scholarly journals Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling

2006 ◽  
Vol 6 (5) ◽  
pp. 1275-1292 ◽  
Author(s):  
J. F. Meirink ◽  
H. J. Eskes ◽  
A. P. H. Goede
Keyword(s):  
Methane Emission ◽  
Measurement Errors ◽  
Inverse Modelling ◽  
Limiting Factor ◽  
Atmospheric Methane ◽  
Cloud Parameters ◽  
Global Emission ◽  
Spatial Coverage ◽  
Methane Source ◽  
The Impact

Abstract. Satellite observations of trace gases in the atmosphere offer a promising method for global verification of emissions and improvement of global emission inventories. Here, an inverse modelling approach based on four-dimensional variational (4D-var) data assimilation is presented and applied to synthetic measurements of atmospheric methane. In this approach, emissions and initial concentrations are optimised simultaneously, thus allowing inversions to be carried out on time scales of weeks to months, short compared with the lifetime of methane. Observing System Simulation Experiments (OSSEs) have been performed to demonstrate the feasibility of the method and to investigate the utility of SCIAMACHY observations for methane source estimation. The impact of a number of parameters on the error in the methane emission field retrieved has been analysed. These parameters include the measurement error, the error introduced by the presence of clouds, and the spatial resolution of the emission field. It is shown that 4D-var is an efficient method to deal with large amounts of satellite data and to retrieve emissions at high resolution. Some important conclusions regarding the SCIAMACHY measurements can be drawn. (i) The observations at their estimated precision of 1.5 to 2% will contribute considerably to uncertainty reduction in monthly, subcontinental (~500 km) methane source strengths. (ii) Systematic measurement errors well below 1% have a dramatic impact on the quality of the derived emission fields. Hence, every effort should be made to identify and remove such systematic errors. (iii) It is essential to take partly cloudy pixels into account in order to achieve sufficient spatial coverage. (iv) The uncertainty in measured cloud parameters may at some point become the limiting factor for methane emission retrieval, rather than the uncertainty in measured methane itself.

scholarly journals Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling

2005 ◽  
Vol 5 (5) ◽  
pp. 9405-9445 ◽  
Author(s):  
J. F. Meirink ◽  
H. J. Eskes ◽  
A. P. H. Goede
Keyword(s):  
Inverse Modelling ◽  
Limiting Factor ◽  
Atmospheric Methane ◽  
Simulation Experiments ◽  
Cloud Parameters ◽  
Global Emission ◽  
Spatial Coverage ◽  
Methane Source ◽  
The Impact ◽  
Modelling Approach

Abstract. Satellite observations of trace gases in the atmosphere offer a promising method for global verification of emissions and improvement of global emission inventories. Here, an inverse modelling approach based on four-dimensional variational (4D-var) data assimilation is presented and applied to synthetic measurements of atmospheric methane. In this approach emissions and initial concentrations are optimised simultaneously, thus allowing inversions to be carried out on time scales of weeks to months, short compared with the lifetime of methane. Observing System Simulation Experiments (OSSEs) have been performed to demonstrate the feasibility of the method and to investigate the utility of SCIAMACHY observations for methane source estimation. The impact of a number of parameters on the error in the methane emission field retrieved has been analysed. These parameters include the measurement error, the error introduced by the presence of clouds, and the spatial resolution of the emission field. It is shown that 4D-var is an efficient method to deal with large amounts of satellite data and to retrieve emissions at high resolution. Some important conclusions regarding the SCIAMACHY measurements can be drawn: (i) the observations at their estimated precision of 1.5 to 2% will contribute considerably to uncertainty reduction in monthly, subcontinental (~500 km) methane source strengths; (ii) it is essential to take partly cloudy pixels into account in order to achieve sufficient spatial coverage; and (iii) the uncertainty in measured cloud parameters may at some point become the limiting factor, rather than the uncertainty in measured methane.

scholarly journals The potential of satellite spectro-imagery for monitoring CO<sub>2</sub> emissions from large cities

2017 ◽  
Author(s):  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Emmanuel Renault ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Measurement Errors ◽  
Transport Model ◽  
Atmospheric Transport ◽  
European Space Agency ◽  
Image Resolution ◽  
Spatial Coverage ◽  
Paris Area ◽  
The Impact ◽  
Atmospheric Transport Model

Abstract. This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the Short Wave Infra Red measurements of a space borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on Observing System Simulation Experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 hours before a given satellite overpass. These 6 hours correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge about the hourly emissions from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically-integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbing missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6-hour mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.

scholarly journals The potential of satellite spectro-imagery for monitoring CO<sub>2</sub> emissions from large cities

2018 ◽  
Vol 11 (2) ◽  
pp. 681-708 ◽  
Author(s):  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Emmanuel Renault ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Measurement Errors ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Image Resolution ◽  
Spatial Coverage ◽  
Paris Area ◽  
Infrared Measurements ◽  
The Impact ◽  
Atmospheric Transport Model

Abstract. This study assesses the potential of 2 to 10 km resolution imagery of CO2 concentrations retrieved from the shortwave infrared measurements of a space-borne passive spectrometer for monitoring the spatially integrated emissions from the Paris area. Such imagery could be provided by missions similar to CarbonSat, which was studied as a candidate Earth Explorer 8 mission by the European Space Agency (ESA). This assessment is based on observing system simulation experiments (OSSEs) with an atmospheric inversion approach at city scale. The inversion system solves for hourly city CO2 emissions and natural fluxes, or for these fluxes per main anthropogenic sector or ecosystem, during the 6 h before a given satellite overpass. These 6 h correspond to the period during which emissions produce CO2 plumes that can be identified on the image from this overpass. The statistical framework of the inversion accounts for the existence of some prior knowledge with 50 % uncertainty on the hourly or sectorial emissions, and with ∼ 25 % uncertainty on the 6 h mean emissions, from an inventory based on energy use and carbon fuel consumption statistics. The link between the hourly or sectorial emissions and the vertically integrated column of CO2 observed by the satellite is simulated using a coupled flux and atmospheric transport model. This coupled model is built with the information on the spatial and temporal distribution of emissions from the emission inventory produced by the local air-quality agency (Airparif) and a 2 km horizontal resolution atmospheric transport model. Tests are conducted for different realistic simulations of the spatial coverage, resolution, precision and accuracy of the imagery from sun-synchronous polar-orbiting missions, corresponding to the specifications of CarbonSat and Sentinel-5 or extrapolated from these specifications. First, OSSEs are conducted with a rather optimistic configuration in which the inversion system is perfectly informed about the statistics of the limited number of error sources. These OSSEs indicate that the image resolution has to be finer than 4 km to decrease the uncertainty in the 6 h mean emissions by more than 50 %. More complex experiments assess the impact of more realistic error estimates that current inversion methods do not properly account for, in particular, the systematic measurement errors with spatially correlated patterns. These experiments highlight the difficulty to improve current knowledge on CO2 emissions for urban areas like Paris with CO2 observations from satellites, and call for more technological innovations in the remote sensing of vertically integrated columns of CO2 and in the inversion systems that exploit it.

scholarly journals Contribution of oxic methane production to surface methane emission in lakes and its global importance

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Marco Günthel ◽  
Daphne Donis ◽  
Georgiy Kirillin ◽  
Danny Ionescu ◽  
Mina Bizic ◽  
...  
Keyword(s):  
Surface Water ◽  
Methane Emission ◽  
Methane Production ◽  
Surface Mixed Layer ◽  
Atmospheric Methane ◽  
Methane Cycle ◽  
Surface Areas ◽  
Balance Analysis ◽  
Littoral Sediment ◽  
Methane Source

AbstractRecent discovery of oxic methane production in sea and lake waters, as well as wetlands, demands re-thinking of the global methane cycle and re-assessment of the contribution of oxic waters to atmospheric methane emission. Here we analysed system-wide sources and sinks of surface-water methane in a temperate lake. Using a mass balance analysis, we show that internal methane production in well-oxygenated surface water is an important source for surface-water methane during the stratified period. Combining our results and literature reports, oxic methane contribution to emission follows a predictive function of littoral sediment area and surface mixed layer volume. The contribution of oxic methane source(s) is predicted to increase with lake size, accounting for the majority (>50%) of surface methane emission for lakes with surface areas >1 km2.

Livestock methane emission and its perspective in the global methane cycle

2008 ◽  
Vol 48 (2) ◽  
pp. 114 ◽  
Author(s):  
Keith R. Lassey
Keyword(s):  
Methane Emission ◽  
Feed Intake ◽  
Anthropogenic Emissions ◽  
Agricultural Expansion ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
Methane Cycle ◽  
The Past ◽  
Global Emission ◽  
Global Emissions

Over the past three centuries, the atmospheric methane burden has grown 2.5-fold, reaching levels unprecedented in at least 650 000 years. Agricultural expansion has played a large part in this anthropogenic signal, with enterically fermented methane emitted by farmed ruminant livestock accounting for about one quarter of all anthropogenic emissions. This paper summarises the range of measurements that give confidence in estimates of the emission per animal and per unit feed intake and in their extrapolation to national and global emission inventories, while noting also some of the inherent uncertainties. Global emissions are discussed in the context of the evolving global methane cycle.

scholarly journals Impact of measurement errors on the inferred stellar asteroseismic ages

2018 ◽  
Vol 620 ◽  
pp. A168 ◽  
Author(s):  
G. Valle ◽  
M. Dell’Omodarme ◽  
P. G. Prada Moroni ◽  
S. Degl’Innocenti
Keyword(s):  
Effective Temperature ◽  
Measurement Errors ◽  
Regression Models ◽  
Linear Models ◽  
Projection Pursuit ◽  
Observational Constraints ◽  
Error Source ◽  
Projection Pursuit Regression ◽  
The Impact ◽  
Age Estimates

Aims. We aim to perform a theoretical investigation on the direct impact of measurement errors in the observational constraints on the recovered age for stars in main sequence (MS) and red giant branch (RGB) phases. We assumed that a mix of classical (effective temperature Teff and metallicity [Fe/H]) and asteroseismic (Δν and νmax) constraints were available for the objects. Methods. Artificial stars were sampled from a reference isochrone and subjected to random Gaussian perturbation in their observational constraints to simulate observational errors. The ages of these synthetic objects were then recovered by means of a Monte Carlo Markov chains approach over a grid of pre-computed stellar models. To account for observational uncertainties the grid covers different values of initial helium abundance and mixing-length parameter, that act as nuisance parameters in the age estimation. Results. The obtained differences between the recovered and true ages were modelled against the errors in the observables. This procedure was performed by means of linear models and projection pursuit regression models. The first class of statistical models provides an easily generalizable result, whose robustness is checked with the second method. From linear models we find that no age error source dominates in all the evolutionary phases. Assuming typical observational uncertainties, for MS the most important error source in the reconstructed age is the effective temperature of the star. An offset of 75 K accounts for an underestimation of the stellar age from 0.4 to 0.6 Gyr for initial and terminal MS. An error of 2.5% in νmax resulted the second most important source of uncertainty accounting for about −0.3 Gyr. The 0.1 dex error in [Fe/H] resulted particularly important only at the end of the MS, producing an age error of −0.4 Gyr. For the RGB phase the dominant source of uncertainty is νmax, causing an underestimation of about 0.6 Gyr; the offset in the effective temperature and Δν caused respectively an underestimation and overestimation of 0.3 Gyr. We find that the inference from the linear model is a good proxy for that from projection pursuit regression models. Therefore, inference from linear models can be safely used thanks to its broader generalizability. Finally, we explored the impact on age estimates of adding the luminosity to the previously discussed observational constraints. To this purpose, we assumed – for computational reasons – a 2.5% error in luminosity, much lower than the average error in the Gaia DR2 catalogue. However, even in this optimistic case, the addition of the luminosity does not increase precision of age estimates. Moreover, the luminosity resulted as a major contributor to the variability in the estimated ages, accounting for an error of about −0.3 Gyr in the explored evolutionary phases.

scholarly journals Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

2017 ◽  
Vol 17 (11) ◽  
pp. 6663-6678 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Mark Parrington ◽  
Anna Agustí-Panareda ◽  
Sebastien Massart ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Transport Model ◽  
A Priori ◽  
Atmospheric Composition ◽  
Random Errors ◽  
Chemical Transport Model ◽  
Spatial Coverage ◽  
Forecasting System ◽  
The Impact ◽  
Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

scholarly journals Implementation of the biogenic emission model MEGAN(v2.1) into the ECHAM6-HAMMOZ chemistry climate model. Basic results and sensitivity tests

2016 ◽  
Author(s):  
Alexandra-Jane Henrot ◽  
Tanja Stanelle ◽  
Sabine Schröder ◽  
Colombe Siegenthaler ◽  
Domenico Taraborrelli ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Climate Model ◽  
High Sensitivity ◽  
Emission Model ◽  
Terrestrial Vegetation ◽  
Biogenic Emission ◽  
Tropical Regions ◽  
Global Emission ◽  
Empirical Coefficients ◽  
The Impact

Abstract. A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the simulation period (2000–2012) is 634 Tg C yr−1. Isoprene is the main contributor to the average emission total accounting for 66 % (417 Tg C yr−1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %) and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated to tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional BVOC emissions of the reference simulation were compared to previous published experiment results with the MEGAN model. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained with the biogenic model are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of the MEGAN model. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about −9 %, but reaches +75 % for α-pinene when switching to PFT-dependent emission factor distributions. Isoprene emissions show the highest sensitivity to soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.

scholarly journals The Use of Radiocarbon Measurements in Atmospheric Studies

Radiocarbon ◽  
1990 ◽  
Vol 32 (1) ◽  
pp. 37-58 ◽  
Author(s):  
M R Manning ◽  
D C Lowe ◽  
W H Melhuish ◽  
R J Sparks ◽  
Gavin Wallace ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Circulation Model ◽  
Current Data ◽  
Atmospheric Methane ◽  
Global Circulation Model ◽  
Fossil Carbon ◽  
Global Circulation ◽  
Methane Source ◽  
Clean Air ◽  
Source Current

14C measured in trace gases in clean air helps to determine the sources of such gases, their long-range transport in the atmosphere, and their exchange with other carbon cycle reservoirs. In order to separate sources, transport and exchange, it is necessary to interpret measurements using models of these processes. We present atmospheric 14CO2 measurements made in New Zealand since 1954 and at various Pacific Ocean sites for shorter periods. We analyze these for latitudinal and seasonal variation, the latter being consistent with a seasonally varying exchange rate between the stratosphere and troposphere. The observed seasonal cycle does not agree with that predicted by a zonally averaged global circulation model. We discuss recent accelerator mass spectrometry measurements of atmospheric 14CH4 and the problems involved in determining the fossil fuel methane source. Current data imply a fossil carbon contribution of ca 25%, and the major sources of uncertainty in this number are the uncertainty in the nuclear power source of 14CH4, and in the measured value for δ14C in atmospheric methane.

scholarly journals Managed infrastructure and services to empower meteorological services in developing countries

2021 ◽  
Author(s):  
Tom Smith
Keyword(s):  
Developing Countries ◽  
Life Cycle ◽  
Value Chain ◽  
Life Cycle Management ◽  
Observation Data ◽  
Negative Consequences ◽  
Observation Systems ◽  
Spatial Coverage ◽  
The World ◽  
The Impact

&lt;p&gt;Often in developing countries the spatial coverage with surface weather observations is sparse and the reliability of existing systems is lower than in other parts of the world. These gaps in the availability of observation data have significant negative consequences, locally and globally. For decades international funds have been used to acquire meteorological infrastructure with little to no focus on life-cycle management. Furthermore, improvements in one part of the value chain are often not connected with further downstream services meaning local benefits are generated with substantial delay, if at all.&lt;/p&gt;&lt;p&gt;DTN is one of the few organizations offering comprehensive solutions across the value chain from deployment and operation of observation systems through to weather analytics creating valuable insights for business, consumers and governments across the globe. DTN not only project manages the setup of weather observation systems but also maintains and operates measurement networks on different continents. The sensor agnostic approach enables us to offer the right sensor solution for each situation.&lt;/p&gt;&lt;p&gt;We see an opportunity to correct the mistakes of the past, changing the focus from acquiring observation systems to life cycle management to ensure the systems are maintained and leveraged effectively to provide forecasts and warnings for protection of life and property and enabling NMSs to focus on fulfilling their mission.&lt;/p&gt;&lt;p&gt;Funding organizations such as the World Bank must change the focus from hardware procurement to a performance-based PPE/P model that ensures the value of investments in infrastructure are realized. This sustainable approach will; ensure long lasting partnerships, harness the innovation in the private sector, create local jobs maintaining infrastructure and enable economic development through improved ability to manage the impact of weather and climate events.&lt;/p&gt;

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