Characterising large-scale meteorological patterns associated with winter precipitation and snow accumulation in a mountain range in the Iberian Peninsula (Sierra de Guadarrama)

Abstract

Snow precipitation in mountains surrounded by semi-arid regions represents an important reservoir of fresh water during the melting season. The snow cover helps to compensate for the scarce precipitation that occurs during their long summer droughts. Knowing the phenomenology that leads to winter precipitation and snow at these areas becomes even more relevant in a context of climate change. Precipitation in Sierra de Guadarrama, a medium size mountain range in the middle of the Iberian Plateau, is the main source of fresh water for millions of inhabitants living under its area of influence, for an active industry and for agriculture and farming. In addition, scarce but heavy snow events affect logistics, transport and security in an area with abundant ground and air traffic. This work analyses the links between large scale atmospheric patterns and the complex winter precipitation and snow cover dynamics observed at local scale. Applying principal component analysis and K-means clustering on geopotential height field, a set of circulation weather types are obtained. The contribution of each circulation weather type to precipitation, snow and heavy snow events is analysed, and favouring conditions leading to snowfalls are identified. Results from this work can be useful as a framework for future modelling exercises, statistical downscaling of climate change scenarios, or even for the development of early warning systems.

© 2022 by the authors. We would like to thank the Agencia Estatal de Meteorología (AEMET) for providing observational data. Special thanks to Navacerrada Observatory staff for their tireless and accurate work. Thanks to the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing the ERA5 Data. Thanks to staff and management of Parque Nacional Sierra de Guadarrama for providing data from Red Meteorológica del Parque Nacional Sierra de Guadarrama, for the manual snow depth observations, for their valuable support and remarks. We would like to thank the referees for their thoughtful reviews that helped to make this a better paper. Partial funding comes from Ministerio de Ciencia e Innovación. Programa de doctorados industriales 2019, DIN2019-010482 and interMET Sistemas y Redes SME.