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A new model for greenhouse gas transport has been developed based on\udEnvironment and Climate Change Canada's operational weather and environmental\udprediction models. When provided with realistic posterior fluxes for\udCO2, the CO2 simulations compare well to NOAA's CarbonTracker\udfields and to near-surface continuous measurements, columns from the Total\udCarbon Column Observing Network (TCCON) and NOAA aircraft profiles. This\udcoupled meteorological and tracer transport model is used to study the\udpredictability of CO2. Predictability concerns the quantification of\udmodel forecast errors and thus of transport model errors. CO2\udpredictions are used to compute model–data mismatches when solving flux\udinversion problems and the quality of such predictions is a major concern.\udHere, the loss of meteorological predictability due to uncertain\udmeteorological initial conditions is shown to impact CO2 predictability.\udThe predictability of CO2 is shorter than that of the temperature field\udand increases near the surface and in the lower stratosphere. When broken\uddown into spatial scales, CO2 predictability at the very largest scales\udis mainly due to surface fluxes but there is also some sensitivity to the\udland and ocean surface forcing of meteorological fields. The predictability\uddue to the land and ocean surface is most evident in boreal summer when\udbiospheric uptake produces large spatial gradients in the CO2 field.\udThis is a newly identified source of uncertainty in CO2 predictions but\udit is expected to be much less significant\udthan uncertainties in fluxes. However, it serves as an upper limit for the\udmore important source of transport error and loss of predictability, which is\uddue to uncertain meteorological analyses. By isolating this component of\udtransport error, it is demonstrated that CO2 can only be defined on\udlarge spatial scales due to the presence of meteorological uncertainty.\udThus, for a given model, there is a spatial scale below\udwhich fluxes cannot be inferred\udsimply due to the fact that meteorological analyses are imperfect. These\udunresolved spatial scales correspond to small scales near the surface but\udincrease with altitude. By isolating other components of transport error, the\udlargest or limiting error can be identified. For example, a model error due\udto the lack of convective tracer transport was found to impact transport\uderror on the very largest (wavenumbers less than 5) spatial scales. Thus for\udwavenumbers greater than 5, transport model error due to meteorological\udanalysis uncertainty is more important for our model than the lack of\udconvective tracer transport

Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO&lt;sub&gt;2&lt;/sub&gt;

Greenhouse gas simulations with a coupled meteorological and transport model: the predictability of CO<sub>2</sub>