Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements
We use an ensemble Kalman filter (EnKF), together with the GEOS-Chem chemistry transport model, to estimate regional monthly methane (CH[subscript 4]) fluxes for the period June 2009–December 2010 using proxy dry-air column-averaged mole fractions of methane (XCH[subscript 4]) from GOSAT (Greenhouse...
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Copernicus GmbH
2013
|
| Online Access: | http://hdl.handle.net/1721.1/80325 https://orcid.org/0000-0001-5925-3801 |
| _version_ | 1811086575626354688 |
|---|---|
| author | Fraser, A. Palmer, Paul I. Feng, L. Boesch, H. Cogan, A. Parker, R. Dlugokencky, E. Fraser, P. J. Krummel, P. B. Langenfelds, R. L. O'Doherty, Simon Steele, L. P. van der Schoot, M. Weiss, R. F. Prinn, Ronald G. |
| author2 | Massachusetts Institute of Technology. Center for Global Change Science |
| author_facet | Massachusetts Institute of Technology. Center for Global Change Science Fraser, A. Palmer, Paul I. Feng, L. Boesch, H. Cogan, A. Parker, R. Dlugokencky, E. Fraser, P. J. Krummel, P. B. Langenfelds, R. L. O'Doherty, Simon Steele, L. P. van der Schoot, M. Weiss, R. F. Prinn, Ronald G. |
| author_sort | Fraser, A. |
| collection | MIT |
| description | We use an ensemble Kalman filter (EnKF), together with the GEOS-Chem chemistry transport model, to estimate regional monthly methane (CH[subscript 4]) fluxes for the period June 2009–December 2010 using proxy dry-air column-averaged mole fractions of methane (XCH[subscript 4]) from GOSAT (Greenhouse gases Observing SATellite) and/or NOAA ESRL (Earth System Research Laboratory) and CSIRO GASLAB (Global Atmospheric Sampling Laboratory) CH[subscript 4] surface mole fraction measurements. Global posterior estimates using GOSAT and/or surface measurements are between 510–516 Tg yr[superscript −1], which is less than, though within the uncertainty of, the prior global flux of 529 ± 25 Tg yr[superscript −1]. We find larger differences between regional prior and posterior fluxes, with the largest changes in monthly emissions (75 Tg yr[superscript −1]) occurring in Temperate Eurasia. In non-boreal regions the error reductions for inversions using the GOSAT data are at least three times larger (up to 45%) than if only surface data are assimilated, a reflection of the greater spatial coverage of GOSAT, with the two exceptions of latitudes >60° associated with a data filter and over Europe where the surface network adequately describes fluxes on our model spatial and temporal grid. We use CarbonTracker and GEOS-Chem XCO[subscript 2] model output to investigate model error on quantifying proxy GOSAT XCH[subscript 4] (involving model XCO[subscript 2]) and inferring methane flux estimates from surface mole fraction data and show similar resulting fluxes, with differences reflecting initial differences in the proxy value. Using a series of observing system simulation experiments (OSSEs) we characterize the posterior flux error introduced by non-uniform atmospheric sampling by GOSAT. We show that clear-sky measurements can theoretically reproduce fluxes within 10% of true values, with the exception of tropical regions where, due to a large seasonal cycle in the number of measurements because of clouds and aerosols, fluxes are within 15% of true fluxes. We evaluate our posterior methane fluxes by incorporating them into GEOS-Chem and sampling the model at the location and time of surface CH[subscript 4] measurements from the AGAGE (Advanced Global Atmospheric Gases Experiment) network and column XCH[subscript 4] measurements from TCCON (Total Carbon Column Observing Network). The posterior fluxes modestly improve the model agreement with AGAGE and TCCON data relative to prior fluxes, with the correlation coefficients (r[superscript 2]) increasing by a mean of 0.04 (range: −0.17 to 0.23) and the biases decreasing by a mean of 0.4 ppb (range: −8.9 to 8.4 ppb). |
| first_indexed | 2024-09-23T13:28:09Z |
| format | Article |
| id | mit-1721.1/80325 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:28:09Z |
| publishDate | 2013 |
| publisher | Copernicus GmbH |
| record_format | dspace |
| spelling | mit-1721.1/803252022-09-28T14:28:49Z Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements Fraser, A. Palmer, Paul I. Feng, L. Boesch, H. Cogan, A. Parker, R. Dlugokencky, E. Fraser, P. J. Krummel, P. B. Langenfelds, R. L. O'Doherty, Simon Steele, L. P. van der Schoot, M. Weiss, R. F. Prinn, Ronald G. Massachusetts Institute of Technology. Center for Global Change Science Prinn, Ronald G. We use an ensemble Kalman filter (EnKF), together with the GEOS-Chem chemistry transport model, to estimate regional monthly methane (CH[subscript 4]) fluxes for the period June 2009–December 2010 using proxy dry-air column-averaged mole fractions of methane (XCH[subscript 4]) from GOSAT (Greenhouse gases Observing SATellite) and/or NOAA ESRL (Earth System Research Laboratory) and CSIRO GASLAB (Global Atmospheric Sampling Laboratory) CH[subscript 4] surface mole fraction measurements. Global posterior estimates using GOSAT and/or surface measurements are between 510–516 Tg yr[superscript −1], which is less than, though within the uncertainty of, the prior global flux of 529 ± 25 Tg yr[superscript −1]. We find larger differences between regional prior and posterior fluxes, with the largest changes in monthly emissions (75 Tg yr[superscript −1]) occurring in Temperate Eurasia. In non-boreal regions the error reductions for inversions using the GOSAT data are at least three times larger (up to 45%) than if only surface data are assimilated, a reflection of the greater spatial coverage of GOSAT, with the two exceptions of latitudes >60° associated with a data filter and over Europe where the surface network adequately describes fluxes on our model spatial and temporal grid. We use CarbonTracker and GEOS-Chem XCO[subscript 2] model output to investigate model error on quantifying proxy GOSAT XCH[subscript 4] (involving model XCO[subscript 2]) and inferring methane flux estimates from surface mole fraction data and show similar resulting fluxes, with differences reflecting initial differences in the proxy value. Using a series of observing system simulation experiments (OSSEs) we characterize the posterior flux error introduced by non-uniform atmospheric sampling by GOSAT. We show that clear-sky measurements can theoretically reproduce fluxes within 10% of true values, with the exception of tropical regions where, due to a large seasonal cycle in the number of measurements because of clouds and aerosols, fluxes are within 15% of true fluxes. We evaluate our posterior methane fluxes by incorporating them into GEOS-Chem and sampling the model at the location and time of surface CH[subscript 4] measurements from the AGAGE (Advanced Global Atmospheric Gases Experiment) network and column XCH[subscript 4] measurements from TCCON (Total Carbon Column Observing Network). The posterior fluxes modestly improve the model agreement with AGAGE and TCCON data relative to prior fluxes, with the correlation coefficients (r[superscript 2]) increasing by a mean of 0.04 (range: −0.17 to 0.23) and the biases decreasing by a mean of 0.4 ppb (range: −8.9 to 8.4 ppb). NASA Upper Atmospheric Research Program 2013-08-30T14:40:09Z 2013-08-30T14:40:09Z 2013-06 2013-04 Article http://purl.org/eprint/type/JournalArticle 1680-7324 1680-7316 http://hdl.handle.net/1721.1/80325 Fraser, A., P. I. Palmer, L. Feng, H. Boesch, A. Cogan, R. Parker, E. J. Dlugokencky, et al. “Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements.” Atmospheric Chemistry and Physics 13, no. 11 (June 13, 2013): 5697-5713. https://orcid.org/0000-0001-5925-3801 en_US http://dx.doi.org/10.5194/acp-13-5697-2013 Atmospheric Chemistry and Physics Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/ application/pdf Copernicus GmbH Copernicus |
| spellingShingle | Fraser, A. Palmer, Paul I. Feng, L. Boesch, H. Cogan, A. Parker, R. Dlugokencky, E. Fraser, P. J. Krummel, P. B. Langenfelds, R. L. O'Doherty, Simon Steele, L. P. van der Schoot, M. Weiss, R. F. Prinn, Ronald G. Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title | Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title_full | Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title_fullStr | Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title_full_unstemmed | Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title_short | Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements |
| title_sort | estimating regional methane surface fluxes the relative importance of surface and gosat mole fraction measurements |
| url | http://hdl.handle.net/1721.1/80325 https://orcid.org/0000-0001-5925-3801 |
| work_keys_str_mv | AT frasera estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT palmerpauli estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT fengl estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT boeschh estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT cogana estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT parkerr estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT dlugokenckye estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT fraserpj estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT krummelpb estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT langenfeldsrl estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT odohertysimon estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT steelelp estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT vanderschootm estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT weissrf estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements AT prinnronaldg estimatingregionalmethanesurfacefluxestherelativeimportanceofsurfaceandgosatmolefractionmeasurements |