The statistical model developed in this study can be applied to climate Forskolin mouse model simulations of the atmosphere to simulate historical wave climate. The resulting historical wave climate can then be compared with an observation or reanalysis dataset, to assess the collective skill of the statistical model and the related climate model in representing historical wave climate. The statistical model can also be applied to projections of the atmosphere by multiple climate models for multiple

emission scenarios. The results can be analyzed to comprehensively quantify inter-model and inter-scenario uncertainties. With the emerging of high resolution projections of the atmosphere by high resolution climate models (such as CMIP5 simulations), it would be also interesting to see if the RCM downscaling step is still necessary in this case. These are interesting topics for future research. This research was carried out within the frame of the Ph.D. program of the first author during her visiting research stay in Climate Research Division of Environment Canada, which was funded by the Ministerio de Educación   (Spanish Ministry of Education). The first author also acknowledges the support received by the Col  ··legi d’Enginyers de Camins, Canals

i Ports (Civil Engineering Association in Catalonia). The authors are grateful to the Organismo Público Puertos del Estado (Spanish Ports and Harbors Authority)

for providing HIPOCAS (wave and atmospheric) data that served to calibrate and validate the statistical Venetoclax Ergoloid model. We also gratefully acknowledge the research centers and institutions that have freely and disinterestedly provided us with the atmospheric climate projections datasets used in this study to project the future wave climate: Danmarks Meteorologiske Institut(DMI, Denmark) – special thanks to Ole B. Christensen, Neil Mackellar and Fredrik Boberg; Koninklijk Nederlands Meteorologisch Instituut (KNMI, The Netherlands) – special thanks to Erik van Meijgaard; Insitut für Meterologie (MPI, Germany) – special thanks to Daniela Jacob and Alberto Elizalde; Sveriges Meteorologiska och Hydrologiska Institut (SMHI, Sweden) – special thanks to Erik Kjellström and Barry Broman. “
“The K-Profile Parameterization (Large et al., 1994) is a commonly employed vertical mixing scheme that parameterizes turbulent fluxes in the ocean boundary layer. Historically, evaluation of the KPP against data have been difficult because of a lack of sufficiently accurate observations of the wind forcing at the ocean surface and turbulent fluxes in the ocean boundary layer. Large et al. (1994) summarized a list of observational tests that almost exclusively focused on convective rather than wind shear mixing processes. This list of tests include wind deepening from the inertial oscillation (Pollard et al.