ALBERT

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.

Description: This manuscript details investigations of a productive, mountain freshwater lake and examines the dynamic relationship between the chemical, stable isotope and microbial composition of lake-bed sediments with the geochemistry of the lake water column. A multi-disciplinary approach was used in order to better understand the lake water-sediment interactions including quantification and sequencing of microbial 16S rRNA genes in a sediment core as well as stable isotope analysis of C, S, N. One visit included the use of a pore water sampler to gain insight into the composition of dissolved solutes within the sediment matrix. Sediment cores showed a general decrease in total C with depth which included a decrease in the fraction of organic C combined with an increase in the fraction of inorganic C. One sediment core showed a maximum concentration of dissolved organic C, dissolved inorganic C and dissolved methane in pore water at the 4 cm depth which corresponded with a sharp increase in the abundance of 16S rRNA templates as a proxy for the microbial population size as well as the peak abundance of a sequence affiliated with a putative methanotroph. The isotopic separation between dissolved inorganic and dissolved organic carbon is consistent with largely aerobic microbial processes dominating the upper water column while anaerobic microbial activity dominates the sediment bed. Using sediment core carbon concentrations, predictions were made regarding the breakdown and return of stored carbon per year from this temperate climate lake with as much as 1.3 Gg C yr -1 being released in the form of CO 2 and CH 4 .

Description: [1]  Receiver functions from the EarthScope SESAME broadband deployment and U.S. Transportable Array were analyzed to constrain average crustal thickness and composition across the southern Appalachians. Low Vp/Vs ratios (1.69-1.72) across the Carolina terrane and parts of the Inner Piedmont indicate the crust has a felsic average composition. The results are consistent with models of thin-skinned thrusting of Carolina arc fragments over Laurentian basement, whereas arc collision models require significant crustal modification to explain the low Vp/Vs. New crustal thickness estimates provide constraints on the extent of the Blue Ridge crustal root. The present root may be a remnant of a broader structure formed by Alleghanian thrust loading. Root preservation is attributed to Mesozoic heating and thinning of lower crust beneath outboard terranes, leaving colder Blue Ridge crust largely intact. However, thickened crust (50-55 km) across the region may also be inherited from continental collision during the Proterozoic Grenville orogeny.

Description: Deconvolved waveforms for two earthquakes (Mw: 6.0 and 5.8) show clear postcritical SsPmp arrivals for broadband stations deployed across the coastal plain of Georgia, allowing mapping of crustal thickness in spite of strong reverberations generated by low-velocity sediments. Precritical SsPmp arrivals are also identified. For a basement in which velocity increases linearly with depth, a bootstrapped grid search suggests an average basement velocity of 6.5 ± 0.1 km/s and basement thickness of 29.8 ± 2.0 km. Corresponding normal-incidence Moho two-way times (including sediments) are 10.6 ± 0.6 s, consistent with times for events interpreted as Moho reflections on coincident active-source reflection profiles. Modeling of an underplated mafic layer (Vp = 7.2-7.4 km/s) using travel time constraints from SsPmp data and vertical-incidence Moho reflection times yields a total basement thickness of 30-35 km and average basement velocity of 6.35-6.65 km/s for an underplate thickness of 0-15 km.

Description: Here we assess earthquake volume balance and the growth of mountains in the context of a new landslide inventory for the M w 7.9 Wenchuan earthquake in central China. Coseismic landslides were mapped from high-resolution remote imagery using an automated algorithm and manual delineation, which allows us to distinguish clustered landslides that can bias landslide volume calculations. Employing a power-law landslide area-volume relation, we find that the volume of landslide-associated mass wasting (~2.8+0.9/-0.7 km 3 ) is lower than previously estimated (~5.7-15.2 km 3 ) and comparable to the volume of rock uplift (~2.6±1.2 km 3 ) during the Wenchuan earthquake. If fluvial evacuation removes landslide debris within the earthquake cycle, then the volume addition from coseismic uplift will be effectively offset by landslide erosion. If all earthquakes in the region followed this volume budget pattern, the efficient counteraction of coseismic rock uplift raises a fundamental question about how earthquakes build mountainous topography. To provide a framework for addressing this question, we explore a group of scaling relations to assess earthquake volume balance. We predict coseismic uplift volumes for thrust-fault earthquakes based on geophysical models for coseismic surface deformation and relations between fault rupture parameters and moment magnitude, M w . By coupling this scaling relation with landslide volume- M w scaling, we obtain an earthquake volume balance relation in terms of moment magnitude M w , which is consistent with the revised Wenchuan landslide volumes and observations from the 1999 Chi-Chi earthquake in Taiwan. Incorporating the Gutenburg-Richter frequency- M w relation, we use this volume balance to derive an analytical expression for crustal thickening from coseismic deformation based on an index of seismic intensity over a defined area. This model yields reasonable rates of crustal thickening from coseismic deformation (e.g.~0.1-0.5 km Ma -1 in tectonically active convergent settings), and implies that moderate magnitude earthquakes (M w ≈6-8) are likely responsible for most of the coseismic contribution to rock uplift, because of their smaller landslide-associated volume reduction. Our first-order model does not consider a range of factors (e.g., lithology, climate conditions, epicentral depth and tectonic setting), nor does it account for viscoelastic or isostatic responses to erosion, and there remain important uncertainties on the scaling relationships used to quantify coseismic deformation. Nevertheless, our study provides a conceptual framework and invites more rigorous modeling of seismic mountain building.

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,

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.

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.

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.

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.