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Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

Artikel i vetenskaplig tidskrift
Författare J. Revuelto
Cesar Azorin-Molina
E. Alonso-Gonzalez
A. Sanmiguel-Vallelado
F. Navarro-Serrano
I. Rico
J. I. Lopez-Moreno
Publicerad i Earth System Science Data
Volym 9
Nummer/häfte 2
Sidor 993-1005
ISSN 1866-3508
Publiceringsår 2017
Publicerad vid Institutionen för geovetenskaper
Sidor 993-1005
Språk en
Länkar doi.org/10.5194/essd-9-993-2017
https://gup.ub.gu.se/file/207282
Ämnesord high-mountain catchment, atmospheric circulation, iberian peninsula, depth, variability, photography, climate, Geology, Meteorology & Atmospheric Sciences
Ämneskategorier Geologi

Sammanfattning

This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which snow dynamics play a determinant role.

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