From the American West to the Middle East: Trickle-down theory applied to snow science

Abstract:

In the Western United States, snowmelt is recognized as a strategic resource supporting a trillion dollar economy. Snow is also a key water resource in the Middle East especially in Lebanon. For instance, the snow-fed Jeita spring provides 75 % of the domestic water supply for the Beirut district and its northern suburbs (about 1.5 million inhabitants). However, there are no operational meteorological stations or snow monitoring in the high elevation snow dominated regions of Lebanon. That is why three automatic weather stations were set up in the high elevation region of Mount Lebanon since 2010 in a collaboration between the Institut de Recherche pour le Développement and Centre d’Etudes Spatiales de la Biosphere (France), the National Council for Scientific Research (Lebanon), and the University of St Joseph (Lebanon). In addition, field surveys were conducted to collect SWE measurements. We also extracted the snow cover area from the publicly available MODIS snow products from the US National Snow and Ice Data Center. All datasets were quality controlled and made available in a public repository under a Creative Commons Attribution 4.0 International license (Fayad et al., 2017). In 2018, we used the same datasets to run and evaluate a distributed snowpack model (SnowModel) in Mount Lebanon over three snow seasons and we obtained mixed results with large overestimation of the SWE in the late snow season. In 2019, an upgrade of the SnowModel code was implemented by Pflug et al. (2019), who also found that the default model tended to strongly overestimate the SWE at a Snow Telemetry station (SNOTEL) in the Washington Olympic Mountains, USA. They identified and corrected this model deficiency with an enhanced representation of snow liquid water percolation into the snowpack. Given that liquid water percolation process is typical of warm maritime snowpacks, such as Lebanon's snowpack, we pulled the modified SnowModel code from Pflug et al. public repository. We found that the new percolation scheme yielded better performances, especially in terms of SWE but also in snow depth and snow cover area. From this simulation we could estimate for the first time spatial distribution of SWE and its variability over three snow seasons over Mount Lebanon. The results were published in the open access journal Hydrology and Earth System Sciences.