Late twentieth century increase in northern Spitsbergen (Svalbard) glacier-derived runoff tracked by coralline algal Ba/Ca ratios

• Published in: Climate Dynamics
• Main Authors: Hetzinger, Steffen, Halfar, Jochen, Zajacz, Zoltan, Möller, Marco, Wisshak, Max
• Other Authors: Deutsche Forschungsgemeinschaft, Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada, Projekt DEAL
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2021
• Subjects: Atmospheric Science; Arctic; Svalbard; arctic cryosphere; glacier; Global warming; Spitsbergen
• Online Access: http://dx.doi.org/10.1007/s00382-021-05642-x; https://link.springer.com/content/pdf/10.1007/s00382-021-05642-x.pdf; https://link.springer.com/article/10.1007/s00382-021-05642-x/fulltext.html

Abstract The Arctic cryosphere is changing rapidly due to global warming. Northern Svalbard is a warming hotspot with a temperature rise of ~ 6 °C over the last three decades. Concurrently, modelled data suggest a marked increase in glacier runoff during recent decades in northern Svalbard, and runoff is projected to increase. However, observational data from before anthropogenic influence are sparse and the potential effects on the surface ocean are unclear. Here, we present a 200-year record of Ba/Ca ratios measured in annual increment-forming coralline algae from northern Spitsbergen as a proxy for past glacier-derived meltwater input. Our record shows a significant increasing trend in algal Ba/Ca ratios from the late-1980s onwards matching modelled regional runoff data, suggesting a drastic increase in land-based runoff. The rate of increase is unprecedented during the last two centuries and captures the impact of amplified warming on the coastal surface ocean in the high Arctic. The algal Ba/Ca runoff proxy offers an opportunity to reconstruct past land-based runoff variability in Arctic settings in high resolution, providing important data for validating and improving climate modelling studies.