Application of the ensemble Kalman filter in the estimation of global methane balance

Ensemble Kalman filter (EnKF) is a useful Bayesian inverse modelling method to make inference of the states of interest from observations, especially in non-linear systems with a large number of states to be estimated. This thesis presents an application of EnKF in estimation of global and regional methane budgets, where methane fluxes are inferred from atmospheric methane concentration observations. The modelling system here requires a highly non-linear atmospheric transport model to convert the state space on to the observation space, and an optimization in both spatial and temporal dimensions is desired. Methane is an important greenhouse gas, strongly influenced by anthropogenic activities, whose atmospheric concentration increased more than twice since pre-industrial times. Although its source and sink processes have been studied extensively, the mechanisms behind the increase in the 21st century atmospheric methane concentrations are still not fully understood. In this thesis, contributions of anthropogenic and natural sources to the increase in the atmospheric methane concentrations are studied by estimating the global and regional methane fluxes from anthropogenic and biospheric sources for the 21st century using an EnKF based data assimilation system (CarbonTracker Europe-CH4 ; CTE-CH4). The model was evaluated using assimilated in situ atmospheric concentration observations and various non-assimilated observations, and the model sensitivity to several setups and inputs was examined to assess the consistency of the model estimates. The key findings of this thesis include: 1) large enough ensemble size, appropriate prior error covariance, and good observation coverage are important to obtain consistent and reliable estimates, 2) CTE-CH4 was able to identify the locations and sources of the emissions that possibly contribute significantly to the increase in the atmospheric concentrations after 2007 (the Tropical and extra Tropical anthropogenic emissions), 3) Europe was found to have an insignificant or negative influence on the increase in the atmospheric CH4 concentrations in the 21st century, 4) CTE-CH4 was able to produce flux estimates that are generally consistent with various observations, but 5) the estimated fluxes are still sensitive to the number of parameters, atmospheric transport and spatial distribution of the prior fluxes.N/

Response of water use efficiency to summer drought in a boreal Scots pine forest in Finland

The influence of drought on plant functioning has received considerable attention in recent years, however our understanding of the response of carbon and water coupling to drought in terrestrial ecosystems still needs to be improved. A severe soil moisture drought occurred in southern Finland in the late summer of 2006. In this study, we investigated the response of water use efficiency to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using eddy covariance flux data from the Hyytiala (southern Finland) flux site. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Based on observed data, the ecosystem level water use efficiency (EWUE; the ratio of gross primary production, GPP, to evapotranspiration, ET) showed a decrease during the severe soil moisture drought, while the inherent water use efficiency (IWUE; a quantity defined as EWUE multiplied with mean daytime vapour pressure deficit, VPD) increased and the underlying water use efficiency (uWUE, a metric based on IWUE and a simple stomatal model, is the ratio of GPP multiplied with a square root of VPD to ET) was unchanged during the drought. The decrease in EWUE was due to the stronger decline in GPP than in ET. The increase in IWUE was because of the decreased stomatal conductance under increased VPD. The unchanged uWUE indicates that the trade-off between carbon assimilation and transpiration of the boreal Scots pine forest was not disturbed by this drought event at the site. The JSBACH simulation showed declines of both GPP and ET under the severe soil moisture drought, but to a smaller extent compared to the observed GPP and ET. Simulated GPP and ET led to a smaller decrease in EWUE but a larger increase in IWUE because of the severe soil moisture drought in comparison to observations. As in the observations, the simulated uWUE showed no changes in the drought event. The model deficiencies exist mainly due to the lack of the limiting effect of increased VPD on stomatal conductance during the low soil moisture condition. Our study provides a deeper understanding of the coupling of carbon and water cycles in the boreal Scots pine forest ecosystem and suggests possible improvements to land surface models, which play an important role in the prediction of biosphere-atmosphere feedbacks in the climate system.Peer reviewe

Utilizing earth observations of soil freeze/thaw data and atmospheric concentrations to estimate cold season methane emissions in the northern high latitudes

The northern wetland methane emission estimates have large uncertainties. Inversion models are a qualified method to estimate the methane fluxes and emissions in northern latitudes but when atmospheric observations are sparse, the models are only as good as their a priori estimates. Thus, improving a priori estimates is a competent way to reduce uncertainties and enhance emission estimates in the sparsely sampled regions. Here, we use a novel way to integrate remote sensing soil freeze/thaw (F/T) status from SMOS satellite to better capture the seasonality of methane emissions in the northern high latitude. The SMOS F/T data provide daily information of soil freezing state in the northern latitudes, and in this study, the data is used to define the cold season in the high latitudes and, thus, improve our knowledge of the seasonal cycle of biospheric methane fluxes. The SMOS F/T data is implemented to LPX-Bern DYPTOP model estimates and the modified fluxes are used as a biospheric a priori in the inversion model CarbonTracker Europe-CH4. The implementation of the SMOS F/T soil state is shown to be beneficial in improving the inversion model’s cold season biospheric flux estimates. Our results show that cold season biospheric CH4 emissions in northern high latitudes are approximately 0.60 Tg lower than previously estimated, which corresponds to 17% reduction in the cold season biospheric emissions. This reduction is partly compensated by increased anthropogenic emissions in the same area (0.23 Tg), and the results also indicates that the anthropogenic emissions could have even larger contribution in cold season than estimated here.peer-reviewe

Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use

The dramatic increase of natural gas use in China, as a substitute for coal, helps to reduce CO2 emissions and air pollution, but the climate mitigation benefit can be offset by methane leakage into the atmosphere. We estimate methane emissions from 2010 to 2018 in four regions of China using the GOSAT satellite data and in-situ observations with a high-resolution (0.1 degrees x 0.1 degrees) inverse model and analyze interannual changes of emissions by source sectors. We find that estimated methane emission over the north-eastern China region contributes the largest part (0.77 Tg CH4 yr(-1)) of the methane emission growth rate of China (0.87 Tg CH4 yr(-1)) and is largely attributable to the growth in natural gas use. The results provide evidence of a detectable impact on atmospheric methane observations by the increasing natural gas use in China and call for methane emission reductions throughout the gas supply chain and promotion of low emission end-use facilities.Peer reviewe

Interannual variability on methane emissions in monsoon Asia derived from GOSAT and surface observations

In Asia, much effort is put into reducing methane (CH4) emissions due to the region's contribution to the recent rapid global atmospheric CH4 concentration growth. Accurate quantification of Asia's CH4 budgets is critical for conducting global stocktake and achieving the long-term temperature goal of the Paris Agreement. In this study, we present top-down estimates of CH4 emissions from 2009 to 2018 deduced from atmospheric observations from surface network and GOSAT satellite with the high-resolution global inverse model NIES-TM-FLEXPART-VAR. The optimized average CH4 budgets are 63.40 +/- 10.52 Tg y(-1) from East Asia (EA), 45.20 +/- 6.22 Tg y(-1) from Southeast Asia (SEA), and 64.35 +/- 9.28 Tg y(-1) from South Asia (SA) within the 10 years. We analyzed two 5 years CH4 emission budgets for three subregions and 13 top-emitting countries with an emission budget larger than 1 Tg y(-1), and interannual variabilities for these subregions. Statistically significant increasing trends in emissions are found in EA with a lower emission growth rate during 2014-2018 compared to that during 2009-2013, while trends in SEA are not significant. In contrast to the prior emission, the posterior emission shows a significant decreasing trend in SA. The flux decrease is associated with the transition from strong La Ninna (2010-2011) to strong El Ninno (2015-2016) events, which modulate the surface air temperature and rainfall patterns. The interannual variability in CH4 flux anomalies was larger in SA compared to EA and SEA. The Southern Oscillation Index correlates strongly with interannual CH4 flux anomalies for SA. Our findings suggest that the interannual variability in the total CH4 flux is dominated by climate variability in SA. The contribution of climate variability driving interannual variability in natural and anthropogenic CH4 emissions should be further quantified, especially for tropical countries. Accounting for climate variability may be necessary to improve anthropogenic emission inventories.Peer reviewe

Evaluating atmospheric methane inversion model results for Pallas, northern Finland

A state-of-the-art inverse model, CarbonTracker Data Assimilation Shell (CTDAS), was used to optimize estimates of methane (CH4) surface fluxes using atmospheric observations of CH4 as a constraint. The model consists of the latest version of the TM5 atmospheric chemistry-transport model and an ensemble Kalman filter based data assimilation system. The model was constrained by atmospheric methane surface concentrations, obtained from the World Data Centre for Greenhouse Gases (WDCGG). Prior methane emissions were specified for five sources: biosphere, anthropogenic, fire, termites and ocean, of which bio-sphere and anthropogenic emissions were optimized. Atmospheric CH 4 mole fractions for 2007 from northern Finland calculated from prior and optimized emissions were compared with observations. It was found that the root mean squared errors of the posterior esti - mates were more than halved. Furthermore, inclusion of NOAA observations of CH 4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH 4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland

Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC

Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC

CH4_4 Fluxes Derived from Assimilation of TROPOMI XCH4_4 in CarbonTracker Europe-CH4_4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes

Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCH$_4$) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH4 fluxes using the CarbonTracker Europe-CH$_4$ (CTE-CH$_4$) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research’s (SRON) operational and University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH$_4$ emission maximum is later, when the SRON’s operational data are assimilated. The TROPOMI inversions show higher CH$_4$ emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates