使用贝叶斯推断评估光谱太阳辐照度和平流层臭氧之间的关系
Assessing the relationship between spectral solar irradiance and stratospheric ozone using Bayesian inference
摘要：
本文研究了热带平流层上部的光谱太阳辐照度（SSI）与臭氧之间的关系。我们发现，太阳周期（SC）的臭氧变化可以很好地近似考虑臭氧响应SSI的变化在176和310 nm之间的一个小数目的个别波长带，相互独立的操作。此外，我们发现，臭氧的变化近似线性的SSI的变化。利用这些事实，我们提出了一个贝叶斯形式主义推断SC SSI的变化和不确定性测得的SC臭氧剖面。贝叶斯推断是一种强大的、数学上自洽的方法，它考虑了数据的不确定性和额外的外部信息，以提供对被估计参数的最佳估计。使用这种方法，我们表明，在臭氧和SSI数据集的测量不确定性，它是目前不可能区分观测或模拟SSI数据集使用现有的臭氧变化曲线的估计，虽然这可能是可能的，包括其他外部约束。我们的方法有潜力，使用更广泛的数据集，以提供更好地了解SSI和大气响应的变化。
英文摘要：
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 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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