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Bodeker Scientific vertical ozone profile - mixing ratio

Update Frequency: Not Planned
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2014-09-22
Download Stats: last 12 months


Bodeker Scientific produced a global combined monthly mean vertical ozone profile database spanning the period 1979 to 2007. The database is completely filled such that there are no missing data. This database is used for assessing or constraining global climate model simulations. These data held at CEDA are a copy from Bodeker Scientific taken on November 2012.

Citable as:  Bodeker, G. (2014): Bodeker Scientific vertical ozone profile - mixing ratio. NCAS British Atmospheric Data Centre, date of citation.
Abbreviation: bodeker-ozone-mixing-ratio
Keywords: bodeker scientific, ozone, mixing ratio


Previous Info:
No news update for this record
Previously used record identifiers:
Access rules:
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
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:

The raw individual ozone data are sourced from the Binary DataBase of Profiles (BDBP).
Data files were acquired at BADC from data provider's FTP server in November 2012.

File Format:

Process overview

This dataset was generated by the computation detailed below.
Title Computation process: Bodeker Scientific vertical ozone profile
Abstract Monthly means are calculated from individual ozone measurements extracted from the The Binary Data Base of Profiles (BDBP), several different satellite-instruments and ozonesondes were used. These are referred to as Tier 0 data. A regression model is fitted to the Tier 0 data at each of 70 pressure/altitude levels. The regression model is of the form: Ozone(t,lat) = A(t,lat) + Offset and seasonal cycle B(t,lat) x t + Linear trend C(t,lat) x EESC(t,AoA) + Age-of-air dependent equivalent effective stratospheric chlorine D(t,lat) x QBO(t) + Quasi-biennial Oscillation E(t,lat) x QBOorthog(t) + Orthogonalized QBO F(t,lat) x ENSO(t) + El-Niño Southern Oscillation G(t,lat) x Solar(t) + Solar cycle H(t,lat) x Pinatubo(t) + Mt. Pinatubo volcanic eruption R(t) Residual Regression model fit coefficients are expanded in Fourier series to account for seasonality and in Legendre polynomials in latitude to account for meridional structure in the fit coefficients. Regression model output is then used to produce 4 gap free Tier 1 data sets, viz.: Tier 1.1 (Anthropogenic): This comprises the mean annual cycle plus contributions from the EESC and linear trend basis functions. Tier 1.2 (Natural): This comprises the mean annual cycle plus contributions from the QBO, solar cycle and El Niño basis functions. Tier 1.3 (Natural & volcanoes): Tier 1.2 but now also including contributions from volcano basis functions. Tier 1.4 (All): Constructed by summing the contributions from all basis functions.
Input Description None
Output Description None
Software Reference None
  • standard_name: altitude
  • var_id: alt
  • units: km
  • long_name: Altitude
  • names: altitude, Altitude
  • var_id: O3
  • standard_name: mole_fraction_of_ozone_in_air
  • units: mole mole^-1
  • long_name: O3
  • names: O3, mole_fraction_of_ozone_in_air
  • units: hPa
  • long_name: Pressure
  • standard_name: air_pressure
  • var_id: plev
  • names: air_pressure, Pressure

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: lat
  • long_name: Latitude
  • names: latitude, Latitude
  • long_name: time
  • standard_name: time
  • var_id: time
  • names: time
Temporal Range
Start time:
End time:
Geographic Extent

Related parties
Authors (1)