83 research outputs found

    Methane on the Rise-Again

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    International audienc

    Atmospheric constraints on changing Arctic CH4 emissions

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    Rapid warming in the Arctic has the potential to release vast reservoirs of carbon into the atmosphere as methane (CH4) resulting in a strong positive climate feedback. This raises the concern that, after a period of near-zero growth in atmospheric CH4 burden from 1999 to 2006, the increase since then may be in part related to increased Arctic emissions. Measurements of CH4 in background air samples provide useful, direct information to determine if Arctic CH4 emissions are increasing. One sensitive first-order indicator for large emission change is the Interpolar Difference, that is the difference in surface atmospheric annual means between polar northern and southern zones (53°–90°), which has varied interannually, but did not increase from 1992 to 2019. The Interpolar Difference has increased moderately during 2020–2022 when the global CH4 burden increased significantly, but not yet to its peak values in the late-1980s. For quantitative assessment of changing Arctic CH4 emissions, the atmospheric measurements must be combined with an atmospheric tracer transport model. Based on multiple studies including some using CH4 isotopes, it is clear that most of the increase in global atmospheric CH4 burden is driven by increased emissions from microbial sources in the tropics, and that Arctic emissions have not increased significantly since the beginning of our measurement record in 1983 through 2022

    New improvements in the Izaña (Tenerife, Spain) global GAW station in-situ greenhouse gases measurement program

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    Póster presentado en: 16th WMO/IAEA Meeting on Carbon Dioxide, Other Greenhouse Gases, and Related Measurement Techniques celebrado del 25 al 28 de octubre de 2011 en Wellington, Nueva Zelanda

    Observación del vapor de agua

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    Separating the influence of temperature, drought, and fire on interannual variability in atmospheric CO 2

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    The response of the carbon cycle in prognostic Earth system models (ESMs) contributes significant uncertainty to projections of global climate change. Quantifying contributions of known drivers of interannual variability in the growth rate of atmospheric carbon dioxide (CO 2 ) is important for improving the representation of terrestrial ecosystem processes in these ESMs. Several recent studies have identified the temperature dependence of tropical net ecosystem exchange (NEE) as a primary driver of this variability by analyzing a single, globally averaged time series of CO 2 anomalies. Here we examined how the temporal evolution of CO 2 in different latitude bands may be used to separate contributions from temperature stress, drought stress, and fire emissions to CO 2 variability. We developed atmospheric CO 2 patterns from each of these mechanisms during 1997–2011 using an atmospheric transport model. NEE responses to temperature, NEE responses to drought, and fire emissions all contributed significantly to CO 2 variability in each latitude band, suggesting that no single mechanism was the dominant driver. We found that the sum of drought and fire contributions to CO 2 variability exceeded direct NEE responses to temperature in both the Northern and Southern Hemispheres. Additional sensitivity tests revealed that these contributions are masked by temporal and spatial smoothing of CO 2 observations. Accounting for fires, the sensitivity of tropical NEE to temperature stress decreased by 25% to 2.9 ± 0.4 Pg C yr −1  K −1 . These results underscore the need for accurate attribution of the drivers of CO 2 variability prior to using contemporary observations to constrain long‐term ESM responses. Key Points Accurate attribution of CO 2 variability is required to constrain coupled models Combined influence of drought and fire exceed ecosystem responses to temperature Temporal and spatial smoothing of CO 2 observations masks variability from firePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109962/1/gbc20215.pd

    Evaluating atmospheric methane inversion model results for Pallas, northern Finland

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    A state-of-the-art inverse model, CarbonTracker Data Assimilation Shell (CTDAS), was used to optimize estimates of methane (CH4) surface fluxes using atmospheric observations of CH4 as a constraint. The model consists of the latest version of the TM5 atmospheric chemistry-transport model and an ensemble Kalman filter based data assimilation system. The model was constrained by atmospheric methane surface concentrations, obtained from the World Data Centre for Greenhouse Gases (WDCGG). Prior methane emissions were specified for five sources: biosphere, anthropogenic, fire, termites and ocean, of which bio-sphere and anthropogenic emissions were optimized. Atmospheric CH 4 mole fractions for 2007 from northern Finland calculated from prior and optimized emissions were compared with observations. It was found that the root mean squared errors of the posterior esti - mates were more than halved. Furthermore, inclusion of NOAA observations of CH 4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH 4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland
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