## 4 Discussion and Conclusions
Nevertheless, it was found (e.g., the surface rain rate) that sometimes the WSM6 scheme, compared to the more complex WDM6, obtained better results despite being single-moment only, which means that using a more complex scheme does not always translate into improving the model performance. For these reasons, it would make sense to increasingly focus on operational TLC forecasting efforts using ensemble approaches, incorporating the multiple benefits of diverse but enriching microphysical parameterization schemes. Last but not least, it is important to comment on the limitations of this study. It was designed to examine only the mature phase of TLC Ianos coinciding with the overpass of the GPM-CO DPR and MetOp-C ASCAT sensors. We focused on a relatively short lead time (12 h) forecast with 6 h considered as spin-up while the Ianos lifecycle was much longer. Furthermore, we tested just a few parameterization schemes within one of the physical categories, whereas it is known that, even if probably not as important as the microphysics, the PBL and surface layer parameterizations also play a prominent role in the correct model prediction of medicanes, according to several studies [27; 29]. In spite of these limitations, this study was aimed at highlighting the key role of satellite observations (in particular, ASCAT surface winds and GPM precipitation measurements) in assessing the medicane forecast performance in terms of intensity and ability to reproduce the precipitation microphysics structure, especially offshore, where often no other wind or precipitation measurements are available. It is important to note that the comparison between the model microphysical output and the GPM-CO observations gave the opportunity to assess the performance of the microphysical schemes used in numerical models in simulating several aspects of the hydrometeors as their phases and dimensions. This gave the opportunity to have a deeper knowledge of the strengths and weaknesses of the different schemes and to refine the microphysical parameterizations of the models. Lastly, we would like to make an open appeal to the community to consider making an official best track reanalysis product for medicanes, as we are sure it would have improved this study and would benefit many more in the future. Conceptualization, A.C.P., S.F. and G.P. ; methodology, A.C.P., S.F., L.P.D. and G.P. ; software, A.C.P., S.F., R.C.T. and L.P.D. ; validation, A.C.P., S.F., R.C.T. and L.P.D. ; investigation, A.C.P., S.F., L.P.D. and G.P. ; data curation, A.C.P., S.F. and L.P.D. ; writing--original draft preparation, A.C.P. ; writing--review and editing, all authors; project administration, G.P. and S.D. ; funding acquisition, S.D. All authors have read and agreed to the published version of the manuscript. This work was partially funded by the Project PON ARS01 00405 OT4 CLIMA Sviluppo di tecnologie innovative di Osservazione della Terra per lo studio del Cambiamento Climatico e dei suoi impatti sull'ambiente (Development of innovative Earth observation technologies for the study of climate change and its impacts on the environment), funded by the Italian Ministry of Education, University, and Research (MIUR) in the framework of the National Operational Program (PON) Research and Innovation 2014-2020, Specialization Area Aerospace. Not applicable. The WRF simulations outputs and GPM-CO DPR data can be requested from the authors. The ASCAT data can be found on the website [[https://podaac.jpl.nasa.gov/dataset/ASCATC-L2-Coastal](https://podaac.jpl.nasa.gov/dataset/ASCATC-L2-Coastal)]([https://podaac.jpl.nasa.gov/dataset/ASCATC-L2-Coastal](https://podaac.jpl.nasa.gov/dataset/ASCATC-L2-Coastal)) (last accessed on 14 January 2021). ECMWF and the Aeronautica Militare (Italian air force) are acknowledged for the use of MARS (Meteorological Archive and Retrieval System) database. The reviewers and the editor are acknowledged for their comments that improved the quality of the paper. The authors declare no conflict of interest.