Philip Cameron-Smith

Three decades of global methane sources and sinks

Methane is an important greenhouse gas, responsible for about 20% of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios-which differ in fossil fuel and microbial emissions-to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003

The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

Assessing future nitrogen deposition and carbon cycle feedback using a multimodel approach: Analysis of nitrogen deposition

n this study, we present the results of nitrogen deposition on land from a set of 29 simulations from six different tropospheric chemistry models pertaining to present-day and 2100 conditions. Nitrogen deposition refers here to the deposition (wet and dry) of all nitrogen-containing gas phase chemical species resulting from NOx (NO + NO2) emissions. We show that under the assumed IPCC SRES A2 scenario the global annual average nitrogen deposition over land is expected to increase by a factor of ∼2.5, mostly because of the increase in nitrogen emissions. This will significantly expand the areas with annual average deposition exceeding 1 gN/m2/year. Using the results from all models, we have documented the strong linear relationship between models on the fraction of the nitrogen emissions that is deposited, regardless of the emissions (present day or 2100). On average, approximately 70% of the emitted nitrogen is deposited over the landmasses. For present-day conditions the results from this study suggest that the deposition over land ranges between 25 and 40 Tg(N)/year. By 2100, under the A2 scenario, the deposition over the continents is expected to range between 60 and 100 Tg(N)/year. Over forests the deposition is expected to increase from 10 Tg(N)/year to 20 Tg(N)/year. In 2100 the nitrogen deposition changes from changes in the climate account for much less than the changes from increased nitrogen emissions.

Global premature mortality due to anthropogenic outdoor air pollution and the contribution of past climate change

Increased concentrations of ozone and fine particulate matter (PM2.5) since preindustrial times reflect increased emissions, but also contributions of past climate change. Here we use modeled concentrations from an ensemble of chemistry?climate models to estimate the global burden of anthropogenic outdoor air pollution on present-day premature human mortality, and the component of that burden attributable to past climate change. Using simulated concentrations for 2000 and 1850 and concentration?response functions (CRFs), we estimate that, at present, 470?000 (95% confidence interval, 140?000 to 900?000) premature respiratory deaths are associated globally and annually with anthropogenic ozone, and 2.1 (1.3 to 3.0) million deaths with anthropogenic PM2.5-related cardiopulmonary diseases (93%) and lung cancer (7%). These estimates are smaller than ones from previous studies because we use modeled 1850 air pollution rather than a counterfactual low concentration, and because of different emissions. Uncertainty in CRFs contributes more to overall uncertainty than the spread of model results. Mortality attributed to the effects of past climate change on air quality is considerably smaller than the global burden: 1500 (?20?000 to 27?000) deaths yr?1 due to ozone and 2200 (?350?000 to 140?000) due to PM2.5. The small multi-model means are coincidental, as there are larger ranges of results for individual models, reflected in the large uncertainties, with some models suggesting that past climate change has reduced air pollution mortality.

TransCom model simulations of hourly atmospheric CO2 : experimental overview and diurnal cycle results for 2002

[1] A forward atmospheric transport modeling experiment has been coordinated by the TransCom group to investigate synoptic and diurnal variations in CO2. Model simulations were run for biospheric, fossil, and air-sea exchange of CO2 and for SF6 and radon for 2000-2003. Twenty-five models or model variants participated in the comparison. Hourly concentration time series were submitted for 280 sites along with vertical profiles, fluxes, and meteorological variables at 100 sites. The submitted results have been analyzed for diurnal variations and are compared with observed CO2 in 2002. Mean summer diurnal cycles vary widely in amplitude across models. The choice of sampling location and model level account for part of the spread suggesting that representation errors in these types of models are potentially large. Despite the model spread, most models simulate the relative variation in diurnal amplitude between sites reasonably well. The modeled diurnal amplitude only shows a weak relationship with vertical resolution across models; differences in near-surface transport simulation appear to play a major role. Examples are also presented where there is evidence that the models show useful skill in simulating seasonal and synoptic changes in diurnal amplitude.

On the influence of shrub height and expansion on northern high latitude climate

There is a growing body of empirical evidence documenting the expansion of shrub vegetation in the circumpolar Arctic in response to climate change. Here, we conduct a series of idealized experiments with the Community Climate System Model to analyze the potential impact on boreal climate of a large-scale tundra-to-shrub conversion. The model responds to an increase in shrub abundance with substantial atmospheric heating arising from two seasonal land?atmosphere feedbacks: a decrease in surface albedo and an evapotranspiration-induced increase in atmospheric moisture content. We demonstrate that the strength and timing of these feedbacks are sensitive to shrub height and the time at which branches and leaves protrude above the snow. Taller and aerodynamically rougher shrubs lower the albedo earlier in the spring and transpire more efficiently than shorter shrubs. These mechanisms increase, in turn, the strength of the indirect sea-ice albedo and ocean evaporation feedbacks contributing to additional regional warming. Finally, we find that an invasion of tall shrubs tends to systematically warm the soil, deepen the active layer, and destabilize the permafrost (with increased formation of taliks under a future scenario) more substantially than an invasion of short shrubs.

Identifying human influences on atmospheric temperature.

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

Cloud structure and atmospheric composition of Jupiter retrieved from Galileo near‐infrared mapping spectrometer real‐time spectra

The first four complete spectra recorded by the near infrared mapping spectrometer (NIMS) instrument on the Galileo spacecraft in 1996 have been analyzed. These spectra remain the only ones which have been obtained at maximum resolution over the entire NIMS wavelength range of 0.7–5.2 μm. The spectra cover the edge of a “warm” spot at location 5°N, 85°W. We have analyzed the spectra first with reflecting layer models and then with full multiple scattering models using the method of correlated-k. We find that there is strong evidence for three different cloud layers composed of a haze consistent with 0.5-μm radius tholins at 0.2 bar, a cloud of 0.75-μm NH3 particles at about 0.7 bar, and a two-component NH4SH cloud at about 1.4 bars with both 50.0- and 0.45-μm particles, the former being responsible for the main 5-μm cloud opacity. The NH3 relative humidity above the cloud tops is found to decrease slightly as the 5-μm brightness increases, with a mean value of approximately 14%. We also find that the mean volume mixing ratio of ammonia above the middle (NH4SH) cloud deck is (1.7±0.1) × 10−4 and shows a similar, though less discernible decrease with increasing 5-μm brightness. The deep volume mixing ratios of deuterated methane and phosphine are found to be constant and we estimate their mean values to be (4.9±0.2) × 10−7 and (7.7±0.2) × 10−7, respectively. The fractional scale height of phosphine above the 1 bar level is found to be 27.1±1.4% and shows a slight decrease with increasing 5-μm brightness. The relative humidity of water vapor is found to be approximately 7%, but while this and all the previous observations are consistent with the assumption that “hot spots” are regions of downwelling, desiccated air, we find that the water vapor relative humidity increases as the 5-μm brightness increases.

Changes in dimethyl sulfide oceanic distribution due to climate change

Dimethyl sulfide (DMS) is one of the major precursors for aerosols and cloud condensation nuclei in the marine boundary layer over much of the remote ocean. Here they report on coupled climate simulations with a state-of-the-art global ocean biogeochemical model for DMS distribution and fluxes using present-day and future atmospheric CO{sub 2} concentrations. They find changes in zonal averaged DMS flux to the atmosphere of over 150% in the Southern Ocean. This is due to concurrent sea ice changes and ocean ecosystem composition shifts caused by changes in temperature, mixing, nutrient, and light regimes. The largest changes occur in a region already sensitive to climate change, so any resultant local CLAW/Gaia feedback of DMS on clouds, and thus radiative forcing, will be particularly important. A comparison of these results to prior studies shows that increasing model complexity is associted with reduced DMS emissions at the equator and increased emissions at high latitudes.

Review of Methane Mitigation Technologies with Application to Rapid Release of Methane from the Arctic

Methane is the most important greenhouse gas after carbon dioxide, with particular influence on near-term climate change. It poses increasing risk in the future from both direct anthropogenic sources and potential rapid release from the Arctic. A range of mitigation (emissions control) technologies have been developed for anthropogenic sources that can be developed for further application, including to Arctic sources. Significant gaps in understanding remain of the mechanisms, magnitude, and likelihood of rapid methane release from the Arctic. Methane may be released by several pathways, including lakes, wetlands, and oceans, and may be either uniform over large areas or concentrated in patches. Across Arctic sources, bubbles originating in the sediment are the most important mechanism for methane to reach the atmosphere. Most known technologies operate on confined gas streams of 0.1% methane or more, and may be applicable to limited Arctic sources where methane is concentrated in pockets. However, some mitigation strategies developed for rice paddies and agricultural soils are promising for Arctic wetlands and thawing permafrost. Other mitigation strategies specific to the Arctic have been proposed but have yet to be studied. Overall, we identify four avenues of research and development that can serve the dual purposes of addressing current methane sources and potential Arctic sources: (1) methane release detection and quantification, (2) mitigation units for small and remote methane streams, (3) mitigation methods for dilute (<1000 ppm) methane streams, and (4) understanding methanotroph and methanogen ecology.