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.

[1] This paper compares six statistical downscaling models (SDMs) and three regional climate models (RCMs) in their ability to downscale daily precipitation statistics in a region of complex topography. The six SDMs include regression methods, weather typing methods, a conditional weather generator, and a bias correction and spatial disaggregation approach. The comparison is carried out over the European Alps for current and future (2071-2100) climate. The evaluation of simulated precipitation for the current climate shows that the SDMs and RCMs tend to have similar biases but that they differ with respect to interannual variations. The SDMs strongly underestimate the magnitude of the year-to-year variations. Clear differences emerge also with respect to the year-to-year anomaly correlation skill: In winter, over complex terrain, the better RCMs achieve significantly higher skills than the SDMs. Over flat terrain and in summer, the differences are smaller. Scenario results using A2 emissions show that in winter mean precipitation tends to increase north of about 45°N and insignificant or opposite changes are found to the south. There is good agreement between the downscaling models for most precipitation statistics. In summer, there is still good qualitative agreement between the RCMs but large differences between the SDMs and between the SDMs and the RCMs. According to the RCMs, there is a strong trend toward drier conditions including longer periods of drought. The SDMs, on the other hand, show mostly nonsignificant or even opposite changes. Overall, the present analysis suggests that downscaling does significantly contribute to the uncertainty in regional climate scenarios, especially for the summer precipitation climate.

ABSTRACT:The evaluation of the possible climate change influence on extreme precipitation is very interesting in the Mediterranean area due to the usual and characteristic high intensities of its rainfall pattern. This analysis is also very important in urban zones, especially those densely populated with complex sewer systems, generally vulnerable to torrential rainfall. In this work, a total of 114 simulated daily rainfall series, 84 for the period 2000-2099 and 30 for the control period 1951-1999, have been analysed. These series were obtained for six thermo-pluviometric stations located in the metropolitan area of Barcelona using the information provided by five general circulation models under four future climate scenarios of greenhouse gas emissions and applying statistical downscaling methods. The potential changes in the intensity-duration-frequency relationships due to climate change have been investigated. For the last third of the 21st century, under A1B, A2 and B2 climate scenarios, an increase of at least 4% has been found on the expected daily rainfall with return period longer than 20 years. Using a temporal downscaling based on scaling properties of rainfall, future hourly extreme rainfall has been estimated. For almost all the scenarios and periods considered, the increase on the expected hourly rainfall has resulted slightly higher than the corresponding daily rainfall. The greatest differences between the future hourly and daily rainfall estimated have been found in the second third of the century under scenarios A1B (8%) and A2 (9%).

This paper addresses the determination of the realized thermal niche and the effects of climate change on the range distribution of two brown trout populations inhabiting two streams in the Duero River basin (Iberian Peninsula) at the edge of the natural distribution area of this species. For reaching these goals, new methodological developments were applied to improve reliability of forecasts. Water temperature data were collected using 11 thermographs located along the altitudinal gradient, and they were used to model the relationship between stream temperature and air temperature along the river continuum. Trout abundance was studied using electrofishing at 37 sites to determine the current distribution. The Representative Concentration Pathways RCP4·5 and RCP8·5 change scenarios adopted by the International Panel of Climate Change for its Fifth Assessment Report were used for simulations and local downscaling in this study. We found more reliable results using the daily mean stream temperature than maximum daily temperature and their respective 7 days moving average to determine the distribution thresholds. Thereby, the observed limits of the summer distribution of brown trout were linked to thresholds between 18·1 and 18·7°C. These temperatures characterize a realized thermal niche narrower than the physiological thermal range. In the most unfavourable climate change scenario, the thermal habitat loss of brown trout increased to 38% (Cega stream) and 11% (Pirón stream) in the upstream direction at the end of the century; however, at the Cega stream, the range reduction could reach 56% due to the effect of a 'warm-window' opening in the piedmont reach.

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