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

Kuai, Le; Bowman, Kevin W.; Miyazaki, Kazuyuki; Deushi, Makoto; Revell, Laura; Rozanov, Eugene; Paulot, Fabien; Strode, Sarah; Conley, Andrew; Lamarque, Jean-François; Jöckel, Patrick; Plummer, David A.; Oman, Luke D.; Worden, Helen; Kulawik, Susan; Paynter, David; Stenke, Andrea; Kunze, Markus

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6 inline-formulaµm 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 (inline-formulaO3), water vapor (inline-formulaH2O), air temperature (inline-formulaTa), and surface temperature (inline-formulaTs). 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 radiative forcing evolution.

To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6 inline-formulaµm ozone band to the vertical distribution of geophysical variables, including inline-formulaO3, inline-formulaH2O, inline-formulaTa, and inline-formulaTs 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 Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric inline-formulaH2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW minline-formula−2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW minline-formula−2 due to inline-formulaH2O. On the other hand, inline-formulaTa radiative bias is negligible in all models (no more than 30 mW minline-formula−2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamicspage282 Laboratory (GFDL) general circulation model and Canadian Middle Atmosphere Model (CMAM) have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to different processes. Overall, the multi-model ensemble mean bias is inline-formula M17inlinescrollmathml - normal 133 ± normal 98 52pt10ptsvg-formulamathimg5389b518f84f2067694b56b2b3c81d83 acp-20-281-2020-ie00001.svg52pt10ptacp-20-281-2020-ie00001.png  mW minline-formula−2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric inline-formulaO3 and inline-formulaH2O. Having too much inline-formulaO3 and inline-formulaH2O in the troposphere would have different impacts on the sensitivity of TOA flux to inline-formulaO3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (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.



Kuai, Le / Bowman, Kevin W. / Miyazaki, Kazuyuki / et al: Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites. 2020. Copernicus Publications.


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