Climate Trends Impact on the Snowfall Regime in Mediterranean Mountain Areas: Future Scenario Assessment in Sierra Nevada (Spain)

Abstract

Snow constitutes a key component of the water cycle, which is directly affected by changes in climate. Mountainous regions, especially those located in semiarid environments, are highly vulnerable to shifts from snowfall to rainfall. This study evaluates the influence of future climate scenarios on the snowfall regime in the Sierra Nevada Mountains, an Alpine/Mediterranean climate region in southern Spain. Precipitation and temperature projections from two future climate scenarios representative concentration pathway (RCP) 4.5 and RCP 8.5, Fifth Assessment Report of the Intergovernmental Panel for Climate Change (AR5 IPCC)) were used to estimate the projected evolution of the snowfall regime on both annual and decadal scales during the period of 2006-2100. Specific snowfall descriptors of torrentiality are also analyzed. A general decrease of the annual snowfall was estimated, with a significant trend that ranged from 0.21 to 0.55 (mm•year −1)•year −1. These changes are dependent on the scenario and region in the study area. However, the major impact of future climate scenarios on the snowfall regime relates to an increased torrentiality of snowfall occurrence, with a decreased trend of the annual number of snowfall days (RCP 4.5: −0.068 (days•year −1)•year −1 and RCP 8.5: −0.111 (days•year −1)•year −1) and an increased trend in the annual mean snowfall intensity (RCP 4.5: 0.006 (mm•days −1)•year −1 and RCP8.5: 0.01 (mm•days −1)•year −1)) under both scenarios. This enhanced torrentiality is heterogeneously distributed, with the most semiarid region, which is currently the one least influenced by snow, being the region most affected within the study area.

The Guadalfeo Monitoring Network (Sierra Nevada, Spain): 14 years of measurements to understand the complexity of snow dynamics in semiarid regions

“…Regarding the precipitation regime, PG2-PG4 show the maximum altitudinal band in the southern face around 1900-2200 m a.s.l., already identified in other works (Pérez-Palazón et al, 2018) Earth Syst. Sci.…”

“…The presented data have been used in different research works on the snow dynamics in Mediterranean regions and as input data sources to operational applications of these results. Figure 7 shows the importance of snowfall at each station in the Guadalfeo Monitoring Network on both an annual and monthly basis (Pérez-Palazón et al, 2018).…”

“…Data Discuss., https://doi.org/10.5194/essd-2018-123 presence of a large number of endemic species (Heywood, 1995;Blanca, 1996, Anderson et al, 2011, as well as the major ski resort in South Europe during the spring. The projections of future climate in this area (Pérez-Palazón et al, 2018) point out the enhancement of the variability of the snowfall regime, and the increased frequency of ablation cycles during the season. However, the weather network was restricted to the area below 1500 m a.s.l.…”

The Guadalfeo Monitoring Network (Sierra Nevada, Spain): 14 years of measurements to understand the complexity of snow dynamics in semiarid regions

“…Georeferencing uses a digital elevation model (DEM) to provide the image with spatial coordinates by means of a standard automatic computer vision algorithm (Foley, 1996;Fiume, 2014). Secondly, for the detection of snow pixels, a clustering Kmeans algorithm is applied (MacQueen, 1967) that classifies the pixels in the image into two clusters: snow-covered and snow-free pixels (Pimentel et al, 2015); finally, the snow cover area in the image is calculated by aggregation of pixels in each cluster. Additionally, the snow depth, h, was obtained in each image using the red-painted poles installed in the scene area and using the same clustering algorithm to deter-mine pole and no-pole pixels in a predefined search window that isolates the poles in the images (Pimentel et al, 2015(Pimentel et al, , 2017a.…”

“…The Guadalfeo Network has been developed and maintained since then by the Fluvial Dynamics and Hydrology Research Group from the Andalusian Institute for Earth System Research. The data set included consists of a 13-year series of weather variables (2004-2018), a 7-year series of snow observations from terrestrial imagery (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) and a number of snow cover maps from a second camera on selected dates (during 2011-2013), from which snow modelling (Herrero et al, , 2011, weather variables' analysis and mapping (Aguilar et al, 2010;Aguilar and Polo, 2011;Herrero and Polo, 2012), snowmelt-evaposublimation partitioning (Herrero and , subgrid-scale effects of patchy snow conditions (Pimentel et al, 2015(Pimentel et al, , 2017c and other snowrelated processes or impacts have been studied (Millares et al, 2009(Millares et al, , 2014Gómez-Beas et al, 2012;Gómez-Giráldez et al, 2014;Egüen et al, 2016;Pimentel et al, 2017a;López-Moreno et al, 2017;Algarra et al, 2019).…”