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The Ability of Atmospheric Data to Resolve Discrepancies in Wetland Methane Estimates Over North America : Volume 12, Issue 12 (23/06/2015)

By Miller, S. M.

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Book Id: WPLBN0003986951
Format Type: PDF Article :
File Size: Pages 28
Reproduction Date: 2015

Title: The Ability of Atmospheric Data to Resolve Discrepancies in Wetland Methane Estimates Over North America : Volume 12, Issue 12 (23/06/2015)  
Author: Miller, S. M.
Volume: Vol. 12, Issue 12
Language: English
Subject: Science, Biogeosciences, Discussions
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Benmergui, J., Janssens-Maenhout, G., Commane, R., J. Worth, D. E., Melton, J. R., Dlugokencky, E. J.,...Andrews, A. E. (2015). The Ability of Atmospheric Data to Resolve Discrepancies in Wetland Methane Estimates Over North America : Volume 12, Issue 12 (23/06/2015). Retrieved from http://www.ebooklibrary.org/


Description
Description: Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA. Existing estimates of methane fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these disagreements, this study uses atmospheric methane observations from the US and Canada to analyze seven different bottom-up, wetland methane estimates reported in a recent model comparison project. We first use synthetic data to explore how well atmospheric observations can constrain wetland fluxes. We find that observation sites can identify an atmospheric pattern from Canadian wetlands but not reliably from US wetlands. The network can also identify the spatial distribution of fluxes in Canada at multi-province spatial scales. Based upon these results, we then use real data to evaluate the magnitude, temporal distribution, and spatial distribution of each model estimate. Most models overestimate the magnitude of fluxes across Canada. Most predict a seasonality that is too narrow, potentially indicating an over-sensitivity to air or soil temperatures. In addition, the LPJ-Bern model has a spatial distribution that is most consistent with atmospheric observations. Unlike most models, LPJ-Bern utilizes land cover maps, not just remote sensing inundation data, to estimate wetland coverage. A flux model with a constant spatial distribution outperforms most other existing flux estimates across Canada.

Summary
The ability of atmospheric data to resolve discrepancies in wetland methane estimates over North America

Excerpt
Andrews, A. E., Kofler, J. D., Trudeau, M. E., Williams, J. C., Neff, D. H., Masarie, K. A., Chao, D. Y., Kitzis, D. R., Novelli, P. C., Zhao, C. L., Dlugokencky, E. J., Lang, P. M., Crotwell, M. J., Fischer, M. L., Parker, M. J., Lee, J. T., Baumann, D. D., Desai, A. R., Stanier, C. O., De Wekker, S. F. J., Wolfe, D. E., Munger, J. W., and Tans, P. P.: CO2, CO, and CH4 measurements from tall towers in the NOAA Earth System Research Laboratory's Global Greenhouse Gas Reference Network: instrumentation, uncertainty analysis, and recommendations for future high-accuracy greenhouse gas monitoring efforts, Atmos. Meas. Tech., 7, 647–687, doi:10.5194/amt-7-647-2014, 2014.; Bohn, T. J., Melton, J. R., Ito, A., Kleinen, T., Spahni, R., Stocker, B. D., Zhang, B., Zhu, X., Schroeder, R., Glagolev, M. V., Maksyutov, S., Brovkin, V., Chen, G., Denisov, S. N., Eliseev, A. V., Gallego-Sala, A., McDonald, K. C., Rawlins, M.A., Riley, W. J., Subin, Z. M., Tian, H., Zhuang, Q., and Kaplan, J. O.: WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia, Biogeosciences, 12, 3321–3349, doi:10.5194/bg-12-3321-2015, 2015.; Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., and Canadell, J.: Carbon and Other Biogeochemical Cycles – Final Draft Underlying Scientific Technical Assessment, chap. 6, IPCC Secretariat, Geneva, 2013.; European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL): Emission Database for Global Atmospheric Research (EDGAR), release EDGARv4.2 FT2010, available at: http://edgar.jrc.ec.europa.eu (last access: 14 June 2015), 2013.; Fang, Y. and Michalak, A. M.: Atmospheric observations inform CO2 flux responses to enviroclimatic drivers, Global Biogeochem. Cy., 29, GB005034, doi:10.1002/2014GB005034, 2015.; Fang, Y., Michalak, A. M., Shiga, Y. P., and Yadav, V.: Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models, Biogeosciences, 11, 6985–6997, doi:10.5194/bg-11-6985-2014, 2014.; Gourdji, S. M., Mueller, K. L., Schaefer, K., and Michalak, A. M.: Global monthly averaged CO2 fluxes recovered using a geostatistical inverse modeling approach: 2. Results including auxiliary environmental data, J. Geophys. Res.-Atmos., 113, D21115, doi:10.1029/2007JD009733, 2008.; Hegarty, J., Draxler, R. R., Stein, A. F., Brioude, J., Mountain, M., Eluszkiewicz, J., Nehrkorn, T., Ngan, F., and Andrews, A.: Evaluation of Lagrangian particle dispersion models with measurements from controlled tracer releases, J. Appl. Meteorol. Clim., 52, 2623–2637, 2013.; Hendriks, D. M. D., van Huissteden, J., and Dolman, A. J.: Multi-technique assessment of spatial and temporal variability of methane fluxes in a peat meadow, Agr. Forest Meteorol., 150, 757–774, doi:10.1016/j.agrformet.2009.06.017, 2010.; Hodson, E. L., Poulter, B., Zimmermann, N. E., Prigent, C., and Kaplan, J. O.: The El Niño–Southern Oscillation and wetland methane interannual variability, Geophys. Res. Lett., 38, L08810, doi:10.1029/2011GL046861, 2011.; Kort, E. A., Eluszkiewicz, J., Stephens, B. B., Miller, J. B., Gerbig, C., Nehrkorn, T., Daube, B. C., Kaplan, J. O., Houweling, S., and Wofsy, S. C.: Emissions of CH4 and N2O over the United States and Canada based on a receptor-oriented

 

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