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Browsing by Author "Steele, LP"

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Atmospheric CO2 and d13C-CO2 reconstruction of the little ice age from antarctic ice cores
(Copernicus Publications, 2015-04-12) Rubino, M; Etheridge, DM; Trudinger, CM; Allison, CE; Rayner, PJ; Mulvaney, R; Steele, LP; Langenfelds, RL; Sturges, WT; Curran, MAJ; Smith, AM
The decrease of atmospheric CO2 concentration recorded in Antarctic ice around 1600 AD is one of the most significant atmospheric changes to have occurred during the last millennia, before the onset of the industrial period.Together with the temperature decrease, the CO2 drop has been used to derive the sensitivity of carbon stores to climate. However, the cause of it is still under debate because models are not yet able to reproduce either its magnitude, or its timing. Here we present new measurements of the CO2 concentration decrease recorded in an ice core from a medium accumulation rate site in Antarctica (DML). We show that the new record is compatible(differences <2 ppm) with the CO2 record from the high accumulation rate DSS site on Law Dome (East Antarctica), when the different age distributions are taken into account. We have also measured the d13C-CO2 change in DML ice, filling a gap around 1600 AD in the DSS d13C record. We use a double deconvolution of the CO2 and d13C records together to provide quantitative evidence that the CO2 decrease was caused by a change in the net flux to the terrestrial biosphere. Finally, we provide a new interpretation of a published record showing increasing atmospheric carbonyl sulphide during the CO2 decrease, suggesting that cooler LIA climate affected terrestrial biospheric fluxes. Altogether our findings support the hypothesis that reduced soil heterotrophic respiration is likely to have given the most significant contribution to the LIA CO2 decrease implying a positive CO2-climate feedback. © 2015, Authors.
Corrigendum to "Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland'' published in Atmos. Chem. Phys., 12, 4259–-4277, 2012
(Copernicus Publications, 2014-04-09) Buizert, C; Martinerie, P; Petrenko, VV; Severinghaus, JP; Trudinger, CM; Witrant, E; Rosen, JL; Orsi, AJ; Rubino, M; Etheridge, DM; Steele, LP; Hogan, C; Laube, JC; Sturges, WT; Levchenko, VA; Smith, AM; Levin, I; Conway, TJ; Dlugokencky, EJ; Lang, PM; Kawamura, K; Jenk, TM; White, JWC; Sowers, T; Schwander, J; Blunier, T
It was kindly pointed out to us by M. Battle that Eq. (2) on p. 4263 contains a typo, and should instead be [X]corr(z) = [X]meas(z) ΔMδgrav(z)/1000 + 1 , (2) where [X]corr ([X]meas) is the gravity-corrected (measured) mixing ratio of gas species X, 1M = MX − Mair is the molar mass difference between gas X and air, and grav(z) is the gravitational fractionation per unit mass difference at depth z. All calculations in the study were done correctly, following Eq. (2) as given here. Furthermore, the present-day 1age value for NEEM is incorrect in the original manuscript, and underestimates Δage by 6 years. The correct value is 188+3 −9 yr. In our original, incorrect calculation we used the ice age in years before 2000 CE (b2k), while we should have used the ice age relative to the surface ice age. In the updated 1age calculation we use the ice age found by annual layer counting of the shallow NEEM 2011 S1 core (Sigl et al., 2013). The NEEM chronology published in Rasmussen et al. (2013) uses the correct, updated Δage estimate. Both errors addressed in this corrigendum affect neither the discussion nor the main conclusions of the original publication. © Author(s) 2014.
Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland
(Copernicus Publications, 2012-05-14) Buizert, C; Martinerie, P; Petrenko, VV; Severinghaus, JP; Trudinger, CM; Witrant, E; Rosen, JL; Orsi, AJ; Rubino, M; Etheridge, DM; Steele, LP; Hogan, C; Laube, JC; Sturges, WT; Levchenko, VA; Smith, AM; Levin, I; Conway, TJ; Dlugokencky, EJ; Lang, PM; Kawamura, K; Jenk, TM; White, JWC; Sowers, T; Schwander, J; Blunier, T
Air was sampled from the porous firn layer at the NEEM site in Northern Greenland. We use an ensemble of ten reference tracers of known atmospheric history to characterise the transport properties of the site. By analysing uncertainties in both data and the reference gas atmospheric histories, we can objectively assign weights to each of the gases used for the depth-diffusivity reconstruction. We define an objective root mean square criterion that is minimised in the model tuning procedure. Each tracer constrains the firn profile differently through its unique atmospheric history and free air diffusivity, making our multiple-tracer characterisation method a clear improvement over the commonly used single-tracer tuning. Six firn air transport models are tuned to the NEEM site; all models successfully reproduce the data within a 1σ Gaussian distribution. A comparison between two replicate boreholes drilled 64 m apart shows differences in measured mixing ratio profiles that exceed the experimental error. We find evidence that diffusivity does not vanish completely in the lock-in zone, as is commonly assumed. The ice age- gas age difference (Δage) at the firn-ice transition is calculated to be 182+3−9 yr. We further present the first intercomparison study of firn air models, where we introduce diagnostic scenarios designed to probe specific aspects of the model physics. Our results show that there are major differences in the way the models handle advective transport. Furthermore, diffusive fractionation of isotopes in the firn is poorly constrained by the models, which has consequences for attempts to reconstruct the isotopic composition of trace gases back in time using firn air and ice core records. © Author(s) 2012.
A global transport model comparison for methane: results for two Australian sites
(International Union of Geodesy and Geophysics, 2011-07-06) Law, RM; Loh, ZM; Corbin, KD; Krummel, PB; Steele, LP; Fraser, PJ; Etheridge, DM; Zahorowski, W
Methane (CH4) is an important greenhouse gas. Using atmospheric CH4 measurements to estimate CH4 emissions requires a good understanding of how CH4 is transported in the atmosphere. Hence, simulations of atmospheric CH4 concentration have been made with two atmospheric models, namely ACCESS and CCAM, as part of the Transport Model Intercomparison project, TransCom-CH4. The simulations ran for the period 1990-2008 and used six different sets of surface CH4 emissions, while the chemical CH4 sink was modelled using prescribed OH and stratospheric loss fields. Radon, sulphur hexafluoride and methyl chloroform tracers were also simulated. Model output has been analysed for two Australian sites with in-situ CH4 measurements: Cape Grim, Tasmania (AGAGE in-situ data) and the CO2CRC Otway project, Victoria. Cape Grim is a coastal site, observing periods of clean (baseline) air from the Southern Ocean and periods of non-baseline air, influenced by emissions from South Eastern Australia including Melbourne. Otway is a rural location, 4 km from the coast, where the land use is predominantly dairy farming, resulting in a large local CH4 signal from enteric fermentation (diurnal amplitudes up to 250 ppb). Nevertheless, during well mixed periods, measured CH4 concentrations at Otway may be similar to the baseline CH4 concentrations measured at Cape Grim or represent broader regional South Eastern Australian emissions. Preliminary findings indicate that CH4 at Otway and non-baseline CH4 at Cape Grim are sensitive to the choice of wetland emissions. There is also some indication that Melbourne emissions may be underestimated in these simulations.
Low atmospheric CO2 levels during the Little Ice Age due to cooling-induced terrestrial uptake
(Springer Nature, 2016-07-25) Rubino, M; Etheridge, DM; Trudinger, CM; Allison, CE; Rayner, PJ; Enting, I; Mulvaney, R; Steele, LP; Langenfelds, RL; Sturges, WT; Curran, MAJ; Smith, AM
Low atmospheric carbon dioxide (CO2) concentration1 during the Little Ice Age has been used to derive the global carbon cycle sensitivity to temperature2. Recent evidence3 confirms earlier indications4 that the low CO2 was caused by increased terrestrial carbon storage. It remains unknown whether the terrestrial biosphere responded to temperature variations, or there was vegetation re-growth on abandoned farmland5. Here we present a global numerical simulation of atmospheric carbonyl sulfide concentrations in the pre-industrial period. Carbonyl sulfide concentration is linked to changes in gross primary production6 and shows a positive anomaly7 during the Little Ice Age. We show that a decrease in gross primary production and a larger decrease in ecosystem respiration is the most likely explanation for the decrease in atmospheric CO2 and increase in atmospheric carbonyl sulfide concentrations. Therefore, temperature change, not vegetation re-growth, was the main cause of the increased terrestrial carbon storage. We address the inconsistency between ice-core CO2 records from different sites8 measuring CO2 and δ13CO2 in ice from Dronning Maud Land (Antarctica). Our interpretation allows us to derive the temperature sensitivity of pre-industrial CO2 fluxes for the terrestrial biosphere (γL = −10 to −90 Pg C K−1), implying a positive climate feedback and providing a benchmark to reduce model uncertainties. © 2016, Nature Publishing Group.
Methane simulations at Cape Grim to assess methane flux estimates for South East Australia
(Centre for Australian Weather and Climate Research, 2011-11-15) Loh, ZM; Law, RM; Corbin, KD; Steele, LP; Krummel, PB; Fraser, PJ; Zahorowski, W
A transport model intercomparison for methane (TransCom-CH4) has been run involving twelve models (Patra et al., 2011). We contributed simulations using two climate models, CCAM and ACCESS. The CCAM simulations were nudged to NCEP analysed meteorology, which allows simulated atmospheric concentrations to be compared to observations on synoptic timescales. The ACCESS simulations were forced only with observed sea surface temperatures and are consequently not expected to match observed synoptic variations. The TransCom experiment involved simulating six CH4 tracers (with different prescribed fluxes) along with SF6, radon and methyl chloroform. We have analysed hourly model output for Cape Grim and find that the magnitude of the non-baseline signal differs, especially in winter, dependent on the CH4 flux scenario used. The magnitude of the non-baseline signal also varies between models, although these differences can be reconciled when methane is scaled by model-simulated radon concentration. Comparison with observed CH4, also scaled using radon, suggests that the CH4 flux scenario with little or no wetland emissions in winter matches the observations. The observations also indicate an apparent extra source of CH4 in October-November not seen in the model simulations. However this appears to be an artefact of this analysis method which assumes that radon emissions are known (and in this case constant in space and time). We have found that the discrepancy between model and observations in spring appears to be due to a poor simulation of radon, rather than CH4. Observed radon shows a larger seasonality than modelled radon, which suggests that temporal and spatial variations in radon flux need to be considered. It would also be helpful to understand why the simulated CCAM and ACCESS radon (and non-baseline CH4) concentrations differ in magnitude. Comparisons with Cape Grim output from the other participating TransCom-CH4 models may provide some insight.
Natural and anthropogenic changes in atmospheric greenhouse gases over the past 2 millennia
(Australian Antarctic Division, 2013-06-24) Etheridge, DM; Rubino, M; Trudinger, CM; Allison, CE; Steele, LP; Thornton, DP; Vollmer, M; Krummel, PB; Smith, AM; Curran, MAJ; Sturgess, WT
Millennial changes in atmospheric trace gas composition are best determined from air enclosed in ice sheets. Air extracted from the open pores in firn and the bubbles in ice is measured to derive the past concentrations and isotopic ratios of the long lived trace gases. The significant increases observed in CO2, CH4 and N2O since about 1750 and the more recent appearance of synthetic gases such as the CFCs in the atmosphere are a key feature of the anthropocene. The millennia preceding the anthropocene, the Late Pre-Industrial Holocene (LPIH), show evidence of natural changes in trace gases that can be used to constrain models and improve their ability to predict future changes under scenarios of anthropogenic emissions and climate change. Precise measurements and ice core air samples that are accurately dated and highly resolved in time are required to record the small and rapid trace gas signals of this period. The atmospheric composition records produced by CSIRO and collaborators using the Law Dome, Antarctica ice cores are widely used in models of climate, atmospheric chemistry and the carbon cycle over the anthropocene and the LPIH. Results from these studies have been influential in informing global policies, including the Montreal and Kyoto Protocols. We will present the recently revised trace gas records from Law Dome and new measurements of tracers from these and other ice sites that reveal the causes of atmospheric changes over the anthropocene and the LPIH.
A new pilot Australian tropical atmospheric research station (ATARS)
(CSIRO Marine and Atmospheric Research, 2014-01-01) van der Schoot, MV; Fraser, PJ; Krummel, PB; Spencer, DA; Loh, ZM; Langenfelds, RL; Steele, LP; Gregory, RL; Meyer, CP; Keywood, MD; Lawson, S; Fedele, R; Atkinson, B; Klau, D; Zahorowski, W
A radon-only technique for characterising baseline constituent concentrations at Cape Grim
(Bureau of Meteorology and CSIRO Oceans and Atmosphere Flagship, 2014-11-12) Chambers, SD; Williams, AG; Crawford, J; Griffiths, AD; Krummel, PB; Steele, LP; Schoot, VD
Nine years (2004-2013) of hourly Radon-222, carbon dioxide and ozone concentration observations at Cape Grim are used to assess the residual terrestrial influence on air masses with radon concentrations below the 100 mBq m-3 threshold traditionally used for ‘baseline’ delineation (Figure 1a). Subsequently, a two step radon-only approach for estimating ‘baseline’ constituent concentrations on monthly timescales is proposed. Based on a stringent 40mBq m-3 radon threshold followed by a simple 10th/90th percentile constitute outlier removal, the technique is completely independent of meteorological or aerosol observations. An initial evaluation of the techniqueusing hourly carbon dioxide and ozone records yielded monthly ‘baseline’ concentration estimates more consistent with expectations of minimally perturbed Southern Ocean air masses than existing baseline selection techniques (Figure 1c). This work builds upon prior studies that have identified radon as a valuable baseline criteria [e.g Gras and Whittlestone, 1992; Molly and Galbally, 2014]. CSIRO Oceans and Atmosphere Flagship Aspendale, Victoria, Australia.
Radon: a universal baseline indicator at sites with contrasting physical settings
(Bureau of Meteorology and CSIRO Oceans and Atmosphere, Climate Science Centre., 2016-11-16) Chambers, SD; Williams, AG; Giemsa, E; Labuschagne, C; Conen, F; Reimann, S; Krummel, PB; Steele, LP; Barnes, JE
The primary goal of World Meteorological Organisation Global Atmosphere Watch (WMO‐GAW) baseline stations is systematic global monitoring of chemical composition of the atmosphere, requiring a reliable, consistent and unambiguous approach for the identification of baseline air. Premier stations in the GAW baseline network span a broad range of physical settings, from remote marine to high‐altitude continental sites, necessitating carefully tailored site‐specific requirements for baseline sampling, data selection, and analysis. Radon‐222 is a versatile and unambiguous terrestrial tracer, widely‐used in transport and mixing studies. Since the majority of anthropogenic pollution sources also have terrestrial origins, radon has become a popular addition to the ‘baseline selection toolkit’ at numerous GAW stations as a proxy for ‘pollution potential’. In the past, detector performance and postprocessing methods necessitated the adoption of a relaxed (e.g. 100 mBq m‐3) radon threshold for minimal terrestrial influence, intended to be used in conjunction with other baseline criteria and analysis procedures, including wind speed, wind direction, particle number, outlier rejection and filtering. However, recent improvements in detector sensitivity, stability and post‐processing procedures have reduced detection limits below 10 mBq m‐3 at Cape Grim and to 25 mBq m‐3 at other baseline stations. Consequently, for suitably sensitive instruments (such as the ANSTO designed and built two‐filter dual‐flow‐loop detectors), radon concentrations alone can be used to unambiguously identify air masses that have been removed from terrestrial sources (at altitude or over ice), or in equilibrium with the ocean surface, for periods of >2‐3 weeks (radon ≤ 40 mBq m‐3). Potentially, radon observations alone can thus provide a consistent and universal (site independent) means for baseline identification. Furthermore, for continental sites with complex topography and meteorology, where true ‘baseline’ conditions may never occur, radon can be used to indicate the least terrestrially‐perturbed air masses, and provide a means by which to apply limits to the level of ‘acceptable terrestrial influence’ for a given application. We demonstrate the efficacy of the radon‐based selection at a range of sites in contrasting physical settings, including: Cape Grim (Tasmania), Cape Point (South Africa), Mauna Loa (Hawaii), Jungfraujoch (Switzerland) and Schneefernerhaus (Germany).
Revised records of atmospheric trace gases CO2, CH4, N2O, and δ13C-CO2 over the last 2000 years from Law Dome, Antarctica
(Copernicus Publications, 2019-04-11) Rubino, M; Etheridge, DM; Thornton, DP; Howden, R; Allison, CE; Francey, RJ; Langenfelds, RL; Steele, LP; Trudinger, CM; Spencer, DA; Curran, MAJ; van Ommen, TD; Smith, AM
Ice core records of the major atmospheric greenhouse gases (CO2, CH4, N2O) and their isotopologues covering recent centuries provide evidence of biogeochemical variations during the Late Holocene and pre-industrial periods and over the transition to the industrial period. These records come from a number of ice core and firn air sites and have been measured in several laboratories around the world and show common features but also unresolved differences. Here we present revised records, including new measurements, performed at the CSIRO Ice Core Extraction LABoratory (ICELAB) on air samples from ice obtained at the high-accumulation site of Law Dome (East Antarctica). We are motivated by the increasing use of the records by the scientific community and by recent data-handling developments at CSIRO ICELAB. A number of cores and firn air samples have been collected at Law Dome to provide high-resolution records overlapping recent, direct atmospheric observations. The records have been updated through a dynamic link to the calibration scales used in the Global Atmospheric Sampling LABoratory (GASLAB) at CSIRO, which are periodically revised with information from the latest calibration experiments. The gas-age scales have been revised based on new ice-age scales and the information derived from a new version of the CSIRO firn diffusion model. Additionally, the records have been revised with new, rule-based selection criteria and updated corrections for biases associated with the extraction procedure and the effects of gravity and diffusion in the firn. All measurements carried out in ICELAB–GASLAB over the last 25 years are now managed through a database (the ICElab dataBASE or ICEBASE), which provides consistent data management, automatic corrections and selection of measurements, and a web-based user interface for data extraction. We present the new records, discuss their strengths and limitations, and summarise their main features. The records reveal changes in the carbon cycle and atmospheric chemistry over the last 2 millennia, including the major changes of the anthropogenic era and the smaller, mainly natural variations beforehand. They provide the historical data to calibrate and test the next inter-comparison of models used to predict future climate change (Coupled Model Inter-comparison Project – phase 6, CMIP6). The datasets described in this paper, including spline fits, are available at https://doi.org/10.25919/5bfe29ff807fb (Rubino et al., 2019). © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions
(Copernicus Publications, 2014-01-13) Loh, ZH; Law, RM; Haynes, KD; Krummel, PB; Steele, LP; Fraser, PJ; Chambers, SD; Williams, AG
This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions. © Author(s) 2015. Creative Commons Attribution 3.0 Licence
Speculation on the origin of sub-baseline excursions of CH4 at Cape Grim
(NOAA Earth System Research Laboratory, 2016-01-01) Loh, ZM; Krummel, PB; Gregory, RL; Steele, LP; Stavert, AR; Schoot, MVVD; Spencer, DA; Mitrevski, B; Thornton, DP; Galbally, IE; Ward, JZ; Somerville, NT; Chambers, SD; Williams, AG
The Advanced Global Atmospheric Gases Experiment (AGAGE) program has historically measured in situ methane (CH4 ) at Cape Grim via gas chromatography with flame ionization detection (GC-FID) in 40 minutely grab samples. By adding continuous, high precision in situ measurements of CH4 (Picarro cavity ring-down spectroscopy [CRDS]) at both Cape Grim, Tasmania, and Casey, Antarctica, a new feature has become apparent in the Cape Grim CH4 record. During the austral summer (December to February), the Cape Grim CH4 record periodically drops below baseline. For example, in Figure 1, a number of sustained episodes of depressed CH4 concentration can be seen below the baseline selected data shown in red. Notably, these episodes are also seen in the GC-FID record. In this presentation, we examine these sub-baseline excursions of CH4 . In conjunction with meteorology and a variety of other chemical species measured at Cape Grim, including radon, ozone, hydrogen and ethane, we speculate on a number of possible mechanisms that might be responsible for these dips in CH4 mixing ratio.
Terrestrial uptake due to cooling responsible for low atmospheric CO2 during the Little Ice Age
(Antarctic Climate and Ecosystems Cooperative Research Centre, 2016-03-07) Rubino, M; Etheridge, DM; Trudinger, CM; Allison, CE; Rayner, PJ; Enting, I; Mulvaney, R; Steele, LP; Langenfelds, RL; Sturges, WT; Curran, MAJ; Smith, AM
Models of future carbon cycle-climate changes predict a large range in atmospheric CO2, mainly because of uncertainties in the response of the land carbon cycle to the future temperature increase. The Little Ice Age (LIA, 1500-1750 AD) CO2 decrease is the most significant pre-industrial atmospheric change over the last millennia and has been used to derive the climate sensitivity of the global carbon cycle (δ). While a recent study confirms that pre-industrial CO2 variations were caused by changes in land carbon stores, there are open questions about the size of the atmospheric LIA CO2 decrease reconstructed from ice cores, and about what caused the land to sequester CO2. To quantify the size of the LIA CO2 decrease, we have produced new CO2 measurements from DML ice, that support the DSS LIA CO2 decrease as a real atmospheric feature. To partition the contribution of ocean and land, we have measured the δ 13C-CO2, showing that the cause of the CO2 drop was uptake by the terrestrial biosphere. To identify whether the land uptake was caused by temperature, or by a decline in farming due to pandemics, we have simulated the effect of a temperature perturbation on atmospheric Carbonyl Sulfide (COS). In agreement with the previously published positive COS anomaly, our results indicate that Global Primary Productivity (GPP) decreased during the LIA, ruling out the early anthropogenic land use change hypothesis as the dominant cause of increased terrestrial carbon storage. This allows us to obtain a new, more coherent estimation of δ in the range -10/-60 Pg of C K-1.
Testing atmospheric monitoring techniques for geological storage of CO2
(Centre for Australian Weather and Climate Research, 2011-11-15) Etheridge, DM; Loh, ZM; Luhar, A; Leuning, R; Steele, LP; Allison, CE; Smith, AM; Hibberd, MF; Feitz, A; Berko, H
The success of CO2 geological storage in mitigating climate change will depend on its ability to withhold large amounts of CO2 from the atmosphere over centuries or more. Atmospheric techniques have been used to monitor Australia’s first geosequestration project, the CO2CRC Otway Project, since its inception (Etheridge et al. 2011; Jenkins et al. 2011). These techniques have been developed to be sensitive (detecting small potential leakage signals against large and variable background CO2 concentrations and fluxes), specific (attributing variations to sources using chemical and isotopic fingerprints and dispersion modelling) and practical (continuous remote operation) (Leuning et al. 2008; Luhar et al. 2009). A recent stage of the Otway project involved periods of controlled releases of injected gas at the surface that could mimic leakage. This provided a test of the original atmospheric scheme, complemented by additional measurements of CO2 and CH4 concentrations and carbon isotopes of CO2. Based on the experience at Otway and recent results from the new Arcturus baseline atmospheric station in Queensland, this presentation will consider the potential merits of atmospheric techniques for monitoring greenhouse gas emissions from emerging energy technologies such as geosequestration and coal seam methane. © 2011 CSIRO and the Bureau of Meteorology.
Towards a universal “baseline” characterisation of air masses for high- and low-altitude observing stations using Radon-222
(Taiwan Association for Aerosol Research, 2015-07-30) Chambers, SD; Williams, AG; Conen, F; Griffiths, AD; Reimann, S; Steinbacher, M; Krummel, PB; Steele, LP; van der Schoot, MV; Galbally, IE; Molloy, SB; Barnes, JE
We demonstrate the ability of atmospheric radon concentrations to reliably and unambiguously identify local and remote terrestrial influences on an air mass, and thereby the potential for alteration of trace gas composition by anthropogenic and biogenic processes. Based on high accuracy (lower limit of detection 10–40 mBq m–3), high temporal resolution (hourly) measurements of atmospheric radon concentration we describe, apply and evaluate a simple two-step method for identifying and characterising constituent mole fractions in baseline air. The technique involves selecting a radon-based threshold concentration to identify the “cleanest” (least terrestrially influenced) air masses, and then performing an outlier removal step based on the distribution of constituent mole fractions in the identified clean air masses. The efficacy of this baseline selection technique is tested at three contrasting WMO GAW stations: Cape Grim (a coastal low-altitude site), Mauna Loa (a remote high-altitude island site), and Jungfraujoch (a continental high-altitude site). At Cape Grim and Mauna Loa the two-step method is at least as effective as more complicated methods employed to characterise baseline conditions, some involving up to nine steps. While it is demonstrated that Jungfraujoch air masses rarely meet the baseline criteria of the more remote sites, a selection method based on a variable monthly radon threshold is shown to produce credible “near baseline” characteristics. The seasonal peak-to-peak amplitude of recent monthly baseline CO2 mole fraction deviations from the long-term trend at Cape Grim, Mauna Loa and Jungfraujoch are estimated to be 1.1, 6.0 and 8.1 ppm, respectively. © Taiwan Association for Aerosol Research
Transport modelling and inversions for the interpretation of greenhouse gas measurements
(Bureau of Meteorology and CSIRO Oceans and Atmosphere Flagship, 2014-11-12) Law, RM; Loh, ZM; Ziehn, T; Haynes, KD; Krummel, PB; Steele, LP; Chambers, SD; Williams, AG
The interpretation of greenhouse gas measurements can be aided by forward transport modelling while greenhouse gas fluxes can be estimated using atmospheric inversions. Here we (a) provide an update on a study of methane model simulations at Cape Grim and their use for determining methane fluxes from SE Australia and (b) show results from some recent CO2 inversions. Observed and model simulated non-baseline methane concentrations at Cape Grim have been compared (Loh et al., 2014). Two atmospheric models (CCAM and ACCESS) and six different methane emission scenarios are used. To minimise the influence of transport model errors on the analysis, deviations of Cape Grim methane concentration above baseline have been compared to coincident radon measurements. This methane to radon ratio shows a clear seasonal signal implying seasonal variations in methane emissions from SE Australia relative to a more temporally uniform radon flux. The ability of the model simulations to match the observed seasonality is dependent on the choice of methane emission scenario but all scenarios underestimate the observed methane to radon ratio in spring. We find that the most likely explanation for the discrepancy is wetland emissions that are too small in some emission scenarios or at the wrong time of year in other scenarios. CO2 inversions have been run recently for two purposes. The first is an international comparison of greenhouse gas inversions focussed on South, East and South East Asia. We have submitted a CCAM inversion for 1993-2012 using a fixed year of winds and expect to submit a second inversion with interannually varying winds. The second purpose is to use a CO2 inversion to estimate the magnitude of regional fluxes that are required to fit the larger difference in annual mean CO2 concentration between Mauna Loa and Cape Grim over recent years.

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