Observations of snowpack distribution and meteorological variables at the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

We present a climatic dataset acquired at Izas Experimental Catchment, in the Central Spanish Pyrenees, from 2011 to 2017 snow seasons. The dataset includes information on different meteorological variables acquired with an Automatic Weather Station including precipitation, air temperature, incoming...

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Detalhes bibliográficos
Autores: Revuelto, Jesús, Azorín-Molina, César, Alonso-González, Esteban, Sanmiguel-Vallelado, Alba, Navarro‐Serrano, Francisco, Rico, Ibai, López-Moreno, Juan I.
Tipo de documento: conjunto de datos
Data de publicação:2017
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/356383
Acesso em linha:http://hdl.handle.net/10261/356383
Access Level:Acceso aberto
Palavra-chave:Snow distribution
Mountain catchments
Meteorological variables
Hydrometeorology
hydrometeorology
Descrição
Resumo:We present a climatic dataset acquired at Izas Experimental Catchment, in the Central Spanish Pyrenees, from 2011 to 2017 snow seasons. The dataset includes information on different meteorological variables acquired with an Automatic Weather Station including precipitation, air temperature, incoming and reflected short and long-wave radiation, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface) and soil temperature; all of them at 10 minute intervals. Snow depth distribution was measured during 23 field campaigns using a Terrestrial Laser Scanner (TLS), and there are also available time-lapse photographs from which can be derived daily information of different variables such as the Snow Covered Area. The experimental site is located in the southern side of the Pyrenees between 2000 and 2300 m above sea level with an extension of 55 ha. The site is a good example of sub-alpine ambient of mid-latitude mountain ranges. Thus, the dataset has a great potential for understanding environmental processes from a hydrometerological or ecological perspective in which snow dynamics play a determinant role.