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The presence of a seasonal snowpack determines the hydrology, geomorphology and ecology of wide parts of the Iberian Peninsula, with strong implications for the economy, transport and risk management. Thus, reliable information on snow is necessary from a scientific and operational point of view. This is the case of the Iberian Peninsula where, lack of observation has impeded proper analysis of snowpack duration, magnitude and interannual variability. In this study, we present the first snow climatology of the entire Iberian Peninsula. The scarcity of in situ observations has been overcome, using a newly developed remote sensing snow database from MODIS satellite sensors for the period 2000–2014 and a physically based snow model (Factorial Snow Model—FSM), driven by a regional atmospheric model (Weather Research and Forecast model—WRF) over the Iberian Peninsula for the period 1980–2014. The snowpack of the main mountain areas (Pyrenees, Cantabrian, Central, Iberian range and Sierra Nevada) are described, estimated from the generated databases. The information has been processed using a k‐means cluster algorithm, looking for similarities in snow indices at different elevation bands. Results show four different types of snowpack in terms of depth, duration and interannual variability, lying over different elevation bands in the different ranges, proving the variability of the snowpack over Iberia. Analyses reveal areas characterized by ephemeral snowpacks, while in some sectors snowpack lasts, on average, 198 days per year with 3.02 m of peak snow depth. The coefficient of variation of interannual peak snow depth oscillated between 35.2 and 162.4%. All the analysed indices show that at common elevations the Cantabrian range and the Pyrenees host the deepest and longest lasting snowpacks, followed by the Central and Iberian ranges. The Sierra Nevada exhibits the shortest, shallowest snowpack and more year‐to‐year variability. [ABSTRACT FROM AUTHOR]

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 snowfalls occur 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 × 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 100 m elevations bands for each 10 × 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 available for free download from Zenodo (DOI: 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. [ABSTRACT FROM AUTHOR]