"Over the past 25 years, the modeling community achieved steady progress in dynamical climate predictions, with skill level that is now considered useful for some societal applications at the seasonal time-scale. However, major factors such as coupled models errors, initialization strategies and unconstrained physical parameterizations are still substantially limiting predictability, particularly over land areas. Long-term improvements in climate predictions must necessarily come by (i) improved understanding and description of the physical processes through dedicated process studies and observations. In the meanwhile, (ii) the multi-model approach can be used combining the imperfect models available to enhance predictions. Progresses in both objectives (i) and (ii) need more international collaborative efforts.By implementing collaboration between European and Asian-Pacific climate prediction communities, this project will largely contribute to objective (ii). In fact, five European and seven Asian Pacific climate prediction systems will be collected to form a grand multi-model. The maximum level of multi-model prediction performance currently attainable will be assessed and innovative techniques will be developed in order to evaluate achievable and attained forecast skill over land and the related multi-model capability to enhance usefulness.The project will contribute to objective (i) by improving land surface-vegetation representation in at least one of the multi-model components (i.e: IPRC global climate model). In particular, effort will be made on assessing the impact of improved land surface on simulation and prediction of the Indian summer monsoon (ISM) and then, in turn, on those of Euro-Mediterranean climate during boreal summer, which is related to global teleconnection patterns emanating from the ISM."