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DOI | 10.5194/acp-20-281-2020 |
Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites | |
Kuai, Le1,2; Bowman, Kevin W.1,2; Miyazaki, Kazuyuki1,3; Deushi, Makoto4; Revell, Laura5; Rozanov, Eugene6; Paulot, Fabien7; Strode, Sarah8; Conley, Andrew9; Lamarque, Jean-Francois9; Joeckel, Patrick10; Plummer, David A.11; Oman, Luke D.12; Worden, Helen9; Kulawik, Susan13; Paynter, David7; Stenke, Andrea14; Kunze, Markus15 | |
2020-01-08 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS |
ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2020 |
卷号 | 20期号:1页码:281-301 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Japan; New Zealand; Switzerland; Germany; Canada |
英文摘要 | The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6 mu m 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 (O-3), water vapor (H2O), air temperature (T-a), and surface temperature (T-s). 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 mu m ozone band to the vertical distribution of geophysical variables, including O-3, H2O, T-a, and T-s 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 O-3 and H2O. Having too much O-3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O-3 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. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000506326400001 |
WOS关键词 | OUTGOING LONGWAVE RADIATION ; TROPOSPHERIC OZONE ; ATMOSPHERIC CHEMISTRY ; GLOBAL CLIMATOLOGY ; OMI ; ASSIMILATION ; SIMULATIONS ; EMISSIONS ; TRANSPORT ; EARTH |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/278542 |
专题 | 地球科学 |
作者单位 | 1.CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA; 2.Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci & Engn, Los Angeles, CA 90032 USA; 3.Japan Agcy Marine Earth Sci & Technol, Yokosuka, Kanagawa, Japan; 4.Meteorol Res Inst, Tsukuba, Ibaraki, Japan; 5.Univ Canterbury, Sch Phys & Chem Sci, Christchurch, New Zealand; 6.PMOD WRC, Davos, Switzerland; 7.NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA; 8.NASA, Goddard Space Flight Ctr, USRA, Greenbelt, MD USA; 9.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA; 10.Deutsch Zentrum Luft & Raumfahrt DLR, Inst Phys Atmosphare, Oberpfaffenhofen, Germany; 11.Environm & Climate Change Canada, Climate Res Branch, Montreal, PQ, Canada; 12.NASA, Goddard Space Flight Ctr, Greenbelt, MD USA; 13.NASA Ames, Bay Area Environm Res Inst, Moffett Field, CA USA; 14.ETHZ, Inst Atmospher & Climate Sci, Zurich, Switzerland; 15.Free Univ Berlin, Berlin, Germany |
推荐引用方式 GB/T 7714 | Kuai, Le,Bowman, Kevin W.,Miyazaki, Kazuyuki,et al. Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2020,20(1):281-301. |
APA | Kuai, Le.,Bowman, Kevin W..,Miyazaki, Kazuyuki.,Deushi, Makoto.,Revell, Laura.,...&Kunze, Markus.(2020).Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(1),281-301. |
MLA | Kuai, Le,et al."Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.1(2020):281-301. |
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