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

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

doi:10.5194/acp-20-281-2020

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

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

Atmospheric Chemistry Observations & Modeling Lab

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

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 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 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 Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW m-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW m-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mW m-2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics 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 <math xmlnsCombining double low line"http://www.w3.org/1998/Math/MathML" idCombining double low line"M17" displayCombining double low line"inline" overflowCombining double low line"scroll" dspmathCombining double low line"mathml"><mrow><mo>-</mo><mn mathvariantCombining double low line"normal">133</mn><mo>±</mo><mn mathvariantCombining double low line"normal">98</mn></mrow></math><svg:svg xmlns:svgCombining double low line"http://www.w3.org/2000/svg" widthCombining double low line"52pt" heightCombining double low line"10pt" classCombining double low line"svg-formula" dspmathCombining double low line"mathimg" md5hashCombining double low line"5389b518f84f2067694b56b2b3c81d83"><svg:image xmlns:xlinkCombining double low line"http://www.w3.org/1999/xlink" xlink:hrefCombining double low line"acp-20-281-2020-ie00001.svg" widthCombining double low line"52pt" heightCombining double low line"10pt" srcCombining double low line"acp-20-281-2020-ie00001.png"/></svg:svg> mW m-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 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.

Original language	English
Pages (from-to)	281-301
Number of pages	21
Journal	Atmospheric Chemistry and Physics
Volume	20
Issue number	1
DOIs	https://doi.org/10.5194/acp-20-281-2020
State	Published - Jan 8 2020

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Kuai, L., Bowman, K. W., Miyazaki, K., Deushi, M., Revell, L., Rozanov, E., Paulot, F., Strode, S., Conley, A., Jöckel, P., Plummer, D. A., Oman, L. D., Worden, H., Kulawik, S., Paynter, D., Stenke, A., & Kunze, M. (2020). Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites. Atmospheric Chemistry and Physics, 20(1), 281-301. https://doi.org/10.5194/acp-20-281-2020

@article{ab75cc6a3e1e49cda9d9c8359b5af335,

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

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 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\ 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 Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100\ mW\ m-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50\ mW\ m-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30\ mW\ m-2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics 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 -133±98\ mW\ m-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 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.",

author = "Le Kuai and Bowman, \{Kevin W.\} and Kazuyuki Miyazaki and Makoto Deushi and Laura Revell and Eugene Rozanov and Fabien Paulot and Sarah Strode and Andrew Conley and Patrick J{\"o}ckel and Plummer, \{David A.\} and Oman, \{Luke D.\} and Helen Worden and Susan Kulawik and David Paynter and Andrea Stenke and Markus Kunze",

note = "Publisher Copyright: {\textcopyright} 2020. This work is distributed under the Creative Commons Attribution 4.0 License.",

year = "2020",

month = jan,

day = "8",

doi = "10.5194/acp-20-281-2020",

language = "English",

volume = "20",

pages = "281--301",

journal = "Atmospheric Chemistry and Physics",

issn = "1680-7316",

publisher = "Copernicus Publications",

number = "1",

}

Kuai, L, Bowman, KW, Miyazaki, K, Deushi, M, Revell, L, Rozanov, E, Paulot, F, Strode, S, Conley, A, Jöckel, P, Plummer, DA, Oman, LD, Worden, H, Kulawik, S, Paynter, D, Stenke, A & Kunze, M 2020, 'Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites', Atmospheric Chemistry and Physics, vol. 20, no. 1, pp. 281-301. https://doi.org/10.5194/acp-20-281-2020

TY - JOUR

T1 - Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites

AU - Kuai, Le

AU - Bowman, Kevin W.

AU - Miyazaki, Kazuyuki

AU - Deushi, Makoto

AU - Revell, Laura

AU - Rozanov, Eugene

AU - Paulot, Fabien

AU - Strode, Sarah

AU - Conley, Andrew

AU - Jöckel, Patrick

AU - Plummer, David A.

AU - Oman, Luke D.

AU - Worden, Helen

AU - Kulawik, Susan

AU - Paynter, David

AU - Stenke, Andrea

AU - Kunze, Markus

PY - 2020/1/8

Y1 - 2020/1/8

N2 - 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 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 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 Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW m-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW m-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mW m-2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics 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 -133±98 mW m-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 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.

AB - 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 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 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 Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW m-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW m-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mW m-2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics 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 -133±98 mW m-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 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.

UR - https://www.scopus.com/pages/publications/85077736672

U2 - 10.5194/acp-20-281-2020

DO - 10.5194/acp-20-281-2020

M3 - Article

AN - SCOPUS:85077736672

SN - 1680-7316

VL - 20

SP - 281

EP - 301

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

IS - 1

ER -

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

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