In this study, we assess the relationships between North Atlantic scale atmospheric regimes and extremes of precipitation and minimum temperature in the Iberian peninsula for an extended (DJFM) winter season. As found in previous studies, large scale atmospheric regimes are well represented in climate simulations while the extreme atmospheric variability is not. The relationship between some of these atmospheric regimes and the probability of occurrence of extreme values in simulations of present day climatic variability is validated here with daily observations at 68 meteorological stations all over the Iberian peninsula. Therefore, the possible changes in the probability of occurrence of winter extremes of minimum temperature and precipitation are obtained by projecting the changes in the probability of occurrence of the winter atmospheric regimes. The trends in the frequency of the observed large scale patterns give an indication of what can be expected in the next decades. For the long term (in a century), the changes are obtained directly from the comparison of the frequencies of the atmospheric regimes in the scenario simulations with those of the historical period. The projections obtained in this way are tested for consistency with the results obtained by comparing the changes in the extremes threshold values in the scenario with those of the historical simulations. The results point to a future with less precipitation extreme events and less minimum temperature extreme events in winter in the westerly central part of the Iberian peninsula.

Offshore wind energy is a promising resource for renewable energy development. Reanalysed wind data are unmatched by other wind data sources in providing a long-term assessment of wind power potential. In this study, 10 of the selected offshore locations close to the Moroccan coast were used to evaluate the ERA5 wind reanalysis dataset against the IFREMER-blended observational dataset covering the years 1993–2016. The ERA5 wind data’s capacity to represent wind variability in the area was confirmed by the results of the statistical methodologies used. All the reanalysed data scored better at capturing the observed wind variability at the southern sites than at the northern ones, where the wind variability was more complex. In a long-term evaluation from 1981 to 2020, the wind power potential in the Moroccan Atlantic coast was found to be very stable except in the northern sites and between Agadir and Bou Arich. Seven of the 10 sites considered were ranked as promising sites for offshore wind power generation, with wind power densities above 420 W/m² at 100 m in height. Additionally, the change in signs in the variability toward the middle of the ERA5 record, which was seen at all locations and was also evident in the observations, did not significantly affect the yearly wind power density. However, the seasonal distribution of the latter was modified according to the local features of the seasonal variability.

Greenhouse gases emissions modify the radiative balance of the Earth, causing changes in its climate. Climate Change is considered one of the greatest threats to economic and social stability. Aviation is responsible for around a 2.5% of greenhouse gases emissions. This contribution is steadily increasing, thus the interest of assessing the impacts that different policies might have on it. The simple feedback model proposed here was intended as a tool in order to investigate the stabilization issue. The model was based on the relationship between the number of air traffic passengers and the associated CO₂ emissions. It incorporated a representation of the feedback of the technological innovation on the emissions rate and of those of the socioeconomic response to the climatic impact on the passengers number. The model parameters were estimated using data from a variety of robust air traffic sources. However, it was found that neither of the feedback terms succeeded at stabilizing the emissions, although they might slow down their growth. In addition, there is also a nonlinear version of the model that includes a representation of the passengers perception of insecurity, similar to the one experienced in the current pandemic. This model favors the stability of both, the number of passengers and CO₂ emissions, as it would also be able to control unprecedented situations.

The Niño3.4 region predictability beyond the persistence barrier