Regional Patterns and Climatic Drivers of Snow Cover Duration

Abstract

Seasonal snow is the major water resource of more than a billion people around the world. In a plethora of regions in the Northern Hemisphere, agricultural, industrial, and drinking water supply are highly dependent on seasonal snow. In addition, the melting of seasonal snow regulates the magnitude and timing of high and low flows, controls the length of the growing season, and determines land surface warming via the albedo feedback. The aim of the study is to quantify the local and regional dynamics of snow cover in the Taurus mountain range and to identify the main climatic drivers responsible for the detected snow cover variability. A data-driven approach based on satellite observations is followed for the systematic analysis of large-scale snow cover in the region of interest. Compared to various remote-sensing snow cover studies that focus either on small/catchment scales, with limited spatial context, or on continental scales that cannot provide detailed insights into a specific region, this study investigates local and regional spatial patterns and temporal dynamics of snow cover across a specific mountain range of interest. The objectives of this study are: (a) to quantify the snow cover temporal variability in the different sub-regions of the Taurus mountain range, (b) to analyze the trends and to identify the regional differences, and (c) to examine the sensitivity of annual snow cover duration to inter-annual climatic variability. The Taurus Mountain Range is divided into sub-regions, using the WWF HydroSHEDS Basins Level 3 dataset and the Köppen–Geiger climate classification map, and in100-m elevation bands. The temporal variability of snow cover is quantified by the Regional Snowline Elevation (RSLE). The Regional Snowline Elevation (RSLE) is estimated in Google Earth Engine (GEE) using the methodology developed by Krajci et al. (2014). The temporal trends of the annual number of snow cover days (Dsc), for the different elevation zones in each sub-region, are derived from the RSLE time series and are analyzed using a modified Mann-Kendall (MK) non-parametric test. The sensitivities of Dsc to the inter-annual variability of winter temperature and precipitation and the snow cover duration trends are estimated in each tile and for all elevation bands in all sub-regions. In general, the analysis carried out, considering its limitations and uncertainties, found that there is no reason to be concerned about future water shortages in the area of the Taurus Mountain Range due to the decrease in the amount of water stored as snow. This is a positive outcome that indicates that there are no significant future changes in snow cover patterns and, as a result, the availability of water in the region will not be at risk.