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Refractive index confidence explorer (RICE): A tool for propagating uncertainties through complex refractive index retrievals from aerosol particles.

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Title: Refractive index confidence explorer (RICE): A tool for propagating uncertainties through complex refractive index retrievals from aerosol particles.
Authors: Frie, Alexander L.1 (AUTHOR), Bahreini, Roya1 (AUTHOR)
Source: Aerosol Science & Technology. Jun2021, Vol. 55 Issue 6, p703-717. 15p.
Subjects: Microsoft Internet explorer (Computer software), Refractive index, Atmospheric aerosols, Optical measurements, Aerosols, Uncertainty, Mie scattering, Radioactive aerosols, Carbonaceous aerosols
Abstract: Accurate and precise retrievals of aerosol complex refractive indices (m) are essential to constraining the direct radiative effect of atmospheric aerosols. Despite this, there is no generally accepted method for constraining the uncertainty in full-distribution aerosol complex refractive index retrievals. This is in part due to condition-dependent and solution-dependent uncertainties which propagate through retrievals. Here, the Refractive Index Confidence Explorer (RICE), a program written in WaveMetrics Igor Pro, is presented. RICE applies a Monte Carlo-like method to propagate uncertainties through a full size distribution inverse Mie method (FD-IMM) for m retrievals. The m retrieval and RICE uncertainty analysis use absorption coefficients, scattering coefficients, aerosol size distributions, and measurement uncertainties as inputs. RICE iteratively tests a series of m values for their ability to produce the retrieved m under perturbed conditions. Perturbations account for uncertainties in optical, particle size, and particle number concentration measurements. RICE then uses these data to calculate semi-empirical probability distributions which are used to provide confidence intervals for the real (n) and imaginary (k) components of m. RICE provides measurement by measurement uncertainty estimations enabling estimation of uncertainty even when conditions are highly dynamic, like those associated with field measurements. When RICE is applied to idealized test cases and external data, uncertainty is shown to be dynamic in relation to the value of the retrieved m (solution) and the nature of the particle size distribution (measurement condition). Within these cases, m uncertainties were shown to be large for the upper end of n and k values explored here (i.e., n = 1.8 and k = 0.5, at 375 nm) under uncertainty conditions typical of modern particle and optical measurement technologies, suggesting FD-IMM's usefulness may be limited by instrumental uncertainties under some measurement conditions. However, FD-IMM retrievals may still provide reasonable estimates of m when n <∼1.6 and k < 0.1. Copyright © 2021 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]
Copyright of Aerosol Science & Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Accurate and precise retrievals of aerosol complex refractive indices (m) are essential to constraining the direct radiative effect of atmospheric aerosols. Despite this, there is no generally accepted method for constraining the uncertainty in full-distribution aerosol complex refractive index retrievals. This is in part due to condition-dependent and solution-dependent uncertainties which propagate through retrievals. Here, the Refractive Index Confidence Explorer (RICE), a program written in WaveMetrics Igor Pro, is presented. RICE applies a Monte Carlo-like method to propagate uncertainties through a full size distribution inverse Mie method (FD-IMM) for m retrievals. The m retrieval and RICE uncertainty analysis use absorption coefficients, scattering coefficients, aerosol size distributions, and measurement uncertainties as inputs. RICE iteratively tests a series of m values for their ability to produce the retrieved m under perturbed conditions. Perturbations account for uncertainties in optical, particle size, and particle number concentration measurements. RICE then uses these data to calculate semi-empirical probability distributions which are used to provide confidence intervals for the real (n) and imaginary (k) components of m. RICE provides measurement by measurement uncertainty estimations enabling estimation of uncertainty even when conditions are highly dynamic, like those associated with field measurements. When RICE is applied to idealized test cases and external data, uncertainty is shown to be dynamic in relation to the value of the retrieved m (solution) and the nature of the particle size distribution (measurement condition). Within these cases, m uncertainties were shown to be large for the upper end of n and k values explored here (i.e., n = 1.8 and k = 0.5, at 375 nm) under uncertainty conditions typical of modern particle and optical measurement technologies, suggesting FD-IMM&#39;s usefulness may be limited by instrumental uncertainties under some measurement conditions. However, FD-IMM retrievals may still provide reasonable estimates of m when n &lt;∼1.6 and k &lt; 0.1. Copyright &#169; 2021 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: &lt;i&gt;Copyright of Aerosol Science &amp; Technology is the property of Taylor &amp; Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/02786826.2021.1895428
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 703
    Subjects:
      – SubjectFull: Microsoft Internet explorer (Computer software)
        Type: general
      – SubjectFull: Refractive index
        Type: general
      – SubjectFull: Atmospheric aerosols
        Type: general
      – SubjectFull: Optical measurements
        Type: general
      – SubjectFull: Aerosols
        Type: general
      – SubjectFull: Uncertainty
        Type: general
      – SubjectFull: Mie scattering
        Type: general
      – SubjectFull: Radioactive aerosols
        Type: general
      – SubjectFull: Carbonaceous aerosols
        Type: general
    Titles:
      – TitleFull: Refractive index confidence explorer (RICE): A tool for propagating uncertainties through complex refractive index retrievals from aerosol particles.
        Type: main
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            NameFull: Frie, Alexander L.
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            NameFull: Bahreini, Roya
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          Dates:
            – D: 01
              M: 06
              Text: Jun2021
              Type: published
              Y: 2021
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              Value: 02786826
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              Value: 55
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              Value: 6
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            – TitleFull: Aerosol Science & Technology
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