EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Modelling the trends and drivers of the CO2 seasonal cycle amplitude in northern high latitudes

Wenjia Cai and Iain Colin Prentice
Wenjia Cai and Iain Colin Prentice
  • Imperial College London, Department of Life Science, London, United Kingdom of Great Britain – England, Scotland, Wales (

Seasonal variations in  atmospheric carbon dioxide (CO2) reflect the responses of terrestrial ecosystems to environmental variations. Accurate estimation of the spatial distribution of global CO2 fluxes would improve our ability to close the global carbon budget and predict the effect of climate change on the terrestrial carbon sink. A large increase in the seasonal cycle amplitude (SCA) of CO2 in northern high latitudes since the 1950s has been observed. However current vegetation models generally fail to reproduce the magnitude of this increase, while the underlying mechanisms are still debated. Using an eco-evolutionary optimality model (the P model) we simulated global gridded atmosphere-ecosystem CO2 exchange from the 1950s onwards and converted the results to atmospheric CO2 concentration variations using the global chemistry-transport model TM5. Our modelled global CO2 flux and derived carbon sink are comparable with that derived from TRENDY models as used in the Global Carbon Project’s annual assessment. The P model could capture the trend of SCA in northern high latitudes, as shown both at remote monitoring stations and in aircraft campaigns. We evaluated the contribution of potential drivers in SCA trends, including atmospheric CO2, climate, land use change and agricultural practices. Our analysis demonstrated that a parameter-sparse model can capture the observed CO2 SCA trend and provide useful insights for carbon cycle dynamics.

How to cite: Cai, W. and Prentice, I. C.: Modelling the trends and drivers of the CO2 seasonal cycle amplitude in northern high latitudes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4189,, 2023.