Description: Large herbivores are a major agent in ecosystems, influencing vegetation structure and carbon and nutrient flows. Yet most of the current global dynamic vegetation models (DGVMs) lack explicit representation of large herbivores. Here we incorporated a grazing module in the ORCHIDEE-MICT DGVM based on physiological and demographic equations for wild large grazers, taking into account the feedbacks of large grazers on vegetation. The model was applied globally for present-day and the last glacial maximum (LGM). Three NetCDF files are included, corresponding to the model results for three periods: present-day (1960-2009 average), pre-industrial (1860-1899 average), and the last glacial maximum (ca. 21 ka before present). Variables include the modeled potential grazer biomass/population density, along with the directly relevant outputs: vegetation distribution (i.e. fractional coverage of the plant functional types), and gross and net primary productivity. Detailed model descriptions and the simulation setup can be found in: Zhu et al. (2018).

Description: These data represent five high-latitude sites studied in the PAGE21 project (https://www.page21.eu): Samoylov, Kytalyk, Abisko, Zackenberg and Bayelva. Please see the linked manuscript for details of the sites. These are meteorological driving data, which were prepared using observations from the sites combined with reanalysis data for the grid cell containing the site. For the period 1901-1979, Water and Global Change forcing data (WFD) were used (Weedon et al., 2011). This has half-degree resolution for the whole globe at 3-hourly time resolution from 1901 to 2001. For the period 1979-2014, WATCH-ForcingData-ERA-Interim (WFDEI) was used (Weedon, 2013). For the time periods in which observed data were available, correction factors were generated by calculating monthly biases relative to the WFDEI data. These corrections were then applied to the time series from 1979 to 2014 of the WFDEI data. The WFD before 1979 were then corrected to match these data and the two datasets were joined at 1979 to provide gap-free 3-hourly forcing from 1901 to 2014. Local meteorological station observations were used for all variables except snowfall, which was estimated from the observed snow depth by treating increases in snow depth as snowfall events with an assumed snow density. See linked manuscript for more details.

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 bottomup 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 TgCH4 yr􀀀1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 TgCH4 yr􀀀1 or 60% is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 TgCH4 yr􀀀1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 TgCH4 yr􀀀1 larger than our estimate for the previous decade (2000–2009), and 24 TgCH4 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 TgCH4 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, 〈30 N) compared to mid-latitudes ( 30 %, 30–60 N) and high northern latitudes ( 4 %, 60–90 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 TgCH4 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 TgCH4 yr􀀀1 by 8 TgCH4 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.

Description: Published

Description: 1561–1623

Description: 6A. Geochimica per l'ambiente e geologia medica

Description: JCR Journal

Description: The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular ( biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 TgCH4 yr􀀀1, range 540–568. About 60% of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH4 yr􀀀1, range 596–884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions ( 64% of the global budget, 〈 30 N) as compared to mid ( 32 %, 30–60 N) and high northern latitudes ( 4 %, 60–90 N). Top-down inversions consistently infer lower emissions in China ( 58 TgCH4 yr􀀀1, range 51–72, 􀀀14 %) and higher emissions in Africa (86 TgCH4 yr􀀀1, range 73–108, C19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30–40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Description: Published

Description: 697–751

Description: 6A. Geochimica per l'ambiente

Description: JCR Journal

Description: Lakes and ponds are abundant in vast regions of the permafrost lowland landscapes in the Arctic. The areal fraction of open water surfaces can amount to more than 25% in some lowland tundra landscapes. In some tundra landscapes, about 50% of the total number of water bodies feature surface areas less than 10m². Several studies emphasize that these water bodies strongly control fundamental ecosystem processes such as the carbon, heat, and water balance. So far, it is poorly understood how these ecosystems will respond to changing climate conditions. In particular, the presence of water bodies is strongly related to the stability of the surrounding permafrost soils. Permafrost is an effective water barrier that largely controls lake formation, drainage, and growth. In return, water bodies strongly affect the thermal state of the surrounding permafrost by modifying the surface energy balance and the subsurface heat transport and storage capabilities. In order to gain a better understanding of the vulnerability of such landscapes the 1D transient permafrost model CryoGrid3 was coupled to the 1D lake model FLake. The development of the model was supported by a large observational dataset of water temperature profile measurements from lakes and ponds in northern Siberia. The coupled model was used for site level simulations for water bodies on Samoylov Island located in the Lena River Delta. Based on extensive Monte-Carlo sensitivity tests, we investigated the thermal impact of water bodies with different depths (0.2 – 5.0m) on the thermal state of sediments underneath. Climate impact simulations until 2100 were performed considering a moderate and a strong climate warming scenario. The results demonstrate that shallow water bodies (water depth 〈 1.5 m) can accelerate permafrost thaw by a factor of five. More importantly, the difference in permafrost thaw rate between moderate and strong climate warming vanish for water bodies deeper than 0.8m. Furthermore, the results demonstrate that lateral heat fluxes play an important role for stabilizing permafrost underneath small water bodies.