Abstract
Aerosol–fog interactions affect the visibility in, and life cycle of, fog and are difficult to represent in weather and climate models. Here we explore processes that impact the simulation of fog droplet number concentrations (Nd) at sub-kilometer scale horizontal grid resolutions in the UK Met Office Unified Model. We modify the parameterization of aerosol activation to include droplet activation by radiative cooling in addition to adiabatic cooling and determine the relative importance of the two cooling mechanisms. We further test the sensitivity of simulated Nd to: (a) interception of droplets by trees and buildings, (b) overestimation of updrafts in temperature inversions (which leads to artificially high Nd values), and (c) potential mechanisms for droplet deactivation due to downward fluctuations in supersaturation. We evaluate our model against observations from the ParisFog and LANFEX field campaigns, building on evaluation described in the companion paper. Including radiative cooling in the activation mechanism improves how accurately we represent the liquid water path and the vertical structure of the fog in our LANFEX case study. However, with radiative cooling, the Nd are overestimated for most of the ParisFog cases and for the LANFEX case. The time-averaged overestimate exceeds a factor of three (the normalized mean bias factor exceeds 2.0) in 4 out of 11 ParisFog cases. Our sensitivity studies demonstrate how these overestimates can be mitigated. Assuming the overestimate affects both radiative and adiabatic cooling, we find that although radiative cooling is more often the dominant source, both cooling sources can sometimes dominate activation.
| Original language | English |
|---|---|
| Pages (from-to) | 11157-11182 |
| Number of pages | 26 |
| Journal | Atmospheric Chemistry and Physics |
| Volume | 25 |
| Issue number | 18 |
| DOIs | |
| State | Published - Sep 24 2025 |
Funding
We thank the scientists responsible for the ParisFog and the LANFEX field campaigns. Model simulations are material produced using Met Office software. The computational resources on Air Force Weather HPC11 are provided by the Oak Ridge Leadership Computing Facility (OLCF) Director's Discretion Project NWP501 and ATM112. The OLCF at Oak Ridge National Laboratory (ORNL) is supported by the Office of Science of the US Department of Energy under contract no. DE-AC05-00OR22725. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation Grant ACI-1548562. Specifically, it used the Bridges-2 system, which is supported by the NSF Award ACI-1928147, at the Pittsburgh Supercomputing Center (PSC). This work also used Bridges-2 at the PSC through allocation atm200005p from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. This research was supported by the US Air Force Life Cycle Management Center (LCMC) collaboration with Oak Ridge National Laboratory (ORNL). We thank the scientists responsible for the ParisFog and the LANFEX field campaigns. Model simulations are material produced using Met Office software. The computational resources on Air Force Weather HPC11 are provided by the Oak Ridge Leadership Computing Facility (OLCF) Director’s Discretion Project NWP501 and ATM112. The OLCF at Oak Ridge National Laboratory (ORNL) is supported by the Office of Science of the US Department of Energy under contract no. DE-AC05-00OR22725. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation Grant ACI-1548562. Specifically, it used the Bridges-2 system, which is supported by the NSF Award ACI-1928147, at the Pittsburgh Supercomputing Center (PSC). This work also used Bridges-2 at the PSC through allocation atm200005p from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.