Articles | Volume 20, issue 1
https://doi.org/10.5194/acp-20-281-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-281-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jan 2020
Research article |
| 08 Jan 2020
| 08 Jan 2020
Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Joint Institute For Regional Earth System Science and Engineering,
University of California, Los Angeles, CA, USA
Kevin W. Bowman
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Joint Institute For Regional Earth System Science and Engineering,
University of California, Los Angeles, CA, USA
Kazuyuki Miyazaki
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Japan Agency for Marine-Earth Science and Technology, Yokosuka, Kanagawa, Japan
Makoto Deushi
Meteorological Research Institute, Tsukuba, Ibaraki, Japan
Laura Revell
School of Physical and Chemical Sciences, University of Canterbury,
Christchurch, New Zealand
Eugene Rozanov
Physikalisch-Meteorologisches Observatorium Davos – World Radiation
Center (PMOD/WRC), Davos, Switzerland
Fabien Paulot
NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Sarah Strode
USRA, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Andrew Conley
National Center for Atmospheric Research, Boulder, CO, USA
Jean-François Lamarque
National Center for Atmospheric Research, Boulder, CO, USA
Patrick Jöckel
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für
Physik der Atmosphäre, Oberpfaffenhofen, Germany
David A. Plummer
Climate Research Branch, Environment and Climate Change Canada,
Montreal, Canada
Luke D. Oman
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Helen Worden
National Center for Atmospheric Research, Boulder, CO, USA
Susan Kulawik
Bay Area Environmental Research Institute, NASA Ames, Moffett Field, CA, USA
David Paynter
NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
Andrea Stenke
Institute for Atmospheric and Climate Science, ETH Zürich (ETHZ),
Zürich, Switzerland
Markus Kunze
Freie Universität Berlin, Berlin, Germany
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Cited
7 citations as recorded by crossref.
- Global tropospheric ozone responses to reduced NO x emissions linked to the COVID-19 worldwide lockdowns K. Miyazaki et al. https://doi.org/10.1126/sciadv.abf7460
- Assessment of regional and interannual variations in tropospheric ozone in chemical reanalyses D. Jones et al. https://doi.org/10.5194/acp-26-6655-2026
- Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018 K. Miyazaki et al. https://doi.org/10.5194/essd-12-2223-2020
- A new methodology for inferring surface ozone from multispectral satellite measurements N. Colombi et al. https://doi.org/10.1088/1748-9326/ac243d
- Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis K. Miyazaki et al. https://doi.org/10.5194/acp-20-931-2020
- Cause of a Lower‐Tropospheric High‐Ozone Layer in Spring Over Hanoi S. Ogino et al. https://doi.org/10.1029/2021JD035727
- Diagnosing the Radiation Biases in Global Climate Models Using Radiative Kernels H. Huang & Y. Huang https://doi.org/10.1029/2023GL103723
7 citations as recorded by crossref.
- Global tropospheric ozone responses to reduced NO x emissions linked to the COVID-19 worldwide lockdowns K. Miyazaki et al. https://doi.org/10.1126/sciadv.abf7460
- Assessment of regional and interannual variations in tropospheric ozone in chemical reanalyses D. Jones et al. https://doi.org/10.5194/acp-26-6655-2026
- Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018 K. Miyazaki et al. https://doi.org/10.5194/essd-12-2223-2020
- A new methodology for inferring surface ozone from multispectral satellite measurements N. Colombi et al. https://doi.org/10.1088/1748-9326/ac243d
- Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis K. Miyazaki et al. https://doi.org/10.5194/acp-20-931-2020
- Cause of a Lower‐Tropospheric High‐Ozone Layer in Spring Over Hanoi S. Ogino et al. https://doi.org/10.1029/2021JD035727
- Diagnosing the Radiation Biases in Global Climate Models Using Radiative Kernels H. Huang & Y. Huang https://doi.org/10.1029/2023GL103723
Saved (final revised paper)
Latest update: 26 Jul 2026
Short summary
The tropospheric ozone increase from pre-industrial to the present day leads to a radiative forcing. The top-of-atmosphere outgoing fluxes at the ozone band are controlled by ozone, water vapor, and temperature. We demonstrate a method to attribute the models’ flux biases to these key players using satellite-constrained instantaneous radiative kernels. The largest spread between models is found in the tropics, mainly driven by ozone and then water vapor.
The tropospheric ozone increase from pre-industrial to the present day leads to a radiative...
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