The influence of internal model variability in GEOS-5 on interhemispheric CO 2 exchange

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Allen, Melissa, Erickson, David, Kendall, Wesley, Fu, Joshua, Ott, Lesley, Pawson, Steven
• Language: unknown
• Published: 2021
• Subjects: 54 ENVIRONMENTAL SCIENCES; South Pole; Grim; South pole
• Online Access: http://www.osti.gov/servlets/purl/1564837; https://www.osti.gov/biblio/1564837; https://doi.org/10.1029/2011jd017059

An ensemble of eight atmospheric CO 2 simulations was completed employing the National Aeronautics and Space Administration (NASA) Goddard Earth Observation System, Version 5 (GEOS–5) for the years 2000–2001, each with initial meteorological conditions corresponding to different days in January 2000 to examine internal model variability. Globally, the model runs show similar concentrations of CO 2 for the two years, but in regions of high CO 2 concentrations due to fossil fuel emissions, large differences among different model simulations appear. The phasing and amplitude of the CO 2 cycle at Northern Hemisphere locations in all of the ensemble members is similar to that of surface observations. In several southern hemisphere locations, however, some of the GEOS–5 model CO 2 cycles are out of phase by as much as four months, and large variations occur between the ensemble members. This result indicates that there is large sensitivity to transport in these regions. The differences vary by latitude—the most extreme differences in the Tropics and the least at the South Pole. Examples of these differences among the ensemble members with regard to CO 2 uptake and respiration of the terrestrial biosphere and CO 2 emissions due to fossil fuel emissions are shown at Cape Grim, Tasmania. Integration–based flow analysis of the atmospheric circulation in the model runs shows widely varying paths of flow into the Tasmania region among the models including sources from North America, South America, South Africa, South Asia and Indonesia. Furthermore, these results suggest that interhemispheric transport can be strongly influenced by internal model variability.