Assessing the relationship between spectral solar irradiance and stratospheric ozone using Bayesian inference

Assessing the relationship between spectral solar irradiance and stratospheric ozone using Bayesian inference
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使用贝叶斯推理评估太阳光谱辐照度与平流层臭氧之间的关系

DOI:
10.1051/swsc/2014023
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发表时间:
2014
影响因子:
3.3
通讯作者:
Ball W
Ball W
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Ball W

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我们研究了热带平流层上层太阳光谱辐照度(SSI)与臭氧之间的关系。我们发现,通过考虑臭氧对 176 至 310 nm 之间少数单独波段(彼此独立运行)中 SSI 变化的响应,可以很好地近似臭氧的太阳周期 (SC) 变化。此外,我们发现臭氧随着 SSI 的变化近似线性变化。利用这些事实,我们提出了一种贝叶斯形式,用于从测量的 SC 臭氧剖面推断 SC SSI 变化和不确定性。贝叶斯推理是一种强大的、数学上自洽的方法,它考虑数据的不确定性和附加外部信息,以提供所估计参数的最佳估计。使用这种方法,我们表明,考虑到臭氧和 SSI 数据集的测量不确定性,目前不可能使用臭氧变化剖面的可用估计来区分观察到的或建模的 SSI 数据集,尽管通过包含其他外部约束这可能是可能的。我们的方法有潜力利用更广泛的数据集,更好地理解 SSI 和大气响应的变化。
We investigate the relationship between spectral solar irradiance (SSI) and ozone in the tropical upper stratosphere. We find that solar cycle (SC) changes in ozone can be well approximated by considering the ozone response to SSI changes in a small number of individual wavelength bands between 176 and 310 nm, operating independently of each other. Additionally, we find that the ozone varies approximately linearly with changes in the SSI. Using these facts, we present a Bayesian formalism for inferring SC SSI changes and uncertainties from measured SC ozone profiles. Bayesian inference is a powerful, mathematically self-consistent method of considering both the uncertainties of the data and additional external information to provide the best estimate of parameters being estimated. Using this method, we show that, given measurement uncertainties in both ozone and SSI datasets, it is not currently possible to distinguish between observed or modelled SSI datasets using available estimates of ozone change profiles, although this might be possible by the inclusion of other external constraints. Our methodology has the potential, using wider datasets, to provide better understanding of both variations in SSI and the atmospheric response.
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