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  • Author or Editor: J. P. Montávez x
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P. A. Jiménez, E. García-Bustamante, J. F. González-Rouco, F. Valero, J. P. Montávez, and J. Navarro

Abstract

Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying connections between wind in each subregion and sea level pressure fields. The results of this work contribute to the characterization of wind variability in a complex terrain region and constitute a framework for the validation of mesoscale model wind simulations over the region.

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S. Jerez, R. M. Trigo, S. M. Vicente-Serrano, D. Pozo-Vázquez, R. Lorente-Plazas, J. Lorenzo-Lacruz, F. Santos-Alamillos, and J. P. Montávez

Abstract

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.

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Pedro A. Jiménez, J. Fidel González-Rouco, Elena García-Bustamante, Jorge Navarro, Juan P. Montávez, Jordi Vilà-Guerau de Arellano, Jimy Dudhia, and Antonio Muñoz-Roldan

Abstract

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999–2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one’s understanding of the wind variability over the area. The subregions identified with the simulation during the 1992–2005 period are similar to those identified with observations (1999–2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.

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