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Europe is investing considerably in renewable energies for a sustainable future, with both Iberian countries (Portugal and Spain) promoting significantly new hydropower, wind, and solar plants. The climate variability in this area is highly controlled by just a few large-scale teleconnection modes. However, the relationship between these modes and the renewable climate-dependent energy resources has not yet been established in detail. The objective of this study is to evaluate the impact of the North Atlantic Oscillation (NAO) on the interannual variability of the main and primary renewable energy resources in Iberia. This is achieved through a holistic assessment that is based on a 10-km-resolution climate simulation spanning the period 1959-2007 that provides physically consistent data of the various magnitudes involved. A monthly analysis for the extended winter (October-March) months shows that negative NAO phases enhance wind speeds (10%-15%) and, thereby, wind power (estimated around 30% at typical wind-turbine altitudes) and hydropower resources (with changes in precipitation exceeding 100% and implying prolonged responses in reservoir storage and release throughout the year), while diminishing the solar potential (10%-20%). Opposite signals were also sporadically identified, being well explained when taking into account the orography and the prevailing wind direction during both NAO phases. An additional analysis using real wind, hydropower, and solar power generation data further confirms the strong signature of the NAO.

This paper reports on an evaluation of the relative roles of choice of parameterization scheme and terrain representation in the Weather Research and Forecasting (WRF) mesoscale model, in the context of a regional wind resource assessment. As a first step, 32 configurations using two different schemes for microphysics, cumulus, planetary boundary layer (PBL), or shortwave and longwave radiation were evaluated. In a second step, wind estimates that were obtained from various experiments with different spatial resolution (1, 3, and 9 km) were assessed. Estimates were tested against data from four stations, located in southern Spain, that provided hourly wind speed and direction data at 40 m above ground level. Results from the first analysis showed that wind speed standard deviation (STD) and bias values were mainly sensitive to the PBL parameterization selection, with STD differences up to 10% and bias differences between −15% and 10%. The second analysis showed a weak influence of spatial resolution on the STD values. On the other hand, the bias was found to be highly sensitive to model spatial resolution. The sign of the bias depended on terrain morphology and the spatial resolution, but absolute values tended to be much higher with coarser spatial resolution. Physical configuration was found to have little impact on wind direction distribution estimates. In addition, these estimates proved to be more sensitive to the ability of WRF to represent the terrain morphology around the station than to the model spatial resolution itself.

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