Affiliation:
1. University of Arizona
2. National Center For Atmospheric Research (NCAR)
Abstract
Abstract
Snowmelt in High Mountain Asia is heavily influenced by interactions of aerosols and meteorology. However, uncertainties persist due to the complexity of these interactions, which are typically addressed using myopic approaches and are insufficiently represented in current climate models. Equally ambiguous is the impact of these interactions on snow processes in the context of climate change. Here we present a broader strategy using network theory to attribute key quantities that influence higher-order processes within snowmelt. We combine statistical and machine learning methods using observational and model data, highlighting the underappreciated relevance of coupled processes between aerosols and meteorology on snow, as well as the inconsistent representation of aerosol-meteorology interactions within major reanalyses. We find that carbonaceous aerosols and large-scale circulation emerge as the main drivers of snow interactions, emphasizing the need for their serious consideration in integrated Earth system models for the accurate assessment of water availability in developing economies.
Publisher
Research Square Platform LLC