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Atmospheric methane (CH 4) is considered to be one of the most important greenhouse gases due to its increasing atmospheric concentrations and the fact that it has a warming potential 28 times that of atmospheric carbon dioxide (CO 2). Over the Indian sub-continent, fluxes and transport both contribute towards CH 4 seasonal variability. Its intra-seasonal variability however is more complex as it is additionally influenced by monsoonal activity during the Asian Summer Monsoon (ASM) period. In this study, the intra-seasonal variability of atmospheric CH 4 is examined using ground-based observations at two sites located in the Southern Indian Peninsula, Sinhagad (SNG) and Cape Rama (CRI); and outputs from three different model simulations. Both, the ground based observations and multi-model simulations show that the dominant spectral variability of CH 4 is coherent with 20–90 day oscillations in the dynamics of the monsoon (termed hereafter as Intra-Seasonal Oscillations, ISOs). The multi-model analysis revealed that CH 4 is heavily influenced by advection due to this intra-seasonal variability. The simulations also display a clear northward propagation of CH 4 anomalies over India. The co-evolution of CH 4 , outgoing long wave radiation (to represent convection) and OH radicals (proxy to CH 4 sinks) is presented. The study quantifies CH 4 variability at intra-seasonal timescales and also its spatial extent. The results suggest that the effect of ISOs on CH 4 needs to be considered along with the corresponding observations for future inverse modeling. Image 1 Composite analysis shows a clear northward propagation of atmospheric CH 4 concentration anomalies with amplitude of ±10 ppb and at a speed of approximately 1.5° latitude per day. On the day when the active spell commences (i.e. at zero on the time axis), the CH 4 concentrations switches from positive to negative at surface, middle and upper troposphere. This is visible in three different model outputs analyzed here although with some differences from model to model.Figure: Active-break composite evolution of atmospheric CH4 anomalies (ppb) over India, as simulated by models LMDz (upper left panel), ACTM (upper right panel), and CAM-Chem (lower panel). The data was averaged from 55 °E to 110 °E and is shown from the equator to 30 °N. • Surface CH 4 observations in India show coherence of 30–90 day oscillations. • Advected CH 4 signal shows clear northward propagation of anomalies during JJAS. • The co-evolutions of CH 4 , OLR, and OH radicals are presented for the JJAS period. [ABSTRACT FROM AUTHOR]

Amongst all the anthropogenically produced greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4) are the most important, owing to their maximum contribution to the net radiative forcing of the Earth. India is undergoing rapid economic development, where fossil fuel emissions have increased drastically in the last three decades. Apart from the anthropogenic activities, the GHGs dynamics in India are governed by the biospheric process and monsoon circulation; however, these aspects are not well addressed yet. Towards this, we have measured CO2 and CH4 concentration at Sinhagad, located on the Western Ghats in peninsular India. The average concentrations of CO2 and CH4 observed during the study period are 406.05 ± 6.36 and 1.97 ± 0.07 ppm (µ ± 1σ), respectively. They also exhibit significant seasonal variabilities at this site. CH4 (CO2) attains its minimum concentration during monsoon (post-monsoon), whereas CO2 (CH4) reaches its maximum concentration during pre-monsoon (post-monsoon). CO2 poses significant diurnal variations in monsoon and post-monsoon. However, CH4 exhibits a dual-peak like pattern in pre-monsoon. The study suggests that the GHG dynamics in the western region of India are significantly influenced by monsoon circulation, especially during the summer season. [ABSTRACT FROM AUTHOR]

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries. [ABSTRACT FROM AUTHOR]