Climate Dynamics

, Volume 50, Issue 7–8, pp 3097–3116 | Cite as

The influence of extratropical cloud phase and amount feedbacks on climate sensitivity

Article

Abstract

Global coupled climate models have large long-standing cloud and radiation biases, calling into question their ability to simulate climate and climate change. This study assesses the impact of reducing shortwave radiation biases on climate sensitivity within the Community Earth System Model (CESM). The model is modified by increasing supercooled cloud liquid to better match absorbed shortwave radiation observations over the Southern Ocean while tuning to reduce a compensating tropical shortwave bias. With a thermodynamic mixed-layer ocean, equilibrium warming in response to doubled CO2 increases from 4.1 K in the control to 5.6 K in the modified model. This 1.5 K increase in equilibrium climate sensitivity is caused by changes in two extratropical shortwave cloud feedbacks. First, reduced conversion of cloud ice to liquid at high southern latitudes decreases the magnitude of a negative cloud phase feedback. Second, warming is amplified in the mid-latitudes by a larger positive shortwave cloud feedback. The positive cloud feedback, usually associated with the subtropics, arises when sea surface warming increases the moisture gradient between the boundary layer and free troposphere. The increased moisture gradient enhances the effectiveness of mixing to dry the boundary layer, which decreases cloud amount and optical depth. When a full-depth ocean with dynamics and thermodynamics is included, ocean heat uptake preferentially cools the mid-latitude Southern Ocean, partially inhibiting the positive cloud feedback and slowing warming. Overall, the results highlight strong connections between Southern Ocean mixed-phase cloud partitioning, cloud feedbacks, and ocean heat uptake in a climate forced by greenhouse gas changes.

Keywords

Climate sensitivity Cloud feedback Ocean heat uptake Greenhouse gas forcing 

Notes

Acknowledgements

We thank Brian Medeiros, Isla Simpson and Kris Karnauskas for helpful conversations related to this work and useful suggestions on the manuscript. We thank Dave Bailey and Bob Tomas for their help with setting up our model runs. We gratefully acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. This work was supported by start-up funds awarded to J. E. Kay by the University of Colorado Cooperative Institute for Research in the Environmental Sciences and NSF award AGS 1554659. W. R. Frey is also supported by the Air Force Institute of Technology. The views expressed in this article are those of the authors and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the US Government.

References

  1. Andrews T, Gregory JM, Webb MJ, Taylor KE (2012) Forcing, feedbacks, and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. GeoPhys Res Lett 39:L09712. doi: 10.1029/2012GL051607 Google Scholar
  2. Andrews T, Gregory JM, Webb MJ (2015) The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models. J Clim 28:1630–1648. doi: 10.1175/JCLI-D-14-00545.1 CrossRefGoogle Scholar
  3. Armour KC, Bitz CM, Roe GH (2013) Time-varying climate sensitivity from regional feedbacks. J Clim 26:4518–4534. doi: 10.1175/JCLI-D-12-00544.1 CrossRefGoogle Scholar
  4. Armour KC, Marshall J, Scott JR, Donohoe A, Newsom ER (2016) Southern Ocean warming delayed by circumpolar upwelling and equatorward transport. Nat Geosci 9(7):549–554. doi: 10.1038/ngeo2731 CrossRefGoogle Scholar
  5. Bodas-Salcedo A, Williams KD, Field PR, Lock AP (2012) The surface downwelling solar radiation surplus over the southern ocean in the met office model: the role of midlatitude cyclone clouds. J Clim 25:7467–7486. doi: 10.1175/JCLI-D-11-00702.1 CrossRefGoogle Scholar
  6. Bodas-Salcedo A, Williams KD, Ringer MA, Beau I, Cole JNS, Dufresne JL, Koshiro T, Stevens B, Wang Z, Yokohata T (2014) Origins of the solar radiation biases over the Southern Ocean in CFMIP2 models. J Clim 27:41–56. doi: 10.1175/JCLI-D-13-00169.1 CrossRefGoogle Scholar
  7. Bodas-Salcedo A, Hill G, Furtado K, Williams KD, Field PR, Manners JC, Hyder P, Kato S (2016) Large contribution of supercooled liquid clouds to the solar radiation budget of the Southern Ocean. J Clim 29:4213–4228. doi: 10.1175/JCLI-D-15-0564.1 CrossRefGoogle Scholar
  8. Bony S, Dufresne JL (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett 32:1–4. doi: 10.1029/2005GL023851 CrossRefGoogle Scholar
  9. Bony S, Dufresne JL, Le Treut H, Morcrette JJ, Senior C (2004) On dynamic and thermodynamic components of cloud changes. Clim Dyn 22:71–86. doi: 10.1007/s00382-003-0369-6 CrossRefGoogle Scholar
  10. Boucher O, Randall D, Artaxo P, Bretherton C, Feingold G, Forster P, Kerminen VM, Kondo T, Liao H, Lohmann U, Rasch P, Satheesh SK, Sherwood S, Stevens B, Zhang XY (2013) Clouds and aerosols. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) 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 571–657. doi: 10.1017/CBO9781107415324.016 Google Scholar
  11. Bretherton CS (2015) Insights into low-latitude cloud feedbacks from high-resolution models. Philos Trans A Math Phys Eng Sci 373:3354–3360. doi: 10.1098/rsta.2014.0415 CrossRefGoogle Scholar
  12. Bretherton CS, Blossey PN (2014) Low cloud reduction in a greenhouse-warmed climate: Results from Lagrangian LES of a subtropical marine cloudiness transition. J Adv Model Earth Syst 6:91–114. doi: 10.1002/2013MS000250 CrossRefGoogle Scholar
  13. Brient F, Bony S (2013) Interpretation of the positive low-cloud feedback predicted by a climate model under global warming. Clim Dyn 40:2415–2431. doi: 10.1007/s00382-011-1279-7 CrossRefGoogle Scholar
  14. Ceppi P, Hartmann DL, Webb MJ (2016a) Mechanisms of the negative shortwave cloud feedback in high latitudes. J Clim. doi: 10.1175/JCLI-D-15-0327.1 Google Scholar
  15. Ceppi P, McCoy DT, Hartmann DL (2016b) Observational evidence for a negative shortwave cloud feedback in mid to high latitudes. Geophys Res Lett 43:1331–1339. doi: 10.1002/2015GL067499 CrossRefGoogle Scholar
  16. Cesana G, Chepfer H (2013) Evaluation of the cloud thermodynamic phase in a climate model using CALIPSO-GOCCP. J Geophys Res Atmos 118:7922–7937. doi: 10.1002/jgrd.50376 CrossRefGoogle Scholar
  17. Choi Y-S, Ho C-H, Park C-E, Storelvmo T, Tan I (2014) Influence of cloud phase composition on climate feedbacks. J Geophys Res Atmos 119:3687–3700. doi: 10.1002/2013JD020582 CrossRefGoogle Scholar
  18. Christensen MW, Carrió GG, Stephens GL, Cotton WR (2013) Radiative impacts of free-tropospheric clouds on the properties of marine stratocumulous. J Atmos Sci 70:3102–3118. doi: 10.1175/JAS-D-12-0287.1 CrossRefGoogle Scholar
  19. Chubb TH, Jensen JB, Siems ST, Manton MJ (2013) In situ observations of supercooled liquid clouds over the Southern Ocean during the HIAPER Pole-to-Pole Observation campaigns. Geophys Res Lett 40:5280–5285. doi: 10.1002/grl.50986 CrossRefGoogle Scholar
  20. Danabasoglu G, Gent PR (2009) Equilibrium climate sensitivity: is it accurate to use a slab ocean model? J Clim 22:2494–2499. doi: 10.1175/2008JCLI2596.1 CrossRefGoogle Scholar
  21. Deser C, Sun L, Tomas RA, Screen J (2016) Does ocean coupling matter for the northern extratropical response to projected Arctic sea ice loss? Geophys Res Lett 43:2149–2157. doi: 10.1002/2016GL067792 CrossRefGoogle Scholar
  22. Gettelman A, Sherwood SC (2016) Processces responsible for cloud feedback. Curr Clim Change Rep 2:179–189. doi: 10.1007/s40641-016-0052-8 CrossRefGoogle Scholar
  23. Gordon ND, Klein SA (2014) Low-cloud optical depth feedback in climate models. J Geophys Res Atmos 119:6052–6065. doi: 10.1002/2013JD021052 CrossRefGoogle Scholar
  24. Gregory JM, Andrews T (2016) Variation in climate sensitivity and feedback parameters during the historical period. GeoPhys Res Lett 43: 3911–3920. doi: 10.1002/2016GL068406 CrossRefGoogle Scholar
  25. Gregory JM, Ingram WJ, Palmer MA, Jones GS, Stott PA, Thorpe RB, Lowe JA, Johns TC, Williams KD (2004) A new method for diagnosing radiative forcing and climate sensitivity. GeoPhys Res Lett 31:L03205. doi: 10.1029/2003GL018747 Google Scholar
  26. Grise KM, Polvani LM, Fasullo JT (2015) Reexamining the relationship between climate sensitivity and Southern Hemisphere radiation budget in CMIP models. J Clim 28:9298–9312. doi: 10.1175/JCLI-D-15-0031.1 CrossRefGoogle Scholar
  27. Hawcroft M, Haywood JM, Collins M, Jones A, Jones AC, Stephens G (2016) Southern Ocean albedo, inter-hemispheric energy transports and the double ITCZ: global impacts of biases in a coupled model. Clim Dyn. doi: 10.1007/s00382-016-3205-5 Google Scholar
  28. Hu Y, Rodier S, Xu K, Sun W, Huang J, Lin B, Zhai P, Josset D (2010a) Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements. J Geophys Res 115:D00H34. doi: 10.1029/2009JD012384 CrossRefGoogle Scholar
  29. Hu Y, Rodier S, Xu K, Sun W, Huang J, Lin B, Zhai P, Josset D (2010b) Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements. J Geophys Res 115:D00H34. doi: 10.1029/2009JD012384 CrossRefGoogle Scholar
  30. Huang Y, Siems ST, Manton MJ, Protat A, Delanoë J (2012) A study on the low-altitude clouds over the Southern Ocean using the DARDAR-MASK. J Geophys Res 117:D18204. doi: 10.1029/2012JD017800 CrossRefGoogle Scholar
  31. Hwang Y-T, Frierson DMW (2013) Link between the double-Intertropical Convergence Zone problem and cloud biases over the Southern Ocean. Proc Natl Acad Sci USA 110:4935–4940. doi: 10.1073/pnas.1213302110 CrossRefGoogle Scholar
  32. Kamae Y, Watanabe M (2012) On the robustness of tropospheric adjustment in CMIP5 models. GeoPhys Res Lett 39:L23808. doi: 10.1029/2012GL054275 CrossRefGoogle Scholar
  33. Kay JE, Holland MM, Bitz CC, Blanchard-Wrigglesworth E, Gettleman A, Conley A, Bailey D (2012) The influence of local feedbacks and northward heat transport on the equilibrium Arctic climate response to increased greenhouse gas forcing. J Clim 25:5433–5450. doi: 10.1175/JCLI-D-11-00622.1 CrossRefGoogle Scholar
  34. Kay JE, Medeiros B, Hwang YT, Gettelman A, Perket J, Flanner MG (2014) Processes controlling Southern Ocean shortwave climate feedbacks in CESM, Geophys Res Lett. doi: 10.1002/2013GL058315 Google Scholar
  35. Kay JE, Deser C, Phillips A et al (2015) The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull Am Meteorol Soc 96:1333–1349. doi: 10.1175/BAMS-D-13-00255.1 CrossRefGoogle Scholar
  36. Kay JE, Bourdages L, Miller NB, Morrison A, Yettella V, Chepfer H, Eaton B (2016a) Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne LIDAR observations. J Geophys Res Atm 121:4162–4176. doi: 10.1002/2015JD024699 CrossRefGoogle Scholar
  37. Kay JE, Wall C, Yettella V, Medeiros, B, Hannay C, Caldwell P, Bitz C (2016b) Global climate impacts of fixing the Southern Ocean shortwave radiation bias in the Community Earth System Model (CESM). J Clim. doi: 10.1017/CBO9781107415324.004 Google Scholar
  38. Klein SA, McCoy RB et al (2009) Intercomparison of model simulations of mixed-phase clouds observed during the ARM mixed-phase Arctic cloud experiment. I: single-layer cloud. Q J R Met Soc 135(641):979–1002. doi: 10.1002/qj.416 CrossRefGoogle Scholar
  39. Knutti R, Rugenstein MAA (2015) Feedbacks, climate sensitivity and the limits of linear models. Phil Trans R Soc A 373:20150146. doi: 10.1098/rsta.2015.0146 CrossRefGoogle Scholar
  40. Li ZX, Le Treut H (1992) Cloud-radiation feedbacks in a general circulation model and their dependence on cloud modelling assumptions. Clim Dyn 7:133–139. doi: 10.1007/BF00211155 CrossRefGoogle Scholar
  41. Loeb NG, Wielicki BA, Doelling DR, Smith GL, Keyes DF, Kato S, Manalo-Smith N, Wong T (2009) Toward optimal closure of the Earth’s top-of-atmosphere radiation budget. J Clim 22:748–766. doi: 10.1175/2008JCLI2637.1 CrossRefGoogle Scholar
  42. Lu J, Vecchi GA, Reichler T (2007) Expansion of the Hadley cell under global warming. Geophys Res Lett 34:L06805. doi: 10.1029/2006GL028443 Google Scholar
  43. McCoy DT, Hartmann DL, Grosvenor DP (2014) Observed Southern Ocean cloud properties and shortwave reflection. Part II: phase changes and low cloud feedback. J Clim 27:8858–8868. doi: 10.1175/JCLI-D-14-00288.1 CrossRefGoogle Scholar
  44. McCoy DT, Hartmann DL, Zelinka MD, Ceppi P, Grosvenor DP (2015) Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models. J Geophys Res Atmos 120:9539–9554. doi: 10.1002/2015JD023603 CrossRefGoogle Scholar
  45. McCoy DT, Tan I, Hartmann DL, Zelinka MD, Storelvmo T (2016) On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs. J Adv Model Earth Syst. doi: 10.1002/2015MS000589 Google Scholar
  46. McCoy DT, Eastman R, Hartmann DL, Wood R (2017) The change in low cloud cover in a warmed climate inferred from AIRS, MODIS and ECMWF-Interim reanalysis. J Clim. doi: 10.1175/JCLI-D-15-0734.1 (press) Google Scholar
  47. Mitchell JFB, Senior CA, Ingram WJ (1989) CO2 and climate: a missing feedback? Nature 341:132–134. doi: 10.1038/341132a0 CrossRefGoogle Scholar
  48. Morrison AE, Siems ST, Manton MJ (2011) A three-year climatology of cloud-top phase over the Southern Ocean and North Pacific. J Clim 24:2405–2418. doi: 10.1175/2010JCLI3842.1 CrossRefGoogle Scholar
  49. Myers TA, Norris JR (2013) Observational evidence that enhanced subsidence reduces subtropical marine boundary layer cloudiness. J Clim 26:7507–7524. doi: 10.1175/JCLI-D-12-00736.1 CrossRefGoogle Scholar
  50. Park S, Bretherton CS (2009) The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the Community Atmosphere Model. J Clim 22:3449–3469. doi: 10.1175/2008JCLI2557.1 CrossRefGoogle Scholar
  51. Park S, Bretherton CS, Rasch PJ (2014) Integrating cloud processes in the Community Atmosphere Model, version 5. J Clim 27:6821–6856. doi: 10.1175/JCLI-D-14-00087.1 CrossRefGoogle Scholar
  52. 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. doi: 10.1007/s00382-013-1945-z CrossRefGoogle Scholar
  53. Raper SCB, Gregory JM, Stouffer RJ (2002) The role of climate sensitivity and ocean heat uptake on AOGCM transient temperature response. J Clim 15:124–130. doi: 10.1175/1520-0442(2002) CrossRefGoogle Scholar
  54. Rieck M, Nuijens L, Stevens B (2012) Marine boundary layer cloud feedbacks in a constant relative humidity atmosphere. J Atmos Sci 69:2538–2550. doi: 10.1175/JAS-D-11-0203.1 CrossRefGoogle Scholar
  55. Rose BEJ, Rayborn L (2016) The effects of ocean heat uptake on transient climate sensitivity. Curr Clim Change Rep. doi: 10.1007/s40641-016-0048-4 Google Scholar
  56. Rose, BEJ, Armour KC, Battisti DS, Feldl N, Koll DDB (2014) The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake, Geophys Res Lett. doi: 10.1002/2013GL058955 Google Scholar
  57. Senior CA, Mitchell JFB (2000) The time-dependence of climate sensitivity. Geophys Res Lett 27(17):2685–2688. doi: 10.1029/2000GL011373 CrossRefGoogle Scholar
  58. Sherwood SC, Bony S, Dufresne JL (2014) Spread in model climate sensitivity traced to atmospheric convective mixing. Nature 505:37–42. doi: 10.1038/nature12829 CrossRefGoogle Scholar
  59. Soden BJ, Broccoli AJ, Hemler RS (2004) On the use of cloud forcing to estimate cloud feedback. J Clim 17(19):3661–3665. doi: 10.1175/1520-0442(2004) CrossRefGoogle Scholar
  60. Storelvmo T, Tan I, Korolev AV. (2015) Cloud phase changes induced by CO2 warming—a powerful yet poorly constrained cloud-climate feedback. Curr Clim Chang Rep 1:288–296. doi: 10.1007/s40641-015-0026-2 CrossRefGoogle Scholar
  61. Tan I, Storelvmo T, Zelinka MD (2016) Observational constraints on mixed-phase clouds imply higher climate sensitivity. Science 352(6282):224–227. doi: 10.1126/science.aad5300 CrossRefGoogle Scholar
  62. Taylor KE, Crucifix M, Braconnot P, Hewitt CD, Doutriaux C, Broccoli AJ, Mitchell JFB, Webb MJ (2007) Estimating shortwave radiative forcing and response in climate models. J Clim 20:2530–2543. doi: 10.1175/JCLI4143.1 CrossRefGoogle Scholar
  63. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  64. Trenberth KE, Fasullo JT (2010) Simulation of present-day and twenty-first-century energy budgets of the southern oceans. J Clim 23:440–454. doi: 10.1175/2009JCLI3152.1 CrossRefGoogle Scholar
  65. Tselioudis G, Lipat BR, Konsta D, Grise KM, Polvani LM (2016) Midlatitude cloud shifts, their primary link to the Hadley cell, and their diverse radiative effects. Geophys Res Lett 43:4594–4601. doi: 10.1002/2016GL068242 CrossRefGoogle Scholar
  66. Tsushima Y, Emori S, Ogura T, Kimoto M, Webb MJ, Williams KD, Ringer MA, Soden BJ, Li B, Andronova N (2006) Importance of the mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study. Clim Dyn 27:113–126. doi: 10.1007/s00382-006-0127-7 CrossRefGoogle Scholar
  67. Vial J, Dufresne JL, Bony S (2013) On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim Dyn 41:3339–3362. doi: 10.1007/s00382-013-1725-9 CrossRefGoogle Scholar
  68. Webb MJ, Senior CA, Sexton DMH, et al (2006) On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim Dyn 27:17–38. doi: 10.1007/s00382-006-0111-2 CrossRefGoogle Scholar
  69. Webb MJ, Lambert FH, Gregory JM (2013) Origins of differences in climate sensitivity, forcing and feedback in climate models. Clim Dyn 40:677–707. doi: 10.1007/s00382-012-1336-x CrossRefGoogle Scholar
  70. Williams KD, Ingram WJ, Gregory JM (2008) Time variation of effective climate sensitivity in GCMs. J Clim 21:5076–5090. doi: 10.1175/2008JCLI2371.1 CrossRefGoogle Scholar
  71. Williams KD, Bodas-Salcedo A, Déqué M, Fermepin S, Medeiros B, Watanabe M, Jakob C, Klein SA, Senior CA, Williamson DL (2013) The transpose-AMIP II experiment and its application to the understanding of southern ocean cloud biases in climate models. J Clim 26:3258–3274. doi: 10.1175/JCLI-D-12-00429.1 CrossRefGoogle Scholar
  72. Winton M, Takahashi K, Held IM (2010) Importance of ocean heat uptake efficacy to transient climate change. J Clim 23:2333–2344. doi: 10.1175/2009JCLI3139.1 CrossRefGoogle Scholar
  73. Wood R, Bretherton CS (2006) On the relationship between stratiform low cloud cover and lower-tropospheric stability. J Clim 19:6425–6432. doi: 10.1175/JCLI3988.1 CrossRefGoogle Scholar
  74. Zelinka MD, Hartmann DL (2010) Why is the longwave cloud feedback positive? J Geophys Res Atm 115:D16117. doi: 10.1027/2010JD013817 CrossRefGoogle Scholar
  75. Zelinka MD, Klein SA, Hartmann DL (2012) Computing and partitioning cloud feedbacks using cloud property histograms part II: attribution to changes in cloud amount, altitude, and optical depth. J Clim 25:3736–3754. doi: 10.1175/JCLI-D-11-00249.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Cooperative Institute for Research in Environmental Sciences (CIRES) and Department of Atmospheric and Oceanic Sciences (ATOC)University of Colorado BoulderBoulderUSA

Personalised recommendations