How well do climate models simulate cloud vertical structure? A comparison between CALIPSO-GOCCP satellite observations and CMIP5 models

Geophysical Research Letters

Volumn 39, Issue 20, 2012, Pages

  Cesana, G ^a   Chepfer, H ^a  

^a LABORATOIRE DE MÉTÉOROLOGIE DYNAMIQUE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84868020148     PISSN: 00948276     EISSN: None     Source Type: Journal    
DOI: 10.1029/2012GL053153     Document Type: Article

References (28)

1. Barkstrom, B. R., and G. L. Smith (1986), The Earth radiation budget experiment: Science and implementation, Rev. Geophys., 24, 379-390, doi:10.1029/RG024i002p00379.
2. Bodas-Salcedo, A., et al. (2011), COSP: Satellite simulation software for model assessment, Bull. Am. Meteorol. Soc., 92, 1023-1043, doi:10.1175/ 2011BAMS2856.1.
3. Bony, S., and J.-L. Dufresne (2005), Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, doi:10.1029/2005GL023851. (Pubitemid 41782740)
4. Chepfer, H., et al. (2008), Use of CALIPSO Lidar observations to evaluate the cloudiness simulated by a climate model, Geophys. Res. Lett., 35, L15704, doi:10.1029/2008GL034207.
5. Chepfer, H., et al. (2010), The GCM Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), J. Geophys. Res., 115, D00H16, doi:10.1029/2009JD012251.
6. Cole, J., et al. (2011), Assessing simulated clouds and radiative fluxes using properties of clouds whose tops are exposed to space, J. Clim., 24, 2715-2727, doi:10.1175/2011JCLI3652.1.
7. de Boer, G., E. W. Eloranta, and M. D. Shupe (2009), Arctic mixed-phase stratiform cloud properties from multiple years of surface-based measurements at two high-latitude locations, J. Atmos. Sci., 66(9), 2874-2887, doi:10.1175/2009JAS3029.1.
8. Dufresne, J.-L., and S. Bony (2008), An assessment of the primary sources of spread of global warming estimates from coupled atmosphere-ocean models, J. Clim., 21, 5135-5144, doi:10.1175/2008JCLI2239.1.
9. Hourdin, F., et al. (2012), LMDZ5B: The atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection, Clim. Dyn., doi:10.1007/s00382-012-1343-y, in press.
10. Jones, C. D., et al. (2011), The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543-570, doi:10.5194/gmd-4-543- 2011.
11. Jungclaus, J. H., et al. (2010), Climate and carbon-cycle variability over the last millennium, Clim. Past, 6, 723-737, doi:10.5194/cp-6-723-2010.
12. Kandel, R. S., et al. (1994), The ScaRaB project: Earth radiation budget observations from Meteor satellites, Adv. Space Res., 14, 47-54, doi:10.1016/0273-1177(94)90346-8. (Pubitemid 24400404)
13. Kay, J. E., and A. Gettelman (2009), Cloud influence on and response to seasonal Arctic sea ice loss, J. Geophys. Res., 114, D18204, doi:10.1029/2009JD011773.
14. Kay, J. E., et al. (2012), Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators, J. Clim., 25, 5190-5207, doi:10.1175/JCLI-D-11-00469.1.
15. Konsta, D., et al. (2012), A process oriented description of tropical oceanic clouds for climate model evaluation, based on a statistical analysis of daytime A-train high spatial resolution observations, Clim. Dyn., in press.
16. Meehl, G. A., et al. (2007), The WCRP CMIP3 multimodel dataset: A new era in climate change research, Bull. Am. Meteorol. Soc., 88, 1383-1394, doi:10.1175/BAMS-88-9-1383. (Pubitemid 47616759)
17. Morrison, H., et al. (2011), Resilience of persistent Arctic mixed-phase clouds, Nat. Geosci., 5, 11-17, doi:10.1038/ngeo1332.
18. Pincus, R., et al. (2012), Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators, J. Clim., 25, 4699-4720, doi:10.1175/JCLI-D-11-00267.1.
19. Randall, D. A. et al. (2007), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Chang, edited by S. Solomon et al., Cambridge Univ. Press, New York.
20. Rossow, W. B., and R. A. Schiffer (1999), Advances in understanding clouds from ISCCP, Bull. Am. Meteorol. Soc., 80, 2261-2287, doi:10.1175/1520- 0477(1999)0802.0.CO;2. (Pubitemid 129572056)
21. Shupe, M. D., S. Y. Matrosov, and T. Uttal (2006), Arctic mixed-phase cloud properties derived from surface-based sensors at SHEBA, J. Atmos. Sci., 63(2), 697-711, doi:10.1175/JAS3659.1.
22. Stephens, G. L., et al. (2002), The CloudSat mission and the A-Train: A new dimension of space-based observations of clouds and precipitation, Bull. Am. Meteorol. Soc., 83, 1771-1790, doi:10.1175/BAMS-83-12-1771.
23. Taylor, K. E., R. J. Stouffer, and G. A. Meehl (2012), An overview of CMIP5 and the experimental design, Bull. Am. Meteorol. Soc., 93, 485-498, doi:10.1175/BAMS-D-11-00094.1.
24. Voldoire, A., et al. (2011), The CNRM-CM5.1 global climate model: Description and basic evaluation, Clim. Dyn., doi:10.1007/s00382-011-1259-y, in press.
25. Wielicki, B. A., et al. (1996), Clouds and the Earth's Radiant Energy System (CERES): An Earth observing system experiment, Bull. Am. Meteorol. Soc., 77, 853-868, doi:10.1175/1520-0477(1996)0772.0.CO;2.
26. Winker, D. M., et al. (2009), Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Oceanic Technol., 26, 2310-2323, doi:10.1175/2009JTECHA1281.1.
27. Winton, M. (2006), Amplified Arctic climate change: What does surface albedo feedback have to do with it?, Geophys. Res. Lett., 33, L03701, doi:10.1029/2005GL025244.
28. Zhang, M. H., et al. (2005), Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements, J. Geophys. Res., 110, D15S02, doi:10.1029/2004JD005021. (Pubitemid 41388466)