Assessing the impact of recent climate change on semi-arid and humid snow-dominated catchments by using a cellular automata model

The Earth's spatial heterogeneity and its climate make certain areas more sensitive to climate change. Its effects in these regions become evident earlier than in others. Snow-dominated catchments, where a significant portion of precipitation falls as snow, are particularly sensitive to climate change and serve as excellent observatories for both current and past climate change effects. These areas act as early warning systems for the rest of the world due to their high sensitivity to climate change.
Recent scientific literature highlights significant reductions in snow across various systems in the context of climate change. However, to our knowledge, a global comparison of the effects of climate change on semi-arid and humid snow-dominated mountains has not yet been conducted. Our objective is to analyze the potential differences in sensitivity to climate change between semi-arid and humid regions.
In this study, we compare historical patterns and trends of precipitation, temperature, and snow cover area in three semi-arid and three humid catchments, using data from long-term series (1950-2023). The semi-arid catchments are located in the Sierra Nevada (Spain), the Southern Rocky Mountains (Colorado), and the Andes (Chile), while the humid catchments are located in the Alps (Italy), the Caucasus Mountains (Georgia), and the Himalayas (Nepal).
Climate variables were obtained from the ERA5-Land reanalysis dataset, and snow cover area was modeled using these climate data along with snow cover area data from the MODIS satellite. Gap filling and extension of the historical snow cover area period were achieved using an improved cellular automata algorithm, which utilizes precipitation, temperature, and elevation as driving variables.
Several statistical indicators (Nash-Sutcliffe efficiency, Kling-Gupta Efficiency and coefficient of determination) were used to assess the goodness-of-fit of the improved cellular automata algorithm. The results demonstrated a very good agreement with observed snow cover data in both semi-arid and humid catchments, with the exception of the Himalayan catchment, where the fit was deemed acceptable. Regarding historical snow cover trend, the findings of this study indicate a negative snow cover trend both in semi-arid and humid catchments.

This research has been partially supported by the project SIERRA-CC (PID2022-137623OA-I00 funded by MICIU/AEI/10.13039/501100011033 and by FEDER, UE); the project SIGLO-PRO (PID2021-128021OB-I00/ AEI/10.13039/501100011033/ FEDER, UE), the project STAGES-IPCC (TED2021-130744B-C21/AEI/10.13039/501100011033/ Unión Europea NextGenerationEU/PRTR).