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F. Navarro-Serrano  - - - 
Top co-authors See all
Luis Gimeno

134 shared publications

Environmental Physics Laboratory (EPhysLab), Facultade de Ciencias, Universidad de Vigo, Ourense 32004, Spain

Raquel Nieto

120 shared publications

Environmental Physics Laboratory (EPhysLab), Facultade de Ciencias, Universidad de Vigo, Ourense 32004, Spain

Juan Ignacio Lopez Moreno

44 shared publications

Department of Geoenvironmental Processes and Global Change, Instituto Pirenaico de Ecologia-CSIC, Zaragoza, Spain

Cesar Azorin-Molina

40 shared publications

Regional Climate Group, Department of Earth Sciences; University of Gothenburg; Gothenburg Sweden

Ahmed El Kenawy

26 shared publications

Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas, Zaragoza, Spain

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Publication Record
Distribution of Articles published per year 
(2015 - 2018)
Total number of journals
published in
 
5
 
Publications See all
Article 0 Reads 0 Citations Mapping seasonal and annual extreme precipitation over the Peruvian Andes Fernando Domínguez-Castro, Sergio M. Vicente-Serrano, Juan I... Published: 29 August 2018
International Journal of Climatology, doi: 10.1002/joc.5739
DOI See at publisher website
Article 0 Reads 1 Citation Estimation of near-surface air temperature lapse rates over continental Spain and its mountain areas F. Navarro-Serrano, J. I. López-Moreno, C. Azorin-Molina, E.... Published: 23 March 2018
International Journal of Climatology, doi: 10.1002/joc.5497
DOI See at publisher website
Article 0 Reads 1 Citation Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014 Esteban Alonso-González, J. Ignacio López-Moreno, Simon Gasc... Published: 20 February 2018
Earth System Science Data, doi: 10.5194/essd-10-303-2018
DOI See at publisher website ABS Show/hide abstract
We 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 10km × 10km 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 10km × 10km 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.
Article 0 Reads 1 Citation Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017 Jesús Revuelto, Cesar Azorin-Molina, Esteban Alonso-González... Published: 13 December 2017
Earth System Science Data, doi: 10.5194/essd-9-993-2017
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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 2300m above sea level, covering an area of 55ha. 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 10min 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.
PROCEEDINGS-ARTICLE 15 Reads 0 Citations Seasonal and annual daily precipitation risk maps for the Andean region of Peru Sergio Vicente-Serrano, Juan Ignacio Lopez-Moreno, Kris Corr... Published: 05 November 2017
Proceedings of First International Electronic Conference on the Hydrological Cycle, doi: 10.3390/chycle-2017-04836
DOI See at publisher website ABS Show/hide abstract
We develop for the first time maps of annual and seasonal extreme precipitation risk in the Andean region of Peru. For this purpose, we used the complete daily precipitation records existing in Peru and after a careful quality control and homogeneity checking we selected 178 stations distributed across the mountainous chain. In each meteorological station, we obtained series of events of de-clustered daily intensity, total precipitation duration, total magnitude and dry-spell length. Using a peak-over-threshold approach we fitted the annual and seasonal series of these variables to a Generalized-Pareto distribution, obtained the distribution parameters and validated the performance of different thresholds to obtain reliable estimations of the precipitation probability. We found that a 90th percentile is in general the most suitable to develop the estimations for the different variables. The parameters obtained in the different meteorological stations were mapped using a universal krigging approach using the elevation and the distance to the ocean as co-variables. Maps of parameters were validated using a jack-knife approach and maximum expected precipitation intensity, magnitude, duration and dry-spell length estimated for a period of 25 and 50 years. The reliability of the spatial methodology was validated comparing observed precipitation and estimated by the spatial modelling in the different stations.
Article 0 Reads 0 Citations Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014 Esteban Alonso-González, J.¬Ignacio López-Moreno, Simon Gasc... Published: 20 October 2017
Earth System Science Data Discussions, doi: 10.5194/essd-2017-106
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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.]]>
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