Column-averaged CO sub(2) concentrations in the subarctic from GOSAT retrievals and NIES transport model simulations
The distribution of atmospheric carbon dioxide (CO sub(2)) in the subarctic was investigated using the National Institute for Environmental Studies (NIES) three-dimensional transport model (TM) and retrievals from the Greenhouse gases Observing SATellite (GOSAT). Column-averaged dry air mole fractio...
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Veröffentlicht in: | Polar science 2014-06, Vol.8 (2), p.129-145 |
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Hauptverfasser: | , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The distribution of atmospheric carbon dioxide (CO sub(2)) in the subarctic was investigated using the National Institute for Environmental Studies (NIES) three-dimensional transport model (TM) and retrievals from the Greenhouse gases Observing SATellite (GOSAT). Column-averaged dry air mole fractions of subarctic atmospheric CO sub(2) (XCO sub(2)) from the NIES TM for four flux combinations were analyzed. Two flux datasets were optimized using only surface observations and two others were optimized using both surface and GOSAT Level 2 data. Two inverse modeling approaches using GOSAT data were compared. In the basic approach adopted in the GOSAT Level 4 product, the GOSAT observations are aggregated into monthly means over 5 degree 5 degree grids. In the alternative method, the model-observation misfit is estimated for each observation separately. The XCO sub(2) values simulated with optimized fluxes were validated against Total Carbon Column Observing Network (TCCON) ground-based high-resolution Fourier Transform Spectrometer (FTS) measurements. Optimized fluxes were applied to study XCO sub(2) seasonal variability over the period 2009-2010 in the Arctic and subarctic regions. The impact on CO sub(2) levels of emissions from enhancement of biospheric respiration induced by the high temperature and strong wildfires occurring in the summer of 2010 was analyzed. Use of GOSAT data has a substantial impact on estimates of the level of CO sub(2) interanual variability. |
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ISSN: | 1873-9652 |
DOI: | 10.1016/j.polar.2014.02.002 |