245 research outputs found

    JULES-GL7: The Global Land configuration of the Joint UK Land Environment Simulator version 7.0 and 7.2

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    This is the final version. Available on open access from the European Geosciences Union via the DOI in this recordData availability. The model configuration and associated forcing data are available via the indicated methods in the manuscript (see Appendix A). JULES and associated configurations are freely available for non-commercial research use as set out in the JULES user terms and conditions (http://jules-lsm.github.io/access_req/JULES_Licence.pdf, last access: 31 January 2020).Code availability. This work is based on JULES version 5.3 with specific configurations included in the form of suites. For full information regarding accessing the code and configurations, please refer to Appendix A.We present the latest global land configuration of the Joint UK Land Environment Simulator (JULES) model as used in the latest international Coupled Model Intercomparison Project (CMIP6). The configuration is defined by the combination of switches, parameter values and ancillary data, which we provide alongside a set of historical forcing data that defines the experimental setup. The configurations provided are JULES-GL7.0, the base setup used in CMIP6 and JULES-GL7.2, a subversion that includes improvements to the representation of canopy radiation and interception. These configurations are recommended for all JULES applications focused on the exchange and state of heat, water and momentum at the land surface. In addition, we provide a standardised modelling system that runs on the Natural Environment Research Council (NERC) JASMIN cluster, accessible to all JULES users. This is provided so that users can test and evaluate their own science against the standard configuration to promote community engagement in the development of land surface modelling capability through JULES. It is intended that JULES configurations should be independent of the underlying code base, and thus they will be available in the latest release of the JULES code. This means that different code releases will produce scientifically comparable results for a given configuration version. Versioning is therefore determined by the configuration as opposed to the underlying code base.BEIS and DEFRA Met Office Hadley Centre Climate ProgrammeEuropean Union Horizon 202

    Description and evaluation of the JULES-ES set-up for ISIMIP2b

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    Global studies of climate change impacts that use future climate model projections also require projections of land surface changes. Simulated land surface performance in Earth system models is often affected by the atmospheric models' climate biases, leading to errors in land surface projections. Here we run the Joint UK Land Environment Simulator Earth System configuration (JULES-ES) land surface model with the Inter-Sectoral Impact Model Intercomparison Project second-phase future projections (ISIMIP2b) bias-corrected climate model data from four global climate models (GCMs). The bias correction reduces the impact of the climate biases present in individual models. We evaluate the performance of JULES-ES against present-day observations to demonstrate its usefulness for providing required information for impacts such as fire and river flow. We include a standard JULES-ES configuration without fire as a contribution to ISIMIP2b and JULES-ES with fire as a potential future development. Simulations for gross primary productivity (GPP), evapotranspiration (ET) and albedo compare well against observations. Including fire improves the simulations, especially for ET and albedo and vegetation distribution, with some degradation in shrub cover and river flow. This configuration represents some of the most current Earth system science for land surface modelling. The suite associated with this configuration provides a basis for past and future phases of ISIMIP, providing a simulation set-up, postprocessing and initial evaluation, using the International Land Model Benchmarking (ILAMB) project. This suite ensures that it is as straightforward, reproducible and transparent as possible to follow the protocols and participate fully in ISIMIP using JULES.</p

    Understanding the glacial methane cycle.

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    Atmospheric methane (CH4) varied with climate during the Quaternary, rising from a concentration of 375 p.p.b.v. during the last glacial maximum (LGM) 21,000 years ago, to 680 p.p.b.v. at the beginning of the industrial revolution. However, the causes of this increase remain unclear; proposed hypotheses rely on fluctuations in either the magnitude of CH4 sources or CH4 atmospheric lifetime, or both. Here we use an Earth System model to provide a comprehensive assessment of these competing hypotheses, including estimates of uncertainty. We show that in this model, the global LGM CH4 source was reduced by 28-46%, and the lifetime increased by 2-8%, with a best-estimate LGM CH4 concentration of 463-480 p.p.b.v. Simulating the observed LGM concentration requires a 46-49% reduction in sources, indicating that we cannot reconcile the observed amplitude. This highlights the need for better understanding of the effects of low CO2 and cooler climate on wetlands and other natural CH4 sources

    Rising atmospheric methane: 2007-2014 growth and isotopic shift

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    From 2007 to 2013, the globally averaged mole fraction of methane in the atmosphere increased by 5.7±1.2ppb yr1^{-1}. Simultaneously, δ13\delta^{13}CCH4_\text{CH4} (a measure of the 13^{13}C/12^{12}C isotope ratio in methane) has shifted to significantly more negative values since 2007. Growth was extreme in 2014, at 12.5±0.4ppb, with a further shift to more negative values being observed at most latitudes. The isotopic evidence presented here suggests that the methane rise was dominated by significant increases in biogenic methane emissions, particularly in the tropics, for example, from expansion of tropical wetlands in years with strongly positive rainfall anomalies or emissions from increased agricultural sources such as ruminants and rice paddies. Changes in the removal rate of methane by the OH radical have not been seen in other tracers of atmospheric chemistry and do not appear to explain short-term variations in methane. Fossil fuel emissions may also have grown, but the sustained shift to more 13^{13}C-depleted values and its significant interannual variability, and the tropical and Southern Hemisphere loci of post-2007 growth, both indicate that fossil fuel emissions have not been the dominant factor driving the increase. A major cause of increased tropical wetland and tropical agricultural methane emissions, the likely major contributors to growth, may be their responses to meteorological change.This work was supported by the UK Natural Environment Research Council projects NE/N016211/1 The Global Methane Budget, NE/M005836/1 Methane at the edge, NE/K006045/1 The Southern Methane Anomaly and NE/I028874/1 MAMM. We thank the UK Meteorological Office for flask collection and hosting the continuous measurement at Ascension, the Ascension Island Government for essential support, and Thumeka Mkololo for flask collection in Cape Tow

    Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics

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    Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2–3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink

    The global methane budget 2000-2017

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    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 ĝ1/4 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 (ĝ1/4 65 % of the global budget, &lt; 30ĝ  N) compared to mid-latitudes (ĝ1/4 30 %, 30-60ĝ  N) and high northern latitudes (ĝ1/4 4 %, 60-90ĝ  N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr-1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr-1 by 8 Tg CH4 yr-1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project

    Temporal changes in the epidemiology, management, and outcome from acute respiratory distress syndrome in European intensive care units: a comparison of two large cohorts

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    Background: Mortality rates for patients with ARDS remain high. We assessed temporal changes in the epidemiology and management of ARDS patients requiring invasive mechanical ventilation in European ICUs. We also investigated the association between ventilatory settings and outcome in these patients. Methods: This was a post hoc analysis of two cohorts of adult ICU patients admitted between May 1–15, 2002 (SOAP study, n = 3147), and May 8–18, 2012 (ICON audit, n = 4601 admitted to ICUs in the same 24 countries as the SOAP study). ARDS was defined retrospectively using the Berlin definitions. Values of tidal volume, PEEP, plateau pressure, and FiO2 corresponding to the most abnormal value of arterial PO2 were recorded prospectively every 24&nbsp;h. In both studies, patients were followed for outcome until death, hospital discharge or for 60&nbsp;days. Results: The frequency of ARDS requiring mechanical ventilation during the ICU stay was similar in SOAP and ICON (327[10.4%] vs. 494[10.7%], p = 0.793). The diagnosis of ARDS was established at a median of 3 (IQ: 1–7) days after admission in SOAP and 2 (1–6) days in ICON. Within 24&nbsp;h of diagnosis, ARDS was mild in 244 (29.7%), moderate in 388 (47.3%), and severe in 189 (23.0%) patients. In patients with ARDS, tidal volumes were lower in the later (ICON) than in the earlier (SOAP) cohort. Plateau and driving pressures were also lower in ICON than in SOAP. ICU (134[41.1%] vs 179[36.9%]) and hospital (151[46.2%] vs 212[44.4%]) mortality rates in patients with ARDS were similar in SOAP and ICON. High plateau pressure (&gt; 29 cmH2O) and driving pressure (&gt; 14 cmH2O) on the first day of mechanical ventilation but not tidal volume (&gt; 8&nbsp;ml/kg predicted body weight [PBW]) were independently associated with a higher risk of in-hospital death. Conclusion: The frequency of and outcome from ARDS remained relatively stable between 2002 and 2012. Plateau pressure &gt; 29 cmH2O and driving pressure &gt; 14 cmH2O on the first day of mechanical ventilation but not tidal volume &gt; 8&nbsp;ml/kg PBW were independently associated with a higher risk of death. These data highlight the continued burden of ARDS and provide hypothesis-generating data for the design of future studies

    Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

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    The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR
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