the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
How Does Cloud-Radiative Heating over the North Atlantic Change with Grid Spacing, Convective Parameterization, and Microphysics Scheme?
Behrooz Keshtgar
Nicole Albern
Elzina Bala
Christoph Braun
Anubhav Choudhary
Johannes Hörner
Hilke Lentink
Georgios Papavasileiou
Abstract. Cloud-radiative heating (CRH) within the atmosphere and its changes with warming affect the large-scale atmospheric wind patterns in a myriad of ways, such that reliable predictions and projections of circulation require reliable calculations of CRH. In order to assess sensitivities of upper-tropospheric midlatitude CRH to model settings, we perform a series of simulations with the Icosahedral Nonhydrostatic Model (ICON) over the North Atlantic using six different grid spacings, parameterized and explicit convection, and one- versus two-moment cloud microphysics. While sensitivity to grid spacing is limited, CRH profiles change dramatically with microphysics and convection schemes. These dependencies are interpreted via decomposition into cloud classes and examination of cloud properties and cloud-controlling factors within these different classes. We trace the model dependencies back to differences in the mass mixing ratios and number concentrations of cloud ice and snow, as well as vertical velocities. Which frozen species are radiatively active and the coupling of microphysics and convection schemes turn out to be crucial factors in altering the modeled CRH profiles.
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Sylvia Sullivan et al.
Status: open (until 25 Apr 2023)
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RC1: 'Reviewer comment on egusphere-2023-109', Anonymous Referee #1, 22 Feb 2023
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This study explores the sensitivity of model representation of atmospheric cloud radiative heating profiles over the North Atlantic to changes in grid resolution, atmospheric convection (explicit or parameterized), and microphysics scheme within the ICON model. While grid resolution is only found to play a small role, cloud radiative heating profiles are highly sensitive to the model representation of convection and microphysics. In particular, the role of cloud ice mass mixing ratio appears to play a critical role.
This manuscript provides a good discussion of the factors governing atmospheric cloud radiative heating profiles at midlatitudes in the ICON model. Technically, the manuscript is sound and just needs some minor corrections/clarifications (detailed below). However, my general impression in reading this paper is that I’m not sure GMD is really the right journal for this work. The manuscript is using the model output data set from a previous study (Senf et al. 2020) and really not describing fundamentally new methods, rather just extending the authors’ previous work from the tropics to the midlatitudes. I'll leave it to the editor to decide whether GMD is the appropriate venue for this work.
Lines 9-10: Isn’t this point (coupling of microphysics and convection schemes) just a hypothesis provided at the end of the paper (Line 352-360)? If so, it doesn’t belong in the abstract as a statement of certainty. I don’t see any formal evidence presented to support this conjecture.
Lines 23-25: Lu et al. (2007) do not discuss cloud-radiative impacts, and models do not agree on whether the presence of cloud radiative effects drive a poleward circulation shift (see discussion in Voigt et al. 2020 review). For example, Li et al. (2015) do not find a poleward expansion of the circulation due to the presence of cloud radiative effects, and they actually show that cloud-radiative effects decrease the static stability in the tropics.
Line 32: The intensification of ENSO due to cloud radiative effects is again a model dependent result. Middlemas et al. (2019) found a differing effect on ENSO.
Lines 136-137: More detail probably needs to be provided here to explain this conclusion, as the numbers in Table S1 do in fact look quite sensitive to the particular thresholds used.
Lines 146-155: It also seems important to note/discuss here that the altitude of the lower and upper tropospheric cooling peaks differs fairly significantly by model.
Lines 169-170: Also convective heating rates appear to be important in this layer
Lines 172-173: Also, the cooling peak appears to be slightly higher in altitude in the one-moment scheme
Line 180, typo: Change “Then” to “The”
Lines 184-185: Also, a large heating peak develops at lower altitudes, which is not present in the simulations with the deep convective parameterization
Lines 221-227: Good to double check the percentage values quoted in this paragraph. They appear to match what is shown in Fig. S3, not Fig. 7.
Lines 230-232: Can you provide a physical explanation for why the isolated high clouds warm and the deeper clouds cool?
Line 243 (and hereafter): The term “higher grid spacing” could be confusing and could imply coarser resolution to some readers. I would either say “higher resolution” or “finer grid spacing”.
Line 269: It doesn’t look like a factor of four. At best, it looks like a factor of two.
Line 271: The relative increase actually appears stronger in the thin cloud layers.
Lines 317, 325: This citation structure is confusing. Initially, I was looking for Fig. 10a and Table 2 in this paper. Please clarify that this figure and table are in the Sullivan et al. (2022) paper, and not this paper.
Line 328: I think you need to elaborate more on why you choose “supersaturation generated by vertical velocity” as one of your cloud controlling factors. The other two are obvious from the above equations, but this one is less obvious.
Line 384, typo: boundary
Figure 1 caption: North Africa, as well
Code and data availability: available is misspelled.
References:
Li, Y., Thompson, D. W. J., & Bony, S. (2015). The influence of atmospheric cloud radiative effects on the large-scale atmospheric circulation.
Journal of Climate, 8, 7263–7278. https://doi.org/10.1175/JCLI-D-14-00825.1
Middlemas, E. A., Clement, A. C., Medeiros, B., & Kirtman, B. (2019). Cloud radiative feedbacks and El Niño–southern oscillation. Journal
of Climate, 32(15), 4661–4680. https://doi.org/10.1175/JCLI-D-18-0842.1
Citation: https://doi.org/10.5194/egusphere-2023-109-RC1 -
CEC1: 'Comment on egusphere-2023-109', Astrid Kerkweg, 14 Mar 2023
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Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section:
http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been fully met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- "If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model,the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
- "Code must be published on a persistent public archive with a unique identifier for the exact model version described in the paper or uploaded to the supplement, unless this is impossible for reasons beyond the control of authors. All papers must include a section, at the end of the paper, entitled "Code availability". Here, either instructions for obtaining the code, or the reasons why the code is not available should be clearly stated. It is preferred for the code to be uploaded as a supplement or to be made available at a data repository with an associated DOI (digital object identifier) for the exact model version described in the paper. Alternatively, for established models, there may be an existing means of accessing the code through a particular system. In this case, there must exist a means of permanently accessing the precise model version described in the paper. In some cases, authors may prefer to put models on their own website, or to act as a point of contact for obtaining the code. Given the impermanence of websites and email addresses, this is not encouraged, and authors should consider improving the availability with a more permanent arrangement. Making code available through personal websites or via email contact to the authors is not sufficient. After the paper is accepted the model archive should be updated to include a link to the GMD paper."
As your study was performed with ICON please add to the title this additional information (including a version number of ICON); e.g. "How Does Cloud-Radiative Heating over the North Atlantic Change with Grid Spacing, Convective Parameterization, and Microphysics Scheme? A case study with ICON vX.Y"
Additionally, state explicitly in you code availability section that ICON is license bound and thus can only be accessed via DWD (or MPI-M?)
Furthermore, if you did not use an official version but an intermediate version of the ICON model take care that this version is permanently archived (i.e with a DOI, e.g. at zenodo. Zenodo does not automatically mean, that the archive is open to the world. I understand that this is not possible, as long as ICON is not open source).
Last but not least, please put the scripts for reproducing the figures also on a permanent archive (github unfortunately is not permanent).
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/egusphere-2023-109-CEC1 -
RC2: 'Comment on egusphere-2023-109', Anonymous Referee #2, 22 Mar 2023
reply
Sullivan et al. (2023) analyze cloud radiative heating (CRH) in the upper troposphere over the North Atlantic Ocean as simulated by the ICON model. They provide a comprehensive analysis of dependencies on model resolution and ice-cloud microphysics parameterizations. They also attribute model differences to different classes of clouds with different vertical structure and to different cloud-controlling environmental factors, which I found useful for understanding the model differences. The paper is well written and logically organized, and the figures are clear. I have one suggestion for generalizing the results and several minor comments. I recommend that the manuscript be accepted if these minor issues are addressed.
General Comments:
The authors comprehensively discuss CRH in the upper troposphere, but they barely mention CRH in the lower troposphere. However, previous studies have shown that the CRH climatology and relationship of CRH to prominent modes of natural variability both have a peak magnitude in the lower troposphere (Haynes et al., 2013; Papavasileiou et al. 2020; Wall et al., 2022). I realize that the authors want to focus on ice microphysics, for which it makes sense to analyze upper tropospheric CRH. However, I think neglecting lower-tropospheric CRH from the discussion gives the (unintentionally) misleading impression that it is less important for the overall CRH throughout the troposphere. Could the authors add a section that analyzes CRH for the low-level cloud classes and some discussion that compares this analysis with the CRH for the upper-level cloud classes? I think this would generalize the findings and add value to the paper.
Specific Comments:
(1) Fig. 12: It would help to plot all of the panels on the bottom row with the same range of vertical-velocity values.
(2) Fig. 13: Has the vertical velocity data been horizontally averaged to a common scale prior to computing these histograms? If not, then is such a comparison meaningful? I would expect finer horizontal resolution to have larger variance of resolved vertical velocity but perhaps a different treatment of unresolved subgrid-scale vertical velocity by the convective parameterization scheme. It might help to discuss this around line 350.
(3) Line 376 states “Strong microphysical and convective sensitivity and weaker grid spacing sensitivity in the CRH profiles do not appear in distributions of cloud class occurrence and appear only weakly in cloud fraction profiles.” Is this result a consequence of the fact that midlatitude synoptic weather systems are mostly resolved by all resolutions in the study? I’m just wondering if this result is specific to the midlatitudes or if it might generalize to the tropics. It would help to clarify this around line 376.
References:
(1) Haynes, J. M., Vonder Haar, T. H., L’Ecuyer, T., & Henderson, D. (2013). Radiative heating characteristics of Earth’s cloudy atmosphere from vertically resolved active sensors. Geophysical Research Letters, 40(3), 624–630. https://doi.org/10.1002/grl.50145
(2) Papavasileiou, G., Voigt, A., & Knippertz, P. (2020). The role of observed cloud-radiative anomalies for the dynamics of the North Atlantic Oscillation on synoptic time-scales. Quarterly Journal of the Royal Meteorological Society, 146(729), 1822–1841. https://doi.org/10.1002/qj.3768
(3) Wall, C. J., Lutsko, N. J., & Vishny, D. N. (2022). Revisiting cloud radiative heating and the Southern Annular Mode. Geophysical Research Letters, 49, e2022GL100463. https://doi.org/10.1029/2022GL100463
Citation: https://doi.org/10.5194/egusphere-2023-109-RC2
Sylvia Sullivan et al.
Data sets
Model Dependencies of Cloud-Radiative Heating over the North Atlantic [postprocessed dataset] Sylvia Sullivan, Aiko Voigt, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Behrooz Keshtgar, Hilke Lentink, and Georgios Papavasileiou https://doi.org/10.5281/zenodo.7236564
Sylvia Sullivan et al.
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