Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus

Rachel E Hawker,Jonathan M Wilkinson,Benjamin J Murray,Jill S Johnson,Annette K Miltenberger,Paul R Field,Ben J Shipway,Ken S Carslaw,Adrian A Hill

doi:10.5194/acp-21-17315-2021

Abstract

Abstract. Ice crystal formation in the mixed-phase region of deep convective clouds can affect the properties of climatically important convectively generated anvil clouds. Small ice crystals in the mixed-phase cloud region can be formed by heterogeneous ice nucleation by ice-nucleating particles (INPs) and secondary ice production (SIP) by, for example, the Hallett–Mossop process. We quantify the effects of INP number concentration, the temperature dependence of the INP number concentration at mixed-phase temperatures, and the Hallett–Mossop splinter production efficiency on the anvil of an idealised deep convective cloud using a Latin hypercube sampling method, which allows optimal coverage of a multidimensional parameter space, and statistical emulation, which allows us to identify interdependencies between the three uncertain inputs. Our results show that anvil ice crystal number concentration (ICNC) is determined predominately by INP number concentration, with the temperature dependence of ice-nucleating aerosol activity having a secondary role. Conversely, anvil ice crystal size is determined predominately by the temperature dependence of ice-nucleating aerosol activity, with INP number concentration having a secondary role. This is because in our simulations ICNC is predominately controlled by the number concentration of cloud droplets reaching the homogeneous freezing level which is in turn determined by INP number concentrations at low temperatures. Ice crystal size, however, is more strongly affected by the amount of liquid available for riming and the time available for deposition growth which is determined by INP number concentrations at higher temperatures. This work indicates that the amount of ice particle production by the Hallett–Mossop process is determined jointly by the prescribed Hallett–Mossop splinter production efficiency and the temperature dependence of ice-nucleating aerosol activity. In particular, our sampling of the joint parameter space shows that high rates of SIP do not occur unless the INP parameterisation slope (the temperature dependence of the number concentration of particles which nucleate ice) is shallow, regardless of the prescribed Hallett–Mossop splinter production efficiency. A shallow INP parameterisation slope and consequently high ice particle production by the Hallett–Mossop process in our simulations leads to a sharp transition to a cloud with extensive glaciation at warm temperatures, higher cloud updraughts, enhanced vertical mass flux, and condensate divergence at the outflow level, all of which leads to a larger convectively generated anvil comprised of larger ice crystals. This work highlights the importance of quantifying the full spectrum of INP number concentrations across all mixed-phase altitudes and the ways in which INP and SIP interact to control anvil properties.

Highlights

Deep convective clouds are an important component of the global hydrological cycle and radiative budget (e.g. Lohmann et al, 2016; Massie et al, 2002)
We find that both λINP and NINP−38 play a role in determining the anvil cloud properties, with the Hallett–Mossop process ice production efficiency (HM-eff) being relatively unimportant in determining the anvil cloud properties
We find that the interaction of λINP with HM-eff is important for determining the resultant amount of ice particle production by the Hallett– Mossop process, which in turn has large effects on the cloud development

Summary

Introduction

Deep convective clouds are an important component of the global hydrological cycle and radiative budget (e.g. Lohmann et al, 2016; Massie et al, 2002). Accurately representing the spatial and temporal complexity of large convective systems and convectively generated cirrus presents extensive challenges for atmospheric modelling (Prein et al, 2015). Deep convective cloud systems extend vertically from the boundary layer to the tropopause and can have a horizontal radius of over 1000 km. They are dynamic and powerful systems with updraught speeds of up to 50 m s−1 (Frank, 1977; Musil et al, 1986; Xu et al, 2001). Mixed-phase microphysics presents a challenge for cloud modelling because it is critical for deep convective cloud properties and poorly understood (Prein et al, 2015)

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Conclusion