This website uses cookies. By continuing to use this website you are agreeing to our use of cookies. 



ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product, version 5.2 (CH4_GOS_OCPR) generated with the OCPR (UoL-PR) algorithm

Latest Data Update: 2015-06-14
Status: Superseded
Online Status: ONLINE
Publication State: Working
Publication Date:
Download Stats: last 12 months
Dataset Size: 1.68K Files | 2GB

This dataset has been superseded. See Latest Version here

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 GOS PR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT).

This version of the proxy product has been generated using version 5.2 of the OCPR University of Leicester Full-Physics Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm, and the link to this product's record page is provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.

The product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.

Citable as:  ESA CCI GHG project team (9999): ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product, version 5.2 (CH4_GOS_OCPR) generated with the OCPR (UoL-PR) algorithm. Centre for Environmental Data Analysis, date of citation.
Abbreviation: Not defined


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: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project

File Format:
The data are stored in Netcdf format which can be read with standard tools in the common programming languages (IDL, Matlab, Python, Fortran90, C++, etc).

Process overview

  • units: K
  • long_name: air_temperature_apriori
  • var_id: air_temperature_apriori
  • names: air_temperature_apriori
  • units: 1e-9
  • var_id: ch4_profile_apriori
  • long_name: ch4_profile_apriori
  • names: ch4_profile_apriori
  • units: 1e-6
  • var_id: co2_profile_apriori
  • long_name: co2_profile_apriori
  • names: co2_profile_apriori
  • units: 1
  • long_name: exposure_id
  • var_id: exposure_id
  • names: exposure_id
  • units: 1
  • long_name: gain
  • var_id: gain
  • names: gain
  • units: 1e-6
  • long_name: h2o_profile_apriori
  • var_id: h2o_profile_apriori
  • names: h2o_profile_apriori
  • units: hPa
  • var_id: pressure_levels
  • long_name: pressure_levels
  • names: pressure_levels
  • units: 1
  • var_id: pressure_weight
  • long_name: pressure_weight
  • names: pressure_weight
  • units: 1e-9
  • long_name: raw_xch4
  • var_id: raw_xch4
  • names: raw_xch4
  • units: 1e-9
  • long_name: raw_xch4_error
  • var_id: raw_xch4_error
  • names: raw_xch4_error
  • units: 1e-6
  • long_name: raw_xco2
  • var_id: raw_xco2
  • names: raw_xco2
  • units: 1e-6
  • long_name: raw_xco2_error
  • var_id: raw_xco2_error
  • names: raw_xco2_error
  • units: degree
  • standard_name: sensor_zenith_angle
  • var_id: sensor_zenith_angle
  • long_name: sensor_zenith_angle
  • names: sensor_zenith_angle, sensor zenith angle
  • units: degree
  • var_id: solar_zenith_angle
  • standard_name: solar_zenith_angle
  • long_name: solar_zenith_angle
  • names: solar zenith angle, solar_zenith_angle
  • units: hPa
  • long_name: surface_air_pressure_apriori
  • var_id: surface_air_pressure_apriori
  • names: surface_air_pressure_apriori
  • units: hPa
  • long_name: surface_air_pressure_apriori_std
  • var_id: surface_air_pressure_apriori_std
  • names: surface_air_pressure_apriori_std
  • units: m
  • standard_name: surface_altitude
  • var_id: surface_altitude
  • long_name: surface_altitude
  • names: surface_altitude, surface altitude
  • units: m
  • long_name: surface_altitude_stdev
  • var_id: surface_altitude_stdev
  • names: surface_altitude_stdev
  • units: 1e-9
  • var_id: xch4
  • long_name: xch4
  • names: xch4
  • units: 1
  • var_id: xch4_averaging_kernel
  • long_name: xch4_averaging_kernel
  • names: xch4_averaging_kernel
  • units: 1
  • var_id: xch4_quality_flag
  • long_name: xch4_quality_flag
  • names: xch4_quality_flag
  • units: 1e-9
  • var_id: xch4_uncertainty
  • long_name: xch4_uncertainty
  • names: xch4_uncertainty
  • units: 1
  • var_id: xco2_averaging_kernel
  • long_name: xco2_averaging_kernel
  • names: xco2_averaging_kernel

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: latitude
  • long_name: latitude
  • names: latitude
  • units: degrees_east
  • standard_name: longitude
  • var_id: longitude
  • long_name: longitude
  • names: longitude
  • long_name: time
  • standard_name: time
  • var_id: time
  • names: time
Temporal Range
Start time:
End time:
Geographic Extent