Published August 25, 2017 | Version v2
Dataset Open

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

  • 1. Pyrenean Institute of Ecology, CSIC, Zaragoza, Spain/ Météo-France - CNRS, CNRM (UMR3589), Centre d'Etudes de la Neige, Grenoble, France
  • 2. Pyrenean Institute of Ecology, CSIC, Zaragoza, Spain/Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden
  • 3. Pyrenean Institute of Ecology, CSIC, Zaragoza, Spain
  • 4. Pyrenean Institute of Ecology, CSIC, Zaragoza, Spain/ University of the Basque Country. Department of Geography, Prehistory and Archaeology. Vitoria, Spain

Description

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.

Files

Files (430.1 MB)

Name Size Download all
md5:7d5cc429e22816fd515576e8a3892d3c
8.2 MB Download
md5:1a6c865dc7171638b5511cc3fbff2600
407.8 MB Download
md5:f248965f41d385fefcdaa783525e054e
14.1 MB Download

Additional details

Related works

Is referenced by
10.5194/essd-2017-43 (DOI)