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P. A. Jiménez, E. García-Bustamante, J. F. González-Rouco, F. Valero, J. P. Montávez, and J. Navarro


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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Etor E. Lucio-Eceiza, J. Fidel González-Rouco, Elena García-Bustamante, Jorge Navarro, Cristina Rojas-Labanda, and Hugo Beltrami


The variability of the surface zonal and meridional wind components over northeastern North America during June–October is analyzed through a statistical downscaling (SD) approach that relates the main wind and large-scale circulation modes. An observational surface wind dataset of 525 sites over 1953–2010 provides the local information. Twelve global reanalyses provide the large-scale information. The large-to-local variability of the wind field can be explained, to a large extent, in terms of four coupled modes of circulation explaining a similar amount of variance. The SD method is mostly sensitive to the number of retained modes and subregionally to the large-scale information variable, but not to the reanalysis source. The SD methodological uncertainty based on the use of multiple configurations is directly related to the variability of the wind, similar in relative terms for both components. With an adequate choice of parameters the SD estimates provide more realistic variances than the reanalysis wind, although their correlations with respect to observations are lower than the latter. Additionally, while these different SD estimations are very similar on the reanalysis used, the various reanalysis wind fields show noticeable differences, especially in their variances. The wind variability is reconstructed back to 1850, making use of century-long reanalyses and two additional SLP gridded datasets, which allows estimating the variability at decadal to multidecadal time scales. Recent negative (significant) trends in the zonal component do not stand out in the multidecadal context, but they are consistent with a global stilling process, and are partially attributable to changes in the large-scale dynamics.

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