤1使估算变得容易。可以通过两种方法估算γ(ti):( 1)假设γ(t)具有有限的谐波展开,以及(2)使用约束最小二乘算法在适当选择的时间子间隔上计算γ{t)的平均值。最终结果是对γ(t)的估计,其准确性足以建立化石燃料使用排放与土地使用变化以及全球平均年温度异常升高之间的联系。

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