1. Sea-ice albedo, clouds, and cloud-radiation interactions in the Arctic in the CMIP5 model ensemble Johannes Karlsson and Gunilla Svensson Department of Meteorology and Bolin Centre for Climate Research Thanks to: Karl-Göran Karlsson, Jennifer Kay, Michael Tjernström and the CMIP5 project

2. Motivation Two previous studies (Karlsson and Svensson, 2011 and Svensson and Karlsson 2011) showed that temperature, humidity, clouds are very different in GCMs, models are often colder and dryer than available observations The representation of Arctic sea-ice extent seems to be improved in the CMIP5 ensemble Has the representation of the atmosphere, in particular the clouds and their effect on the surface energy balance, improved in the models? Photo: M. Tjernström

3. We define the Arctic as the region north of the Arctic Circle (> 66.6°N) Random GCM’s September situation Analysis Considering the huge contrasts in surface fluxes, we separate the analysis according to surface category: > 80% sea ice < 20% sea ice Sea-ice covered ocean Marginal ice-zone Open ocean Land surface (>20% land) and

4. Analysis 17 CMIP5 GCMs + ERA-Interim reanalysis Monthly averaged data The historical simulation,1980-2004 Two AVHRR-based retrieval datasets  APP-x (Wang and Key, 2005 J. Clim)  CLARA-A1 (Riihelä et al. and KG Karlsson et al, both 2013 in ACP disc.)

5. Total cloud fraction, IWP, LWP and IWP/TWP over sea ice CMIP3 model envelope Karlsson and Svensson (Clim. Dyn., 2011) Ice water path/Total water path Ice water path [gm -2 ] 1980-2004 Liquid water path [gm -2 ]

6. CMIP3 model envelope Surface cloud radiative effect over sea ice 1980-2004

7. CMIP3 model envelope 1980-2004 Surface cloud radiative effect over sea ice

8. The cloud radiative effect at the surface:

9. Surface cloud radiative effect over sea ice The cloud radiative effect at the surface: SmallerLarger Longwave cloud greenhouse effect dominates Shortwave cloud albedo effect dominates

10. Sea ice albedo Sea-ice albedo 1982-2009) 1980-2004 “sunlit season” CLARA-A1 (EUMETSAT Sfc. Cloud effect [Wm -2 ]

11. Seasonal averaged sea-ice albedo May June July August 1980-2004 The seasonally averaged effective sea-ice albedo is derived from the monthly averaged and area- weighted surface shortwave fluxes: represents the time-changing area of the sea-ice

12. Seasonal sea-ice albedo and summer CRE AVHRR RETRIEVALS (APP-X and CLARA-A1) APP-x Interannual range May June July August 1980-2004

13. AVHRR RETRIEVALS (APP-X and CLARA-A1) APP-x Interannual range The sea ice albedo dependency of the surface cloud radiative effect determines its magnitude and sign A change in cloudiness will feed back very differently on the models’ surface energy budget Seasonal sea-ice albedo and summer CRE May June July August 1980-2004

14. median model range HISTORICAL 1980-2004 Frac. area of Arctic ocean Sea-ice cover 1980-2004

15. median model range HISTORICAL 1980-2004 Frac. area of Arctic ocean Sea-ice cover 1980-2004 Can differences in sea-ice albedo explain the model- spread in the annual amplitude of sea-ice cover?

16. Sea-ice extent and summer sea-ice albedo AVHRR RETRIEVALS (APP-X and CLARA- A1) NSIDC NIMBUS data Interannual range May June July August 1980-2004

17. Present day sea-ice concentration and sea-ice albedo conditions the potential future change of absorbed surface solar radiation in the Arctic. Isolines indicate the increase in absorbed solar radiation [Wm -2 ] at the surface in the transition to an ice-free Arctic ocean, assuming 80% winter sea-ice extent, 0.1 ocean albedo and unchanged summer surface insolation of 220 Wm -2. Sea-ice extent and summer sea-ice albedo May June July August 1980-2004

18. 75Wm -2 The models differ by up to 75 Wm -2, as seasonal average, in how much energy the ice-free ocean could potentially absorb Sea-ice extent and summer sea-ice albedo May June July August 1980-2004

19. Conclusions Across-model spread in cloud variables in the Arctic remains large and no improvement compared to CMIP3 is evident Summertime model-spread in surface cloud radiative effect is primarily not related to cloudiness variables but to the albedo of sea-ice. In models with high (low) sea-ice albedo clouds warm (cool) the surface There is also a significant across-model correlation between models’ summer sea-ice albedo and their annual amplitude in sea ice concentration Present-day spread in sea-ice concentration and albedo strongly conditions the increase in Arctic absorbed surface solar radiation in a potential transition to ice-free conditions

20. Biases in modeled wintertime radiative fluxes over the Arctic and consequences for the surface energy balance Welcome to our poster Photo: M. Tjernström Questions?

21. CALIPSO total cloud fraction, max/min monthly average, Jun 2006 – Dec 2009 envelope Total cloud fraction over sea ice CALIPSO simulator

22. Seasonal averaged sea ice albedo May June July August 1980-2004 The seasonally averaged sea-ice albedo is derived from the seasonally averaged and area-weighted surface shortwave fluxes. This is the effective albedo of the summer sea-ice: Where area i represents the time-changing area of the sea-ice category