Ozone stratospheric trends from regional Bayesian composite of ground-based partial columns
Artikel i vetenskaplig tidskrift, 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.
Författare
Louis Mirallie
Federal Office of Meteorology and Climatology MeteoSwiss
Universität 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
Université Pierre et Marie Curie (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
Universität Bern
Peter Effertz
University of Colorado
National Oceanic and Atmospheric Administration
Julian Gröbner
Universidad San Francisco de Quito
Gerard Ancellet
Université Pierre et Marie Curie (UPMC)
María Cazorla
University of Toronto
Petra Duff
Karlsruher Institut für Technologie (KIT)
Matthias Max Frey
Met Éireann
Michael Gill
National Center for Atmospheric Research
J. W. Hannigan
University of Wollongong
N. Jones
Finnish Meteorological Institute
Rigel Kivi
Helmholtz-Gemeinschaft Deutscher Forschungszentren
Raphael Köhler
Ministerstwo Srodowiska, Poland
Bogumil Kois
National Aeronautics and Space Administration (NASA)
Debra E. Kollonige
ADNET Systems, Inc.
Universite de Liège
E. Mahieu
Universite de Liège
Glen McConville
National Oceanic and Atmospheric Administration
Johan Mellqvist
Chalmers, Rymd-, geo- och miljövetenskap, Geovetenskap och fjärranalys
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
Karlsruher Institut für Technologie (KIT)
K. Strong
Karlsruher Institut für Technologie (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 10303-10330Ämneskategorier (SSIF 2025)
Meteorologi och atmosfärsvetenskap
DOI
10.5194/acp-26-10303-2026