|ABSTRACT||Land-surface variables play an essential role in predicting the potential effect of climate change, particularly in the Mediterranean region where a strong coupling land-atmosphere occurs at least during warm seasons. In this framework, Regional Climate Model (RCMs) are able to resolve land-surface processes with more detail than Global Climate Models (GCMs), which is needed to adequately represent variables such as the surface evapotranspiration or the soil moisture content. This work aims to evaluate the skill of the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model (LSM) to represent land-surface variables over the Iberian Peninsula (IP).
Thus, three 35-year (1980-2014) runs were completed using WRF over a domain centered in the IP with a 0.088 degrees of spatial resolution (c.10 km) and nested in a coarser domain that corresponds to the 0.44 EURO-CORDEX domain (c. 50 km). The simulations were conducted by the bias-corrected outputs from two CMIP5 GCMs: the version 1 of NCAR’s Community Earth System Model (CESM1) and the Max Planck Institute’s Earth System Model at Low Resolution (MPI-ESM-LR). Additionally, a simulation driven by the ECMWF ERA-Interim Reanalysis dataset was also carried out in order to examine uncertainties associated with the RCM.
The evaluation consisted of the direct comparison of surface evapotranspiration and soil moisture content from WRF and those from the Global Evaporation Amsterdam Model (GLEAM) at annual and seasonal scale.
In general, results revealed that the WRF model, although with a certain difficulty, represented quite well the spatiotemporal variability of land-surface variables. This suggests that WRF is a valuable tool to study the potential effects of climate change in regions with important land-surface-atmosphere feedbacks such as the IP.
Key Words: Regional Climate Models, WRF, land-surface variables, Iberian Peninsula.
ACKNOWLEDGEMENTS: This work has been financed by the projects CGL2013-48539-R (MINECO-Spain, FEDER) and CGL2017-89836-R (MINECO-Spain, FEDER).|