Objective climatology of cyclones in the Mediterranean region: a consensus view among methods with different system identification and tracking criteria

Through the use of the climatic classification of Köppen–Trewartha (K‐T), the ability to reproduce the current climate of Europe has been shown for an ensemble of 15 regional climate model simulations nested in six global climate models. Depending on the simulation, between 55.4 and 81.3% of the grid points are in agreement with observations regarding the location of climate types in current climate simulations (1971–2000). In this respect, the result of the ensemble of 15 simulations is better than that of any individual model, with 83.5% of the grid points in agreement with observations. K‐T classification has also been used to analyse the projected climate change over the 21^st century under the SRES‐A1B emissions scenario. It was found that 22.3% of the grid points in the domain change their climate by the period 2021–2050 compared to current climate and 48.1% change by 2061–2090. The climate shifts affecting the biggest extensions are projected in Central Europe and Fennoscandia, but other smaller areas suffer more intense changes which potentially are more dangerous to vegetation and ecosystems. Generally, these changes occur at a sustained rate throughout the century, reaching speeds of up to 90 × 10³ km² decade⁻¹ in the retreat or expansion of some climates.

As solar energy will be an increasingly important renewable energy source in future years, the study of how climate change affects both its temporal and spatial variability is very relevant. In this paper, we study future changes of the solar radiation resource in the Iberian Peninsula (IP) through a set of simulations from ESCENA project (generation of regionalized scenarios of climate change in Spain with high‐resolution models) until mid‐century. The evaluation of the simulations against observations indicates contrasting biases for the different regional climate models (RCMs) in terms of solar irradiation amount and its inter‐annual variability. We propose a diagnostic for the quality of solar energy resource, in which the gridpoints are classified in four categories depending on the combination of solar irradiation amount and variability. The observed large percentage of points in the optimal category (high irradiation/low variability) in the IP is well‐captured by the RCMs in general terms.The analysis of scenarios indicates a future increase in solar irradiation, although not all scenarios agree in the geographical distribution of this increase. The quality of solar energy resource is projected to increase, mostly due to a decrease in variability. This is an important result, as a more stable inter‐annual resource should decrease the need for backup sources and also reduce inter‐annual electricity price variations. Finally, results from a first approximation to the issue of the ability of solar energy to cover power demand peaks in summer show important differences between regions of the IP. However, the spatially averaged correlation of solar irradiation and summer surface temperatures for the whole IP is rather high, which is a positive result as the strong interconnections of the power grid within the IP could allow a distribution of solar power surpluses in certain regions for such high‐temperature episodes.

Background: Recent reports have suggested that air pollution may impact thyroid function, although the evidence is still scarce and inconclusive. In this study we evaluated the association of exposure to air pollutants to thyroid function parameters in a nationwide sample representative of the adult population of Spain. Methods: The Di@bet.es study is a national, cross-sectional, population-based survey which was conducted in 2008-2010 using a random cluster sampling of the Spanish population. The present analyses included 3859 individuals, without a previous thyroid disease diagnosis, and with negative thyroid peroxidase antibodies (TPO Abs) and thyroid-stimulating hormone (TSH) levels of 0.1-20 mIU/L. Participants were assigned air pollution concentrations for particulate matter <2.5μm (PM_2.5) and Nitrogen Dioxide (NO₂), corresponding to the health examination year, obtained by means of modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). TSH, free thyroxine (FT4), free triiodothyronine (FT3) and TPO Abs concentrations were analyzed using an electrochemiluminescence immunoassay (Modular Analytics E170 Roche). Results: In multivariate linear regression models, there was a highly significant negative correlation between PM_2.5 concentrations and both FT4 (p<0.001), and FT3 levels (p<0.001). In multivariate logistic regression, there was a significant association between PM_2.5 concentrations and the odds of presenting high TSH [OR 1.24 (1.01-1.52) p=0.043], lower FT4 [OR 1.25 (1.02-1.54) p=0.032] and low FT3 levels [1.48 (1.19-1.84) p=<0.001] per each IQR increase in PM_2.5 (4.86 μg/m³). There was no association between NO₂ concentrations and thyroid hormone levels. No significant heterogeneity was seen in the results between groups of men, pre-menopausal and post-menopausal women. Conclusions: Exposures to PM_2.5 in the general population were associated with mild alterations in thyroid function.