ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model.

Figure compares TOMCAT and ML-TOMCAT profiles with the three altitude-based ozone data sets with a focus on the Equator (0 HT <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi /><mo> </mo></msup></math> ht latitude). The bottom panel shows the ozone sub-column over the Antarctic (poleward of 70 HT <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi /><mo> </mo></msup></math> ht S latitude) integrated between 12 and 20 km for TOMCAT, ML-TOMCAT and MLS averaged over September-October months. We use ozone profile output from a CTM to create a machine-learning-based satellite-corrected long-term chemically (and dynamically) consistent ozone profile data set (hereafter, ML-TOMCAT) for the 1979-2020 time period. [Extracted from the article]