https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1136745

Arndt, K.A., Christensen, T.R., Euskirchen, E.S., et al. (2022) Strategic expansion of the Arctic-Boreal carbon flux network. American Geophysical Meeting, Chicago, United States of America, (December 12-16). https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1136745

Permafrost soils vast soil carbon stores, twice as much as the atmosphere. With climate warming is occurring at a rate three to four times the global average in Arctic-boreal ecosystems this carbon is at risk of being released to the atmosphere in the form of carbon dioxide or methane (hereby, carbon fluxes) exacerbating global climate warming. However, gaps in carbon flux data in high latitude ecosystems limit our ability to understand, upscale, model, and project carbon fluxes, which in turn limit our ability to set accurate emissions reduction targets to stay within globally agreed upon temperature thresholds such as 1.5 or 2°C. To address this, we are strategically expanding the informal Arctic-boreal carbon flux network through the installation of ~10 new eddy covariance sites and supporting expanded measurements (during winter and for CH4) at existing sites. To guide site selection decision making, we are using a representativeness analysis of the current eddy covariance network, determining the Euclidean distance in environmental data space using key carbon flux drivers at a 1 km2 resolution across the Arctic-boreal region (Pallandt et al., 2022). Analyses show a lack of representation in the high Arctic, Siberia, and Eastern Canada, and representation is substantially lower when considering only sites with year-round measurement or that measure methane, limiting our ability to estimate the full impact of carbon fluxes from the Arctic-boreal region. Additional consideration is given to logistical constraints, partnerships, and modeling gaps. Work has begun including a re-installation in Churchill, MB, and upgrades for year-round and additional instrumentation for 4 towers in Alberta and the Northwest Territories and a site in Iqaluit, NU. We will further synthesize existing network data to inform the Dynamic Vegetation [Model] Dynamic Organic Soil Terrestrial Ecosystem Model (DVM-DOS-TEM) model and use machine learning approaches to upscale Arctic-boreal carbon fluxes

https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1136745