Seasonally variant low cloud adjustment over cool oceans

Abstract

The Earth’s solar reflectance is reduced through rapid climate adjustments to increasing CO2, via a decrease in total cloud cover over ocean. Perturbations to marine boundary-layer clouds are essentially important for the global radiative balance at the top of the atmosphere. However, the physical robustness of low cloud adjustments to increasing CO2 has not been assessed systematically. Here we show that low cloud adjustment is distinct from that in total cloud and is seasonally variant. Among multiple climate models, marine boundary-layer clouds over the subtropics and extratropics (especially over the Northern Hemisphere) are consistently increased in the rapid adjustment, while middle and high clouds are greatly reduced. The increase in low cloud cover is only found during summer, associated with a summertime enhancement of lower tropospheric stability. We further examine mechanisms behind the rapid adjustments of low cloud and inversion strength of the boundary layer, using land surface temperature prescribing experiments in an atmospheric general circulation model (AGCM). Summertime increases in low cloud and enhanced inversion strength over the ocean simulated in this AGCM are attributed to (1) CO2-induced land warming; and (2) reduced radiative cooling in the lower troposphere due to increased CO2. The seasonality in the cloud adjustment implies an importance of seasonal variations in background cloud and atmospheric circulation related to the Hadley and monsoon circulations for radiative forcing, feedback and climate sensitivity.

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References

  1. Abe M, Shiogama H, Yokohata T, Emori S, Nozawa T (2015) Asymmetric impact of the physiological effect of carbon dioxide on hydrological responses to instantaneous negative and positive CO2 forcing. Clim Dyn 45:2181–2192

    Article  Google Scholar 

  2. Ackerley D (2017) AMIP ACCESS 1.0 prescribed land experiment collection v1.0: PLAMIP. NCI National Research Data Collection, https://researchdata.ands.org.au/prescribed-land-amip-experiments-collection/940117, https://doi.org/10.4225/41/59521137d6c42. Accessed 15 Mar 2018

  3. Ackerley D, Dommenget D (2016) Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface 5 temperatures. Geosci Model Dev 9:2077–2098

    Article  Google Scholar 

  4. Ackerley D, Chadwick R, Dommenget D, Petrelli P (2018) An ensemble of AMIP simulations with prescribed land surface temperatures. Geosci Model Dev 11:3865–3881

    Article  Google Scholar 

  5. Andrews T, Ringer MA (2014) Cloud feedbacks, rapid adjustments, and the forcing-response relationship in a transient CO2 reversibility scenario. J Clim 27:1799–1818

    Article  Google Scholar 

  6. Andrews T, Gregory JM, Forster PM, Webb MJ (2012) Cloud adjustment and its role in CO2 radiative forcing and climate sensitivity: a review. Surv Geophys 33:619–635

    Article  Google Scholar 

  7. Bi D, Dix M, Marsland SJ et al (2013) The ACCESS coupled model: description, control climate and evaluation. Aust Meteorol Ocean J 63:41–64

    Article  Google Scholar 

  8. Blossey PN, Bretherton CS, Cheng A, Endo S, Heus T, Lock AP, van der Dussen JJ (2016) CGILS Phase 2 LES intercomparison of response of subtropical marine low cloud regimes to CO2 quadrupling and a CMIP3 composite forcing change. J Adv Model Earth Syst 8:1714–1726

    Article  Google Scholar 

  9. Bony S, Bellon G, Klocke D, Sherwood S, Fermepin S, Denvil S (2013) Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat Geosci 6:447–451

    Article  Google Scholar 

  10. Boucher O, Jones A, Betts RA (2009) Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3. Clim Dyn 32:237–249

    Article  Google Scholar 

  11. Boucher O, Randall D, Artaxo P et al (2014) Clouds and aerosols. In: Stocker TF (ed) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 571–658

    Google Scholar 

  12. Bretherton CS (2015) Insights into low-latitude cloud feedbacks from high-resolution models. Philos Trans R Soc A 373:3354–3360

    Article  Google Scholar 

  13. Bretherton CS, Blossey PN, Jones CR (2013) Mechanisms of marine low cloud sensitivity to idealized climate perturbations: A single-LES exploration extending the CGILS cases. J Adv Model Earth Syst 5:316–337

    Article  Google Scholar 

  14. Bretherton CS, Blossey PN, Stan C (2014) Cloud feedbacks on greenhouse warming in the superparameterized climate model SP-CCSM4. J Adv Model Earth Syst 6:1185–1204

    Article  Google Scholar 

  15. Ceppi P, Brient F, Zelinka MD, Hartmann DL (2017) Cloud feedback mechanisms and their representation in global climate models. WIREs Clim Change 8:e465. https://doi.org/10.1002/wcc.465

    Article  Google Scholar 

  16. Cess RD, Potter GL, Blanchet J (1989) Interpretation of cloud-climate feedback as produced by 14 atmospheric general circulation models. Science 245:513–516

    Article  Google Scholar 

  17. Chadwick R, Good P, Andrews T, Martin G (2014) Surface warming patterns drive tropical rainfall pattern responses to CO2 forcing on all timescales. Geophys Res Lett 41:610–615

    Article  Google Scholar 

  18. Chadwick R, Ackerley D, Ogura T, Dommenget D (2018) Separating the influences of land warming, the direct CO2 effect, the plant physiological effect and SST warming on regional precipitation and circulation changes. J Geophys Res Atmos (submitted)

  19. Chen J, Bordoni S (2016) Early summer response of the East Asian Summer Monsoon to atmospheric CO2 forcing and subsequent sea surface warming. J Clim 29:5431–5446

    Article  Google Scholar 

  20. Chung E-S, Soden BJ (2018) On the compensation between cloud feedback and cloud adjustment in climate models. Clim Dyn 50:1267–1276

    Article  Google Scholar 

  21. Collins WD, Ramaswamy V, Schwarzkopf MD et al (2006) Radiative forcing by well-mixed greenhouse gases: estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) fourth assessment report (AR4). J Geophys Res 111:D14317. https://doi.org/10.1029/2005JD006713

    Article  Google Scholar 

  22. Colman R (2003) Seasonal contributions to climate feedbacks. Clim Dyn 20:825–841

    Article  Google Scholar 

  23. Colman RA, McAvaney BJ (2011) On tropospheric adjustment to forcing and climate feedbacks. Clim Dyn 36:1649–1658

    Article  Google Scholar 

  24. Cox PM, Betts RA, Bunton CB, Essery RLH, Rowntree PR, Smith J (1999) The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim Dyn 15:183–203

    Article  Google Scholar 

  25. DeAngelis AM, Qu X, Hall A (2016) Importance of vegetation processes for model spread in the fast precipitation response to CO2 forcing. Geophys Res Lett 43:12550–12559

    Article  Google Scholar 

  26. Dong B, Gregory JM, Sutton RT (2009) Understanding land–sea warming contrast in response to increasing greenhouse gases. Part I: transient adjustment. J Clim 22:3079–3097

    Article  Google Scholar 

  27. Doutriaux-Boucher M, Webb MJ, Gregory JM, Boucher O (2009) Carbon dioxide induced stomatal closure increases radiative forcing via a rapid reduction in low cloud. Geophys Res Lett 36:L02703. https://doi.org/10.1029/2008GL036273

    Article  Google Scholar 

  28. Essery R, Best MJ, Cox PM (2001) Hadley Centre Technical Note 30: MOSES2.2 technical documentation, Tech. rep. United Kingdom Met Office, https://digital.nmla.metoffice.gov.uk/file/sdb%3AdigitalFile%7Cd5dbe569-5ef7-41c8-b55b-3b63dff5afbe/

  29. Frauen C, Dommenget D, Tyrrell N, Rezny M, Wales S (2014) Analysis of the nonlinearity of El Niño Southern Oscillation teleconnections. J Clim 27:6225–6244

    Article  Google Scholar 

  30. Gregory JM, Webb MJ (2008) Tropospheric adjustment induces a cloud component in CO2 forcing. J Clim 21:58–71

    Article  Google Scholar 

  31. Hansen J et al (2002) Climate forcings in Goddard Institute for Space Studies SI2000 simulations. J Geophys Res 107:4347. https://doi.org/10.1029/2001JD001143

    Article  Google Scholar 

  32. He J, Soden BJ (2015) Anthropogenic weakening of the tropical circulation: the relative roles of direct CO2 forcing and sea surface temperature change. J Clim 28:8728–8742

    Article  Google Scholar 

  33. He J, Soden BJ (2016) A re-examination of the projected subtropical precipitation decline. Nat Clim Change 7:53–57

    Article  Google Scholar 

  34. Huang Y, Tan X, Xia Y (2016) Inhomogeneous radiative forcing of homogeneous greenhouse gases. J Geophys Res Atmos 121:2780–2789

    Article  Google Scholar 

  35. Kamae Y, Watanabe M (2012) On the robustness of tropospheric adjustment in CMIP5 models. Geophys Res Lett 39:L23808. https://doi.org/10.1029/2012GL054275

    Article  Google Scholar 

  36. Kamae Y, Watanabe M (2013) Tropospheric adjustment to increasing CO2: its timescale and the role of land–sea contrast. Clim Dyn 41:3007–3024

    Article  Google Scholar 

  37. Kamae Y, Watanabe M, Kimoto M, Shiogama H (2014) Summertime land–sea thermal contrast and atmospheric circulation over East Asia in a warming climate–Part II: Importance of CO2-induced continental warming. Clim Dyn 43:2569–2583

    Article  Google Scholar 

  38. Kamae Y, Watanabe M, Ogura T, Yoshimori M, Shiogama H (2015) Rapid adjustments of cloud and hydrological cycle to increasing CO2: a review. Curr Clim Change Rep 1:103–113

    Article  Google Scholar 

  39. Kamae Y, Ogura T, Shiogama H, Watanabe M (2016a) Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review. Geosci Lett 3:17. https://doi.org/10.1186/s40562-016-0053-4

    Article  Google Scholar 

  40. Kamae Y, Ogura T, Watanabe M, Xie S-P, Ueda H (2016b) Robust cloud feedback over tropical land in a warming climate. J Geophys Res Atmos 121:2593–2609

    Article  Google Scholar 

  41. Kawai H, Koshiro T, Webb MJ (2017) Interpretation of factors controlling low cloud cover and low cloud feedback using a unified predictive index. J Clim 30:9119–9131

    Article  Google Scholar 

  42. Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6:1587–1606

    Article  Google Scholar 

  43. Luo T, Wang Z, Zhang D, Chen B (2016) Marine boundary layer structure as observed by A-train satellites. Atmos Chem Phys 16:5891–5903

    Article  Google Scholar 

  44. Martin GM, Bellouin N, Collins WJ, The HadGEM2 Development Team et al (2011) The HadGEM2 family of Met Office Unified Model climate configurations. Geosci Model Dev 4:723–757

    Article  Google Scholar 

  45. Merlis TM (2015) Direct weakening of tropical circulations from masked CO2 radiative forcing. Proc Natl Acad Sci USA 112:13167–13171

    Article  Google Scholar 

  46. Myers TA, Norris JR (2016) Reducing the uncertainty in subtropical cloud feedback. Geophys Res Lett 43:2144–2148

    Article  Google Scholar 

  47. Noda AT, Satoh M (2014) Intermodel variances of subtropical stratocumulus environments simulated in CMIP5 models. Geophys Res Lett 41:7754–7761

    Article  Google Scholar 

  48. Norris JR (1998) Low cloud type over the ocean from surface observations. Part I: relationship to surface meteorology and the vertical distribution of temperature and moisture. J Clim 11:369–382

    Article  Google Scholar 

  49. Ogura T, Webb MJ, Watanabe M, Lambert FH, Tsushima Y, Sekiguchi M (2014) Importance of instantaneous radiative forcing for rapid tropospheric adjustment. Clim Dyn 43:1409–1421

    Article  Google Scholar 

  50. Qu X, Hall A, Klein SA, Caldwell PM (2014) On the spread of changes in marine low cloud cover in climate model simulations of the 21st century. Clim Dyn 42:2603–2626

    Article  Google Scholar 

  51. Qu X, Hall A, Klein SA, Caldwell PM (2015a) The strength of the tropical inversion and its response to climate change in 18 CMIP5 models. Clim Dyn 45:375–396

    Article  Google Scholar 

  52. Qu X, Hall A, Klein SA, DeAngelis AM (2015b) Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors. Geophys Res Lett 42:7767–7775

    Article  Google Scholar 

  53. Ringer MA, Andrews T, Webb MJ (2014) Global-mean radiative feedbacks and forcing in atmosphere-only and fully-coupled climate change experiments. Geophys Res Lett 41:4035–4042

    Article  Google Scholar 

  54. Shaw TA, Voigt A (2015) Tug of war on summertime circulation between radiative forcing and sea surface warming. Nat Geosci 8:560–566

    Article  Google Scholar 

  55. Shaw TA, Voigt A (2016) Land dominates the regional response to CO2 direct radiative forcing. Geophys Res Lett 43:11383–11391

    Article  Google Scholar 

  56. Sherwood SC, Bony S, Boucher O, Bretherton C, Forster PM, Gregory JM, Stevens B (2015) Adjustments in the forcing-feedback framework for understanding climate change. Bull Am Meteorol Soc 96:217–228

    Article  Google Scholar 

  57. Shine KP, Cook J, Highwood EJ, Joshi MM (2003) An alternative to radiative forcing for estimating the relative importance of climate change mechanisms. Geophys Res Lett 30:2047. https://doi.org/10.1029/2003GL018141

    Article  Google Scholar 

  58. Shiogama H, Watanabe M, Yoshimori M et al (2012) Perturbed physics ensemble using the MIROC5 coupled atmosphere-ocean GCM without flux corrections: experimental design and results. Clim Dyn 39:3041–3056

    Article  Google Scholar 

  59. Soden BJ, Broccoli AJ, Hemler RS (2004) On the use of cloud forcing to estimate cloud feedback. J Clim 17:3661–3665

    Article  Google Scholar 

  60. Soden BJ, Held IM, Colman R, Shell KM, Kiehl JT, Shields CA (2008) Quantifying climate feedbacks using radiative kernels. J Clim 21:3504–3520

    Article  Google Scholar 

  61. Sud YC, Walker GF, Lau KM (1999) Mechanisms regulating sea-surface temperatures and deep convection in the tropics. Geophys Res Lett 26:1019–1022

    Article  Google Scholar 

  62. Sugi M, Yoshimura J (2004) A mechanism of tropical precipitation change due to CO2 increase. J Clim 17:238–243

    Article  Google Scholar 

  63. Taylor PC, Ellingson RG, Cai M (2011) Seasonal variations of climate feedbacks in the NCAR CCSM3. J Clim 24:3433–3444

    Article  Google Scholar 

  64. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Article  Google Scholar 

  65. Vial J, Dufresne J-L, Bony S (2013) On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim Dyn 41:3339–3362

    Article  Google Scholar 

  66. Watanabe M, Shiogama H, Yoshimori M, Ogura T, Yokohata T, Okamoto H, Emori S, Kimoto M (2012) Fast and slow timescales in the tropical lowcloud response to increasing CO2 in two climate models. Clim Dyn 39:1627–1641

    Article  Google Scholar 

  67. Webb MJ, Lambert FH, Gregory JM (2013) Origins of differences in climate sensitivity, forcing and feedback in climate models. Clim Dyn 40:677–707

    Article  Google Scholar 

  68. Wood R, Bretherton CS (2006) On the relationship between stratiform low cloud cover and lower-tropospheric stability. J Clim 19:6425–6432

    Article  Google Scholar 

  69. Wyant MC, Bretherton CS, Blossey PN, Khairoutdinov M (2012) Fast cloud adjustment to increasing CO2 in a superparameterized climate model. J Adv Model Earth Syst 4:M05001. https://doi.org/10.1029/2011MS000092

    Article  Google Scholar 

  70. Xu KM, Li Z, Cheng A, Hu Y (2018) Changes in clouds and atmospheric circulation associated with rapid adjustment induced by increased atmospheric CO2: a multiscale modeling framework study. Clim Dyn. https://doi.org/10.1007/s00382-018-4401-2

    Google Scholar 

  71. Zelinka M, Klein S, Taylor K, Andrews T, Webb M, Gregory J, Forster P (2013) Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5. J Clim 26:5007–5027

    Article  Google Scholar 

  72. Zhang C (1993) Large-scale variability of atmospheric deep convection in relation to sea surface temperature in the tropics. J Clim 6:1898–1913

    Article  Google Scholar 

  73. Zhou C, Zelinka MD, Klein SA (2016) Impact of decadal cloud variations on the Earth’s energy budget. Nat Geosci 9:871–874

    Article  Google Scholar 

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Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table S1 in the online supplement) for producing and making available their model output. For CMIP5, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provided coordinating support, and led the development of the software infrastructure in partnership with the Global Organization for Earth System Science Portals. This work was supported by JSPS KAKENHI Grant Numbers 17K14388 and 17K05657, and the Integrated Research Program for Advancing Climate Models (TOUGOU program) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The authors are grateful to two anonymous reviewers for their constructive comments. We would like to acknowledge M. Watanabe and H. Shiogama for helpful discussions.

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Correspondence to Youichi Kamae.

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Kamae, Y., Chadwick, R., Ackerley, D. et al. Seasonally variant low cloud adjustment over cool oceans. Clim Dyn 52, 5801–5817 (2019). https://doi.org/10.1007/s00382-018-4478-7

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Keywords

  • Cloud adjustment
  • Instantaneous radiative forcing
  • Inversion strength
  • Low cloud