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Discussion papers
https://doi.org/10.5194/acp-2019-231
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-231
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 04 Jun 2019

Submitted as: research article | 04 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites

Le Kuai1,2, Kevin W. Bowman1,2, Helen Worden3, Kazuyuki Miyazaki2,4, Susan Kulawik5, Andrew Conley3, Jean-François Lamarque3, Fabien Paulot3, David Paynter6, Luke D. Oman7, Sarah Strode8, Eugene Rozanov9, Andrea Stenke10, Laura Revell11, David A. Plummer12, Makoto Deushi13, Patrick Jöckel14, and Markus Kunze15 Le Kuai et al.
  • 1Joint Institute For Regional Earth System Science and Engineering, University of California, Los Angeles, USA
  • 2Jet Propulsion Laboratory, California Institute of Technology, USA
  • 3National Center for Atmospheric Research, USA
  • 4Japan Agency for Marine-Earth Science and Technology
  • 5Bay Area Environmental Research Institute, USA
  • 6NOAA, Geophysical Fluid Dynamics Laboratory, USA
  • 7NASA Goddard Space Flight Center, USA
  • 8USRA, NASA Goddard Space Flight Center, USA
  • 9Physikalisch-Meteorologisches Observatorium Davos– World Radiation Center (PMOD/WRC), Davos, Switzerland
  • 10Institute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, Switzerland
  • 11School of Physical and Chemical Sciences, University of Canterbury, Christchurch, New Zealand
  • 12Climate Research Branch, Environment and Climate Change Canada, Montreal, Canada
  • 13Meteorological Research Institute, Japan
  • 14Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 15Freie Universität Berlin, Berlin, Germany

Abstract. The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting its evolution.

To that end, we construct observational instantaneous radiative kernels (IRKs) representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm−2 attributable to tropospheric ozone bias. Another set of five models flux biases over 50 mWm−2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm−2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of difference processes. Overall, the multi-model ensemble mean bias is −132.9 ± 98 mWm−2, indicating that they are too atmospherically opaque thereby reducing sensitivity of TOA flux to ozone and potentially an underestimate of ozone radiative forcing. We find that the inter-model TOA OLR difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Le Kuai et al.
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Short summary
The tropospheric ozone increase from pre-industrial to present day leads to a radiative forcing. The top-of-atmosphere outgoing fluxes at 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 present day leads to a radiative forcing....
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