| 23 Feb 2026
Assessment of an updated polar stratospheric cloud parameterisation for the UK Earth System Model (UKESM1.1) within the UK Met Office Unified Model (v13.9) using CALIOP and MLS observations
Abstract. Accurately representing polar stratospheric clouds (PSCs) in global Chemistry-Climate Models and Earth System Models is important as they play a key role in springtime ozone depletion in polar regions by activating both chlorine and bromine species through heterogeneous reactions and denitrifying the stratosphere. Here, we present and evaluate an updated PSC parameterisation scheme implemented in the UK Earth System Model (UKESM1.1). The scheme includes the kinetic formation of nitric acid trihydrate (NAT) particles, the formation of supercooled ternary solution (STS) droplets assuming thermodynamic equilibrium, and accounts for ice and sulphate aerosols. To evaluate the new scheme, we compare modelled PSC production with satellite observations from the Cloud-Aerosol and Lidar with Orthogonal Polarization (CALIOP) instrument and model concentrations of gas-phase nitric acid and ozone concentrations with observations from the Aura Microwave Limb Sounder (MLS) instrument for the 2008 Antarctic and 2009/2010 Arctic winters. In comparison with the current, simpler scheme, the updated parameterisation increases both the range of PSC types that form and the seasonal variability, resulting in better agreement with CALIOP observations. It also slows the growth of NAT particles and enables nitric acid partitioning between gas, liquid, and solid phases, leading to improved agreement with MLS observations. However, there is comparatively little impact on stratospheric ozone, with the exception near the edge of the polar vortex where the new scheme improves comparisons with MLS observations.
This paper is well written with thorough citations, documenting all the before-and-after details of the model development, explaining all the methods used for data analysis especially trying to have apple-to-apple comparison with satellite data.
However, the results part still need some attention. The current SAD analysis is not convincing; there’s missing necessary plots and analysis for Arctic and Water vapor. Once these two issures are address, more discussion need to be added in the summary session. I provide several major concerns here for your consideration.
1. Line 317-318: This statement is not correct. NATmix is always the dominant composition category in the CALIPSO Antarctic data (Pitts 2008). From Figure 3, it's hard to know if your new simulation of PSC categories are consistent with what CALIPSO shows for STS and NAT. CALIPSO shows NATmix usually dominant the mid-winter, while the STS dominant the early winter. you should show three panels of absolute values of STS, NAT and ice from RUN_HH. You ice might be ok, maybe a little bit too long into September. Your RUN_HH is not showing early winter SAD (later may to June), which should be dominant by STS. Also why does you simulated PSCs so low in altitude in RUN_HH? The CONTROL has better altitude representation (match the temperature threshold better and more consistent with CALIPSO cloud area). Is it because your background HNO3 is too low? What about your background water vapor? From your SAD plot, I am not convinced your new PSC scheme is better than before.
2. Section 3 misses dehydration comparison with MLS. Also, what about Arctic denitrification and dehydration?
3. Figure 1 and Figure 2: The color bars between the model and CALIPSO are completely different. It's hard to compare. You should not use log scale color bar. If your concern is your total counts are different, at least, you should interpolate your color bar proportional to CALISPO color bar. For example, the cyan color is 700 for CALIPSO, you don't have a cyan color but maybe it is like 20 in your color bar. That's a huge difference.
Other smaller points:
Line 26: There's no such a thing called Tsts. STS grows as the temperature decrease, not suddenly at a certain temperature. You could say 191 K is a typical temperature that HNO3 condenses rapidly in a typcial stratospheric chemical conditions (i.e. HNO3 ~ 10 ppb, H2O~ 5ppm and 50 hpa), but HNO3 still condenses slowly on the particle at higher temperatures based on vapor pressure.
Line 33: Are you talking about H2SO4-H2O sulfate binary? or also other binary?
Line 76: atmospheric variables -> atmospheric gas variables
Figure 1: Zhu et al. 2017a talked about how to adding noise to the model run to have a closer comparison with the CALIPSO data. Adding noise will spread the model results to more categories. You may try that.