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New climate modelling and new climate analysis tools

Samuel Somot, Météo-France/CNRM, France

In the CLIM-RUN project, the WP2 is in charge of developing and applying new climate modelling tools as well as new climate analysis tools in order to answer the stakeholder demands for climate services. This full bottom-up approach is quite new for most of the climate researchers involved in WP2, compared to former, less innovative EU projects dealing with climate modelling. However, we deeply believe that it prepares future climate service organisation system.

To full-fill this goal, WP2 had to hire specialists of various fields in climate modelling: Regional Climate Modelling (RCM), Global Climate Modelling (GCM), seasonal, decadal and centennial time scales, past variability and future scenario, uncertainty assessment, etc. with a common interest in exploring climate variability in the Mediterranean region. This could be achieved thanks to the participation of ENEA, ICTP, CMCC, USMD, IC3 and Météo-France/CNRM (WP2 leader) in WP2.

The main material used in WP2 to answer the stakeholder needs is as follows:

The first project year was dedicated to the following main tasks:

The figure on the left shows the domain of the new high-resolution RCM models (12 km + sub-grid tiling at 2 km) to be developed within CLIM-RUN by ICTP and CNRM and dedicated to the study of the Mediterranean climate change. It is worth noting the quality of the representation of the Mediterranean orography and coastline as well as the possibility for the first time to study small Mediterranean islands. On the right hand, an illustration of a probability way of assessing regional climate change using the ENSEMBLES RCM runs for temperature and precipitation for a given case study is provided. Comment: the most probable change is here +1.7°C and -0.2 mm/d but this figure also allows to underline that the sign of the precipitation change is highly uncertain and that the “no warming” state is quite impossible whereas a warming less than 3°C has a probability of 90%. We let you guess where it is and for which temporal horizon!