A new lightning scheme in Canada's Atmospheric Model, CanAM5.1: Implementation, evaluation, and projections of lightning and fire in future climates

General comments:

There were no lightning schemes (no lightning calculated) in Canda's Earth System Model 5.1 before this study, which introduced a lightning scheme into CanESM5.1. The Etten-Bohm scheme is based on a logistic relation between lightning occurrence and multiple environmental variables (CAPE, LCL, r), which is unique among existing lightning schemes. The Etten-Bohm scheme is expected to show a relatively acceptable performance in CanESM, but unfortunately, due to the large biases in CAPE, LCL, and r simulations in CanESM, the lightning simulation accuracy cannot be considered satisfactory. I am not sure about the statistical metrics such as R and RMSE (root mean squared error) values between lightning simulations and observations in this study, but previous studies achieved better lightning prediction accuracy in their models (Finney et al., 2014; Lopez, 2016; He et al., 2022).

Is this paper valuable for publication? Yes, this is the first time the authors introduced a new lightning scheme to CanESM. However, I considered the following aspects that may improve the scientific significance of this paper:

1. If possible, try to implement more existing lightning schemes (as you listed in L35-L45) into CanAm5.1 and compare those lightning schemes with the Etten-Bohm scheme. The benefit of doing so is that you can evaluate how different lightning schemes influence the prediction accuracy to what degree. By comparing several different lightning schemes in a New ESM, you can provide more information for the scientific community. I also recommend that you consider the uncertainties that existed in observations when evaluating lightning schemes (you can refer to (He et al., 2022) Figure 4). Even you can use a second ESM (such as CESM) to provide additional supporting information (for example, if CESM can better represent CAPE, LCL, how these improvements can influence the prediction accuracy of lightning).
2. I am not sure whether if you applied meteorological nudging (u, v, T) in your simulations, by the way, you need a detailed experiment setup in your paper (use a chart). You can evaluate how meteorological nudging influences the prediction accuracy of lightning in the Etten-Bohm scheme by turning on/off nudging. For example, if meteorological nudging can significantly improve the simulation accuracy of CAPE et al. as well as lightning, this can prove that improving the simulation of CAPE et al. in CanESM can definitely lead to the improvement of lightning simulations (and the extent of this improvement to which degree).
3. What caused the large biases in CAPE, LCL, r? → Please provide some explanations in your paper. You mentioned you will use a new TKE deep convection scheme, if possible, please test this new convection scheme and estimate how it impacts the simulations of lightning and burned area.
4. You conducted future projections; however, I recommend that you can firstly evaluate the response of global lightning activities to short-term surface warming (1993-2013) of Etten-Bohm scheme in CanESM. Evidence shows that there was no statistically significant trend in global lightning activities during 1993-2013 (LIS/OTD, (Williams, 1992)).
5. You predicted a decreasing lightning trend with global warming (Table2), what is the reason (CAPE, LCL, r decreased?)? He and Sudo (2023) suggested that historical global warming enhanced lightning activities, but increases in aerosol burden exerted an opposite effect (1960-2014). Can you also separate the effects of warming and aerosols?
6. "Control lightning" vs. "interactive lightning", what is the implication? The simulated lightning trends can largely impact the simulated burned area, but this is not a new finding.

Anyway, please try to improve the scientific significance.

Specific comments:

1. Please show statistical metrics (R, RMSE, MBE) between simulations and observations.
2. He et al. (2022) recently developed a new lightning scheme based on Lopez (2016) and McCaul et al. (2009). This paper can provide additional information for your paper's introduction (L32, L35-L45, L48-49).
3. L104, Uman (1986) only mentioned a blurry concept, could you please provide the detailed equations (to calculate the fraction) and relevant explanations. Another widely used equation for calculating cloud-to-ground fraction was proposed by Princ and Rind 1993. I am not sure which one is better but for your reference.
4. Which cumulus convection scheme is used? You need to add a detailed experiment setup into your paper.
5. L159 over some parts of the western …
6. L174, But from about 30S to 50N, the zonal pattern is modelled correctly → The lightning is systematically underestimated in the model? Which parameters mostly contributed to this systematic bias?
7. L171, what does TKE represent?
8. L198, Figure S3 and Figure3, it looks like there is a rectangular dark blue box over polar regions, which is weird. It looks like there are bugs in your computer program, please check and justify this situation.
9. Figure 6 and Figure 11. The figures are blurry, please provide figures with at least 300 dpi.
10. Figure S2, model largely underestimated CAPE within low-latitude regions, could you please explain it?
11. Figure S5, model can partially capture the spatial pattern of r but systematically overestimte r compared to MERRA-2, what is the reason?

Technical corrections

Supplement, Figure S0, in the following sentence:

uppermost level (zt) may be reached by moists onvection.

Change "onvection" to "convection".

Reference

Finney, D. L., Doherty, R. M., Wild, O., Huntrieser, H., Pumphrey, H. C., and Blyth, A. M.: Using cloud ice flux to parametrise large-scale lightning, Atmospheric Chemistry and Physics, 14, 12665–12682, https://doi.org/10.5194/acp-14-12665-2014, 2014.

He, Y. and Sudo, K.: Historical (1960–2014) lightning and LNO_x trends and their controlling factors in a chemistry–climate model, Atmospheric Chemistry and Physics, 23, 13061–13085, https://doi.org/10.5194/acp-23-13061-2023, 2023.

He, Y., Hoque, H. M. S., and Sudo, K.: Introducing new lightning schemes into the CHASER (MIROC) chemistry–climate model, Geoscientific Model Development, 15, 5627–5650, https://doi.org/10.5194/GMD-15-5627-2022, 2022.

Lopez, P.: A lightning parameterization for the ECMWF integrated forecasting system, Monthly Weather Review, 144, 3057–3075, https://doi.org/10.1175/MWR-D-16-0026.1, 2016.

McCaul, E. W., Goodman, S. J., LaCasse, K. M., and Cecil, D. J.: Forecasting lightning threat using cloud-resolving model simulations, Weather and Forecasting, 24, 709–729, https://doi.org/10.1175/2008WAF2222152.1, 2009.

Williams, E. R.: The schumann resonance: A global tropical thermometer, Science, 256, 1184–1187, https://doi.org/10.1126/science.256.5060.1184, 1992.

The manuscript presents some results of the CanAM5.1 model with a new lightning scheme. In general, the manuscript is interesting, but I think it does not fit the scope of GMD. Judging from the title, a new lightning scheme is the main subject of the manuscript, but it is taken from previously published paper and described in just less than 80 lines. The rest of the manuscript is devoted to the analysis and evaluation of the CanAM5.1 performance in the modeling of the cloud related quantities, which fully define rather low (see figure 1, 2, 4, 5) accuracy of the simulated lightning frequency. Analysis of the burning areas and future projections looks interesting but irrelevant to the main aim of the manuscript. I understand that the accuracy of the proposed parameterization is comparable to other available parameterizations, but it is not shown in the manuscript. I think that the manuscript should be transferred to the more relevant journal (I think ACP is a good alternative).