Mistral and Tramontane are wind systems in southern France and the western Mediterranean
Sea. Both are caused by similar synoptic situations and channeled in valleys. Their relevance for the climate of the western Mediterranean region motivated this work. The representation of Mistral and Tramontane in regional climate simulations was surveyed with the models ALADIN, WRF, PROMES, COSMO-CLM, RegCM, and LMDZ. ERA-Interim and global CMIP5 simulations (MPI-ESM, CMCC-CM, HadGEM2-ES, and CNRM-CM5) provided the lateral boundary data for the regional simulations regarding the 20th century and two representative concentration pathways for the 21st century (RCP4.5 and RCP8.5).

A Mistral and Tramontane time series, a principal component analysis of pressure fields, and a Bayesian network were combined to develop a classification algorithm to identify pressure patterns in favor of Mistral and Tramontane. The regional climate models were able to reproduce the observed climatology of Mistral and Tramontane. Compared to observational data (SAFRAN and QuikSCAT), the simulations underestimate the wind speed over the Mediterranean Sea, mainly at the borders of the main flow. Simulations with smaller grid spacing showed better agreement with the observations. 

A sensitivity study tested the influence of the Charnock parameter on the Mistral wind field. Its value impacted both wind speed and wind direction. Decreasing the orographic resolution in idealized simulations using COSMO-CLM caused a reduction in wind speed and a broader flow area. Including a parameterization for subgrid scale orography improved the simulation. However, an accurate simulation of Mistral and Tramontane still requires a high-resolution orography.

The classification algorithm also was applied to pressure fields from regional climate simulations driven by global simulation data. At the end of the 21st century, only small, non-significant changes in the number of Mistral days per year occur in the projection simulations. The number of Tramontane days per year decreased significantly.