ausblenden:
Schlagwörter:
General-circulation model
Carbon-dioxide
Inversions
Delta-c-13
Emissions
Cycle
Land
Zusammenfassung:
Large-scale carbon sources and sinks can be estimated by combining atmospheric CO2 concentration data with atmospheric transport inverse modeling. This approach has been limited by sparse spatiotemporal tropospheric sampling. CO2 estimates from space using observations on recently launched satellites (Atmospheric Infrared Sounder (AIRS)), or platforms to be launched (Infrared Atmospheric Sounding Interferometer (IASI), Orbiting Carbon Observatory (OCO)) have the potential to fill some of these gaps. Here we assess the realism of initial AIRS-based mid-to-upper troposphere CO2 estimates from European Centre for Medium-Range Weather Forecasts by comparing them with simulations of two transport models (TM3 and Laboratoire Meteorologie Dynamique Zoom (LMDZ)) forced with one data-based set of surface fluxes. The simulations agree closer with one another than with the retrievals. Nevertheless, there is good overall agreement between all estimates of seasonal cycles and north-south gradients within the latitudinal band extending from 30 degrees S to 30 degrees N, but not outside this region. At smaller spatial scales, there is a contrast in the satellite-based retrievals above continents versus above oceans that is absent in the model predictions. Hovmoeller diagrams indicate that in the models, high Northern Hemisphere winter CO2 concentrations propagate toward the tropical upper troposphere via Northern Hemisphere high latitudes, while in retrievals, elevated winter CO2 appears instantaneously throughout the Northern Hemisphere. This raises questions about lower-to-upper troposphere transport pathways. Prerequisites for use of retrievals to provide an improved constraint on surface fluxes are therefore further improvements in retrievals and better understanding/validation of lower-to-upper troposphere transport and its modeling. This calls for more independent upper troposphere transport tracer data like SF6 and CO2. [References: 41]
