Abstract

In this study, which is the third part of the HaloCam series after Forster et al. (2017) and Forster et al. (2020), we present a novel technique to retrieve quantitative information about ice crystal optical and microphysical properties making use of ground-based imaging observations of halo displays. Comparing HaloCam’s calibrated RGB images of 22° and 46° halo observations against a look-up table of simulated radiances, this technique allows the retrieval of size and shape of randomly oriented crystals as well as the fraction of smooth and rough ice crystals for cirrus clouds. We analyzed 4400 HaloCam images between September 2015 and November 2016 showing a visible 22° halo. The optical properties of hexagonal 8-element columns with a mean ice crystal effective radius of about 20 μm and a mixture of 37 % smooth and 63 % rough crystals on average best match the HaloCam observations. Implemented on different sites, HaloCam in combination with the machine-learning based halo detection algorithm HaloForest can provide a consistent dataset for climatological studies of ice crystal properties representing typical cirrus clouds. Representative ice crystal optical properties are required for remote sensing of cirrus clouds as well as climate modeling. Since ground-based passive imaging observations provide information about the forward scattering part of the ice crystal optical properties, the results of this work ideally complement the results of satellite-based and airborne studies.

Highlights

  • 15 Cirrus clouds cover about one third of the globe on average (Wylie and Menzel, 1999; Stubenrauch et al, 2006) and consist of small ice crystals

  • We present a novel imaging remote sensing method to retrieve ice crystal optical and microphysical properties, with a special focus on ice crystal roughness and shape

  • Using calibrated RGB images of the automated sun-tracking camera system HaloCam, we exploit the scattering features of the 22 and 46◦ halo which are formed by randomly oriented hexagonal ice crystals

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Summary

Introduction

15 Cirrus clouds cover about one third of the globe on average (Wylie and Menzel, 1999; Stubenrauch et al, 2006) and consist of small ice crystals. Shape, and surface roughness predominantly govern the single scattering properties and the radiative forcing of cirrus clouds (e.g. Liou, 1986; Wielicki et al, 1995; Wendisch et al, 2007; Yi et al, 2013). We investigate a new method to retrieve ice crystal shape and surface roughness from calibrated camera observations of halo displays using HaloCam (Forster et al, 2020). Quantitative analysis of the frequency of occurrence as well as the brightness contrast of halo displays can help determine ice crystal shape, 10 surface roughness and orientation in cirrus clouds. In this study we present a novel method to retrieve ice crystal shape and surface roughness in cirrus clouds using groundbased imaging observations of the 22 and 46◦ halo scattering angle region.

Retrieval of ice crystal properties
Ice crystal shape and roughness models
HaloCam observations and ancillary data
Using information of the 22◦ halo
Adding information about the 46◦ halo
Discussion
Ice crystal shape
Ice crystal roughness
10 5 Summary and Conclusions
Ancillary data
Aerosol optical thickness
Cirrus optical thickness
Findings
Surface albedo
15 Acknowledgements

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