Abstract
Abstract. The Pyrenees, located in the transition zone of Atlantic and Mediterranean climates, constitute a paradigmatic example of mountains undergoing rapid changes in environmental conditions, with potential impact on the availability of water resources, mainly for downstream populations. High-resolution probabilistic climate change projections for precipitation and temperature are a crucial element for stakeholders to make well-informed decisions on adaptation to new climate conditions. In this line, we have generated high–resolution climate projections for 21st century by applying two statistical downscaling methods (regression for max and min temperatures, and analogue for precipitation) over the Pyrenees region in the frame of the CLIMPY project over a new high-resolution (5 km × 5 km) observational grid using 24 climate models from CMIP5. The application of statistical downscaling to such a high resolution observational grid instead of station data partially circumvent the problems associated to the non-uniform distribution of observational in situ data. This new high resolution projections database based on statistical algorithms complements the widely used EUROCORDEX data based on dynamical downscaling and allows to identify features that are dependent on the particular downscaling method. In our analysis, we not only focus on maximum and minimum temperatures and precipitation changes but also on changes in some relevant extreme indexes, being 1986–2005 the reference period. Although climate models predict a general increase in temperature extremes for the end of the 21st century, the exact spatial distribution of changes in temperature and much more in precipitation remains uncertain as they are strongly model dependent. Besides, for precipitation, the uncertainty associated to models can mask – depending on the zones- the signal of change. However, the large number of downscaled models and the high resolution of the used grid allow us to provide differential information at least at massif level. The impact of the RCP becomes significant for the second half of the 21st century, with changes – differentiated by massifs – of extreme temperatures and analysed associated extreme indexes for RCP8.5 at the end of the century.
Highlights
Along the last decades, the issue of climate change has grown in importance, in the scientific world, and in the political and civil society arena, escalating recently to the category of climate emergency
Climate models predict a general increase in temperature extremes for the end of the 21st century, the exact spatial distribution of changes in temperature and much more in precipitation remains uncertain as they are strongly model dependent
We have addressed the analysis of climate change projections developed at AEMET, putting special emphasis on uncertainty analysis, considering various sources, i.e. several Representative Concentration Pathways (RCPs) (RCP4.5, RCP6.0 and RCP8.5) and several Coupled Model Intercomparison project Phase 5 (CMIP5) models
Summary
The issue of climate change has grown in importance, in the scientific world, and in the political and civil society arena, escalating recently to the category of climate emergency. Climate change and related issues (as e.g., water scarcity, loss of biodiversity, increased frequency of extreme meteorological events) (Kitoh et al, 2016) appears as the top risk in terms of impact and likelihood among the global risks analyzed by the World Economic Forum (WEF, 2018, 2019, 2020). High mountain regions are especially vulnerable regions and in particular smaller glaciers around the world are projected – if no immediate and drastic reduction of greenhouse gases are achieved – to lose more than 80 % of their current ice mass by 2100 (IPCC, 2019). High-resolution downscaling is vital to project climate extremes and their future changes by resolving fine topography reasonably well, which is key for representing local climatology and impacts of weather extremes (Kitoh et al, 2016)
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