As you probably know, there are a wide range of models that its correct or incorrect results depend on its testing. Therefor in my opinion there aren't any wondering if you decide to utilize WRF Model for your purpose as around the world you can find a considerable number of articles that ran by WRF. Finally, WRF is a meteorological model and for its run you don't need extra time in spite of it can be followed good and suitable results.

I should recommend to verify WRF also with GOES satellite imagery and associated PGE for Total precitation wáter and different channels of WV and IR; radar and lightning networks are also recommended. Nowcasting ans very short range forecasting with WRF has also to be checked and completed with all this tools in tropical-equatorial latitudes due to thunderstorms and MSC mesoescale complex systems. High resolution of WFR may be not enough. You can find details in the Spanish useful references of Ricardo Riosalido and Olinda Carretero can complete this info. (Technical Notes of AEMET, Madrid, Spain, number 37 and 38 of "Servicio de Técnicas de Análisis y Predicción: STAP)

Dear thanks for your question

I would ask you to read some papers over that region and follow the options they have used in namelist. this is the only shortcut but if you have time then I would like to recommend you to test the model as even domain configuration has relation with the physical paramterization (the options you used in namelist), similarly it also depends on your ultimate goals.

Cheers!

 WRF model is widely used model and reasonably performing better especially in mesoscale weather systems. The model configuration consists of physics and dynamical aspects. In the physical aspects the physical and dynamical interactions from surface through LSM + PBL + CUMULUS + CLOUD MICROPHYSICS parameterization schemes. Each of these schemes represent the physical processes different from each other. Hence the researcher who wish to use this modeling system should know the physical and dynamical aspects of the weather system they wish to simulate. Based on that do the customization of the model by conducting series of numerical experiments of different combination of the schemes and as well as grid resolutions. After validation with available observations one can customise it for its integration over the study domain. No model would be perfect t. After analyse you should understand where the model is not performing and try to improve the physics or other aspects of the model. You can read my papers on these aspects. All the best with your work and hope my answer is useful to your work.

Hi Cazorla,

You have mentioned that your domain is  over the equatorial Andes in South America, which has  very complex topographic distribution. I do not know how big is your domain and at what resolution you are planning to run WRF and how many nest? 

WRF model's physical parameterization depends on the all the above above factors. If you look at available literature on WRF models sensitivity analysis then you will see that nearly all study concluded their papers as saying that do not choose physical parameterization combinations based on other study as WRF results depends on season, study location, variables of interest, domain size, length of simulation.

In my PhD research, I have done a comprehensive sensitivity analysis of WRF model over Canada and find that WRF results are sensitive to the above listed factors. 

Nevertheless, you will not find any other places which has steep mountain (Andes) and very cold ocean (East pacific). So, I would suggest you to do a small ensemble sensitivity experiment over your domain if you have computing resources and time.

Last but not least, I would strongly suggest you not to follow blindly other peoples selections. 

I hope that helps.

Thanks