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Deriving stratospheric age of air spectra using an idealized set of chemically active trace gases

机译:使用一组理想的化学活性痕量气体推算空气的平流层年龄

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Analysis of stratospheric transport from an observational point of view is frequently realized by evaluation of the mean age of air values from long-lived trace gases. However, this provides more insight into general transport strength and less into its mechanism. Deriving complete transit time distributions (age spectra) is desirable, but their deduction from direct measurements is difficult. It is so far primarily based on model work. This paper introduces a modified version of an inverse method to infer age spectra from mixing ratios of short-lived trace gases and investigates its basic principle in an idealized model simulation. For a full description of transport seasonality the method includes an imposed seasonal cycle to gain multimodal spectra. An ECHAM/MESSy Atmospheric Chemistry (EMAC) model simulation is utilized for a general proof of concept of the method and features an idealized dataset of 40 radioactive trace gases with different chemical lifetimes as well as 40 chemically inert pulsed trace gases to calculate pulse age spectra. It is assessed whether the modified inverse method in combination with the seasonal cycle can provide matching age spectra when chemistry is well-known. Annual and seasonal mean inverse spectra are compared to pulse spectra including first and second moments as well as the ratio between them to assess the performance on these timescales. Results indicate that the modified inverse age spectra match the annual and seasonal pulse age spectra well on global scale beyond 1.5 years of mean age of air. The imposed seasonal cycle emerges as a reliable tool to include transport seasonality in the age spectra. Below 1.5 years of mean age of air, tropospheric influence intensifies and breaks the assumption of single entry through the tropical tropopause, leading to inaccurate spectra, in particular in the Northern Hemisphere. The imposed seasonal cycle wrongly prescribes seasonal entry in this lower region and does not lead to a better agreement between inverse and pulse age spectra without further improvement. Tests with a focus on future application to observational data imply that subsets of trace gases with 5 to 10?species are sufficient for deriving well-matching age spectra. These subsets can also compensate for an average uncertainty of up to ±20 % in the knowledge of chemical lifetime if a deviation of circa ±10 % in modal age and amplitude of the resulting spectra is tolerated.
机译:从观测的角度对平流层运移进行分析通常是通过评估长寿命痕量气体的平均空气年龄来实现的。但是,这提供了对一般运输强度的更多了解,而对它的机理的了解较少。需要获得完整的渡越时间分布(年龄谱),但是很难从直接测量中推导它们。到目前为止,它主要基于模型工作。本文介绍了一种反演方法的改进版本,可以从短期痕量气体的混合比推断年龄谱,并在理想的模型仿真中研究其基本原理。对于运输季节性的完整描述,该方法包括一个施加的季节性周期以获取多峰频谱。 ECHAM / MESSy大气化学(EMAC)模型模拟​​被用作该方法概念的一般证明,并具有理想化的数据集,其中包含40种具有不同化学寿命的放射性痕量气体以及40种化学惰性脉冲痕量气体以计算脉冲寿命谱。当化学方法众所周知时,评估改进的逆方法与季节性周期的组合是否可以提供匹配的年龄谱。将年度和季节平均逆频谱与包括第一时刻和第二时刻以及它们之间的比率的脉冲频谱进行比较,以评估这些时标上的性能。结果表明,修改后的逆年龄谱与全球平均年龄超过1.5年的全球尺度上的年度和季节性脉冲年龄谱非常匹配。施加的季节性周期成为将运输季节性包括在年龄谱中的可靠工具。在平均空气年龄不到1.5年时,对流层影响加剧并打破了通过热带对流层顶单次进入的假设,导致光谱不准确,特别是在北半球。强加的季节周期错误地规定了在该较低区域的季节进入,并且在没有进一步改进的情况下不会导致逆向和脉动年龄谱之间更好的一致性。着眼于未来在观测数据上的应用的测试表明,具有5至10种物种的痕量气体的子集足以推导年龄匹配的光谱。如果允许模态寿命和所得光谱幅度的偏差约为±10%,那么根据化学寿命,这些子集还可以补偿高达±20%的平均不确定度。

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