NSF-SNSF: Darkening the Arctic: Bioalbedo Feedbacks from Snow and Ice Algae

Glacier melt has increased over the past decade. This accelerates sea-level rise and reduces Earth's ability to reflect incoming solar radiation. In warming polar regions, snow and glacial algae (SGA) grow on melting ice surfaces. This makes the ice darker and causes it to absorb more solar heat. That in turn melts more ice, which lets more algae grow, creating a positive feedback loop. This project studies where SGA grow, how they respond to environmental conditions, and their role in melting the Greenland Ice Sheet now and in the future. International experts from the U.S. and Switzerland will build a first-of-its-kind, open-access database combining field observations with high-resolution satellite data. This will help map and predict algal blooms through the year 2100. Ultimately, this research will give policymakers and the public clear, science-based information that wll help them make better decisions by improving sea-level rise predictions. The project will train a U.S. graduate student and share results with the public in Greenland in accessible formats. The primary objective of this project is to develop an innovative, observation-constrained modeling framework that estimates how SGA affect the surface energy balance across Greenland's snow and ice-covered landscapes. To achieve this, the project integrates expert ecological knowledge, in situ measurements, high-resolution satellite remote sensing, species distribution modeling, and Earth system modeling. The research spans three interconnected work packages. First, an international workshop will synthesize expert knowledge on Arctic SGA ecology. This will produce a comprehensive, open-access database of in situ observations, supplemented by occurrence data from high-resolution satellite imagery. Second, this dataset will parameterize species distribution models using topographic, light, and environmental predictors. These models will identify current growth-limiting factors and project future SGA distributions through the year 2100 under various scenarios. Third, the resulting distribution maps will be coupled with the Community Land Model (CLM5) using advanced SGA radiative transfer models, specifically the Snow, Ice, and Aerosol Radiation (SNICAR-AD) model versions 3 and 4. The resulting Earth system simulations for the Greenland Ice Sheet will quantify biological albedo reduction, changes in net shortwave radiation, and associated radiative forcing effects. This framework will establish scalable methods for future pan-Arctic and global cryosphere applications. This collaborative US-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.