Ozone stratospheric trends from regional Bayesian composite of ground-based partial columns
Journal article, 2026
Large uncertainties and variability in individual ground-based instrument records limit the detection of statistically significant ozone trends, particularly in the lower stratosphere. Available merging studies are typically performed by latitude bands on satellite-based data records. This study derives correlation-based regional composites of ground-based timeseries towards reducing trend uncertainties. We address fundamental heterogeneities resulting from grouping individually homogenized ground-based datasets to enable robust merging. Uneven temporal and vertical resolutions of five ozone measurement techniques (Ozonesondes, FTIR, Dobson Umkehr, Lidar and Microwave radiometers) are handled by integrating monthly mean ozone profiles in two sets of four independent partial columns. Spatial heterogeneity is resolved by defining coherent regions using the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. Regional timeseries are merged by the BAyeSian Integrated and Consolidated (BASIC) algorithm, adapted to consider propagated measurement uncertainties and the agreement between individual timeseries by Principal Component Analysis (PCA). Trends for the 2000–2024 period are then estimated by Multiple Linear Regression using the LOTUS model. We compare BASIC with a conventional weighted mean. While the weighted mean fails to capture variability during periods of low instrument consensus, BASIC produces more representative timeseries by robustly handling outliers. Accordingly, for the selected regions, BASIC reduces average uncertainties of the trend estimates by 9.4 % relative to the weighted-mean approach. Our results support positive trends in the upper stratosphere, predominantly negative trends in the middle stratosphere and non-significant trends in the lower stratosphere. This study establishes a consolidated ground-based reference to be used for comparison with global satellite-based ozone trends.
Author
Louis Mirallie
Federal Office of Meteorology and Climatology MeteoSwiss
University of Bern
Eliane Maillard Barras
Federal Office of Meteorology and Climatology MeteoSwiss
Caroline Jonas
Belgian Institute for Space Aeronomy (BIRA-IASB)
C. Vigouroux
Belgian Institute for Space Aeronomy (BIRA-IASB)
Roeland Van Malderen
Royal Meteorological Institute of Belgium
I. Petropavlovskikh
National Oceanic and Atmospheric Administration
University of Colorado
Sophie Godin-Beekmann
Pierre and Marie Curie University (UPMC)
Thierry Leblanc
California Institute of Technology (Caltech)
Wolfgang Steinbrecht
Deutscher Wetterdienst
Antoine Vadès
Physikalisch-Meteorologisches Observatorium Davos World Radiation Center
Rolf Ruefenacht
Federal Office of Meteorology and Climatology MeteoSwiss
A. Haefele
Federal Office of Meteorology and Climatology MeteoSwiss
Gunter Stober
University of Bern
Peter Effertz
University of Colorado
National Oceanic and Atmospheric Administration
Julian Gröbner
Universidad San Francisco de Quito
Gerard Ancellet
Pierre and Marie Curie University (UPMC)
María Cazorla
University of Toronto
Petra Duff
Karlsruhe Institute of Technology (KIT)
Matthias Max Frey
The Irish Meteorological Service
Michael Gill
National Center for Atmospheric Research
J. W. Hannigan
University of Wollongong
N. Jones
Finnish Meteorological Institute (FMI)
Rigel Kivi
Helmholtz Association of German Research Centres
Raphael Köhler
Ministry of Climate and Environment, Poland
Bogumil Kois
National Aeronautics and Space Administration (NASA)
Debra E. Kollonige
ADNET Systems, Inc.
University of Liège
E. Mahieu
University of Liège
Glen McConville
National Oceanic and Atmospheric Administration
Johan Mellqvist
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
Gary Morris
National Oceanic and Atmospheric Administration
Isao Murata
Nagoya University
Tomoo Nagahama
Naval Research Laboratory
G.E. Nedoluha
Japan Agency for Marine-Earth Science and Technology
Shin Ya Ogino
Earth Sciences New Zealand
Richard Querel
Universidad Nacional Autónoma de México
Ryan M. Stauffer
ADNET Systems, Inc.
W. Stremme
Karlsruhe Institute of Technology (KIT)
K. Strong
Karlsruhe Institute of Technology (KIT)
R. Sussmann
Saint Petersburg State University - Spsu
Anne M. Thompson
ADNET Systems, Inc.
National Aeronautics and Space Administration (NASA)
Yana Virolainen
Saint Petersburg State University - Spsu
Atmospheric Chemistry and Physics
1680-7316 (ISSN) 1680-7324 (eISSN)
Vol. 26 14 10303-10330Subject Categories (SSIF 2025)
Meteorology and Atmospheric Sciences
DOI
10.5194/acp-26-10303-2026