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  • 1
    Publication Date: 2020-08-31
    Description: The GEOS-Chem simulation of atmospheric CH4 was evaluated against observations from the Thermal and Near Infrared Sensor for Carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Total Carbon Column Observing Network (TCCON). We focused on the model simulations at the 4∘×5∘ and 2∘×2.5∘ horizontal resolutions for the period of February–May 2010. Compared to the GOSAT, TCCON, and ACE-FTS data, we found that the 2∘×2.5∘ model produced a better simulation of CH4, with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH4 bias, with higher column abundances of CH4 at high latitudes and lower abundances at low latitudes at the 4∘×5∘ resolution than at 2∘×2.5∘. We also found large differences in CH4 column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH4 emission estimates from the two model resolutions. We performed several experiments using 222Rn, 7Be, and CH4 to determine the origins of the resolution-dependent errors. The results suggested that the major source of the latitude-dependent errors is excessive mixing in the upper troposphere and lower stratosphere, including mixing at the edge of the polar vortex, which is pronounced at the 4∘×5∘ resolution. At the coarser resolution, there is weakened vertical transport in the troposphere at midlatitudes to high latitudes due to the loss of sub-grid tracer eddy mass flux in the storm track regions. The vertical air mass fluxes are calculated in the model from the degraded coarse-resolution wind fields and the model does not conserve the air mass flux between model resolutions; as a result, the low resolution does not fully capture the vertical transport. This produces significant localized discrepancies, such as much greater CH4 abundances in the lower troposphere over China at 4∘×5∘ than at 2∘×2.5∘. Although we found that the CH4 simulation is significantly better at 2∘×2.5∘ than at 4∘×5∘, biases may still be present at 2∘×2.5∘ resolution. Their importance, particularly in regards to inverse modeling of CH4 emissions, should be evaluated in future studies using online transport in the native general circulation model as a benchmark simulation.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
    Publication Date: 2020-07-15
    Description: Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget,
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 3
    Publication Date: 2020-09-11
    Description: Scientific data are almost always represented graphically in figures or in videos. With the ever-growing interest from the general public in understanding climate sciences, it is becoming increasingly important that scientists present this information in ways that are both accessible and engaging to non-experts. In this pilot study, we use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces. Each of these pieces presents a unique aspect of the ocean component of the UKESM1, either in terms of a scientific principle or a practical aspect of modelling. In addition, each piece is arranged using a different musical progression, style and tempo. These pieces were created in the Musical Instrument Digital Interface (MIDI) format and then performed by a digital piano synthesiser. An associated video showing the time development of the data in time with the music was also created. The music and video were published on the lead author's YouTube channel. A brief description of the methodology was also posted alongside the video. We also discuss the limitations of this pilot study and describe several approaches to extend and expand upon this work.
    Print ISSN: 2569-7102
    Electronic ISSN: 2569-7110
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2019-12-11
    Description: Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5∘×0.625∘) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
    Publication Date: 2019-06-12
    Description: We use 2010–2015 observations of atmospheric methane columns from the GOSAT satellite instrument in a global inverse analysis to improve estimates of methane emissions and their trends over the period, as well as the global concentration of tropospheric OH (the hydroxyl radical, methane's main sink) and its trend. Our inversion solves the Bayesian optimization problem analytically including closed-form characterization of errors. This allows us to (1) quantify the information content from the inversion towards optimizing methane emissions and its trends, (2) diagnose error correlations between constraints on emissions and OH concentrations, and (3) generate a large ensemble of solutions testing different assumptions in the inversion. We show how the analytical approach can be used, even when prior error standard deviation distributions are lognormal. Inversion results show large overestimates of Chinese coal emissions and Middle East oil and gas emissions in the EDGAR v4.3.2 inventory but little error in the United States where we use a new gridded version of the EPA national greenhouse gas inventory as prior estimate. Oil and gas emissions in the EDGAR v4.3.2 inventory show large differences with national totals reported to the United Nations Framework Convention on Climate Change (UNFCCC), and our inversion is generally more consistent with the UNFCCC data. The observed 2010–2015 growth in atmospheric methane is attributed mostly to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH trends is small in comparison. We find that the inversion provides strong independent constraints on global methane emissions (546 Tg a−1) and global mean OH concentrations (atmospheric methane lifetime against oxidation by tropospheric OH of 10.8±0.4 years), indicating that satellite observations of atmospheric methane could provide a proxy for OH concentrations in the future.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
    Publication Date: 2018-08-24
    Description: We use 7 years (2010–2016) of methane column observations from the Greenhouse Gases Observing Satellite (GOSAT) to examine trends in atmospheric methane concentrations over North America and infer trends in emissions. Local methane enhancements above background are diagnosed in the GOSAT data on a 0.5∘×0.5∘ grid by estimating the local background as the low (10th–25th) percentiles of the deseasonalized frequency distributions of the data for individual years. Trends in methane enhancements on the 0.5∘×0.5∘ grid are then aggregated nationally and for individual source sectors, using information from state-of-science bottom-up inventories. We find that US methane emissions increased by 2.5±1.4  % a−1 (mean ± 1 standard deviation) over the 7-year period, with contributions from both oil–gas systems (possibly unconventional oil–gas production) and from livestock in the Midwest (possibly swine manure management). Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent. The US emission trends inferred from the GOSAT data account for about 20 % of the observed increase in global methane over the 2010–2016 period.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
    Publication Date: 2017-05-09
    Description: Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. XCH4, can be used to quantify methane emissions. Maps of time-averaged satellite-derived XCH4 show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1σ uncertainties directly from maps of annually averaged satellite XCH4. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100 %) but also find that our method tends to underestimate emissions by typically about 40 %. To what extent these findings are model dependent needs to be assessed. We apply our method to an ensemble of satellite XCH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003–2014. We obtain annual emissions of four source areas: Four Corners in the south-western USA, the southern part of Central Valley, California, Azerbaijan, and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50 % higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 5–8 higher emissions compared to EDGAR, albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in EDGAR.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
    Publication Date: 2017-11-06
    Description: This paper describes the global height-resolved methane (CH4) retrieval scheme for the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp, developed at the Rutherford Appleton Laboratory (RAL). The scheme precisely fits measured spectra in the 7.9 micron region to allow information to be retrieved on two independent layers centred in the upper and lower troposphere. It also uses nitrous oxide (N2O) spectral features in the same spectral interval to directly retrieve effective cloud parameters to mitigate errors in retrieved methane due to residual cloud and other geophysical variables. The scheme has been applied to analyse IASI measurements between 2007 and 2015. Results are compared to model fields from the MACC greenhouse gas inversion and independent measurements from satellite (GOSAT), airborne (HIPPO) and ground (TCCON) sensors. The estimated error on methane mixing ratio in the lower- and upper-tropospheric layers ranges from 20 to 100 and from 30 to 40 ppbv, respectively, and error on the derived column-average ranges from 20 to 40 ppbv. Vertical sensitivity extends through the lower troposphere, though it decreases near to the surface. Systematic differences with the other datasets are typically  
    Print ISSN: 1867-1381
    Electronic ISSN: 1867-8548
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
    Publication Date: 2017-04-12
    Description: We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4 : XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. This work builds on the previously reported theory that takes into account that (1) these ratios are less prone to systematic error than either the full-physics data products or the proxy CH4 data products; and (2) the resulting CH4 and CO2 fluxes are self-consistent. We show that a posteriori fluxes inferred from the GOSAT data generally outperform the fluxes inferred only from in situ data, as expected. GOSAT CH4 and CO2 fluxes are consistent with global growth rates for CO2 and CH4 reported by NOAA and have a range of independent data including new profile measurements (0–7 km) over the Amazon Basin that were collected specifically to help validate GOSAT over this geographical region. We find that large-scale multi-year annual a posteriori CO2 fluxes inferred from GOSAT data are similar to those inferred from the in situ surface data but with smaller uncertainties, particularly over the tropics. GOSAT data are consistent with smaller peak-to-peak seasonal amplitudes of CO2 than either the a priori or in situ inversion, particularly over the tropics and the southern extratropics. Over the northern extratropics, GOSAT data show larger uptake than the a priori but less than the in situ inversion, resulting in small net emissions over the year. We also find evidence that the carbon balance of tropical South America was perturbed following the droughts of 2010 and 2012 with net annual fluxes not returning to an approximate annual balance until 2013. In contrast, GOSAT data significantly changed the a priori spatial distribution of CH4 emission with a 40 % increase over tropical South America and tropical Asia and a smaller decrease over Eurasia and temperate South America. We find no evidence from GOSAT that tropical South American CH4 fluxes were dramatically affected by the two large-scale Amazon droughts. However, we find that GOSAT data are consistent with double seasonal peaks in Amazonian fluxes that are reproduced over the 5 years we studied: a small peak from January to April and a larger peak from June to October, which are likely due to superimposed emissions from different geographical regions.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
    Publication Date: 2018-12-07
    Description: The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. Annual mean CO2 growth rates have been determined from satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2, for the years 2003 to 2016. The XCO2 growth rates agree with National Oceanic and Atmospheric Administration (NOAA) growth rates from CO2 surface observations within the uncertainty of the satellite-derived growth rates (mean difference ± standard deviation: 0.0±0.3 ppm year−1; R: 0.82). This new and independent data set confirms record-large growth rates of around 3 ppm year−1 in 2015 and 2016, which are attributed to the 2015–2016 El Niño. Based on a comparison of the satellite-derived growth rates with human CO2 emissions from fossil fuel combustion and with El Niño Southern Oscillation (ENSO) indices, we estimate by how much the impact of ENSO dominates the impact of fossil-fuel-burning-related emissions in explaining the variance of the atmospheric CO2 growth rate. Our analysis shows that the ENSO impact on CO2 growth rate variations dominates that of human emissions throughout the period 2003–2016 but in particular during the period 2010–2016 due to strong La Niña and El Niño events. Using the derived growth rates and their uncertainties, we estimate the probability that the impact of ENSO on the variability is larger than the impact of human emissions to be 63 % for the time period 2003–2016. If the time period is restricted to 2010–2016, this probability increases to 94 %.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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