Abstract ID: 3.11248 | Accepted as Talk | Talk | TBA | TBA

The Andes is the longest mountain range in the world, stretching over 7000 kilometres from Colombia in the tropics to the bottom of Chile in the extratropics. Millions of people depend on water supply from the Andes for their consumption, agriculture, hydropower, and ecosystem services. Often, this water comes from snow and glacier melt, and these water stores can be especially important in times of drought, or during dry seasons for regions with strong annual cycles of precipitation. The inaccessibility of the higher regions in Andes makes setting up weather stations difficult, and the extremely complex topography leads to sharp gradients in weather and climate with varying altitudes of snowline, therefore requiring very high-resolution models to accurately capture the small-scale processes occurring. Due to these challenges, snowfall and snow cover in the Andes remain poorly understood and difficult to model, which are critical to address in the face of a changing climate, with potential for future precipitation occurring in fewer, more extreme snowfall events.

Here we present results from the Weather Research and Forecasting (WRF, version 4.6) regional climate model run at convective-permitting scale (4km) over the entire Andes from 2000-2024. Comparing with MODIS satellite data, we assess the model’s ability to capture the timing and spatial extent of snow cover and determine the climatic influences on snow cover change and their variation over the Andes. We further investigate precipitation and snowfall extremes over a short timescale, and the spatial variation in climatic drivers. Lastly, we determine how these snowfall extremes at different spatial and temporal scales will vary in the future, by dynamically-downscaling a CMIP6 model.