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dc.contributor.authorAlonso-González, Esteban
dc.contributor.authorLópez-Moreno, J.I.
dc.contributor.authorGascoin, Simón
dc.contributor.authorGarcía Valdecasas Ojeda, Matilde María del Valle 
dc.contributor.authorSanmiguel-Vallelado, Alba
dc.contributor.authorNavarro-Serrano, Francisco
dc.contributor.authorRevuelto, Jesús
dc.contributor.authorCeballos, Antonio
dc.contributor.authorEsteban Parra, María Jesús 
dc.contributor.authorEssery, Richard
dc.date.accessioned2024-02-06T10:56:37Z
dc.date.available2024-02-06T10:56:37Z
dc.date.issued2018
dc.identifier.citationAlonso-González, E., López-Moreno, J. I., Gascoin, S., García-Valdecasas Ojeda, M., Sanmiguel-Vallelado, A., Navarro-Serrano, F., Revuelto, J., Ceballos, A., Esteban-Parra, M. J., and Essery, R.: Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014, Earth Syst. Sci. Data, 10, 303–315, https://doi.org/10.5194/essd-10-303-2018, 2018.es_ES
dc.identifier.urihttps://hdl.handle.net/10481/88378
dc.description.abstractWe present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100m elevations bands for each 10 km 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.es_ES
dc.description.sponsorshipEsteban Alonso-González is supported by the Spanish Ministry of Economy and Competitiveness (BES- 2015-071466). This study was funded by the Spanish Ministry of Economy and Competitiveness projects CGL2014-52599-P 10 (Estudio del manto de nieve en la montaña española y su respuesta a la variabilidad y cambio climatico) and CGL2017- 82216-R (HIDROIBERNIEVE) and (with additional support from the European Community funds, FEDER) CGL2013-48539-R (Impactos del cambio climático en los recursos hídricos de la cuenca del Duero a alta resolución). Also, the Regional Government of Andalusia has funded this research with the project P11-RNM-7941 (Impactos del Cambio Climático en la cuenca del Guadalquivir, LICUA).es_ES
dc.language.isoenges_ES
dc.publisherCopernicuses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDaily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014es_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doihttps://doi.org/10.5194/essd-10-303-2018
dc.type.hasVersionVoRes_ES


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