Cloud Droplet Growth in Shallow Cumulus Clouds Considering 1D and 3D Thermal Radiative Effects

Abstract

<p><strong>Abstract.</strong> The effect of 1D and 3D thermal radiation on cloud droplet growth in shallow cumulus clouds is investigated using large eddy simulations with size resolved cloud microphysics. A two step approach is used for separating microphysical effects from dynamical feedbacks. In step one, an offline parcel model with bin resolved microphysics is used where cloud droplets are grown along previously recorded Lagrangian trajectories. It is shown that thermal heating and cooling rates can enhance droplet growth and rain production. Droplets grow to larger size bins in the 10–30 μm radius range. The main effect in terms of rain production arises from recirculating parcels, where a small number of droplets is exposed to strong thermal cooling at cloud edge. These recirculating parcels, comprising about 6–7 % of all parcels investigated, make up 45 % of the accumulated rain rate for the no radiation simulation and up to 60 % when 3D radiative effects are considered. The effect of 3D thermal radiation on rain production is stronger than that of 1D thermal radiation. 3D thermal radiation can enhance the rain rate up to 40 % compared to standard droplet growth without radiative effects in this idealized framework.</p> <p>In the second stage, fully coupled large eddy simulations show that dynamical effects are stronger than microphysical effects, as far as the production of rain is concerned. 3D thermal radiative effects again exceed 1D thermal radiative effects. Small amounts of rain are produced in more clouds (over a larger area of the domain) when thermal radiation is applied to microphysics. The dynamical feedback is shown to be an enhanced cloud circulation with stronger subsiding shells at the cloud edges due to thermal cooling, and stronger updraft velocities in the cloud center. It is shown that an evaporation-circulation feedback reduces the amount of rain produced in simulations where 3D thermal radiation is applied to microphysics and dynamics, in comparison where 3D thermal radiation is only applied to dynamics.</p>

The Radiative Effect on Cloud Microphysics from the Arctic to the Tropics

“…This interaction between REM and clouds is similar to that described in Bott et al (1990). • REM broadens the drop spectrum near the top of small cumulus that in turn helps the rain initiation of small cumulus (Austin et al 1995;Harrington et al 2000;Small and Chuang 2008;Zeng 2018b;Klinger et al 2019).…”

“…REM near cloud top cooperates with drop collection, accelerating the rain initiation in warm clouds (Austin et al 1995). Nevertheless, the effect of REM on rain initiation in an air parcel depends on the residence time of the parcel near cloud top or edge (Harrington et al 2000;Klinger et al 2019), which becomes complicated by involving condensation nuclei and turbulent mixing (Ackerman et al 1995).…”

“…( 5) for its definition]. The ratio was used to classify REM (see section "Three modes of REM"), suggesting that REM be split into three subtopics: 1) microscale study of individual ice crystals and ice crystal spectrum with a given η z (Fuchs 1959;Heymsfield 1973), 2) macroscale study for the spatial and temporal variations of η z (Stephens 1983;Harrington et al 2000;Zeng 2008;Klinger et al 2019), and 3) the interaction between the microscale and macroscale processes (or the interaction between η z and clouds; Bott et al 1990). In reference to the three subtopics, the major studies over the past decades are reviewed in Tables 1 and 2 for ice and warm clouds, respectively, with their clouds studied, methodology used, and conclusions obtained.…”

A Path‐Tracing Monte Carlo Library for 3‐D Radiative Transfer in Highly Resolved Cloudy Atmospheres

“…Although many components of the Earth system interact with radiation, clouds play a key role because of their strong impact (globally cooling the Earth) (Ramanathan et al, 1989), their high frequency of occurrence (Rossow & Dueas, 2004) and their inherent complexity in both space and time (Davis et al, 1994). Radiation and its interactions with clouds are involved in various atmospheric applications at a large range of scales: from the Earth energy balance and cycle relevant to numerical weather predictions (Hogan et al, 2017) and climate studies (Cess et al, 1989;Dufresne & Bony, 2008), to the inhomogeneous heating and cooling rates modifying dynamics and cloud processes at small scales (Klinger et al, 2017(Klinger et al, , 2018, and to the retrieval of atmospheric state and properties from radiative quantities such as photon path statistics, spectrally resolved radiances or polarized reflectances (Cornet et al, 2018), observed by both active and passive remote sensors.…”