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\def\htune{htexplo}
\def\htunelong{{\it High-Tune Explorer}}
\def\XX{XX$^{\mbox{th}}$ century}

\def\CO{CO\textsubscript{2}}
\def\ACO{4$\times$\CO}
\def\abrupt{\texttt{abrupt\ACO}}
\def\picontrol{\texttt{piControl}}
\def\historical{\texttt{historical}}
\def\CTRL{CTRL}
\def\clim{\texttt{clim}}
\def\climp{\texttt{clim+4K}}
\def\wpmc{W/m$^2$}


%\def\textart#1{{\it #1}}
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\begin{document}

\def\fig#1{Fig.~\ref{fg:#1}}
 \def\afaire#1{{\bf\textcolor{red}{#1}}}
%%\def\afaire#1{{\bf{#1}}}
\def\ie{i.~e.~}
%\def\tbd{\afaire{TBD}}
 \def\wpmc{W~m$^{-2}$}

 \def\wk{\mbox{\footnotesize wk}}
\def\ex{\mbox{\footnotesize ex}}
\def\htexplo{\texttt{htexplo}}

\def\Cstar{C_{*}}
\def\Cmax{C_{\mbox{max}}}
\def\qv{q_v}
\def\qvb{q_v}
\def\Lv{L_v}
\def\Cpair{C_p}
\def\tempp{\theta}
\def\derLag#1{\dfrac{D #1}{Dt}}
\def\densair{\rho}

\def\Qun#1{{Q_1}^{\mbox{\footnotesize #1}}}
\def\Qdeux#1{{Q_2}^{\mbox{\footnotesize #1}}}
\def\dzreynolds#1{\frac{1}{\rho}\dfrac{\partial \densair\overline{w' #1'}}{\partial z}}
\def\reynoldsflux#1{\densair\overline{w' #1'}}
\def\Cmax{C_{\mbox{max}}}
\def\qv{q_v}
\def\qvb{q_v}
\def\Lv{L_v}
\def\Cpair{C_p}
\def\tempp{\theta}
\def\derLag#1{\dfrac{D #1}{Dt}}
\def\densair{\rho}
\def\fg{f_g}
\def\Lf{L_f}



\def\mytab#1{Table~\ref{tb:#1}}


\def\wbmax{wb_{\mbox{max}}}
\def\wbsrf{wb_{\mbox{srf}}}
\def\sigdz{\sigma_{\mbox{desc}}}
\def\EPmax{EP_{\mbox{max}}}
\def\alpblk{k_{\mbox{ALP,BL}}}
\def\tildewb{\tilde{w}_{b}}

\def\WK{\mbox{\footnotesize wk}}
\def\BL{\mbox{\footnotesize bl}}
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\def\wb{w_{b}}
\def\wbgust{w_{\mbox{\footnotesize{b,gust}}}}
\def\Dwk{D_{\WK}}
\def\sigwk{\sigma_{\WK}}
\def\ewk{e_{\WK}}
\def\dwk{d_{\WK}}
\def\sigmaint{\chi}
\def\wkpupper{\gamma_{\mbox{\footnotesize wk,upper}}}
\def\Ps{p_{\mbox{\footnotesize srf}}}


% Ancienne def des hauteurs
\def\pupper{h_{m}}  % pupper = altitude maximale de subsidence des masses d'air sec
\def\ptop{h_{wk}}   % ptop = lesommet de la poche
\def\sigmawk{k_{twk}}

% Nouvelle def des hauteurs
\def\Pupper{p_{\mbox{\small upper}}}  % pupper = altitude maximale de subsidence des masses d'air sec
\def\Ptop{p_{\WK}}
\def\hwk{h_{\WK}}

\def\afaire#1{{\bf\textcolor{magenta}{#1}}}
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\def\sigmawk{k_{twk}}
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Dear Editor,
\\\medskip

You will find enclosed the new version of the manuscript and our reply 
to the reviewers' comments.
We really want to thank the two reviewers and you for your very positive comment on our work and manuscript.
We reply to each one of the reviewers remarks below.


For the sake of readability, we reproduce the full Editor's and reviewers' comments together with our reply
with the following convention for text fonts:

\reviewers{Reviewer comments}

\answer{Reply to reviewers}

\textart{Pieces of text taken from the manuscript}

\bigskip

A pdf file, showing the differences with the original version
in red and blue, is also provided.

\bigskip\bigskip

With best regards,

\bigskip\bigskip

Mamadou Lamine Thiam

\newpage

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Editor comments:}

\reviewers{
Editor comment 
please ensure that the colour schemes used in your maps and charts allow readers with colour vision deficiencies to correctly interpret your findings. Please check your figures using the Coblis -- Color Blindness Simulator (https://www.color-blindness.com/coblis-color-blindness-simulator/) and revise the colour schemes accordingly. \texttt{=>} Figs. 4 and 11
}

\answer{Dear Editor,
\\
Thanks a lot for the comments and suggestions. We answered positively almost all the reviewers comments as detailed bellow.
        First, regarding your comments on Figures 4 and 11, we agree to improve their readability.}


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Answer to reviewer \#1}

\reviewers{General comments}

\reviewers{RC1: 'Comment on egusphere-2025-5329', Anonymous Referee \#1, 23 Jan 2026}

\reviewers{This study presents a systematic framework for tuning and modifying the cold-pool parameterization in LMDZ using the High-Tune-Explorer (HTE), with large-eddy simulations (LES) serving as the physical reference. Motivated by insights from LES, several key parameter assumptions are revised, and the use of HTE to optimize free parameters leads to a substantial reduction of biases in single-column model (SCM) simulations.}


\reviewers{A major strength of the manuscript lies in its clear and well-structured description of the LMDZ convective parameterization associated with cold-pool processes. The results demonstrate clear benefits for representing cold-pool effects and are potentially valuable for future LMDZ CMIP7 simulations. Overall, this is a solid and well-executed study.}

\reviewers{I recommend publication after the following points are addressed or discussed.
}

\answer{Thanks a lot for these very positive comments and for all your suggestions. We answered them all and tried to use them to improve the text.}

\reviewers{
1.LES cases used for tuning
\\
The LES cases employed in this study include radiative-convective equilibrium (RCE) simulations and a diurnal cycle over land (AMMA) case. While these configurations are appropriate for examining cold-pool impacts on convection initiation and diurnal timing, cold-pool dynamics are also closely linked to the organization of mesoscale convective systems through mechanisms such as those described by RKW theory. It would be helpful for the authors to discuss whether incorporating LES cases of squall lines or other organized mesoscale convective systems could further constrain or refine the parameterization, or whether such regimes lie beyond the intended scope or intrinsic limits of the current cold-pool formulation.
}

\answer{That is a very good remark. Wind shear could modify the dynamics of cold pools within organized convective systems. Although the effect of wind shear on cold pools is not yet taken into account in LMDZ at present, a parameterization aimed at representing this effect is currently under development. This justifies the relevance of already calibrating the model against LES that feature organized convective systems. In the LES of AMMA case, we observe relatively organized structures, although these are not comparable to what is found in a true MCS or in squall lines. With this AMMA LES simulation, we therefore hope to constrain the cold pool model in a situation where the effect of wind shear on cold pools is relatively well represented. Nevertheless, the use of LES data for squalls or MCS, where the effect of wind shear on cold pools is more pronounced, could allow to constraining yet the cold pools parameterization. 
Yes, it would be interesting to add explanations to the article. Here are the added lines on the conclusions:}

\tbd{Il faut répondre à cette question dans les conclusions de l'articles. Il faut dire ce qu'on anticipe : on a déjà des trucs relativement organisés sur AMMAs. Mais bien sûr ce serait mieux d'avoir d'autres cas. Premier jet par Lamine. Le texte ci-dessous, ajouté dans la conclusion par Lamine, est peut être un début de réponse:}

\textart{ The LES of the AMMA case, characterized by relatively organized convection, made it possible to constrain the cold pool model in a configuration where the effect of wind shear on these pools is already relatively well represented. Although at this stage the interaction between wind shear and cold pools is not yet explicitly taken into account in LMDZ, a parameterization aimed at describing this interaction is currently under development. This justifies the relevance of already calibrating the cold pool model using an LES where the effect of shear is fairly well represented, even though the use of LES of squall lines or Mesoscale Convective Systems (MCS), in which this effect is more pronounced, could allow for better constraint of the model.}

\reviewers{
2.Remaining bias in diurnal cycle timing
\\
The simulated diurnal cycle remains delayed by approximately three hours. Previous studies (e.g., Khairdinov and Randall 2009) have suggested that cold-pool processes may play an important role in regulating convective timing. It would be useful to clarify whether this timing bias could potentially be reduced through further tuning of the cold-pool parameters, or whether it reflects a more fundamental limitation of the parameterization in capturing timing as opposed to intensity or spatial structure.
}

\answer{ Yes, cold pools can play a role in regulating the onset of convection. In our case, however, we do not have a specific parameter in the cold-pool model that could correct this bias, and we do not believe that this bias is related to the cold-pool model itself. There is, however, a parameter in the convection scheme that can slightly shift the timing of convection onset in the AMMA case: the threshold size at which a cumulus evolves into a cumulonimbus, which is currently prescribed in the model. We consider that this lag more likely reflects a physical limitation of LMDZ, possibly related to the lack of an representation of the transition between shallow and deep convection. This is what we explained in the paper between lines 484 and 485. Indeed, this may not have been very clear. We have added sentences in the revised version to better clarify this point. The added sentences are as follows:}


\tbd{Faire un morceau de texte à inclure dans l'article. Premier jet Lamine.}

\def\textartbias{\textart{This premature triggering in the LMDZ model for the AMMA case has already been showed in \cite{rio2009} and represents a known limitation of the LMDZ. In intermediate tests, we found that adjusting $S_{trig}$ (the cumulus size threshold used to trigger deep convection) could help reduce the timing delay of convection onset. We therefore hypothesize that an explicit parameterization of the transition between shallow and deep convection could help correct this bias.}}

\textartbias

\reviewers{
3.From SCM tuning to coupled simulations
\\
The SCM experiments provide a clean and controlled framework for evaluating the impact of the revised parameterization. However, it is well known that parameterizations optimized in SCM settings may degrade performance once fully coupled to a three-dimensional model. Before proceeding to fully coupled CMIP-style simulations, it would be valuable to consider an intermediate hindcast-type evaluation (e.g., following Ma et al. 2015). The authors are encouraged to comment on whether such an approach is planned or feasible within the scope of this work.
}

\answer{Effectively, this is a very general remark. Parameters calibrated in a 1D framework may degrade once implemented in a 3D, which justifies the need for intermediate testing before full integration into the global model. In our case, we performed 3D tests and found a behavior overall similar to that observed in 1D. This suggests that the calibrations carried out in 1D remain valid in the 3D, here.
We also found that the new numerical scheme for the computation of $\Ptop$ is more robust, significantly reducing crashes during 3D simulations.
This aspect was not discussed in the initial version of the manuscript, but it is indeed worth including. We have therefore added new sentences in the revised version to address this point. The added sentences are as follows:}

\tbd{Dire à la fois que c'est vrai et qu'il faut effectivement des stratégies intermédiaires, mais que, là, ca change peu la nature du modèle, et que les changements ont déjà été testé en 3D, et seront dans la version CMIP7 Fastrac, et qu'on retrouve un comportement similaire à ce qu'on voit en 1D. On a déjà mis une phrase pour dire que les modifs de l'annexe on permis de résoudre des plantages 3D ? Premier jet Lamine.}

\textart{Parameter calibrations performed in an SCM may nevertheless degrade once implemented in a global model, due to the inclusion of dynamical processes that are absent in the SCM configuration, which may require intermediate testing before full implementation \citep{Ma2015}. In our case, however, 3D tests show a behavior that is overall similar to that obtained in SCM (not shown), suggesting that the calibrations performed in SCM remain valid in the 3D configuration. The new numerical scheme proposed for the computation of $\Ptop$ also proved to be more robust, significantly reducing crashes during 3D simulations. All these modifications will be included in the CMIP7 Fast Track version.}

\reviewers{
4.Effectiveness and physical interpretation of the tuning framework
\\
The manuscript would benefit from a more explicit discussion of the effectiveness of the HTE tuning framework itself. In particular, further elaboration on how the adjusted parameters relate to the underlying physics of cold pool processes-such as their fundamental structure, triggering mechanisms, and interaction with convection would strengthen the physical interpretation of the tuning results and improve the broader applicability of the methodology 
}

\answer{Thank you for this relevant suggestion. We have tried to add more explanation to the text. We hope that these sentences, added below to the text, bring more clarity.}


\def\texttuning{\textart{The fact that the $\htexplo$ tool retrieves cold pool model parameter values close to those from LES, whether directly estimated (e.g., $k$, \mytab{LESvsLES}) or determined by comparison (e.g., $\wkpupper$, Section \ref{modif2}), highlights its ability to produce settings that are physically consistent with the properties of cold pools. Likewise, the range of values selected for $\sigma_{int}$ leads to cold pool heights of about 600~m in the RCE case and 2~km in the AMMA case, in agreement with the expected orders of magnitude over ocean and over land, respectively. The increase of $\sigdz$ is also consistent with the intensification of cold pools in the RCE case, through a strengthening of precipitating downdrafts. In the AMMA case, however, the opposite effect (less colder cold pools) is explained by the rather large increase in $\Cstar$ (from 3 to 5~m/s), induced by the adjustment of $k$. This increase in $\Cstar$ accelerates the evolution of cold pools surface, reducing the efficiency of evaporative cooling, which can no longer compensate for the dilution due to their rapid evolution. Although this mechanism is also present in the RCE case (with an increase in $\Cstar$ from about 1 to 2~m/s), it remains much less pronounced there, allowing the evaporation obtained with these $\sigdz$ values to effectively strengthen the cold pools. This highlights the importance of parameter interactions in \htexplo\, since the adjustment of their values relies on their combined effects rather than on their individual effects, leading to physically consistent parameter values.
We also consider that the increase of 1-$\EPmax$ and $\sigdz$ played an important role in the improvement of the specific humidity profiles for the RCE and AMMA cases, although other parameters may also play a role. Indeed, the increase of the difference 1-$\EPmax$ increases the amount of condensed water released at the top of the convective columns, thereby moistening the upper layers of the atmosphere. The value of $\EPmax$ was set to $0.999$ in the initial configuration. The increase in $\sigdz$, for its part, can enhance humidity through greater evaporation in the atmospheric levels where this process occurs, while generating a drying of the boundary layer, as in the AMMA case, linked to an increase in the advection of dry air from upper levels by subsidence.
During intermediate tests, we found, compared to configuration V2, a decrease in undiluted adiabatic updrafts (which represent the theoretical capacity of the column to transport air and moisture) as well as a decrease in saturated updrafts in the tuned simulations. This reduction in saturated updrafts would be linked, on the one hand, to the reduction in undiluted adiabatic updrafts, which limits the moisture supply to the convective column, and, on the other hand, to the increase in the export of condensed water out of convective clouds, which also dries the column. These conditions thus promote a state of lower saturation within the convective column.}}

%\def\texttuning{\textart{It would be difficult to attribute this results in BEST TUNE simulation to a specific parameter. The calibration result actually arises from a combination of the values of the different parameters used for tuning.  Even if a parameter has been significantly modified, its effect on the final result still depends on the other parameters. However, during intermediate tests, we found that the cold pool model is highly sensitive to the parameter $\sigdz$. An increase in its value leads to stronger cooling of the cold pools. We therefore assume that this parameter played a key role in the BEST TUNE results.}}

\texttuning

\tbd{Cette question est très proche d'une des dernières question du reviewer 2 qui demande de l'interprétation du tuning. Il faut répondre. En fait l'outil de tuning permet justement de faire beaucoup de choses dans cette direction, notamment avec les émulateurs, sous exploités jusque là. Il faut donc largement reprendre ce bout de texte ajouté par Lamine en fin de  de section 5. Premier jet Lamine et Maëlle.}

\reviewers{
My suggestion would be replacing Figure 1 with more coherent parameters of cold pools
}

\answer{Excellent suggestion. We did provide a totally new version of Figure 1, giving more insight to the cold pool parameterizations and of its coupling with parametrizations of shallow and deep convection}
 
\reviewers{
Citation: https://doi.org/10.5194/egusphere-2025-5329-RC1
}

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section*{Answer to reviewer \#2}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


\reviewers{
RC2: 'Comment on egusphere-2025-5329', Anonymous Referee \#2, 26 Jan 2026
\\
General comment:
\\
This paper addresses an important problem of validating cold-pool parameterizations in coarse-resolution models, on the example of LMDZ model. The study is very interesting and presents an insightful LES-based analysis of downdrafts and cold-pool effects. I recommend the paper for publication after the authors address a number of technical issues, primarily aimed at improving the clarity of the manuscript, through a major revision.
\\
Major points:
    Please add a schematic explaining how your cold-pool parameterization works and what it changes in your convection parameterization.
    I suggest using either one LES model for both numerical experiments, or the same pair of models for both experiments, for consistency.
    Please show a comparison of the results without the cold-pool parameterization to demonstrate its impact on the solution.
    Please comment on the changes in the behavior of convection due to cold pools. 
}

\answer{Thanks a lot for these very positive comments and for all your suggestions. We answered them all and tried to use them to improve the text.
Since the major comments appear mostly within the specific comments, our responses to them can be found in the responses to the specific comments.}

\tbd{Il faudra faire une synthèse ici des grandes modifications. Premier jet Frédéric}


\subsection*{Specific comments:}

\reviewers{
Title: Specify which model this is for to avoid confusion.
}

\answer{
The title was changed according to the referee's suggestion:
}\\
\textart{New title : Evaluation and improvement of the cold pool parameterization in the LMDZ climate model against Large Eddy Simulations
}\\

\reviewers{
Abstract: Briefly explain which cases are used for validation (quasi-equilibrium and time-dependent).
}

\answer{We added the information in the abstract :
}\\
\textart{
The evaluation is done both on case of radiative–convective equilibrium that allows the study of convective processes in a well-controlled and quasi-stationary framework, without the influence of large-scale dynamics, as well as on the time-dependent continental case AMMA (African Monsoon Multidisciplinary Analysis), representative of typical Sahelian conditions with local initiation during the afternoon.
}\\

\reviewers{
Equations: Could you please double-check all equations for correctness? They may be fine, but it would be useful to verify them once more. For instance, Eq. 1 seems to be missing the theta/T term, which may be unimportant for shallow convection but becomes important for deep convection where cold pools are present. Also, please unify the notation: you use symbols in some instances and letters in others, such as div.
}

\answer{
Thanks a lot for pointing to this missing $\theta/T$ term in the equations of the paper. In fact, those terms were already missing in the original paper by Grandpeix and Lafore (2010). Hopefully, the error is not present in the parameterization itself, which is written in terms of static energy rather than potential temperature. This term has been corrected and all the other equations were double checked, very carefully. We did not find other mistakes in the equations.
}\\
\tbd{Est-ce bien vrai que vous n'avez pas trouvé d'autres erreurs ?}


\reviewers{
Equations are part of the text and should include proper punctuation as well.
}

\answer{
Done
}\\


\reviewers{
L5: This reads unfortunately and suggests that the model developers have not accurately evaluated their parameterization before implementing it. Please rephrase.
}

\answer{We agree that this sentence was somehow misleading.  We’ve clarified things in the new version of the abstract :
}\\
\textart{
The introduction of a cold pool parameterization into the LMDZ climate model has significantly improved the representation of convection, in particular its diurnal cycle. Thanks to this indirect evaluation, the parameterization of cold pool
 was retained in the further versions of LMDZ. However, no detail evaluation of
the representations of cold pools themselves was done so far.
This work provides for the first time such an evaluation based on Large Eddy Simulation (LES).
}\\
\remarque{Tu avais écrit : "We have ultimately decided to remove this sentence. Please see the new abstract above" mais en laissant en fait "This work provides for the first time such an evaluation". C'est important de ne pas botter en touche et bien dire ce qu'on a fait.}


\reviewers{
L20: There are papers in which cold pools are not referred to as cold density currents when they form wind gustiness. For a cold pool to expand, a non-zero velocity must be present. "Density currents" appears to be a more general term from hydrodynamics. Please rephrase. I believe the authors use the term "cold pools" for both downdrafts and cold pools, which should either be changed or clarified.
}

\answer{
We agree that the wording was not well enough defined in the original manuscript. We make a clear distinction between the downdrafts (which are part of the convective parameterization in the model) and cold pools. As for the later,
we decided to conserve the wording "cod pools" specific of density currents created by reevaporation of convective rainfall.
The modified text (beginning of Section 1) is reproduced bellow:
}\\
\textart{
During thunderstorms, precipitation forms inside convective clouds. When it falls either to the side or below the cloud, into air that is not saturated with water vapor, a portion of this precipitation evaporates. This evaporation cools the air, making it denser and creating so-called unsaturated downdrafts.
Below cloud base, this cold air spreads out horizontally. These expanding masses of cold air are generally called "cold pools" or "wakes". The later term was retained when developing the code and will be used here in the equations for consistency. The former term will be used throughout the text of this paper.
The cold pool, that spreads horizontally because its air is warmer than its environment, can also be seen as a density current \citep{charba1974,droegemeier1987}.
Cold pools are most often associated with a gust front, capable of lifting the surrounding warm air and thus promoting the development of new convective cells.
}\\


\reviewers{
Furthermore, the literature review needs to be improved. A number of papers on cold-pool parameterizations for weather and climate models have been published and are worth mentioning, for example Park et al. (2024), Suselj et al. (2019), Rooney et al. (2022), and Freitas et al. (2024).
}

\answer{We agree. We added the following to the text:}
\textart{Cold pools also play a role in triggering elevated convection (i.e., convection initiated at a certain altitude), a process that should be taken into account in GCMs to improve the representation of nocturnal precipitation \citep{park2024}.}
and
\textart{One of the first attempts to parameterize cold pools was proposed by \cite{qian1998}.
Later on, \cite{GL10I} proposed an autonomous parameterization based on a population of identical circular cold pools that are cooled by the evaporation of precipitation, this cooling term being provided by the parameterization of deep convection. This new scheme was further coupled to the \cite{emanuel1991} deep convection scheme and has since become a key parameterization of the LMDZ global climate model \cite{rio2008}.
Other parameterizations of cold pools were proposed more recently, either independent from the convective model as is the case in LMDZ \citep{rooney2022,freitas2024} or as part of it \citep{Suselj2019}.
The works of \cite{rooney2022} and \cite{freitas2024} introduced propagation from one model grid cell to another, a process which is not represented so far in LMDZ although it known to be important for representing their impact on convective organization \citep{freitas2024}.}


\reviewers{
L49: This statement is unclear. See Suselj et al. (2019) for an example of how LES was used to develop a cold-pool parameterization within a convection scheme. They use a no-cold-pool solution as a reference to which the SCM must converge, and only then extend it to account for cold-pool effects. In the current study, you appear to compare the SCM only to full-physics LES, which should be clarified.
}

\answer{
	At line L49, we clarify that, to our knowledge, LES have not yet been used to directly evaluate cold-pool parameterizations. However, they can guide the development of such parameterizations, as we mention at line L48 with the reference to Kurowski et al. (2018). From what we understand from \cite{Suselj2019}, the authors use LES to evaluate in detail their unified convection parameterization (shallow, moderate, and deep). They also use LES to study the effect of cold pools on convection, but not to directly evaluate the representation of the cold pools themselves in their model. But we can include Suselj et al. (2019) among the references that have used LES to evaluate convection parameterizations. We added to the introduction:}

\textart{\cite{Suselj2019} used LES to evaluate in detail the internal variables of their unified convection (dry, shallow and deep) parameterization, for example by validating the surface fraction covered by moist updrafts. They also used LES to validate an approximation regarding the timing of when cold pools begin to invigorate convection in their unified convection scheme, and to study the effect of cold pools in the  convection. Other studies have used LES to better understand cold pool processes \citep{feng2015,meyer2020,lochbihler2021} and to guide the development of cold pool parameterizations \citep{kurowski2018}. However, to our knowledge, no study has yet exploited LES to evaluate in detail the internal variables of a cold pool parameterization.}

\reviewers{
L76: Is it possible to specify which ones?
}

\answer{Not sure we got the question propertly. Do you mean specifying "which other exercises". We rather simplified the sentence from (submitted manuscript): }
\textart{The latter is one of around twenty coupled models taking part in major international model intercomparison exercises, such as those of the CMIP (Coupled Model Intercomparison Project), the results of which are used in IPCC (Intergovernmental Panel on Climate Change) reports.}
\answer{to (revised manuscript):}
\textart{The latter is one of around twenty coupled models taking part regularly in the international model intercomparison project (CMIP), the results of which are used in IPCC (Intergovernmental Panel on Climate Change) reports.}



\reviewers{
L93: Are Q1 and Q2 relevant to Yanai et al. (1973; JAS)?
}

\answer{
Yes. The reference was added to the text at the first mention of Q1 and Q2:
}\\
\textart{
The role of convective parameterizations is to provide sources of heating $\Qun{}$ and moistening $\Qdeux{}$ \cite[folowing notations first  introduiced by][]{yanai1973} [...]
}\\


\reviewers{
L99: Unclear. Which term is discussed here?
}

\answer{
The wording was not clear indeed. We write in the new version:
}\\
\textart{
The role of convective parameterizations is to provide sources of heating $\Qun{}$ and moistening $\Qdeux{}$ \cite[folowing notations first  introduiced by][]{yanai1973} to the conservation equations of potential temperature $\tempp$ and specific humidity $\qv$~:
\begin{eqnarray}
    \Cpair\derLag{\tempp}    = \frac{\tempp}{T}[Q_R + (\Lv +\fg \Lf) ( c - e )] - \Cpair \dzreynolds{\tempp} & = \displaystyle{\frac{\tempp}{T}\ [Q_R + \Qun{}] }, \\
       \dfrac{D\qv}{Dt}      =       e - c   -\dzreynolds{\qv}                  & = \ -\Qdeux{}/\Lv, 
\end{eqnarray}
where $\Cpair$ is the heat capacity of dry air,
$Q_R$ is the radiative heating, $c$ and $e$ are condensation and evaporation rates, $\fg$ is the condensate ice fraction, $\Lv$ is the latent heat of vaporization, $\Lf$ the latent heat of fusion and $-\partial_z \reynoldsflux{\phi}/\rho$ (with $\phi=\tempp$ or $\qv$) is the vertical convergence of the Reynold turbulent flux of $\phi$ accounting for the effect of the subgrid-scale turbulent or convective motions on the explicitly resolved large scale flow.
}\\


\reviewers{Subsections 2.2.1-2.2.3: It appears that the beginnings of paragraphs are missing.}

\answer{This was a LaTeX issue: these are not sections but paragraphs. Corrected in the revised manuscript.}

\reviewers{L111: It may be sufficient to state that this is a bulk-plume approach applied to the subcloud layer, if that is the case.}

\answer{We agree that the text was not clear enough. It is indeed a bulk-plume model but we prefer to use the idea of an effective plume.
The new text is reproduced bellow : }
\textart{
Shallow convection (dry or cloudy) is handled in LMDZ with the so-called ``thermal plume model", a mass flux scheme which was developed to account for non local vertical transport by organised thermal plumes, cells or rolls in the convective boundary layer \citep{hourdin2002,rio2008}. The combination of an eddy diffusion with a mass flux scheme for the representation of turbulent transport in the convective boundary layer, first proposed by \cite{Chat:87}, has since be popularized as the EDMF (Eddy Diffusion Mass Flux) approach.\\
\def\fth{f_{th}}
\def\ath{\alpha_{th}} 
\def\tth{\tempp_{th}}
\def\phith{\phi_{th}} 
\def\qth{q_{th}} 
\def\wth{w_{th}}
In the thermal plume model, more specifically, the population of convective structures within a grid cell are summarized into a unique effective ascending plume, [...]
}\\


\reviewers{I find this description somewhat confusing. You first describe organized thermal plumes in the boundary layer without specifying whether this refers to a dry or cloudy layer. From the context, it seems to be a shallow convection scheme. Please clarify.}

\answer{It is indeed a shallow convection scheme. We hope the text above makes it clear.}

\reviewers{L124: This suggests that your shallow-convection parameterization represents cumulonimbus clouds. Please double-check this description. Is it also a bulk-plume scheme?}

\answer{ It may be the beginning of the sentence that makes the text a bit confusing in the submitted manuscript. The shallow convection scheme does not represent cumulonimbus clouds. Yes, the deep convection scheme is also a bulk-plume scheme.  The new paragraph:}
\textart{Deep convection is represented with the \cite{emanuel1991} mass flux scheme modified by \cite{grandpeix2004}. Its fundamental principles are retained, with a representation of a population of cumulonimbus clouds as a collection of saturated updrafts and downdrafts together with an unsaturated downdraft (mass flux scheme). This parameterization simultaneously represents transport, condensation, cloud formation, and precipitation.}


\reviewers{L128-140: Please be precise and avoid this type of jargon. It is unclear what is meant by "exchange matrix" and by "compartments" in your scheme. Is this a description of a bulk updraft that is diluted with height using a buoyancy-sorting mechanism?}

\answer{The idea was to give insight to the code but we agree that this sentence was somewhat confusing. The sentence was removed.  The new paragraph in the revised manuscript, following the one reproduced above, is:}
\textart{The core of the cumulonimbus is represented as an undiluted updraft that does not entrain air laterally above cloud base, but is gradually ``eroded" while rising. This updraft is assumed to be fast enough to carry the liquid or solid water condensed within it.
Following the Episodic Mixing and Buoyancy Sorting approach, a population of diluted ascending or descending air masses [...]}


\reviewers{There is no need to use bold fonts here.}

\answer{Bold font were removed.}

\reviewers{L140: Here you already use "cold pools" and "density currents" interchangeably. I suggest sticking with "cold pools," which is the more common terminology in the literature.}

\answer{Done}

\reviewers{L145: Is this the modification proposed here? Please clarify. Since the cold-pool parameterization was already proposed in GL10, I assume this aspect is not novel to this paper.}

\answer{We agree that this paragraph was confusing. The first modification to the scheme, concerning the air mixture between the updraft and environment is part of the convective scheme and should not be presented as a "modification". In the new version, we start the description of the deep convection scheme by:
}
\textart{Deep convection is represented with the \cite{emanuel1991} mass flux scheme modified by \cite{grandpeix2004}.}
\answer{The other modification mentioned in this paragraph was anticipating the section {\bf 2.4 Triggering and closure of the deep convection scheme}. This paragraph (just before {\bf 2.3 Cold pools}) was thus simply removed.}

\reviewers{Fig. 1: Using a figure from another paper may require copyright permission. I suggest removing it and preparing a new one, explaining both the details of the cold pool parameterization and how it affects the convection parameterization. This is the essence of this paper.}

\answer{
As suggested in the reviewer's major points as well as by reviewer \#1,  we proposed a new schematic view of the parameterization and of its coupling with convective parameterizations (see new Fig. 1).
}\\

\reviewers{
L151: The cold-pool model description is difficult to follow. Why is it designed on an infinite plane, and how does this relate to the model grid-box size? 
}

\answer{We hope that the detailed and most often relevant reviewer's remarks helped us improved the description of the cold pool model.\\
To start with, the mention of the grid-box is confusing and useless here. The idea behind infinite plane is made more explicit:}
\textart{The cold pool model represents a population of circular cold pools (or wakes) over an infinite plane, consistently with the way the Reynolds decomposition is used to separate, in GCMs, the 3D dynamical core from the 1D world of parameterizations of subgrid transport, assuming that the statistics of the turbulent or convective motions responsible for this transport are horizontally homogeneous on an infinite plane.}

\remarque{plutôt pour Jean-Yves. Est-ce que tu ressens le besoin de dire "containing the grid cell" dans "an infinite plane containing the grid cell" ? Il me semble qu'à ce stade on n'a pas besoin d'invoquer la grid cell.}

\reviewers{
Why do all cold pools have the same radius, and does it change with time or remain fixed?
}

\answer{It is a simplification of the model. The text has be changed as follows:}
\textart{An important simplification of the model consists in assuming that, within a given column of the model and at a given time step, all the wakes have the same height, radius, and vertical profiles of thermodynamic variables which is equivalent to say that we are representing the population of cold pools through a mean effective cold pool. All those variables however evolve in time according to the cold pool physics, as detailed below.
}


\remarque{pour Lamine. Tu avais écrit "The assumption that all cold pools have the same radius is also a simplifying choice of the model, although it is a very crude approximation.". C'est bizarre. De dire "c'est une simplification bien que ce soit une groissère approximation"}

\reviewers{If their centers are statistically distributed with a uniform density $\Dwk$, does this imply a constant distance between adjacent cold pools?}

\answer{Not necessarily. Text modified as follows:}
\textart{The centers of those cold pools are randomly distributed with a uniform number density $\Dwk$ (number of cold pools per unit area) assuming no overlap between two of them.}

\reviewers{Does each cold pool have an associated downdraft, or is this only a conceptual model?}

\answer{Difficult to answer this question, linked to the fact that both the convective and cold pools parameterizations are conceptual, or bulk, or effective models.
We agree that the text was particularly confusing there. It was reorganized and we say more precisely on this question:}
\textart{The main driving of the parameterization is the cooling associated with convective unsaturated downdrafts.
All this cooling, provided by the deep convection scheme, is applied to the interior of the cold pools thus creating a contrasts in temperature $\delta T$ between the interior and exterior of the pool (see Fig 1.).}

\remarque{pour Lamine. Tu as ajouté pour le reviewer "Each cold pool has an associated downdraft." Je ne vois pas le sens.}


\reviewers{What is the relationship between cold-pool area and the environment?}

\answer{The space is divided into two parts: the cold-pool region and its environment. Each has its own profiles of temperature, humidity, and vertical velocity. The definition of $\delta X$ is grouped now with the introduction of the separation between cold pool and environment to make it clearer:}
\textart{In practice, the model divides the space into two parts, the interior ($\wk$) and exterior (or environment) of cold pools  ($\ex$) respectively.
For temperature, humidity and vertical velocity, we introduce a wake anomaly
$\delta X = X_{\wk} - X_{\ex}$ defined as the difference of its mean values in the two subdomains and $\overline{X}$ the average over the horizontal domain.}

\reviewers{When are cold pools initialized? What determines their lifecycle, from initialization to decay? Is it linked to the amount of evaporating precipitation?}

\answer{Cold pools are initialized as soon as convection is triggered and disappear when the evaporation of precipitation becomes weak, when WAPE falls below a given threshold. This shows that their lifecycle is indeed linked to the amount of precipitation evaporation. We finally decided to add a full paragraph describing this life cycle before entering the detail of the parameterization and equestions:}
\textart{The main driver of the parameterization is the cooling associated with convective unsaturated downdrafts.
All this cooling, provided by the deep convection scheme, is applied to the interior of the cold pools thus creating a contrast in temperature $\delta T$ between the interior and exterior of the pool (see \fig{fg:poche}).
Once the cold pools are initiated (which requires a prior activation of deep convection), they enter a positive feedback loop with deep convection. Cold pools reinforce deep convection both because the undiluted ascent, at the core of the parameterization of deep convection, is fed by air coming from the environment of the cold pool (warmer near the surface than the average grid cell), and because of a lifting energy provided by the cold pool spreading as detailed in the following section.
The temperature difference between the cold pools and their environment is controlled by competing effects: it increases due to cooling by convective downdrafts and decreases due to cold pools spreading and gravity wave damping.
When deep convection stops, this temperature contrasts decreases until switching off the cold pool parameterization based on a combination of thresholds.
Details of the scheme are given hereafter.}


\remarque{pour Lamine. Là tu avais mis d'un coup une page extraite du manuscrit révisé en guise de réponse. Ca ne peut pas être ça. Il faut répondre point par point.}
\remarque{pour Jean-Yves : c'est bien 2\% ? Je en retrouve pas le courriel ou le post mattermost dans lequel tu précisais ça.}

\reviewers{I suggest preparing a new Fig. 1 that explains how your cold-pool parameterization works.}

\answer{Done}

\reviewers{L170: Using "probably" casts doubt on the approach. Please rephrase. It is acceptable for a parameterization not to account for all processes.}

\answer{Yes. The sentence was removed.}

\reviewers{L173: What is meant by the spread rate of cold pools? Are they initialized at the surface with a fixed radius and then allowed to grow?}

\answer{Yes. We have revised the description of this aspect as well:}
\textart{When cold pools appear in a grid cell were they were not present before, their fractional cover $\sigwk=\pi r^2 \Dwk$ (where $r$ is the cold pool radius) is set arbitrarily to 2\%, corresponding to an initial radius of about 2.5~km over ocean and 30~km over land with the values chosen for the wake number density in LMDZ6A.
The cold pool radius then grow with rate $\dot{r}=\Cstar$ so that the time evolution of the fractional surface reads:
\begin{equation}
  \partial_{t} \sigwk = 2\pi r\Cstar \Dwk = 2\Cstar \sqrt{\pi \Dwk \sigwk},
        \label{taux_exp}
\end{equation}
This surface fraction increases over time. It is limited to 40$\%$ of the domain. When this threshold is reached the growth of the cold pools is stopped and the radius remains constant.}
     

\reviewers{L180: "Hope" is not a scientific term. Please rephrase.}

\answer{We agree and rather removed the sentance which was not adding to the text}

\reviewers{L189: What is the role of lateral entrainment here? Does it reduce WAPE?}

\answer{Yes. Lateral entrainment warms the cold pool and thus reduces the WAPE. The information was added as follows:}
\textart{The vertical subsidence which thus increases downward between $\Pupper$ and $\Ptop$ is fed by lateral entrainment $\ewk$ without detrainment so that
$\ewk = \sigwk(1 - \sigwk) \partial_{p} \delta \omega + \partial_{t} \sigwk$. This lateral entrainment accounts for the horizontal component of the meso-scale circulation known to entrain dry and warm (in terms of potential temperature) air from low- or mid- tropospheric air into the cold pool (see Fig. 1), in turn reducing the WAPE.}

\reviewers{L195: Why is this important?}

\answer{It is not. The text was made more explicit on this point:}
\textart{In the version used here, $\delta{\omega}^{cv}=0$ above this level while it was not the case in GL10. We realized that the GL10 version was introducing a double counting of the vertical mass flux of saturated downdraft at $\Pupper$. This modification has however little effect on the parameterization results since the mass flux associated with downdrafts is small at $\Pupper$ (result not shown).}

\reviewers{L199: Please clarify whether your cold pools are also part of downdrafts. If so, this would be an important distinction from other approaches. For example, Suselj et al. (2019) use separate parameterizations for downdrafts and cold pools.}

\answer{No, the cold pools are not part of downdrafts. We hope that Fig. 1 and all the modifications of the text will help remove ambiguities on that point. In the GL10 model, cold pools and downdrafts are represented as two distinct processes. The cooling by unsaturated downdraft is computed by the convection scheme. This cooling is assumed to take place within the fraction of the grid cell covered by cold pools. This cooling is driving the the subsidence and horizontal spread of cold pools. In order to help clarify this point, we reorganized a little bit this sction by moving the description of the cold pool tendencies ($\Qun{\wk}$ and $\Qdeux{\wk}$) which was containing L199 to the end of the section. We also tried to insist on the fact that downdraft are part of the convection scheme and not of the cold pool shceme:}
\textart{As already said, it is the cooling associated with the re-evaporation of rain in unsaturated downdrafts that is the primary driver of cold pool development.
This process is reflected in the model by assigning the heating term $\Qun{unsat}$ computed by the convective scheme to the interior of cold pools, while $\Qun{sat}$ acts on their environment.}

\reviewers{L225: This is a risky statement. The model needs additional explanation to link downdrafts with near-surface cold pools.}

\answer{The risky statement "The cold pool model is now fully described. It includes:" :) was replaced by a less risky one:}
\textart{Finally, the cold pool models includes:}

\reviewers{L226: If cold pools are part of downdrafts, how should the horizontal size and spacing be interpreted at higher altitudes? Do these properties change with height?}

\answer{Cold pools are not part of the downdrafts.}

\reviewers{L263: This appears to be an assumption of the model that is difficult to validate. Please clarify.}

\answer{We added:}
\textart{This rather arbitrary choice is tested hereafter.}

\reviewers{Eqs. 20-21: These equations appear unexplained.}

\answer{This equations have been replaced by the following text and equations:}
\textart{AEach cold pool provides a power associated with its horizontal spreading. This power is calculated as the product of the kinetic energy supplied by the pool and the mass flux, evaluated over the entire contour of the pool ($L_{g} = 2\pi r$), over the full height of the pool $\hwk$, and using the spreading velocity $\Cstar$.
The power ($ALP_{\WK , i}$) of an individual cool pool $i$ is therefore:
\begin{equation}
        ALP_{\WK , i} = \frac{1}{2}\rho C_{*}^{3} \hwk L_{g}.
\end{equation}
To obtain the average power ($\ALPwk$) over all cold pools in the domain, this individual power is multiplied by the cold pool number density $\Dwk$:
\begin{equation}
\ALPwk = ALP_{\WK , i} \Dwk.
\end{equation}
\\
Since $\sigwk$ = $\Dwk \pi r^{2}$, the lifting power $\ALPwk$ reads:
\begin{equation}
\ALPwk = \epsilon \rho {\Cstar}^{3} \hwk \sqrt{\sigwk \Dwk \pi},
\label{eq:fp_alp_wk}
\end{equation}}

\reviewers{Eq. 22: Once you derive an equation that is important for the model, please provide some interpretation. For instance, what are the consequences of this formulation, and which parameters dominate?}

\answer{Done in the text reproduced just above.}

\reviewers{Overall, this section would benefit from a schematic explaining how the parameterization works, from initialization through intermediate stages to decay. Please also interpret the major components to help the reader understand the model.}

\answer{Thanks a lot. We hope that the reviewer's comments helped us to do a better job in that respect.}

\reviewers{L265: What does this mean? Is this truly power (or energy), and how does it enter the convection parameterization? Does it affect entrainment, organization, or other aspects, or does it help initiate stronger updrafts?}

\answer{This line corresponds simply to an intermediate calculation allowing $\ALPwk$ to be expressed as a function of $\sigwk$. Indeed, $\ALPwk$ is computed by integrating over the entire perimeter of the cold pool (referred to here as the gust front length $L_{g}$), which is $2 \pi r$ for a circle. The radius r can then be expressed as a function of $\sigwk$ using equation (21). We have tried to explain it more clearly in the revised version. Please refer once again to the new paragraph reproduced above.}\\

\reviewers{L270: There is no need to explain this.}

\answer{We decided to skip this sentence however, as an introduction to LES.}

\reviewers{L273: This statement is risky. You cite only two papers for shallow convection. LES has been used to simulate a wide range of PBL regimes with both finer and coarser resolutions, depending on the problem. Please rephrase or remove.}

\answer{We replaced the statement by:}
\textart{They provide an explicit and detailed representation of turbulent and convective motions within the boundary layer and of the associated clouds \citep[see e.~g.][among many others]{brown2002,siebesma2003}.}

\reviewers{L275-277: In papers such as Tan et al. (2018) or Suselj et al. (2019), previous LES-based studies are cited systematically. You can simply cite earlier work.}

\answer{We did not want to give to many references but we added:}
\textart{LES were used as well for assessing parameterizations of deep convection, including cold pools that are represented explicitly in such simulations \citep[see e.~g.][]{Suselj2019}.}

\reviewers{L278-294: Please edit this section carefully, explaining why three cases are needed and why two different LES models are used. I suggest either using two LES models for both cases, for example to address uncertainty, or using a single LES model for all cases. Ensure the sentences are clear and avoid vague phrasing such as "The destabilization leads to convection."}

\answer{We edited this section carefully (please refer to the pdf file with change track, section 2.5). We choose to keep 3 LES for the reason explained in the new version of the texte:}
\textart{In the present study, we use the outputs of LES for to test cases, one over ocean and the other one over land.
The test case over ocean was run with two different models, SAM and MesoNH, with the exactly same setup in order to assess the uncertainty in LES simulations.}

\reviewers{It should be clearly stated that the LES provides full physics, including cold-pool effects, and therefore does not allow validation against a no-cold-pool reference solution. Moreover, the RCE approach simplifies the time dependence of cold pools because the mean state does not evolve. Only the second experiment appears to introduce time dependence.}

\answer{We agree that LES provides simulations that include an explicit representation of cold pools, and also about the remark concerning the time dependance. We added to the text:}
\textart{LES were used as well for assessing parameterizations of deep convection, including cold pools that are represented explicitly in such simulations \citep[see e.~g.][]{Suselj2019}}
\answer{and, at the end of section 2.5:}
\textart{One advantage of RCE for parameterization development is that it targets a steady state regime.
By contrasts, the AMMA case corresponds to a diurnal cycle of deep convection over land, for which the time matters, and for which errors in the phasing of the triggering of deep convection can alter comparisons.}

\reviewers{L294: What surface fluxes are used here, fixed or time-dependent? Table 1 shows that AMMA data were averaged over five hours. Does this correspond to a quasi-steady state? The role of cold pools in the diurnal cycle over land is strongly time-dependent.}

\answer{The surface fluxes are fixed here, as stated in the text. The AMMA case is not stationary: our intermediate analyses showed that cold pools vary significantly over the diurnal cycle. However, to avoid overly long analyses, we chose to examine the average properties of the cold pools over the entire period rather than analyzing them at each individual time step.}

\reviewers{L308: Please remove "fairly immediately" and check the manuscript for similar phrasing.}

\answer{Done}

\reviewers{Fig. 9b: Why are the LES results much moister than LMDZ? The differences appear large. Do they also affect cloudiness? If so, please describe this.}

\tbd{Lamine, propose nous quelque chose. On a fait des tests et tout}

\answer{Yes, this also affects cloudiness. Where this difference of humidity is pronounced, LMDZ produces almost no clouds, likely due to the overly dry atmosphere obtained at these altitude levels. We agree to include this description in the text. Here is the added part:}

\textart{At the altitudes where these dry biases are found, notably between 800 and 400~hPa for the RCE case and between 700 and 600~hPa for the AMMA case, LMDZ produces almost no clouds, likely due to an overly dry atmosphere (not shown).}


\reviewers{Figure 11 shows a significant improvement after tuning, but it would be helpful to understand what changes in the convection lead to this result.}

\answer{We agree with this remark, which aligns with one of the comments from Reviewer 1. We sought to provide a more physical interpretation of the tuning results and tried to comment on the modifications that led to these results. Below is the description we added to the text:}

%\answer{It would be difficult to attribute this change to a specific convection parameter. The calibration resuats actually arises from a combination of the values of the different parameters used for tuning. Even if a parameter has been significantly modified, its effect on the final result still depends on the other parameters.}

\texttuning

\tbd{Cette question est très proche d'une du reviewer 1 qui demande de l'interprétation du tuning. Il faut répondre. En fait l'outil de tuning permet justement de faire beaucoup de choses dans cette direction, notamment avec les émulateurs, sous exploités jusque là. Il faut donc largement reprendre ce bout de texte ajouté par Lamine en fin de  de section 5. Premier jet Lamine et Maëlle.}


\reviewers{Although the paper focuses on downdrafts and cold pools, it would be useful to briefly discuss the behavior of the convective updrafts as well, since these processes are strongly coupled.}

\tbd{On peut essayer de regarder ce que ca donne dans les expériences de tuning. Premier jet Lamine}

\answer{Okay. We have attempted to add a description of the behavior of the updrafts. Here is the added sentences:}

\textart{During intermediate tests, we found, compared to configuration V2, a decrease in undiluted adiabatic updrafts (which represent the theoretical capacity of the column to transport air and moisture) as well as a decrease in saturated updrafts in the tuned simulations. This reduction in saturated updrafts would be linked, on the one hand, to the reduction in undiluted adiabatic updrafts, which limits the moisture supply to the convective column, and, on the other hand, to the increase in the export of condensed water out of convective clouds, which also dries the column. These conditions thus promote a state of lower saturation within the convective column.}


\reviewers{Temporal bias (delay) in triggering the diurnal cycle of convection is typical of convection parameterizations. One potential way to alleviate this bias is by linking cold-pool effects with entrainment. Have the authors explored this approach?}

\tbd{Premier jet Lamine}

\answer{We understand the idea, but we do not think that this approach can correct the triggering delay obtained in the AMMA case. Indeed, the AMMA case corresponds to primarily local convection (not advected from elsewhere); there are therefore no pre-existing cold pools to influence the triggering. Moreover, in LMDZ, the cold pool scheme is only activated once deep convection triggers. Rather, we think that this delay is related to the transition from shallow to deep convection, which is not currently parameterized in LMDZ. We have added sentences in the new version of the paper to discuss this delay}

\textartbias

\reviewers{Conclusions: Consider simplifying this section so that the main messages can be understood by a general reader. For example, when you state (L611) that the value of coefficient k was increased from 0.33 to 0.56, this result is difficult to interpret without carefully reading the entire paper. I suggest rephrasing the conclusions so they are accessible even to readers who have not engaged with all the technical details. Think of a general picture here.
}

\tbd{Reprendre en toute fin}

\answer{Agreed, we are in favor of a clearer revision of the conclusion. We have tried to modify certain paragraphs to make it understandable to readers who could not read the entire document. Here are the main paragraphs that have been reworked:}

\textart{This study presents a detailed evaluation of the cold-pool model \cite{GL10I} within the LMDZ climate model, based on Large Eddy Simulations (LES). We evaluate both the fundamental assumptions of the model, its internal variables and those involved in the coupling with deep convection, based on two LES over oceanic in the RCE regime and a LES over land of the AMMA case. The RCE case offers a controlled and quasi-stationary framework for studying convective processes, whereas the AMMA case represents a typically Sahelian deep convection where the time dependence is important.}

and
\textart{We valited relationship internal to the parameterizations, by diagnostics of the LES.
This validation mainly relies on comparisons between LES. The cold-pool model variables, diagnosed within the LES according to the formulation of the parameterization, were compared with those obtained directly through sampling in the same LES. The good consistency between the results confirms the fundamental assumptions of the model. The discrepancies observed for some variables are mainly explained by the choice of a free parameter value, which we adjusted depending on the estimates provided by the LES.}

and
\textart{Warm and cold biases were also observed at the surface of the cold pools, respectively for the RCE and AMMA cases. These biases led to a poor estimation of certain cold-pool model variables ($WAPE$ and $\Cstar$), as well as those involved in the coupling, notably $\ALPwk$, since these variables strongly depend on the temperature of the cold pools in the model. In order to check whether this limitation may come from a coupling with the other model parameterizations, and in particular that of deep convection, we conducted a calibration experiment using the HighTune explorer software to jointly adjust the free parameters of the cold pools and deep convection models.}

\bibliography{bibliographie}

\reviewers{
References:
\\
Freitas, S. R., Grell, G. A., Chovert, A. D., Silva Dias, M. A. F.,  de Lima Nascimento, E. (2024). A parameterization for cloud organization and propagation by evaporation-driven cold pool edges. Journal of Advances in Modeling Earth Systems, 16, e2023MS003982.
\\
Suselj, K., M. J. Kurowski, and J. Teixeira, 2019: A Unified Eddy-Diffusivity/Mass-Flux Approach for Modeling Atmospheric Convection. J. Atmos. Sci., 76, 2505-2537,
\\
Park, S., Song, C., Kim, S., \& Kim, J. (2024). Parameterization of the elevated convection with a unified convection scheme (UNICON) and its impacts on the diurnal cycle of precipitation. Journal of Advances in Modeling Earth Systems, 16, e2023MS003651.
\\
Rooney, G.G., Stirling, A.J., Stratton, R.A. \& Whitall, M.(2022) C-POOL: A scheme for modelling convective cold pools in the Met Office Unified Model. Q J R Meteorol Soc, 962-980.
\\
Tan, Z., Kaul, C. M., Pressel, K. G., Cohen, Y., Schneider, T., \& Teixeira, J. (2018). An extended eddy-diffusivity mass-flux scheme for unified representation of subgrid-scale turbulence and convection. Journal of Advances in Modeling Earth Systems, 10, 770-800.
}


\end{document}
