• English 
  • Spanish 

Statistical Downscaling of Snow Trends in Northern Spain from Global Climate Models

In this study we simulate with statistical downscaling techniques the snow trends observed in the Northern Iberian Peninsula using daily snow occurrence data from a network of 33 stations ranging from 60 to 1350 metres. To this aim, we consider the annual snow frequency measured as the annual number of snow days, which exhibits a significant decreasing trend since the mid seventies. We first simulate the observed trends using the connection of daily snow occurrence with large-scale fields simulated by a GCM; for this purpose we apply an analog-based statistical downscaling method working in perfect prognosis conditions using reanalysis data. The annual frequency obtained by adding the simulated daily snow occurrences reproduces very well both the observed trends and the high interannual variability. In the second part of the work, we investigate the capabilities of this technique to simulate future trends in a climate change scenario. For such a purpose, we analyze the problem under non-stationary climate conditions, using the 10 coldest consecutive years as training period to simulate the snow frequency in warmer conditions (the remaining period). Finally, we present some results obtained by applying this methodology to the outputs of different global climate models from the ENSEMBLES project.


Abstracts CD

Volume 5, 2008, ISSN 1812-7053