Climate Dynamics

, Volume 36, Issue 3–4, pp 623–635

The simulation of Arctic clouds and their influence on the winter surface temperature in present-day climate in the CMIP3 multi-model dataset

Article

Abstract

We investigate the influence of clouds on the surface energy budget and surface temperature in the sea-ice covered parts of the ocean north of the Arctic circle in present-day climate in nine global climate models participating in the Coupled Model Intercomparison Project phase 3, CMIP3. Monthly mean simulated surface skin temperature, radiative fluxes and cloud parameters are evaluated using retrievals from the extended AVHHR Polar Pathfinder (APP-x) product. We analyzed the annual cycle but the main focus is on the winter, in which large parts of the region experience polar night. We find a smaller across-model spread as well as better agreement with observations during summer than during winter in the simulated climatological annual cycles of total cloudiness and surface skin temperature. The across-model spread in liquid and ice water paths is substantial during the whole year. These results qualitatively agree with earlier studies on the present-day Arctic climate in GCMs. The climatological ensemble model mean annual cycle of surface cloud forcing shows good agreement with observations in summer. However, during winter the insulating effect of clouds tends to be underestimated in models. During winter, most of the models as well as the observations show higher monthly mean total cloud fractions, associated with larger positive surface cloud forcing. Most models also show good correlation between the surface cloud forcing and the vertically integrated ice and liquid cloud condensate. The wintertime ensemble model mean total cloud fraction (69%) shows excellent agreement with observations. The across-model spread in the winter mean cloudiness is substantial (36–94%) however and several models significantly underestimate the cloud liquid water content. If the two models not showing any relationship between cloudiness and surface cloud forcing are disregarded, a tentative across-model relation exists, in such a way that models that simulate large winter mean cloudiness also show larger surface cloud forcing. Even though the across-model spread in wintertime surface cloud forcing is large, no clear relation to the surface temperature is found. This indicates that other processes, not explicitly cloud related, are important for the simulated across-model spread in surface temperature.

Keywords

GCM Arctic clouds CRF CMIP3 APP-x Surface energy budget 

References

  1. ACIA (2005) Impacts of a warming Arctic. Arctic Climate Impact Assessment (ACIA). Tech. rep., Cambridge University Press, Cambridge, pp 140Google Scholar
  2. Ackerman TP, Stokes GM (2003) The atmospheric radiation measurement program. Phys Today 56(1): 010. doi:10.1063/1.1554135 CrossRefGoogle Scholar
  3. Arzel O, Fichefet T, Goosse H (2006) Sea ice evolution over the 20th and 21st centuries as simulated by current AOGCMs. Ocean Model 12:401–415CrossRefGoogle Scholar
  4. Cavalieri D, Parkinson C, Gloersen P, Zwally HJ (1996) Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data [1982–1999]. Technical report, National Snow and Ice Data Center, Boulder, Colorado USA. Digital media. http://nsidc.org/data/nsidc-0051.html (updated 2006)
  5. Chapman WL, Walsh JE (2007) Simulations of Arctic temperature and pressure by global coupled models. J Clim 20:609. doi:10.1175/JCLI4026.1 CrossRefGoogle Scholar
  6. Curry JA et al (2000) FIRE Arctic clouds experiment. Bull Am Meteor Soc 81:5–30CrossRefGoogle Scholar
  7. Drobot SD, Maslanik JA, Fowler C (2003) Atmospheric and sea ice conditions during the SHEBA year: historical and spatial assessment. Polar Geogr 27:15–37CrossRefGoogle Scholar
  8. Eisenman I, Untersteiner N, Wettlaufer JS (2007) On the reliability of simulated Arctic sea ice in global climate models. Geophys Res Lett 34:10 501. doi:10.1029/2007GL029914 CrossRefGoogle Scholar
  9. Gorodetskaya V, Tremblay LB, Liepert B, Cane MA, Cullather RI (2008) Simulations of Arctic temperature and pressure by global coupled models. J. Clim 21:866. doi:10.1175/2007JCLI1614.1 CrossRefGoogle Scholar
  10. Intrieri JM, Fairall CW, Shupe MD, Persson POG, Andreas EL, Guest PS, Moritz RE (2002) An annual cycle of Arctic surface cloud forcing at SHEBA. J Geophys Res (Oceans) 107:8039. doi:10.1029/2000JC000439 CrossRefGoogle Scholar
  11. Intrieri JM, Shupe MD, Uttal T, McCarty BJ (2002) An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA. J Geophys Res 107(C10):8030. doi:10.1029/2000JC000423 CrossRefGoogle Scholar
  12. Kållberg P, Berrisford P, Hoskins B, Simmmons A, Uppala S, Lamy-Thépaut S, Hine R (2005): ERA-40 atlas. Tech. rep., ERA-40 Project Report Series no 19, The European Centre for Medium-Range Weather ForecastsGoogle Scholar
  13. Key J (2002) The cloud and surface parameter retrieval (CASPR) System for Polar AVHRR User’s Guide. Tech. rep., Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Wisconsin, 61 pp. http://stratus.ssec.wisc.edu/caspr/documentation.html
  14. Liou K (1992) Radiation and cloud processes in the atmosphere: theory, observation, and modeling. Oxford University Press, New York, pp 487Google Scholar
  15. Maslanik J, Fowler C, Key J, Scambos T, Hutchinson T, Emery W (1997) AVHRR-based Polar Pathfinder products for modeling applications. Ann Glaciol 25:388–392Google Scholar
  16. Maslanik JA, Key J, Fowler CW, Nguyen T, Wang X (2001) Spatial and temporal variability of satellite-derived cloud and surface characteristics during FIRE-ACE. J. Geophys. Res 106:15233–15250. doi:10.1029/2000JD900284 CrossRefGoogle Scholar
  17. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteor Soc 88:1383–1394. doi:10.1175/BAMS-88-9-1383 CrossRefGoogle Scholar
  18. Persson POG, Fairall CW, Andreas EL, Guest PS, Perovich DK (2002) Measurements near the Atmospheric Surface Flux Group tower at SHEBA: Near-surface conditions and surface energy budget. J Geophys Res 107:8045. doi:10.1029/2000JC000705 CrossRefGoogle Scholar
  19. Ramanathan V, Cess RD, Harrison EF, Minnis P, Barkstrom BR, Ahmad E, Hartmann D (1989) Cloud-radiative forcing and climate: results from the Earth radiation budget experiment. Science 243:57–63CrossRefGoogle Scholar
  20. Raschke E, Bauer P, Lutz HJ (1992) Remote sensing of clouds and surface radiation budget over polar regions. Int J Remote Sens 13(1):13–22CrossRefGoogle Scholar
  21. Schweiger AJ, Lindsay RW, Key JR, Francis JA (1999) Arctic clouds in multiyear satellite data sets. Geophys Res Lett 26:1845–1848. doi:10.1029/1999GL900479 CrossRefGoogle Scholar
  22. Shupe M, Intrieri J (2004) Cloud radiative forcing of the Arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle. J Clim 17:616–628CrossRefGoogle Scholar
  23. Shupe MD, Matrosov SY, Uttal T (2006) Arctic mixed-phase cloud properties derived from surface-based sensors at SHEBA. J Atmos Sci 63:697–711CrossRefGoogle Scholar
  24. Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M (eds) HM (2007) IPCC-AR4, IPCC: Climate Change 2007: The scientific basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Technical report, Cambridge University Press, Cambridge pp 996Google Scholar
  25. Sorteberg A, Kattsov V, Walsh JE, Pavlova T (2007) The Arctic surface energy budget as simulated with the IPCC AR4 AOGCMs. Clim Dyn 29:131–156CrossRefGoogle Scholar
  26. Stephens GL et al (2002) The Cloudsat Mission and the A-Train. Bull. Am Meteorol Soc 83:1771–1790CrossRefGoogle Scholar
  27. Tao X, Walsh J, Chapman W (1996) An assessment of global climate model simulations of Arctic air temperatures. J Clim 9:1060–1076CrossRefGoogle Scholar
  28. Tjernström M, Sedlar J, Shupe MD (2008) How well do regional climate models reproduce radiation and clouds in the Arctic? An evaluation of ARCMIP simulations. J Appl Meteorol Clim 47:2405. doi:10.1175/2008JAMC1845.1 CrossRefGoogle Scholar
  29. Uppala SM et al (2005) The ERA-40 re-analysis. Q J R Meteorol Soc 131:2961–3012CrossRefGoogle Scholar
  30. Uttal T, Frisch S, Wang X, Key J, Schweiger A, Sun-Mack S, Minnis P (2005) Comparison of monthly mean cloud fraction and cloud optical depth determined from surface cloud radar, TOVS, AVHRR, AND MODIS over Barrow, Alaska. AMS 8th conference on polar meteorology, San DiegoGoogle Scholar
  31. Uttal T, Matrosov SY, Snider JB, Kropfli RA (1994) Relationship between ice water path and downward longwave radiation for clouds optically thin in the infrared: observations and model calculations. J Appl Meteorol 33:348–357CrossRefGoogle Scholar
  32. Uttal T et al (2002) Surface heat budget of the Arctic Ocean. Bull Am Meteorol Soc 83:255–276CrossRefGoogle Scholar
  33. Vavrus S, Waliser D, Schweiger A, Francis J (2008) Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4. Clim Dyn. doi:10.1007/s00382-008-0475-6
  34. Walsh JE, Chapman WL (1998) Arctic cloud–radiation–temperature associations in observational data and atmospheric reanalyses. J Clim 11:3030–3045CrossRefGoogle Scholar
  35. Walsh JE, Kattsov VM, Chapman WL, Govorkova V, Pavlova T (2002) Comparison of Arctic climate simulations by uncoupled and coupled global models. J Clim 15:1429–1446CrossRefGoogle Scholar
  36. Wang X, Key J (2003) Recent trends in arctic surface, cloud, and radiation properties from space. Science 299:1725–1728CrossRefGoogle Scholar
  37. Wang X, Key J (2005a) Arctic surface, cloud, and radiation properties based on the AVHRR Polar Pathfinder data set. Part I: spatial and temporal characteristics. J Clim 18(14):2558–2574CrossRefGoogle Scholar
  38. Wang X, Key J (2005b) Arctic surface, cloud, and radiation properties based on the AVHRR Polar Pathfinder data set. Part II: recent trends. J Clim 18(14):2575–2593CrossRefGoogle Scholar
  39. Winker DM, Hunt WH, McGill MJ (2007) Initial performance assessment of CALIOP. Geophys. Res. Lett 34:19 803. doi:10.1029/2007GL030135 CrossRefGoogle Scholar
  40. Winker DM, Pelon J, McCormick MP (2003) The CALIPSO mission: spaceborne lidar for observation of aerosols and clouds. Proc SPIE Int Soc Opt Eng 4893:1–11Google Scholar
  41. Zuidema P, Joyce R (2008) Water vapor, cloud liquid water paths, and rain rates over northern high latitude open seas. J Geophys Res 113(D12): 5205. doi:10.1029/2007JD009040 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Department of MeteorologyStockholm UniversityStockholmSweden

Personalised recommendations