Constraining mass–diameter relations from hydrometeor images and cloud radar reflectivities in tropical continental and oceanic convective anvils

Abstract

Abstract. In this study the density of ice hydrometeors in tropical clouds is derived from a combined analysis of particle images from 2-D-array probes and associated reflectivities measured with a Doppler cloud radar on the same research aircraft. Usually, the mass-diameter m(D) relationship is formulated as a power law with two unknown coefficients (pre-factor, exponent) that need to be constrained from complementary information on hydrometeors, where absolute ice density measurement methods do not apply. Here, at first an extended theoretical study of numerous hydrometeor shapes simulated in 3-D and arbitrarily projected on a 2-D plan allowed to constrain the exponent βof the m(D) relationship from the exponent σ of the surface-diameter S(D) relationship, which is likewise written as a power law. Since S(D) always can be determined for real data from 2-D optical array probes or other particle imagers, the evolution of the m(D) exponent can be calculated. After that, the pre-factor α of m(D) is constrained from theoretical simulations of the radar reflectivities matching the measured reflectivities along the aircraft trajectory.The study was performed as part of the Megha-Tropiques satellite project, where two types of mesoscale convective systems (MCS) were investigated: (i) above the African continent and (ii) above the Indian Ocean.

Evaluation of radar reflectivity factor simulations of ice crystal populations from in situ observations for the retrieval of condensed water content in tropical mesoscale convective systems

“…This more sophisticated method allows for a more dynamic solution with varying mass-size coefficients related to the variability of microphysics (PSD and aspect ratio of ice crystals). Fontaine et al (2014) end up with the retrieval of an average CWC calculated as a function of time from multiple possible m(D) solutions for the T-matrix simulations of the radar reflectivity factor (Ze) simulations compared to measured Z. The method has been established and published without validation from simultaneous direct measurements of CWC.…”

“…As a matter of fact this would mean that mass-size coefficients are constant and are linked neither to temperature nor to the variability of PSDs or the type of clouds. In Fontaine et al (2014), these simplistic assumptions were not used. This more sophisticated method allows for a more dynamic solution with varying mass-size coefficients related to the variability of microphysics (PSD and aspect ratio of ice crystals).…”

“…The principle of the cloud radar reflectivity simulation method ) is then briefly recalled. The third section is dedicated to the evaluation of the Fontaine et al (2014) method by comparing averaged in retrieved CWCs from the T-matrix simulations with direct measurements of CWC IKP . Moreover, the study suggests correction functions for calculated CWC (based on T-matrix simulations of the reflectivity factors) as a function of tem-perature, largest size of hydrometeors in PSDs, and ice crystal concentrations.…”

“…The objective of our study is to use this comprehensive HAIC/HIWC dataset to evaluate the method presented by Fontaine et al (2014).…”

“…Even though a mass-size relationship for ice crystals with constant coefficients has been utilized, the study of Hogan et al (2011) claimed minimal errors between measured and simulated radar reflectivity factors, even smaller than the calibration uncertainty of the cloud radar. Fontaine et al (2014) also used the oblate spheroid approximation for ice crystals to calculate CWC in mesoscale convective systems (MCS), and Drigeard et al (2015) used the Fontaine et al (2014) results to simulate radar reflectivity factors at 5.5 GHz. Although simulations of radar reflectivity factors agreed with reflectivity observations at 94 and 5.5 GHz, no direct bulk measurements of CWC were available to evaluate the retrieved CWCs.…”