Reply on RC2

Response: the structure of the work needs to be improved. Authors recognize this fact. In the next proposal, section 2 will be dedicated to present data and section 2 for the methodology. In section 2 the reference to our previous work using MSG-MPE will be added. Paragraph 81-91 will be reformulated. the subsection 2.2 will be removed (as title). The word "event" will be replaced by "day" in all the manuscript. Also Section 2.4 will be suppressed (as title).

Response: the structure of the work needs to be improved. Authors recognize this fact. In the next proposal, section 2 will be dedicated to present data and section 2 for the methodology. In section 2 the reference to our previous work using MSG-MPE will be added. Paragraph 81-91 will be reformulated. the subsection 2.2 will be removed (as title). The word "event" will be replaced by "day" in all the manuscript. Also Section 2.4 will be suppressed (as title).
-The methodology is based on the use of conventional performance criteria such as RMSE, Pearson correlation coefficient and ratio test in the comparison of the maps obtained by interpolating ground observations and those obtained using WRF predictions. In addition more sophisticated performance criteria such as SAL and FSS are used because they consider the internal spatial variability of the rainfall fields. Moreover, the methodology adopts the combination of PBL and Cu schemes assuming a given MP scheme. The criteria as rescaled and summed in order to base the comparison on a single composed criterion.
-the analysis is applied to the study of 4 days representing different conditions with respect to rainfall amounts and spatial variability. Results show that no single scheme can be recommended for the 4 studied days. The more difficult to be predicted are the day displaying the greatest rainfall amounts (12/1/2009) and that with the highest spatial variability (13/9/2008).
The objectives of the work are not clearly established, and the low quality writing makes very difficult to find a storyline.
Response: Thank you for critical feedback. We ensure that the overall purpose of the study will be more clearly defined.
WRF has many parametrizations the most common in the literature sensitive parametrizations for rainfall localization and intensity, are Cu, and much less PBL and Mp (Hewitson et al.2004;Tadross et al.2006). In this study, for each day, we will need to do 792 simulations (Cu with 11 schemes, PBL with 9 schemes and Mp with 8 schemes) to get a satisfactory configurations which can be find only with testing numerous physical parameterizations. 10 simulations takes in average 4 days which depends on the UIB department server availability. Also, usually we should run again about 20% of the simulations each time because of WRF crash or internet interruption. Then, for the 792 simulations we will need 380 days for each event. It is clear that the simulations duration is very long and it should be reduced with conservation of the performance of the WRF rainfall estimation. The aim of this study is to choose the best representing schemes of extreme rainfall by WRF over Northern Tunisia which will make the use of WRF more efficient for users in short time.
In general, the article is written in a fuzzy and lazy way. This makes very difficult to follow it and understand the message that the authors try to send. For all these reasons, I cannot recommend this paper for publication.

Response:
We ensure that the revised manuscript will be edited by a native English speaker to improve comprehension and quality.
The authors should rewrite the article again, trying to give it a rational structure, a more complete and rational exposition of the configuration of the experiments carried out, and a more detailed and clarifying analysis of the results.

Response:
Thank you for the suggestion. In the updated manuscript, we will ameliorate the redaction quality of the whole paper, add deeper discussion, compare our results with many previous founds as suggested.

Below I list as an example some of the points on which I base my review l-15. latitude should be location
Response: Yes, thank you. l-22. "What schemes?" Response: WRF is based on parameters representing the various physical processs. We consider particularly Cumulus (Cu), Planetary boundary level (PBL) and micro physics (MP).These parameters have many options which depend of the physical process complexity. These options are what we call "schemes". The schemes description is presented in Table 1. They are 9 different schemes for representing Cu and 11 for representing PBL.
-After line 58. What are your objectives? What do you can provide as new knowledge?
Response: the reviewer is right. The literature review shows that the performance of the parameterization of WRF is not known a priori. No best parameterization can be recommended for a given case study. It depends on the metrics used for evaluation, and on the case study itself (the geographical region and the type of rainfall event). All previous mentioned research examines few schemes from each parameter. It is the first sensitivity study for rainfall estimation over Tunisia. The originality of this research appears in two components. Firstly, we will test all the schemes of each parameter. Secondly, we will choose not one best combination but the 10 best combinations which will be averaged later to give an ensemble map. This ensemble map will give the best estimation in comparison with all the other individual combinations. Secondly, based on the sensitivity study we selected 3 best schemes for each parameter (PBL, Cu) which have the ability to give a good results for the various extreme event types. l-63. In situ data....Observations??
Response: In situ data are observed rainfall amounts using the national rainfall network of Tunisia. Observations are daily rainfall.

l-68. spatial resolution?
Response: interpolation of in situ data is achieved using a 10 km spatial resolution l-72,94. Where do you interpolate precipitation data? Some information about the mesh must be provided.
Response: the mesh is 10 km. It is represented in figure 1. l-94. Why interpolate data?? In fact, the results of the crossvalidation show not very good results.

Response:
The in-situ stations are not well scattered in the 10 km resolution. Some pixels have 5 stations and many others pixel without any information. That is why we interpolated data. Other approaches may be used such as comparing WRF grid nodes with the nearest observed locations. l-112 are these the variables you use to build initial and boundary conditions. This has no sense. 122 (ERA) is dynamically downscaled using WRF to obtain downscaled reanalysis at 10 km resolution.
Response: paragraph 108-122 is aimed to briefly describe the ERA-Interim global atmospheric reanalysis variables and WRF model. We will rewrite it in clearer way.