Marcin Jackowicz-Korczynski
Forskningsingenjör
A satellite data driven biophysical modeling approach for estimating northern peatland and tundra CO2 and CH4 fluxes
Författare
Summary, in English
The northern terrestrial net ecosystem carbon balance (NECB) is contingent on inputs from vegetation gross primary productivity (GPP) to offset the ecosystem respiration (R-eco) of carbon dioxide (CO2) and methane (CH4) emissions, but an effective framework to monitor the regional Arctic NECB is lacking. We modified a terrestrial carbon flux (TCF) model developed for satellite remote sensing applications to evaluate wetland CO2 and CH4 fluxes over pan-Arctic eddy covariance (EC) flux tower sites. The TCF model estimates GPP, CO2 and CH4 emissions using in situ or remote sensing and reanalysis-based climate data as inputs. The TCF model simulations using in situ data explained >70% of the r(2) variability in the 8 day cumulative EC measured fluxes. Model simulations using coarser satellite (MODIS) and reanalysis (MERRA) Records accounted for approximately 69% and 75% of the respective r(2) variability in the tower CO2 and CH4 records, with corresponding RMSE uncertainties of <= 1.3 gCm(-2) d(-1) (CO2) and 18.2 mg Cm-2 d(-1) (CH4). Although the estimated annual CH4 emissions were small (<18 gCm(-2) yr(-1)) relative to R-eco (>180 gCm(-2) yr(-1)), they reduced the across-site NECB by 23% and contributed to a global warming potential of approximately 165 +/- 128 gCO(2)eqm(-2) yr(-1) when considered over a 100 year time span. This model evaluation indi-cates a strong potential for using the TCF model approach to document landscape-scale variability in CO2 and CH4 fluxes, and to estimate the NECB for northern peatland and tundra ecosystems.
Avdelning/ar
- Institutionen för naturgeografi och ekosystemvetenskap
Publiceringsår
2014
Språk
Engelska
Sidor
1961-1980
Publikation/Tidskrift/Serie
Biogeosciences
Volym
11
Issue
7
Dokumenttyp
Artikel i tidskrift
Förlag
Copernicus GmbH
Ämne
- Physical Geography
Aktiv
Published
ISBN/ISSN/Övrigt
- ISSN: 1726-4189