Dataset
Posterior South American monthly mean surface flux of methane (2010-2018) produced using the INVICAT 4D-Var inverse model.
Abstract
The emissions estimates archived here were produced through assimilation of surface flask samples of methane produced by the National Oceanic and Atmospheric Administration’s Global Monitoring Division (NOAA GMD), and column-averaged dry-air mole fractions of CH4 (XCH4) from the University of Leicester Proxy retrieval scheme v7.2 for GOSAT (Parker et al., 2011, 2020). This data was produced using the TOMCAT chemical transport model, and the INVICAT inverse transport model at the University of Leeds, in 2020. For further information on the model please see the documentation section.
This data set consist of a single file which contains a set of optimised global surface fluxes of methane (CH4), produced through variational inverse methods using TOMCAT/INVICAT. These surface fluxes are produced as monthly mean values on the (approximately) 5.6-degree horizontal model grid. The associated uncertainty for the flux from each grid cell is also included. The fluxes and uncertainties are global and cover the period Jan 2010 - Dec 2018. The emissions from fossil fuels are labelled FF_FLUX, whilst the uncertainties are labelled FF_ERROR. The emissions from natural, agricultural and biomass burning sources are labelled NAT_FLUX, whilst the uncertainties are labelled NAT_ERROR. These two sectors (fossil fuel and non-fossil fuel) are solved for separately in the inversion. Flux and uncertainty units are kg(CH4)/m2/s, and time units are days since January 1st 2010. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in Wilson et al. (2020) in the documentation section.
Details
| Previous Info: |
No news update for this record
|
|---|---|
| Previously used record identifiers: |
No related previous identifiers.
|
| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). |
| Data Quality: |
Data checked by provider prior to archiving. Data passed CEDA quality control procedure, ceda-cc.
|
| File Format: |
NetCDF
|
Related Documents
Citations: 1
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
| Wilson, C., Chipperfield, M.P., Gloor, M. et al. (2021) Large and increasing methane emissions from eastern Amazonia derived from satellite data, 2010–2018. Atmospheric Chemistry and Physics 21, 10643–10669. https://doi.org/10.5194/acp-21-10643-2021 https://doi.org/10.5194/acp-21-10643-2021 |
Process overview
| Title | INVICAT data assimilation framework |
| Abstract | INVICAT is the inverse modelling framework based on the TOMCAT 3-D global chemical transport model, developed and maintained at the University of Leeds as part of the National Centre for Earth Observation (NCEO). It uses four-dimensional variational data assimilation (4D-Var) to optimise gridded distributions of sources and sinks of atmospheric trace gases from atmospheric observations. INVICAT incorporates ATOMCAT, the adjoint version of TOMCAT, to efficiently calculate sensitivities required for the optimisation. INVICAT can assimilate observations from surface monitoring networks, aircraft campaigns and satellite instruments. INVICAT has been applied to greenhouse gases, halocarbons and other trace species, including carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), ethane (C₂H₆), carbonyl sulfide (OCS), sulfur hexafluoride (SF₆) and various chlorofluorocarbons (CFCs). The modular framework can readily be extended to additional species. Fluxes can currently be optimised at horizontal resolutions of up to 1.125° × 1.125°, and posterior uncertainty estimates can optionally be calculated. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
- units: degrees_north
- var_id: LAT_EDGE
- units: degrees_east
- var_id: LON_EDGE
- units: degrees_north
- var_id: latitude
- units: degrees_east
- var_id: longitude
- units: kg m-2 s-1
- long_name: posterior_surface_flux_of_methane_from_fossil_fuel_emissions
- var_id: FF_FLUX
- units: kg m-2 s-1
- long_name: posterior_surface_flux_of_methane_from_natural_agriculture_fire_emissions
- var_id: NAT_FLUX
- units: kg m-2 s-1
- long_name: posterior_surface_flux_uncertainty_for_methane_from_fossi_fuel_emissions
- var_id: FF_ERROR
- units: kg m-2 s-1
- long_name: posterior_surface_flux_uncertainty_for_methane_from_natural_agriculture_fire_emissions
- var_id: NAT_ERROR
- var_id: time
Co-ordinate Variables
Temporal Range
2009-12-31T23:59:59
2018-12-31T00:00:00
Geographic Extent
16.6133° |
||
-92.8100° |
-25.1200° |
|
-60.9108° |