Title of article :
Column-averaged CO2 concentrations in the subarctic from GOSAT retrievals and NIES transport model simulations
Author/Authors :
Belikov، نويسنده , , D.A. and Bril، نويسنده , , A. and Maksyutov، نويسنده , , S. and Oshchepkov، نويسنده , , S. and SAEKI، نويسنده , , T. and Takagi، نويسنده , , H. and Yoshida، نويسنده , , Y. and Ganshin، نويسنده , , A. and Zhuravlev، نويسنده , , R. and Aoki، نويسنده , , S. and Yokota، نويسنده , , T.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2014
Pages :
17
From page :
129
To page :
145
Abstract :
The distribution of atmospheric carbon dioxide (CO2) 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 CO2 (XCO2) 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° × 5° grids. In the alternative method, the model–observation misfit is estimated for each observation separately. The XCO2 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 XCO2 seasonal variability over the period 2009–2010 in the Arctic and subarctic regions. The impact on CO2 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 CO2 interanual variability.
Keywords :
carbon cycle , atmospheric transport , Inverse modeling , GOSAT
Journal title :
Polar Science
Serial Year :
2014
Journal title :
Polar Science
Record number :
2317453
Link To Document :
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