The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)
Open accessAbstract
Abstract. Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemical transport models (WetCHARTs version 1.0). Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation reanalyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature dependence parameterizations for the period 2009–2010; an extended ensemble subset based solely on precipitation and the data-constrained terrestrial carbon cycle analysis is derived for the period 2001–2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare the model against surface measurements of atmospheric CH4; the model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and the wetland extent together account for more than 80 % of the dominant uncertainty in the timing, magnitude and seasonal variability in wetland CH4 emissions, although uncertainty in the temperature CH4 : C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty that is critical for top-down estimates of wetland CH4 fluxes. Specifically, our ensemble can provide enhanced information on the prior CH4 emission uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain the biogeochemical process controls of global wetland CH4 emissions.
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Self-citationDevelopment and validation of a global database of lakes, reservoirs and wetlands
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Benchmark map of forest carbon stocks in tropical regions across three continents
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Three decades of global methane sources and sinks
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler, L., et al. (2013) · Nature Geoscience · doi:10.1038/ngeo1955 · Cited by 2,247
Freshwater Methane Emissions Offset the Continental Carbon Sink
Bastviken, D., Tranvik, L. J., Downing, J. A., Crill, P. M., & Enrich-Prast, A. (2011) · Science · doi:10.1126/science.1196808 · Cited by 1,549
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Methane fluxes show consistent temperature dependence across microbial to ecosystem scales
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Cited by
The tropical forest carbon cycle and climate change
Mitchard, E. T. A. (2018) · Nature · doi:10.1038/s41586-018-0300-2 · Cited by 836
Satellite observations of atmospheric methane and their value for quantifying methane emissions
Jacob, D. J., Turner, A. J., Maasakkers, J. D., Sheng, J., Sun, K., Liu, X., Chance, K., Aben, I., McKeever, J., & Frankenberg, C. (2016) · Atmospheric Chemistry and Physics · doi:10.5194/acp-16-14371-2016 · Cited by 506
Self-citationInterpreting contemporary trends in atmospheric methane
Turner, A. J., Frankenberg, C., & Kort, E. A. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814297116 · Cited by 426
Self-citationZheng, B., Chevallier, F., Yin, Y., Ciais, P., Fortems-Cheiney, A., Deeter, M. N., Parker, R. J., Wang, Y., Worden, H. M., & Zhao, Y. (2019) · Earth System Science Data · doi:10.5194/essd-11-1411-2019 · Cited by 232
Worden, J. R., Cusworth, D. H., Qu, Z., Yin, Y., Zhang, Y., Bloom, A. A., Ma, S., Byrne, B. K., Scarpelli, T., Maasakkers, J. D., et al. (2022) · Atmospheric Chemistry and Physics · doi:10.5194/acp-22-6811-2022 · Cited by 90
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Metadata
- Authors
- Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., & Jacob, D. J.
- Venue
- Geoscientific Model Development
- Publisher
- Copernicus GmbH
- Published
- 2017-06-06
- Volume
- 10
- Issue
- 6
- Pages
- 2141-2156
- ISSN
- 1991-959X (ISSN-L)
- 1991-9603
- OpenAlex
- W2622992239
- Cited by
- 319
- References
- 57
- FWCI
- 8.97
- Type
- journal article
- Language
- en
- Open access
- gold
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- Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., & Jacob, D. J. (2017). A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0). Geoscientific Model Development. https://doi.org/10.5194/gmd-10-2141-2017
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