Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

Abstract

Abstract. Aerosol-aware microphysics parameterisation schemes are increasingly being introduced into numerical weather prediction models, allowing for regional and case-specific parameterisation of cloud condensation nuclei (CCN) and cloud droplet interactions. In this paper, the Thompson aerosol-aware microphysics scheme, within the Weather Research and Forecasting (WRF) model, is used for two fog cases during September 2017 over Namibia. Measurements of CCN and fog microphysics were undertaken during the AErosols, RadiatiOn and CLOuds in southern Africa (AEROCLO-sA) field campaign at Henties Bay on the coast of Namibia during September 2017. A key concept of the microphysics scheme is the conversion of water-friendly aerosols to cloud droplets (hereafter referred to as CCN activation), which could be estimated from the observations. A fog monitor 100 (FM-100) provided cloud droplet size distribution, number concentration (Nt), liquid water content (LWC), and mean volumetric diameter (MVD). These measurements are used to evaluate and parameterise WRF model simulations of Nt, LWC, and MVD. A sensitivity analysis was conducted through variations to the initial CCN concentration, CCN radius, and the minimum updraft speed, which are important factors that influence droplet activation in the microphysics scheme of the model. The first model scenario made use of the default settings with a constant initial CCN number concentration of 300 cm−3 and underestimated the cloud droplet number concentration, while the LWC was in good agreement with the observations. This resulted in droplet size being larger than the observations. Another scenario used modelled data as CCN initial conditions, which were an order of magnitude higher than other scenarios. However, these provided the most realistic values of Nt, LWC, MVD, and droplet size distribution. From this, it was concluded that CCN activation of around 10 % in the simulations is too low, while the observed appears to be higher reaching between 20 % and 80 %, with a mean (median) of 0.55 (0.56) during fog events. To achieve this level of activation in the model, the minimum updraft speed for CCN activation was increased from 0.01 to 0.1 m s−1. This scenario provided Nt, LWC, MVD, and droplet size distribution in the range of the observations, with the added benefit of a realistic initial CCN concentration. These results demonstrate the benefits of a dynamic aerosol-aware scheme when parameterised with observations.

Numerical prediction of fog: A novel parameterization for droplet formation

“…In the case of fog formation when the real updraft velocity is negligible, it is assumed that the updraft is 0.01 m·s −1 . Numerical experiments performed by Weston et al (2022) revealed that increasing the minimum updraft velocity from 0.01 to 0.1 m·s −1 corresponds better to the observation data. Zhang and Musson‐Genon et al (2014) suggested evaluating aerosol activation by taking radiative cooling into account.…”

“…They found that the TE14 gave the best result for the case investigated. Weston et al (2022) studied how WRF with TE14 simulated the evolution of fog on the coastal area of Namibia. They asserted that the numerical simulation significantly underestimated the number concentration of the activated aerosol particles.…”

Interactions between trade-wind clouds and local forcings over the Great Barrier Reef: A case study using convection-permitting simulations

“…to have promising skill in representing both supercooled and warm liquid conditions of grid-scale clouds (Weston et al, 2022;Wilkinson et al, 2013).…”