COS-derived GPP relationships with temperature and light help explain high-latitude atmospheric CO2 seasonal cycle amplification

Abstract

In the Arctic and Boreal region (ABR) where warming is especially pronounced, the increase of gross primary production (GPP) has been suggested as an important driver for the increase of the atmospheric CO₂ seasonal cycle amplitude (SCA). However, the role of GPP relative to changes in ecosystem respiration (ER) remains unclear, largely due to our inability to quantify these gross fluxes on regional scales. Here, we use atmospheric carbonyl sulfide (COS) measurements to provide observation-based estimates of GPP over the North American ABR. Our annual GPP estimate is 3.6 (2.4 to 5.5) PgC · y^-1 between 2009 and 2013, the uncertainty of which is smaller than the range of GPP estimated from terrestrial ecosystem models (1.5 to 9.8 PgC · y^-1). Our COS-derived monthly GPP shows significant correlations in space and time with satellite-based GPP proxies, solar-induced chlorophyll fluorescence, and near-infrared reflectance of vegetation. Furthermore, the derived monthly GPP displays two different linear relationships with soil temperature in spring versus autumn, whereas the relationship between monthly ER and soil temperature is best described by a single quadratic relationship throughout the year. In spring to midsummer, when GPP is most strongly correlated with soil temperature, our results suggest the warming-induced increases of GPP likely exceeded the increases of ER over the past four decades. In autumn, however, increases of ER were likely greater than GPP due to light limitations on GPP, thereby enhancing autumn net carbon emissions. Both effects have likely contributed to the atmospheric CO₂ SCA amplification observed in the ABR.

Keywords: Arctic and Boreal ecosystems; CO2 seasonal cycle amplitude; carbonyl sulfide; climate change; gross primary production.

Fig. 1.

Regional GPP for the North American ABR, estimated from bottom-up terrestrial models participating in Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) (dashed lines), FluxCom (cyan squares with solid lines), FluxSat (green triangles with solid lines), and SiB4 (red circles with solid lines) and our top-down atmospheric COS inversions (dark gray shading indicates the 2.5th to 97.5th of our best inversion ensemble estimates, whereas the light gray shading denotes the range of our best ensemble estimates plus 2$\sigma$ uncertainties from each inversion). The North American ABR is indicated in B. (A) Annual GPP estimates between 2000 and 2019. (B) Multiyear average seasonal cycle of GPP from MsTMIP (2008–2010), FluxSat (2001–2019), FluxCom (2001–2018), SiB4 (2009–2013), and this study (2009–2013). (C) Spatial distribution of GPP in July 2010 from three selected TEMs (LPJ-wsl, SiB4, and DLEM) and average GPP from July in 2009 to 2013 derived from COS-based inversions. The spatial distribution of GPP from other TEMs is shown in SI Appendix, Fig. S12.

Fig. 2.

NOAA’s atmospheric COS mole fraction observations in the mid and high latitudes of North America. (A) Regular flask-air samples from towers (daily and weekly) and aircraft flights (biweekly to monthly). Color shading indicates average footprint sensitivity (in a log10 scale) of COS observations to surface fluxes during 2009 to 2013. (B) Seasonal average aircraft profiles at sites above 40°N (Left and Right: December to February, March to May, June to August, and September to November). Black symbols represent observed median mole fractions within each season and each altitude range with error bars indicating the 25th to 75th percentiles of the observed mole fractions. Colored dash lines denote median mole fractions of three different background (upwind) estimates in each season.

Fig. 3.

Multiyear average monthly COS fluxes between 2009 and 2013 from anthropogenic sources, biomass burning, and plant and soil fluxes used and derived from this study for the North American ABR. (Upper) Multiyear average monthly anthropogenic COS fluxes (blue lines), biomass burning COS fluxes (red lines), soil COS fluxes (green shading), and plant COS fluxes simulated from SiB4 (black dashed line) and derived from this study (gray shading). Multiple lines with the same color indicate multiple different estimates. (Lower) The daytime and nighttime plant uptake derived from this study (a red solid line with light red shading and a blue solid line with light blue shading) and from SiB4 (red and blue dashed lines).

Fig. 4.

Comparison of COS inversion-estimated GPP with the CSIF (46), NIRv (24), soil temperature (Soil Temp), and downward shortwave radiation flux (DWSRF). (A) Spatial maps of monthly GPP derived from atmospheric COS observations, CSIF, and NIRv averaged between 2009 and 2013 for January, April, July, and October. (B) Monthly estimates of GPP estimated from COS inversions and monthly area-weighted average CSIF, NIRv, Soil Temp, and DWSRF over the North American ABR, averaged between 2009 and 2013. The dark gray shading indicates the 2.5th to 97.5th percentile range of the best estimates from our inversion ensembles, whereas the light gray shading indicates the range of our inversion ensemble estimates plus 2$\sigma$ uncertainties from each inversion. The black symbols connected by a black line denote multiyear average monthly mean GPP from all COS ensemble inversions. (C) Scatter plots between COS-based monthly GPP estimates and monthly area-weighted average CSIF or NIRv over the North American ABR for all months of the year. (D) The calculated SOS and EOS inferred from CSIF and NIRv versus the SOS and EOS indicated by COS-based GPP between 2009 and 2013. The values at 5% or 10% above their seasonal minima relative to their seasonal maxima were used as thresholds for calculating the SOS or EOS in each year (Methods).

Fig. 5.

The atmosphere-based estimates of the multiyear average seasonal cycle of GPP, ER, and NEE and estimation of their warming-induced seasonal cycle amplification over the North American ABR. (A) Multiyear average monthly GPP, ER (“Resp” as labeled in the figure), and NEE between 2009 and 2013 over the North American ABR. The solid lines represent the ensemble means, whereas the color shadings indicate their uncertainties. (B) Relationship between monthly GPP and ER derived from this study and monthly area-weighted soil temperature (Soil Temp) over North American ABR. The solid lines represent a linear fit between GPP and soil temperature for April to July (red) and August to November (green) and a quadratic regression between ER and soil temperature for all months. (C) Estimated increases of GPP, ER, and NEE from 1979 to 1988 and 2010 to 2019 over the North American ABR. The color shading represents our estimation errors, constructed from 100 ensemble empirical relationships of GPP/ER with Soil Temp and DWSRF, considering the uncertainty of our monthly GPP and ER estimates shown in A. (D) Annual Soil Temp and DWSRF (Left) and monthly Soil Temp and DWSRF increases between 1979 and 1988 and 2010 and 2019. The error bars represent the sum of SEs of the monthly means between 1979 and 1988 and 2010 and 2019. The monthly increases of Soil Temp and DWSRF and their errors were normalized relative to the average SCA in 1979 and 1988.