Sunda Cloud (K-Cycle Series)

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Two LGM scenarios were run, one without a human influence and a second including a parameterization of the fire activities of hunter-gatherers estimated for this time period The resultant vegetation distribution was then used with the observed termite biomass per unit area of forest versus grasslands and the observed CH 4 emissions per unit biomass 69 to estimate the global emissions. Soil uptake was simulated using the model of ref. Soil types were derived from the Harmonized World Soil Database v1.

The soil NO x model is a semi-empirical scheme 74 , which has been used previously in this context 8. Peatlands CH 4 emissions are simulated using LPJ-WHyMe 26 , a process-based model of peatland and permafrost processes that includes two peatland plant functional types, vertically resolved production, oxidation and transport of CH 4 in soil and water table dynamics. The peatland area is prescribed from HadGEM2-ES as the fractional coverage with saturated soil conditions following ref. For consistency when including the peatland fluxes in budget calculations, the non-peatland wetland CH 4 flux is scaled so that the global pre-industrial wetland plus peatland CH 4 flux is unchanged.

The overall non-CH 4 trace gas emission budget is summarized in Supplementary Table 1. The model simulations consist of three phases see Supplementary Fig.

The monthly climatologies were then used to force each of the offline trace gas emissions models and the soil CH 4 uptake model described above. The atmospheric chemistry trace gases were initialized with fields from a separate pre-industrial simulation with HadGEM2-ES with tropospheric chemistry activated. The climate-chemistry model was then spun up for years using the trace gas emissions and soil CH 4 uptake calculated with offline models in phase 1.

The last 30 years of each chemistry-climate simulation were averaged for analysis. In phase 3, further sensitivity simulations were branched off from year 50 of the phase 2 simulations. Simulations i and ii were branched off from the emissions-driven LGM simulation and simulation iii was branched off from the pre-industrial simulation. Prescribed surface CH 4 mixing ratio that is, concentration-driven simulations were also branched off from the dynamic emissions-driven runs in phase 2 and are 30 years long for the offline photolysis and 20 years long when the photolysis rates are interactively calculated within HadGEM2-ES see Supplementary Note 1.


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Because of the computational expense of HadGEM2-ES, we use a simplified mass balance calculation of the atmospheric concentration to test the sensitivity to different combinations of total CH 4 emissions and lifetime changes between the pre-industrial and LGM. B is converted to a volume concentration using a conversion factor k which can vary as a function of tropopause height and the distribution of atmospheric CH 4.

Changes in the net source and lifetime are imposed based on the offline trace gas emission simulations and the coupled climate-chemistry simulations Tables 1 and 2. Hence the self-feedback factor for CH 4 lifetime is implicitly included. Details of these calculations are given in Supplementary Table 2 and examples are given in Supplementary Note 4. In this case, the constant k is reduced by 2. The Met Office Unified Model is available for use under licence.

The Earth System model variables analysed in the study are available from www. How to cite this article: Hopcroft, P. Understanding the glacial methane cycle.

Sunda Cloud (K-Cycle Series)

Mitchell, L. Constraints on the late Holocene anthropogenic contribution to the atmospheric methane budget. Science , — MacFarling Meure, C. Kirschke, S. Three decades of global methane sources and sinks. Myhre, G. Nisbet, E. Methane on the Rise—Again. Schaefer, H. A 21st century shift from fossil-fuel to biogenic methane emissions indicated by 13 CH4. Science , 80—84 Kaplan, J. Wetlands at the last glacial maximum: distribution and methane emissions.

Valdes, P. The ice age methane budget. Weber, S. Wetland methane emissions during the last glacial maximum estimated from PMIP2 simulations: climate, vegetation, and geographic controls. Singarayer, J.

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Late Holocene methane rise caused by orbitally controlled increase in tropical sources. Nature , 82—85 Ringeval, B. Response of methane emissions from wetlands to the Last Glacial Maximum and an idealised Dansgaard-Oeschger event: insights from two models of different complexity.


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Contrasting wetland CH4 emission responses to simulated glacial atmospheric CO2 in temperate bogs and fens.

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