Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia

Abstract

Abstract. Site-level observations have shown pervasive cold season CO2 release across Arctic and boreal ecosystems, impacting annual carbon budgets. Still, the seasonality of CO2 emissions are poorly quantified across much of the high latitudes due to the sparse coverage of site-level observations. Space-based observations provide the opportunity to fill some observational gaps for studying these high latitude ecosystems, particularly across poorly sampled regions of Eurasia. Here, we show that data-driven net ecosystem exchange (NEE) from atmospheric CO2 observations implies strong summer uptake followed by strong autumn release of CO2 over the entire cold northeastern region of Eurasia during the 2015–2019 study period. Combining data-driven NEE with satellite-based estimates of gross primary production (GPP), we show that this seasonality implies less summer heterotrophic respiration (Rh) and greater autumn Rh than would be expected given an exponential relationship between respiration and surface temperature. Furthermore, we show that this seasonality of NEE and Rh over northeastern Eurasia is not captured by the TRENDY v8 ensemble of dynamic global vegetation models (DGVMs), which estimate that only 52 % of annual Rh occurs during Aug–Apr, while the data-driven estimate suggests 64–70 % of annual Rh occurs over this period. We explain this seasonal shift in Rh by respiration from soils at depth during the zero curtain period, when sub-surface soils remain unfrozen up to several months after the surface has frozen. Additional impacts of physical processes related to freeze-thaw dynamics may contribute to the seasonality of Rh. This study confirms a significant and spatially extensive early cold season CO2 efflux in the permafrost rich region of northeast Eurasia, and suggests that autumn Rh from subsurface soils in the northern high latitudes is not well captured by current DGVMs.

Solar-Induced Chlorophyll Fluorescence (SIF): Towards a Better Understanding of Vegetation Dynamics and Carbon Uptake in Arctic-Boreal Ecosystems

“…Missing the onset and cessation of GPP can cause large uncertainties in the net carbon flux during the shoulder seasons, when the majority of net carbon emission happens in the Arctic-Boreal region [122]. Such artificial cutoffs of growing season also fail to precisely track the temporal shifts of growth onset and cessation with climate change [33,123,124].…”

“…However, the current availability of airborne and tower-based instruments is constrained to a few sites and a brief sampling duration in the Arctic-Boreal region compared to lower latitudes. Additionally, regional studies on the Arctic-Boreal vegetation dynamics are imbalanced across continents, with a greater focus on North America than Eurasia as a result of imbalanced data availability, while Eurasia is also a significant contributor to the global carbon cycle [124]. Therefore, enhancing the international network of airborne and tower-based SIF measurements is the key to validating spaceborne measurements and investigating scaledependent vegetation dynamics throughout the entire Arctic-Boreal region [91,107].…”

Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale

“…In this case, the air sample measurements are rather used to constrain some bias correction of the remote sensing data (Bergamaschi et al, 2009) and/or the model (Locatelli et al, 2015), or they are implicitly used to dampen the effect of these systematic errors. The gradual improvement in the quality of retrievals and models over time has just recently opened the door to a more harmonious use of remote sensing data and air sample measurements for inverse modelling (Byrne et al, 2022).…”