Speaker
Description
We present the coherent pair of the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) and the novel GOME-type Ozone Profile Essential Climate Variable (GOP-ECV) data records. Both GTO-ECV and GOP-ECV cover more than two and a half decades starting in mid-1995, and both rely on measurements performed with an extended series of European nadir-viewing satellite sensors including GOME, SCIAMACHY, GOME-2, and OMI. On top of that, TROPOMI data has been ingested in the total ozone record. Ozone information from the individual instruments is harmonized and finally merged in order to generate a consistent long-term product with global coverage that is suitable for applications relevant to climate studies.
The first version of GOP-ECV has recently been developed in the framework of the European Space Agency’s Climate Change Initiative+ ozone project (Ozone_cci+), while the well-matured total ozone data set GTO-ECV is by now extended and released on a quasi-operational basis as part of the EU Copernicus Climate Changes Service (C3S) together with an internal DLR project. Both data records benefit from the common retrieval algorithms that are used to derive the total columns (GOME direct fitting version 4 algorithm) and the ozone profiles (Rutherford Appleton Laboratory retrieval scheme), respectively. Remaining inter-sensor deviations are minimized by means of a bias correction with respect to the reference sensor OMI. In case of the ozone profile record the approach comprises a follow-up step. The profiles are clustered using machine learning techniques, and for each class a Neural Network approach is used to compute the profiles’ Jacobians, which provide information about the altitude-dependent change of the partial columns due to a change in the total column. This facilitates a refined scaling of the profiles as a function of the total column from the GTO-ECV record. Thereby, full consistency between total ozone and ozone profile data records is achieved.
The monthly mean products are freely available and common applications include the estimation of (height-resolved) decadal trends in order to determine robust ozone recovery signals and the evaluation of Chemistry-Climate Model simulations.
