the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Jan 2026
Impacts of Secondary Ice Production on the Microphysics and Dynamics of Deep Convective Clouds in Different Environments
Abstract. This study numerically investigates the impact of secondary ice production (SIP) on cloud microphysical, and diabatic properties in continental and marine deep convective clouds (DCCs). Four cases are simulated using the Icosahedral Nonhydrostatic (ICON) model with a 2-moment cloud microphysics scheme at 2 km horizontal grid spacing. ICON forms secondary ice via rime splintering, fragmentation during raindrop freezing (RDF), ice-ice collision, and sublimational breakup. A more detailed RDF scheme is implemented and compared to the existing simpler scheme. Both schemes predict similar overall properties in the simulated DCCs, suggesting that a simpler scheme can represent RDF in numerical models.
In the simulated DCCs, SIP processes accurately reproduce observed ice number concentrations. SIP enhances ice numbers by 10–103, decreasing (increasing) supercooled-liquid (ice) mass by 10–30 %, leading to sustained upper-level glaciation and prolonged convective activity. Including SIP increases surface precipitation by 4 % in marine DCCs, with no significant change in continental DCCs. SIP enhance longwave absorption in the mixed-phase region and increased (20 % in continental and 40 % in marine DCCs) cloud radiative heating. SIP intensifies latent heating by up to 20 %, reaching 20–40 K d−1 in continental and 80 K d−1 in marine DCCs, from increased depositional growth of ice particles. This enhanced diabatic heating increases buoyancy, leading to a 10 % rise in mean vertical velocity, strengthening convection. These findings highlight the pivotal role of SIP in shaping the microphysical structure and dynamical behavior of deep convection, highlighting the need for its representation in numerical models.
- Preprint
(23196 KB) - Metadata XML
-
Supplement
(3982 KB) - BibTeX
- EndNote
Status: open (until 03 Mar 2026)
- RC1: 'Comment on egusphere-2025-6129', Anonymous Referee #1, 12 Feb 2026 reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 182 | 154 | 18 | 354 | 34 | 17 | 24 |
- HTML: 182
- PDF: 154
- XML: 18
- Total: 354
- Supplement: 34
- BibTeX: 17
- EndNote: 24
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review of the manuscript titled: Impacts of Secondary Ice Production on the Microphysics and Dynamics of Deep Convective Clouds in Different Environments, by Waman et al.
This study investigates the impact of incorporating four SIP processes, rime splintering (Hallett–Mossop process, HM), fragmentation during raindrop freezing (RDF), ice–ice collision breakup (IIC), and sublimational breakup (SBF), into NWP simulations using the ICON model with an advanced two-moment microphysical scheme. Four case studies were selected, including three continental and one maritime DCC events.
Comparisons with in situ and satellite observations indicate that the inclusion of SIP processes generally improves the simulation results. Further analysis shows that, relative to simulations without SIP, the inclusion of SIP reduces supercooled liquid water, increases IWC and INC, and enhances both total latent heating and net cloud radiative heating in the mixed-phase region. An increase in cloud-top height is also found. The impact on precipitation is limited for the continental cases, while a positive (increasing) effect is found for the maritime case. Two parameterizations of the RDF process were tested and produced fairly similar results. The influence of the SBF process is found to be negligible.
Overall, the findings provide a valuable contribution to the understanding of SIP in deep convective systems. The manuscript is clearly written and the results are well presented. I offer several suggestions below to further strengthen the study.
General:
ORCESTRA case: there should be remote sensing data available from this campaign (e.g., airborne radar reflectivity). It would significantly strengthen the study if these campaign observations could be incorporated into the analysis. Otherwise, the rationale for selecting this specific case is not entirely clear, as in principle any case with an EarthCARE overpass could have been chosen. Please clarify the scientific motivation for focusing on the ORCESTRA event. In addition, the manuscript states that the CPR reflectivity appears to be biased low. This claim could potentially be evaluated by comparison with available airborne radar reflectivity measurements. Such a comparison would provide stronger support for this conclusion.
CAIPEEX case: the exclusion of ice particles with size smaller than 400 µm will have a non-negligible impact on the estimated INC. This needs to be clearly addressed. For example, in the comparison between in situ and simulated INC, a fraction of the simulated INC should be excluded with the same size distributions that the microphysical scheme is used.
The choice of 1 m/s in the analysis needs to be justified. 1 m/s might be relatively low to isolate the convective updrafts and will probably include more areas affected by wave structures within clouds.
Technical:
L121-122: repeated phrase to be deleted.
L123: How many flights were conducted during this campaign? Why choose this specific one? Any other DCCs? Similar for the other three campaigns.
Fig 1a: It will be better if the surface elevation, boarder, etc. could be added in panel (a). Similar for the other three figures.
Fig 2c: would it be better to show 2D-S images with higher resolution instead of CIP for this case? Please use the same color map among all the three OAP images. The legend is missing for the panel c as well (same for Fig. 3).
L186: be careful, EarthCARE is not a radiation budget mission, although it conducts radiative closure assessment. I would suggest: …to study the relationship of cloud, aerosol and radiation.
L210: how is CCN simulated in ICON?
L263: Why the rime fraction is set to 0.4 (for 'snow', I assume)? In Philips et al. 2017, the rime fraction is a variable. This could introduce an uncertainty for the simulation. Should different rime fractions be tested first?
L319: the cloud top can’t be seen in Fig. 6e, f.
L319-320: The observed radar reflectivity stayed relatively stable above 5 km. To me the two panels (e, f) are very different, especially for the altitude above the melting layer. It's also better to include a T profile so that we can easily identify the correspondence of T vs. altitude in panel e and f.
L327: “simulated IWC four orders of magnitude higher”. I believe it’s 1 to 2 orders of magnitude instead of 4?
L329: INC differs by about 4 orders of magnitude rather than 1?
L343-346: Interestingly that the simulated Z is much higher than the observation, although the pattern looks similar. Any thoughts on the difference? I believe it’s important to clarify this difference.
Fig 8c: At some altitudes, there are two distribution bars from HVPS-3. The altitudes might be wrong for one of the two.
L352: Which EarthCARE product is used here? C-CLD? The product baseline (version) should also be included for reference. This is important as the products are evolving constantly.
L363: same as above but for radar reflectivity.
L368-369: “This is chiefly because at higher spatial resolution (1.6 km),”. This is not true; CPR product is at ~1 km resolution. To confirm the attenuation of radar signal, it’s better to show the quality flag of the CPR products. The 1 m/s threshold should include a lot of regions of mild convection or just regions affected by gravity waves.
L376: “In summary, ICON adequately reproduces…” might be an overstatement. It is clear though that with SIP, the simulation results improved.
L386: RDF represent 1% of the SIP: this depends on which parameterization is used. Lawson et al. will produce higher amounts. Note that those results are based on proposed parameterizations, not the 'truth'. Therefore, the statement should be nuanced.
Fig 13: the x-label of time is misleading: it says a given day (UTC), but the time in the x-axis spans through different days (12 UTC to 12 UTC of the next day).
L184-186: It looks like for the first two continental DCCs, excluding SIP increase latent heating during the early growth phase (blue in c & f), opposite to what was stated here?
L513: “which weakens CRH through reduced (to up to 20%) depositional growth of ice particles” to “which weakens CRH through radiative effect of reduced (to up to 20%) depositional growth of ice particles”?