Accurate prediction of future methane abundances following a climate scenario requires understanding the lifetime changes driven by anthropogenic emissions, meteorological factors, and chemistry-climate feedbacks. Uncertainty in any of these influences or the underlying processes implies uncertainty in future abundance and radiative forcing. We simulate methane lifetime in three chemical transport models (CTMs) – UCI CTM, GEOS-Chem, and Oslo CTM3 – over the period 1997–2009 and compare the models' year-to-year variability against constraints from global methyl chloroform observations. Using sensitivity tests, we find that temperature, water vapor, stratospheric ozone column, biomass burning and lightning NO_x are the dominant sources of interannual changes in methane lifetime in all three models. We also evaluate each model's response to forcings that have impacts on decadal time scales, such as methane feedback, and anthropogenic emissions. In general, these different CTMs show similar sensitivities to the driving variables. We construct a parametric model that reproduces most of the interannual variability of each CTM and use it to predict methane lifetime from 1980 through 2100 following a specified emissions and climate scenario (RCP 8.5). The parametric model propagates uncertainties through all steps and provides a foundation for predicting methane abundances in any climate scenario. Our sensitivity tests also enable a new estimate of the methane global warming potential (GWP), accounting for stratospheric ozone effects, including those mediated by water vapor. We estimate the 100-yr GWP to be 32, which is 25% larger than past assessments

The lifetime of nitrous oxide, the third‐most‐important human‐emitted greenhouse gas, is based to date primarily on model studies or scaling to other gases. This work calculates a semiempirical lifetime based on Microwave Limb Sounder satellite measurements of stratospheric profiles of nitrous oxide, ozone, and temperature; laboratory cross‐section data for ozone and molecular oxygen plus kinetics for O(1D); the observed solar spectrum; and a simple radiative transfer model. The result is 116 ± 9 years. The observed monthly‐to‐biennial variations in lifetime and tropical abundance are well matched by four independent chemistry‐transport models driven by reanalysis meteorological fields for the period of observation (2005–2010), but all these models overestimate the lifetime due to lower abundances in the critical loss region near 32 km in the tropics. These models plus a chemistry‐climate model agree on the nitrous oxide feedback factor on its own lifetime of 0.94 ± 0.01, giving N2O perturbations an effective residence time of 109 years. Combining this new empirical lifetime with model estimates of residence time and preindustrial lifetime (123 years) adjusts our best estimates of the human‐natural balance of emissions today and improves the accuracy of projected nitrous oxide increases over this century.

Abstract. Observations at surface sites show an increase in global mean surface methane (CH4) of about 180 parts per billion (ppb) (above 10 %) over the period 1984–2012. Over this period there are large fluctuations in the annual growth rate. In this work, we investigate the atmospheric CH4 evolution over the period 1970–2012 with the Oslo CTM3 global chemical transport model (CTM) in a bottom-up approach. We thoroughly assess data from surface measurement sites in international networks and select a subset suited for comparisons with the output from the CTM. We compare model results and observations to understand causes for both long-term trends and short-term variations. Employing Oslo CTM3 we are able to reproduce the seasonal and year-to-year variations and shifts between years with consecutive growth and stagnation, both at global and regional scales. The overall CH4 trend over the period is reproduced, but for some periods the model fails to reproduce the strength of the growth. The model overestimates the observed growth after 2006 in all regions. This seems to be explained by an overly strong increase in anthropogenic emissions in Asia, having global impact. Our findings confirm other studies questioning the timing or strength of the emission changes in Asia in the EDGAR v4.2 emission inventory over recent decades. The evolution of CH4 is not only controlled by changes in sources, but also by changes in the chemical loss in the atmosphere and soil uptake. The atmospheric CH4 lifetime is an indicator of the CH4 loss. In our simulations, the atmospheric CH4 lifetime decreases by more than 8 % from 1970 to 2012, a significant reduction of the residence time of this important greenhouse gas. Changes in CO and NOx emissions, specific humidity, and ozone column drive most of this, and we provide simple prognostic equations for the relations between those and the CH4 lifetime. The reduced lifetime results in substantial growth in the chemical CH4 loss (relative to its burden) and dampens the CH4 growth.

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Abstract. Aerosols have important impacts on air quality and climate, but the processes affecting their removal from the atmosphere are not fully understood and are poorly constrained by observations. This makes modelled aerosol lifetimes uncertain. In this study, we make use of an observational constraint on aerosol lifetimes provided by radionuclide measurements and investigate the causes of differences within a set of global models. During the Fukushima Dai-Ichi nuclear power plant accident of March 2011, the radioactive isotopes cesium-137 (137Cs) and xenon-133 (133Xe) were released in large quantities. Cesium attached to particles in the ambient air, approximately according to their available aerosol surface area. 137Cs size distribution measurements taken close to the power plant suggested that accumulation-mode (AM) sulfate aerosols were the main carriers of cesium. Hence, 137Cs can be used as a proxy tracer for the AM sulfate aerosol's fate in the atmosphere. In contrast, the noble gas 133Xe behaves almost like a passive transport tracer. Global surface measurements of the two radioactive isotopes taken over several months after the release allow the derivation of a lifetime of the carrier aerosol. We compare this to the lifetimes simulated by 19 different atmospheric transport models initialized with identical emissions of 137Cs that were assigned to an aerosol tracer with each model's default properties of AM sulfate, and 133Xe emissions that were assigned to a passive tracer. We investigate to what extent the modelled sulfate tracer can reproduce the measurements, especially with respect to the observed loss of aerosol mass with time. Modelled 137Cs and 133Xe concentrations sampled at the same location and times as station measurements allow a direct comparison between measured and modelled aerosol lifetime. The e-folding lifetime τe, calculated from station measurement data taken between 2 and 9 weeks after the start of the emissions, is 14.3 days (95 % confidence interval 13.1–15.7 days). The equivalent modelled τe lifetimes have a large spread, varying between 4.8 and 26.7 days with a model median of 9.4 ± 2.3 days, indicating too fast a removal in most models. Because sufficient measurement data were only available from about 2 weeks after the release, the estimated lifetimes apply to aerosols that have undergone long-range transport, i.e. not for freshly emitted aerosol. However, modelled instantaneous lifetimes show that the initial removal in the first 2 weeks was quicker (lifetimes between 1 and 5 days) due to the emissions occurring at low altitudes and co-location of the fresh plume with strong precipitation. Deviations between measured and modelled aerosol lifetimes are largest for the northernmost stations and at later time periods, suggesting that models do not transport enough of the aerosol towards the Arctic. The models underestimate passive tracer (133Xe) concentrations in the Arctic as well but to a smaller extent than for the aerosol (137Cs) tracer. This indicates that in addition to too fast an aerosol removal in the models, errors in simulated atmospheric transport towards the Arctic in most models also contribute to the underestimation of the Arctic aerosol concentrations.