Estimation of Methane and Carbon Dioxide Surface Fluxes using a 3-D Global Chemical Transport Model

Student Dissertation or Thesis
Estimation of Methane and Carbon Dioxide Surface Fluxes using a 3-D Global Chemical Transport Model
Chen, Y.-H. (2004)
Ph.D. Thesis, MIT Department of Earth, Atmospheric, and Planetary Sciences

Abstract/Summary:

Methane (CH4) and carbon dioxide (CO2) are the two most radiatively important greenhouse gases attributable to human activity. Large uncertainties in their source and sink magnitudes currently exist. We estimate global methane surface emissions between 1996 and 2001, using a top-down approach that combines observed and simulated atmospheric CH4 concentrations. As a secondary study, we describe our participation in a CO2 inverse-modeling intercomparison.

The available methane time-series data used in this work include observations from 13 high-frequency stations (in-situ) and 74 low-frequency sites (flask). We also construct an annually-repeating reference emissions field from pre-existing datasets of individual methane processes. For our forward simulations, we use the 3-D global chemical transport model MATCH driven by NCEP meteorology. A prescribed, annually-repeating OH field scaled to fit methyl chloroform observations is used as the methane sink. A total methane source of approximately 600 Tg/yr best reproduces the methane growth rate between 1993-2001. Using the reference emissions, MATCH can reproduce the observed methane variations at many sites. Interannual variations in transport, including those associated with ENSO and the NAO, are found to be important at certain locations.

We adapt the Kalman Filter to estimate methane flux magnitudes and uncertainties between 1996 and 2001. Seven seasonal processes (3 wetland, rice, and 3 biomass burning) are optimized at each month, while three aseasonal processes (animals/waste, coal, and gas) are optimized as constant emissions. These optimized emissions represent adjustments to the reference emissions. For the entire period, the inversion reduces coal and gas emissions, and increases rice and biomass burning emissions. The optimized seasonal emission has a strong peak in July, largely due to increased emissions from rice producing regions. The inversion also attributes the large 1998 increase in atmospheric CH4 to global wetland emissions, consistent with a bottom-up study based on a wetland process model. The current observational network can significantly constrain northern emitting regions, but is less effective at constraining tropical emitting regions due to limited observations. We further assessed the inversion sensitivity to different observing sites and model sampling strategies. Better estimates of global OH fluctuations are also necessary to fully describe the interannual behavior of methane observations. Carbon dioxide inversions were conducted as part of the Transcom 3 (Level 1) modeling intercomparison. We further explored the sensitivity of our CO2 inversion results to different parameters.

Citation:

Chen, Y.-H. (2004): Estimation of Methane and Carbon Dioxide Surface Fluxes using a 3-D Global Chemical Transport Model. Ph.D. Thesis, MIT Department of Earth, Atmospheric, and Planetary Sciences (http://globalchange.mit.edu/publication/13952)
  • Student Dissertation or Thesis
Estimation of Methane and Carbon Dioxide Surface Fluxes using a 3-D Global Chemical Transport Model

Chen, Y.-H.

MIT Department of Earth, Atmospheric, and Planetary Sciences
2004

Abstract/Summary: 

Methane (CH4) and carbon dioxide (CO2) are the two most radiatively important greenhouse gases attributable to human activity. Large uncertainties in their source and sink magnitudes currently exist. We estimate global methane surface emissions between 1996 and 2001, using a top-down approach that combines observed and simulated atmospheric CH4 concentrations. As a secondary study, we describe our participation in a CO2 inverse-modeling intercomparison.

The available methane time-series data used in this work include observations from 13 high-frequency stations (in-situ) and 74 low-frequency sites (flask). We also construct an annually-repeating reference emissions field from pre-existing datasets of individual methane processes. For our forward simulations, we use the 3-D global chemical transport model MATCH driven by NCEP meteorology. A prescribed, annually-repeating OH field scaled to fit methyl chloroform observations is used as the methane sink. A total methane source of approximately 600 Tg/yr best reproduces the methane growth rate between 1993-2001. Using the reference emissions, MATCH can reproduce the observed methane variations at many sites. Interannual variations in transport, including those associated with ENSO and the NAO, are found to be important at certain locations.

We adapt the Kalman Filter to estimate methane flux magnitudes and uncertainties between 1996 and 2001. Seven seasonal processes (3 wetland, rice, and 3 biomass burning) are optimized at each month, while three aseasonal processes (animals/waste, coal, and gas) are optimized as constant emissions. These optimized emissions represent adjustments to the reference emissions. For the entire period, the inversion reduces coal and gas emissions, and increases rice and biomass burning emissions. The optimized seasonal emission has a strong peak in July, largely due to increased emissions from rice producing regions. The inversion also attributes the large 1998 increase in atmospheric CH4 to global wetland emissions, consistent with a bottom-up study based on a wetland process model. The current observational network can significantly constrain northern emitting regions, but is less effective at constraining tropical emitting regions due to limited observations. We further assessed the inversion sensitivity to different observing sites and model sampling strategies. Better estimates of global OH fluctuations are also necessary to fully describe the interannual behavior of methane observations. Carbon dioxide inversions were conducted as part of the Transcom 3 (Level 1) modeling intercomparison. We further explored the sensitivity of our CO2 inversion results to different parameters.