Preprints
https://doi.org/10.5194/egusphere-2024-3441
https://doi.org/10.5194/egusphere-2024-3441
15 Nov 2024
 | 15 Nov 2024
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

A Novel Method to Quantify the Uncertainty Contribution of Aerosol-Radiative Interaction Factors

Bishuo He and Chunsheng Zhao

Abstract. The IPCC's assessment report shows that the radiative forcing of aerosol-radiation interactions still involves significant uncertainty. The commonly used method for factor uncertainty estimation is the One-at-A-Time (OAT) method which evaluates factor sensitivity by controlling the change in a single variable while keeping others constant. The outcomes from the OAT method require high data quality to ensure accuracy, and the results are only valid near the selected constant. This study proposes a new method called Constrained Parameter (CP) to quantify the uncertainty contribution of factors in a multi-factor system. This method constrains the uncertainty of a single factor and evaluates its sensitivity by analyzing how this change affects output uncertainty. The most significant advantage of the CP method is that it can be applied to any data distribution, and its results can reflect the overall data characteristics. By comparing the results calculated by the CP method and the OAT method, the proportion of factor interactions in the factor uncertainty contributions can be obtained. As an application of the CP method, it is used to perform a detailed analysis of aerosol-radiation interaction factors’ uncertainty contributions. The top 3 most sensitive factors are the complex refractive index of aerosol shell materials, light-absorbing carbon parameters, and Mie theory parameters. Due to their high sensitivity and low observational precision, these factors represent significant sources of uncertainty in aerosol-radiation interactions. These factors need to be prioritized for operational observation programs and model parameter inputs.

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Bishuo He and Chunsheng Zhao

Status: open (until 27 Dec 2024)

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Bishuo He and Chunsheng Zhao
Bishuo He and Chunsheng Zhao

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Short summary
Factor-uncertainty analysis helps us understand their impacts on complex systems. Traditional methods have many limitations. This study introduces a new method to measure how each factor contributes to uncertainty. It gains insights into the role of each variable and works for all multi-factor systems. As an application, we analyzed how aerosols affect solar radiation and identified the key factors. These analyses can improve our understanding of the role of aerosols in climate change.