Effective Radius of Ice Particles in Cirrus and Contrails

Abstract

This paper discusses the ratio C between the volume mean radius and the effective radius of ice particles in cirrus and contrails. The volume mean radius is proportional to the third root of the ratio between ice water content and number of ice particles, and the effective radius measures the ratio between ice particle volume and projected cross-sectional area. For given ice water content and number concentration of ice particles, the optical depth scales linearly with C. Hence, C is an important input parameter for radiative forcing estimates. The ratio C in general depends strongly on the particle size distribution (PSD) and on the particle habits. For constant habits, C can be factored into a PSD and a habit factor. The PSD factor is generally less than one, while the habit factor is larger than one for convex or concave ice particles with random orientation. The value of C may get very small for power-law PSDs with exponent n between 24 and 0, which is often observed. For such PSDs, most of the particle volume is controlled by a few large particles, while most of the cross-sectional area is controlled by the many small particles. A new particle habit mix for contrail cirrus including small droxtal-shape particles is suggested. For measured cirrus and contrails, the dependence of C on volume mean particle radius, ambient humidity, and contrail age is determined. For cirrus, C varies typically between 0.4 and 1.1. In contrails, C 5 0.7 6 0.3, with uncertainty ranges increasing with the volume radius and contrail age. For the small particles in young contrails, the extinction efficiency in the solar range deviates considerably from the geometric optics limit.

Effects of optical depth variability on contrail radiative forcing

“…It causes CRF biases of 10−20% which are of similar magnitude to effects caused by other factors determining the optical response of contrails, e.g. optical depth of low-level clouds or ground albedo, altitude or ice water content of contrails, ice crystal habit, or 3D effects (Meerkötter et al, 1999;Gounou and Hogan, 2007;Yang et al, 2010;Markowicz and Witek, 2011;Schumann et al, 2011). We note that differences in the SW and LW CRF among various optical models-in which ice crystal radiative properties are treated by different methods-have been found to reach 44% and 23%, respectively, relative to the mean model value (Markowicz and Witek, 2011).…”

A contrail cirrus prediction model

“…The computations show ice particle concentrations n decreasing more strongly than N because of dilution from about 0.1 cm −3 to 0.001 cm −3 for 1-h aged contrails, which is roughly consistent with extensive in-situ observations in cirrus (Krämer et al, 2009). For aged contrails, one expects ice particle concentrations similar to ambient cirrus (Gayet et al, 1996;Spinhirne et al, 1998;Schröder et al, 2000;Schumann et al, 2011b).…”

“…Its value C r = 0.9 ± 0.3 depends on the particle shape and size distribution of the ice particles, which are variable, so that this value is uncertain (Schumann et al, 2011b). According to Appendix A11, the local value of τ (y) = f τ (y) τ for given y, as needed for analysis of contrail cover for given optical depth, is a factor…”

Comparing parameterized versus measured microphysical properties of tropical convective cloud bases during the ACRIDICON–CHUVA campaign

“…Its measurement principle is developed based on the FSSP-300 (Baumgardner et al, 1985;Korolev et al, 1985), which has been previously used to study the particle size range in ice clouds (Voigt et al, 2010Schumann et al, 2011;Jeßberger et al, 2013). The intensity of forward-scattered light in the angular range of 4-12 • is detected and sorted into 30 size bins.…”