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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.
The aim of this study is a better understanding of radiation processes in regional climate models (RCMs) in order to quantify their impact and to reduce possible errors. A first important task in finding an answer to this question was to examine the accuracy of the components of the radiation budget in regional climate simulations. To this end, the simulated radiation budgets of two regional climate simulations for Europe were compared with a satellite-based reference. In the simulations with the RCM COSMO-CLM there were some serious under- and overestimations of short- and long-wave net radiation in Europe. However, taking into account the differences in the reference datasets, the results of the COSMO-CLM were quite satisfactory.
Using statistical methods, the influence of potential sources of uncertainties was estimated. Uncertainties in the cloud cover and surface albedo had a significant impact on uncertainties in short-wave net radiation, the explained variance of uncertainties in cloud cover was two to three times higher than that of uncertainties in surface albedo. Uncertainties in the cloud cover resulted in significant errors in the net long-wave radiation. However, the influence of uncertainties in soil temperature on errors in the long-wave radiation budget was low or even negligible. These results were confirmed in a comparison with simulations of the REMO and ALADIN regional climate models. It is reasonable to expect that a better parameterization of relatively simple parameters such as cloud cover and surface albedo is a means of significantly improving the simulation of radiation budget components in the COSMO-CLM.
An important question for the application of RCMs is to examine whether the results of radiation uncertainties and their impact factors are comparable if the model is applied in a region that is not the one for which it was originally created. Comparisons of the simulated radiation budgets of different RCMs for West Africa showed that problems in the simulation of short- and long-wave radiation fluxes were a widespread problem. Most of the tested models showed some considerable under- or overestimation of the short- and long-wave radiation fluxes.
Similar to Europe uncertainties in cloud cover were also in the simulations for Africa a significant factor affecting uncertainties in the simulated radiation fluxes. However, for the African simulations uncertainties in the parameterization of surface albedo were much more important than in Europe. On average, overland uncertainties in the cloud cover and surface albedo were of similar importance. Uncertainties in soil temperature simulations were of higher importance in Africa, and reached overland similar values of the mean explained variance (R2 ≈ 0.2) such as uncertainties in the cloud cover. This indicates a geographical dependence of the model error. This study confirmed the assumption that an improved parameterization of relatively simple parameters such as the surface albedo in RCMs leads to a significant improvement in the modeled radiation budget, particularly in Africa.
The influence of errors in the simulated radiation budget components on the simulation of climate processes, such as the West-African monsoon (WAM), was investigated in a next step. The evaluation of ERA-Interim and ECHAM5 driven COSMO-CLM simulations for Africa showed that the main features of the WAM were well reproduced by the model, but there were only slight improvements compared to the driving data. The index of convective activity in the model simulations was much too high and precipitation was underestimated in large parts of tropical Africa. The partly considerable differences between the ERA-Interim and ECHAM5 driven simulations demonstrated the sensitivity of the RCM to the boundary conditions and in particular to the sea surface temperature. An excessive northwards shift of the monsoon in the model was influenced by the land-sea temperature gradient and the strength of the Saharan heat low. Consequently, a part of the error was due to the driving data and the model itself produced another part.
By modifying the parameterization of the bare soil albedo the errors in the radiation budget and 2 m temperature in the Sahara region were significantly reduced. Similarly, the overesti-mation of precipitation and convection has been reduced in the Sahel. The effect of this modifi-cation on the examined WAM area was low. This confirmed that especially in desert regions, errors in the surface albedo were a driving factor for errors in the radiation budget. However, there are other important factors not yet sufficiently understood that have a strong influence on the quality of the simulation of the WAM.
The analysis of the actual state, the quantification of error sources and the highlighting of connections made it possible to find means to reduce uncertainties in the simulated radiation in RCMs and to have a better understanding of radiation processes. However, the magnitude of the errors found, the number of possible influencing factors, and the complexity of interactions, indicate that there is still a need for further research in this area.