Preprints
https://doi.org/10.5194/amt-2022-141
https://doi.org/10.5194/amt-2022-141
 
09 May 2022
09 May 2022
Status: a revised version of this preprint is currently under review for the journal AMT.

A universally applicable method of calculating confidence bands for ice nucleation spectra derived from droplet freezing experiments

William D. Fahy1,a, Cosma Rohilla Shalizi2,3, and Ryan Christopher Sullivan1,4 William D. Fahy et al.
  • 1Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  • 2Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  • 3Santa Fe Institute, Santa Fe, NM 87501, USA
  • 4Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
  • anow at: Department of Chemistry, University of Toronto, Toronto, ON M5S 3H6, Canada

Abstract. A suite of generally applicable statistical methods based on empirical bootstrapping is presented for calculating uncertainty and testing the significance of quantitative differences in temperature and/or ice active site densities between ice nucleation temperature spectra derived from droplet freezing experiments. Such experiments are widely used to determine the heterogeneous ice nucleation properties and ice nucleation particle concentration spectra of different particle samples, as well as in studies of homogeneous freezing. Our methods avoid most of the assumptions and approximations inherent to existing approaches and if used properly can capture the full range of random variability and error in ice nucleation spectra. Applications include calculation of accurate confidence intervals and confidence bands, quantitative statistical testing of differences between observed freezing spectra, accurate subtraction of the background filtered water freezing signal, and calculation of a range of statistical parameters using data from a single droplet array freezing experiment if necessary. By improving the statistical tools available, this work will improve the quality and accuracy of future ice nucleation research and will allow quantitative comparisons of the ice nucleation ability of different particles and surfaces.

William D. Fahy et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-141', Anonymous Referee #1, 16 Jun 2022
    • AC1: 'Response to Referee 1', Ryan Sullivan, 13 Sep 2022
  • RC2: 'Comment on amt-2022-141', Anonymous Referee #2, 02 Aug 2022
    • AC2: 'Response to Referee 2', Ryan Sullivan, 13 Sep 2022

William D. Fahy et al.

Data sets

Code and data accompanying “A universally applicable method of calculating confidence bands for ice nucleation spectra derived from droplet freezing experiments” William D. Fahy, Ryan C. Sullivan https://doi.org/10.1184/R1/19494188

Model code and software

Code and data accompanying “A universally applicable method of calculating confidence bands for ice nucleation spectra derived from droplet freezing experiments” William D. Fahy, Ryan C. Sullivan https://doi.org/10.1184/R1/19494188

William D. Fahy et al.

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Short summary
Heterogeneous ice nucleation (IN) alters cloud microphysics and climate, and droplet freezing assays are widely used to determine a material's IN ability. Existing statistical procedures require restrictive assumptions that may bias reported results, and there is no rigorous way to compare IN spectra. To improve the accuracy of reported IN data, we present a method for calculating statistics, confidence bands, and testing statistical differences between IN activities in different materials.