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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.

Abstract. This is the first of two papers that documents the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. An optimal combination of model setup and parameterisations was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They confirmed that the largest differences in annual mean wind speed at 100 m above ground level mostly coincide with areas of high surface roughness length and not with the location of the domains or maximum wind speed. Then an ensemble of more than 50 simulations with different setups for a single year was carried out for one domain covering Northern Europe, for which tall mast observations were available. Many different parameters were varied across the simulations, for example, model version, forcing data, various physical parameterisations and the size of the model domain. These simulations showed that although virtually every parameter change affects the results in some way, significant changes on the wind climate in the boundary layer are mostly due to using different physical parameterisations, especially the planetary boundary layer scheme, the representation of the land surface, and the prescribed surface roughness length. Also, the setup of the simulations, such as the integration length and the domain size can considerably influence the results. The degree of similarity between winds simulated by the WRF ensemble members and the observations was assessed using a suite of metrics, including the Earth Mover's Distance (EMD), a statistic that measures the distance between two probability distributions. The EMD was used to diagnose the performance of each ensemble member using the full wind speed distribution, which is important for wind resource assessment. The most realistic ensemble members were identified to determine the most suitable configuration to be used in the final production run, which is fully described and evaluated in the second part of this study.

Abstract. Energy exchanges among climate subsystems are of critical importance to determine the climate sensitivity of the Earth's system to greenhouse gases, to quantify the magnitude and evolution of the Earth's energy imbalance, and to project the evolution of future climate. Thus, ascertaining the magnitude and change of the Earth's energy partition within climate subsystems has become urgent in recent years. Here, we provide new global estimates of changes in ground surface temperature, ground surface heat flux and continental heat storage derived from geothermal data using an expanded database and new techniques. Results reveal markedly higher changes in ground heat flux and heat storage within the continental subsurface than previously reported, with land temperature changes of 1 K and continental heat gains of around 12 ZJ during the last part of the 20th century relative to preindustrial times. Half of the heat gain by the continental subsurface since 1960 have occurred in the last twenty years.

Abstract. Past climate variations may be known from reconstruction methods that use proxy data as predictors. Among them, borehole reconstructions is a well established technique to recover the long term past surface air temperature (SAT) evolution. It is based on the assumption that SAT changes are strongly coupled to ground surface temperature (GST) changes and transferred to the subsurface by thermal conduction. We evaluate the SAT-GST coupling during the last millennium (LM) using simulations from the Community Earth System Model LM Ensemble (CESM-LME). The validity of such premise is explored by analyzing the structure of the SAT-GST covariance during the LM and also by investigating the evolution of the long term SAT-GST relationship. The multiple and single-forcing simulations in the CESM-LME are used to analyze the SAT-GST relationship within different regions and spatial scales and derive the influence of the different forcing factors on producing feedbacks mechanisms that alter the energy balance at the surface. The results indicate that SAT-GST coupling is strong at global and above multi-decadal time scales in the CESM-LME however a relative small variation in the long term SAT-GST relationship is also represented. Although at global scale such variation does not impact significantly the SAT-GST coupling, at local to regional scales this relationship experiences considerable long term changes mostly after the end of the 19th century. Land use land cover (LULC) changes are the main driver for decoupling SAT and GST locally and regionally since they modify the land surface properties such as albedo, surface roughness and hydrology, and thus the energy fluxes at the surface. Snow cover feedbacks due to the influence of other external forcing are also important for corrupting the long term SAT-GST coupling. Our findings suggest that such local and regional SAT-GST decoupling processes may represent a source of bias for SAT reconstructions from borehole measurement since the thermal signature imprinted in the subsurface over the affected regions is not fully representative of the long term SAT variations.