Strategy for generation of climate change projections feeding Spanish impact community

• Published in: Advances in science and research 2018-08, Vol.15, p.217-230
• Main Authors: Amblar-Francés, María Pilar, Pastor-Saavedra, María Asunción, Casado-Calle, María Jesús, Ramos-Calzado, Petra, Rodríguez-Camino, Ernesto
• Format: Article
• Language: English
• Subjects: Climate change; Climate change scenarios; Climate models; Climate system; Climatic evolution; Computer simulation; Dependence; Ecosystems; Environmental aspects; Environmental assessment; Environmental changes; Environmental impact; Global climate; Global climate models; Methods; Simulation; Uncertainty; Weather forecasting
• ISSN: 1992-0636; 1992-0628; 1992-0636
• DOI: 10.5194/asr-15-217-2018

Over the past decades, the successive Coupled Model Intercomparison Projects (CMIPs) have produced a huge amount of global climate model simulations. Along these years, the climate models have advanced and can thus provide credible evolution of climate at least at continental or global scales since they are better representing physical processes and feedbacks in the climate system. Nevertheless, due to the coarse horizontal resolution of global climate models, it is necessary to downscale these results for their use to assess possible future impacts of climate change in climate sensitive ecosystems and sectors and to adopt adaptation strategies at local and national level. In this vein, the Spanish State Meteorological Agency (AEMET) has been producing since 2006 a set of reference downscaled climate change projections over Spain either applying statistical downscaling techniques to the outputs of the Global Climate Models (GCMs) or making use of the information generated by dynamical downscaling techniques through European projects or international initiatives such as PRUDENCE, ENSEMBLES and EURO-CORDEX. The AEMET strategy aims at exploiting all the available sources of information on climate change projections. The generalized use of statistical and dynamical downscaling approaches allow us to encompass a great number of global models and therefore to provide a better estimation of uncertainty. Most impact climate change studies over Spain make use of this reference downscaled projections emphasizing the estimation of uncertainties. Additionally to the rationale and history behind the AEMET generation of climate change scenarios, we focus on some preliminary analysis of the dependency of estimated uncertainties on the different sources of data.