Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Abstract

We present snow observations and a validated daily gridded snowpack dataset that was 15 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 20 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 25 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 30 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 role of meteorological forcing and snow model complexity in winter glacier mass balance estimation, Columbia River basin, Canada

“…This study suggests that a one‐layer energy balance model is sufficient to estimate winter mass balance, but there may be limitations for simulating snowmelt patterns. Similar studies have demonstrated the SnowModel ability to estimate snow depth and SWE forced by WRF dataset in Spain and Chile (Alonso‐González, Ignacio López‐Moreno, Gascoin, García‐Valdecasas Ojeda, et al, 2018; Réveillet et al, 2020). Therefore, our results suggest that SnowModel can be a better choice for estimating winter mass balance in alpine terrain in terms of simplicity, time and computing demand and data distribution over the domain.…”

Detecting snow-related signals in radial growth of Pinus uncinata mountain forests

“…WRF outputs were projected to the target elevation, using hygrobarometric formulas and lapse rates and the new projected meteorological information as driving data of FSM. The methodology to develop the snow dataset and its validation is shown in Alonso-González et al (2018).…”

performance assessment of gridded snow products in the Upper Euphrates

“…Under such limitation, the 9 km ERA-land product has been raised as a promising dataset covering the emerged part of the earth hourly since 1981, including its snow product, which has obtained the best scores in this work. When higher resolution is required, pseudo-physical downscaling approaches (Esteban Alonso-González et al, 2017;Liston and Elder, 2006) may be successfully applied over this dataset to run offset snow models from finer interpolated input data.…”

“…In addition, the high spatial variability and the very dynamical nature of a snowpack, subject to fast changes during both the accumulation and melting periods, poses great difficulty in interpolating those measurements over complex topography, hence, quantifying the volume of water stored in a snowpack which will be available during the melting period (López-Moreno et al, 2013;López-Moreno and Nogués-Bravo, 2006;Sexstone et al, 2021). Many efforts have been made to create snow products that properly characterize the spatial and temporal fluctuations of snowpacks at the regional scale (Wrzesien et al, 2017), remote sensing products, and the combination of atmospheric simulations with snow energy balance models being two of the most promising approaches (Alonso-González et al, 2017). Remote sensing made a noticeable advance in mapping snow cover area, snow cover fraction and even snow water equivalent from microwave radiometry (Andreas et al, 2012).…”