The Mass‐Dimensional Properties of Cirrus Clouds During TC4

Abstract

Remote sensing retrievals and ice microphysical parameterizations in global climate models typically use assumptions about the distribution of ice mass as a function of particle size using mass‐dimensional (m‐D) relationships. This study investigates the ice crystal m‐D properties of tropical anvil cirrus during the Tropical Composition, Cloud and Climate Coupling Experiment (TC4) to better document the distribution of ice mass with size in this particular class of tropical ice clouds. Two optimal estimation algorithms (XIWC and MZ) are used to estimate the m‐D relationship for each particle size distribution (PSD) collected in situ. The XIWC algorithm minimizes the difference between measured ice water content (IWC) and PSD calculated IWC, while the MZ algorithm minimizes the difference between measured radar reflectivity factors and those calculated from the in situ PSDs. Results from these algorithms are compared to previous studies to establish consistency of the methodologies. The XIWC results show that both parameters in the m‐D relationship increase with temperature. Changes in m‐D with temperature have substantial implications for remote sensing retrievals. With the prefactor varying by a factor of 5 and the exponent varying by some 16% over a typical range of ice cloud temperatures, forward modeling errors in radar reflectivity could be typically in excess of 5 dB, further suggesting that retrievals of IWC and precipitation rates from radar measurements in ice clouds be in error by factors easily exceeding 3.

A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E

“…Radars at other wavelengths collected data during MC3E. However, attenuation through liquid portions of the cloud (e.g., Bringi et al, 1990;Park et al, 2005;Matrosov, 2008) and non-Rayleigh scattering by larger particles (e.g., Lemke and Quante, 1999;Matrosov, 2007) could not be accounted for and prompted exclusive use of the S-band radar.…”

“…A full list of these m-D coefficients and their corresponding references is available as a supplement. Coefficients derived using data over mountainous terrain (e.g., Nakaya and Terada, 1935;Locatelli and Hobbs, 1974), cirrus clouds (e.g., Heymsfield, 1972;Hogan et al, 2000), convective clouds (e.g., Liu and Curry, 2000;Cazenave et al, 2016;Leroy et al, 2016), regions of large-scale ascent (e.g., Szyrmer and Zawadzki, 2010), and computer-generated shapes (e.g., Matrosov, 2007;Olson et al, 2016) are shown. A total of 119 relations are shown in Fig.…”

“…While previous studies (e.g., McFarquhar et al, 2007b;Heymsfield et al, 2010;Mascio et al, 2017) have considered how m-D relations vary with environmental conditions, such as temperature, the derived relations were fixed regardless of potential fluctuations for that environment. Further uncertainties were associated with measurement errors induced by shattering of large ice crystals on probe tips and subsequent detection within the probe's sample volume (Field et al, 2003), from the processing techniques used (McFarquhar et al, 2017), and from the statistical counting of par-ticles (e.g., Hallett, 2003;McFarquhar et al, 2007a).…”

Retrieval of snowflake microphysical properties from multifrequency radar observations

“…Multifrequency radars have emerged as a potential tool for ice microphysics investigations. It has been recognized for a while that snowflake size can be constrained with collocated measurements at two different frequencies (Matrosov, 1993(Matrosov, , 1998Hogan et al, 2000;Liao et al, 2005). More recently, several studies have shown, using detailed numerical scattering simulations and empirical evidence, that triplefrequency measurements provide information on both the size and density of icy hydrometeors (Kneifel et al, 2011(Kneifel et al, , 2015Leinonen et al, 2012a;Kulie et al, 2014;Stein et al, 2015;Leinonen and Moisseev, 2015;Leinonen and Szyrmer, 2015;Gergely et al, 2017;Yin et al, 2017).…”

Response to Reviewer #1

“…Multifrequency radars have emerged as a potential tool for ice microphysics investigations. It has been recognized for a while that snowflake size can be constrained with collocated measurements at two different frequencies (Matrosov, 1993(Matrosov, , 1998Hogan et al, 2000;Liao et al, 2005). More recently, several studies have shown, using detailed numerical scattering simulations and empirical evidence, that triplefrequency measurements provide information on both the size and density of icy hydrometeors (Kneifel et al, 2011(Kneifel et al, , 2015Leinonen et al, 2012a;Kulie et al, 2014;Stein et al, 2015;Leinonen and Moisseev, 2015;Leinonen and Szyrmer, 2015;Gergely et al, 2017;Yin et al, 2017).…”