Inversion modelling

Carbon Tracker Europe - CH4 data assimilation system

Carbon Tracker Europe-CH4 (CTE-CH4) is a state-of-the-art atmospheric inverse model developed by Finnish Meteorological Institute for estimating European and global methane (CH4) emissions.

CTE-CH4 belongs to a family of CarbonTracker model systems (Peters et al., 2005), of which the optimization method is based on ensemble Kalman filter (Evensen, 2003). CTE-CH4 emission estimates are constrained by global atmospheric methane concentration observations with extensive network in Europe. The link between the emissions and the atmospheric concentrations are defined by Eulerian atmospheric chemistry transport model, TM5 (Krol et al., 2005). CTE-CH4 focuses on European domain by applying TM5 with two-way zoom grid; the coarsest grid of 1°×1° (latitude×longitude) zoom is applied over Europe. The prior emission fields are obtained from existing databases and models, and divided here to anthropogenic, biosphere, fire, termite and oceanic fluxes. Only anthropogenic and biosphere emissions are optimized.

CTE-CH4 development is supported by Nessling Foundation, Centers of Excellence DFROST, eSTICC, Finnish Academy CARB-ARC project, EU-FP7 InGOS project, ICOS Carbon Portal (ICOS-ERIC) and Academy of Finland Center of Excellence (See Projects).

Applications

The variants of Carbon Tracker model system are being developed in many countries for many applications. The development work, focusing on carbon dioxide, originated in NOAA/ESRL for Carbon Tracker North America and was continued in University of Wageningen, Netherlands, for Carbon Tracker Europe. For methane, two versions exists: CarbonTracker Europe-CH4 developed at FMI, based on Carbon Tracker Europe, and CarbonTracker-CH4, developed at NOAA/ESRL based on CarbonTracker North America.

References

  • Evensen, G. The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dynam. 53, 343–367 (2003).

  • Krol, M. et al. The two-way nested global chemistry-transport zoom model TM5: algorithm and applications. Atmos. Chem. Phys. 5, 417–432 (2005).

  • Peters, W. et al. An ensemble data assimilation system to estimate CO2 surface fluxes from atmospheric trace gas observations. J. Geophys. Res. 110, D24304 (2005).

  • Tsuruta, A. et al. evaluating atmospheric methane inversion model results for Pallas, northern Finland. Boreal Environ. Res. 20, (2015).