VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques. Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on). Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value-cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value-cost.eu/validationportal.

The observed trend towards warmer and drier conditions in southern Europe is projected to continue in the next decades, possibly leading to increased risk of large fires. However, an assessment of climate change impacts on fires at and above the 1.5 °C Paris target is still missing. Here, we estimate future summer burned area in Mediterranean Europe under 1.5, 2, and 3 °C global warming scenarios, accounting for possible modifications of climate-fire relationships under changed climatic conditions owing to productivity alterations. We found that such modifications could be beneficial, roughly halving the fire-intensifying signals. In any case, the burned area is robustly projected to increase. The higher the warming level is, the larger is the increase of burned area, ranging from ~40% to ~100% across the scenarios. Our results indicate that significant benefits would be obtained if warming were limited to well below 2 °C.

Summer fires frequently rage across Mediterranean Europe, often intensified by high temperatures and droughts. According to the state-of-the-art regional fire risk projections, in forthcoming decades climate effects are expected to become stronger and possibly overcome fire prevention efforts. However, significant uncertainties exist and the direct effect of climate change in regulating fuel moisture (e.g. warmer conditions increasing fuel dryness) could be counterbalanced by the indirect effects on fuel structure (e.g. warmer conditions limiting fuel amount), affecting the transition between climate-driven and fuel-limited fire regimes as temperatures increase. Here we analyse and model the impact of coincident drought and antecedent wet conditions (proxy for the climatic factor influencing total fuel and fine fuel structure) on the summer Burned Area (BA) across all eco-regions in Mediterranean Europe. This approach allows BA to be linked to the key drivers of fire in the region. We show a statistically significant relationship between fire and same-summer droughts in most regions, while antecedent climate conditions play a relatively minor role, except in few specific eco-regions. The presented models for individual eco-regions provide insights on the impacts of climate variability on BA, and appear to be promising for developing a seasonal forecast system supporting fire management strategies.

SummaryMast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown .Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations.Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time.These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data.