Diagnosis of regime-dependent cloud simulation errors in CMIP5 models using "a-Train" satellite observations and reanalysis data

Journal of Geophysical Research Atmospheres

Volumn 118, Issue 7, 2013, Pages 2762-2780

  Su, Hui ^a   Jiang, Jonathan H ^a   Zhai, Chengxing ^a   Perun, Vince S ^a   Shen, Janice T ^a   Del Genio, Anthony ^b   Nazarenko, Larissa S ^b   Donner, Leo J ^c   Horowitz, Larry ^c   Seman, Charles ^c   Morcrette, Cyril ^d   Petch, Jon ^d   Ringer, Mark ^d   Cole, Jason ^e   Von Salzen, Knut ^e   Mesquita, Michel D S ^f   Iversen, Trond ^g   Kristjansson, Jon Egill ^h   Gettelman, Andrew ⁱ   Rotstayn, Leon ^j   Jeffrey, Stephen ^k   Dufresne, Jean Louis ^l   Watanabe, Masahiro ^m   Kawai, Hideaki ⁿ   Koshiro, Tsuyoshi ⁿ   Wu, Tongwen ^o   Volodin, Evgeny M ^p   L'Ecuyer, Tristan ^q   Teixeira, Joao ^a   Stephens, Graeme L ^a   more..

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b NASA GODDARD INSTITUTE FOR SPACE STUDIES   (United States)

^c NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^d MET OFFICE   (United Kingdom)

^e ENVIRONMENT CANADA   (Canada)

^f BJERKNES CENTRE FOR CLIMATE RESEARCH   (Norway)

^g NORWEGIAN METEOROLOGICAL INSTITUTE   (Norway)

^h UNIVERSITY OF OSLO   (Norway)

ⁱ NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^j CSIRO   (Australia)

^k DEPARTMENT OF ENVIRONMENT AND RESOURCE MANAGEMENT   (Australia)

^l LABORATOIRE DE MÉTÉOROLOGIE DYNAMIQUE   (France)

^m UNIVERSITY OF TOKYO   (Japan)

ⁿ JAPAN METEOROLOGICAL AGENCY   (Japan)

^o NATIONAL CLIMATE CENTER   (China)

^p INSTITUTE OF NUMERICAL MATHEMATICS   (Russian Federation)

^q UNIVERSITY OF WISCONSIN MADISON   (United States)

more..

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC THERMODYNAMICS; CLIMATE MODELS; CLOUDS; ERRORS;

CLOUD TOP HEIGHTS; COUPLED MODEL INTERCOMPARISON PROJECT; DEEP CONVECTIVE CLOUDS; LOWER TROPOSPHERE; SATELLITE OBSERVATIONS; VERTICAL DISTRIBUTIONS; VERTICAL STRUCTURES; VERTICAL VELOCITY;

COMPUTER SIMULATION;

CALIPSO; CLIMATE MODELING; CLOUDSAT; CONDENSATE; CONVECTIVE CLOUD; DATA SET; ERROR ANALYSIS; MOISTURE CONTENT; SATELLITE IMAGERY; TROPOSPHERE;

EID: 84881651440     PISSN: None     EISSN: 21698996     Source Type: Journal    
DOI: 10.1029/2012JD018575     Document Type: Article

References (56)

1. Arora, V. K., J. F. Scinocca, G. J. Boer, J. R. Christian, K. L. Denman, G. M. Flato, V. V. Kharin,W. G. Lee, andW. J. Merryfield (2011), Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases, Geophys. Res. Lett., 38, L05805, doi:10.1029/2010GL046270.
2. Austin, R. T., A. J. Heymsfield, and G. L. Stephens (2009), Retrieval of ice cloud microphysical parameters using the CloudSat millimeter-wave radar and temperature, J. Geophys. Res., 114, D00A23, doi:10.1029/2008JD010049.
3. Bennhold, F., and S. Sherwood (2008), Erroneous Relationships among Humidity and Cloud Forcing Variables in Three Global Climate Models. J. Climate, 21, 4190-4206.
4. Bentsen, M., I. Bethke, J. B. Debernard, T. Iversen, A. Kirkevag, Ø. Seland, H. Drange, C. Roelandt, I. A. Seierstad, C. Hoose, and J. E. Kristjansson (2012), The Norwegian Earth System Model, NorESM1-M - Part 1: Description and basic evaluation, Geosci. Model Dev. Discuss., 5, 2843-2931, doi:10.5194/gmdd-5-2843-2012.
5. Bodas-Salcedo, A., et al. (2011), COSP: Satellite simulation software for model assessment, Bull. Amer. Met. Soc., 92, 1023-1043. doi:10.1175/ 2011BAMS2856.1.
6. Bodas-Salcedo A., M. J. Webb, M. E. Brooks, M. A. Ringer, K. D. Williams, S. F. Milton, and D. R.Wilson (2008), Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities, J. Geophys. Res., 113, D00A13, doi:10.1029/2007JD009620.
7. Bony, S., and J.-L. Dufresne, H. LeTreut, J.-J. Morcrette, and C. Senior (2004), On dynamic and thermodynamic components of cloud changes. Clim. Dyn., 22, 71-86.
8. 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.
9. Collins, W. J., et al. (2011), Development and evaluation of an Earth-system model - HadGEM2, Geosci. Model Dev. Discuss., 4, 997-1062, doi:10.5194/gmdd-4-997-2011.
10. Dai, A. (2006), Precipitation characteristics in eighteen coupled climate models, J. Climate, 19, 4605-4630.
11. Diansky, N. A., A. V. Bagno, and V. B. Zalesny (2002), Sigma model of global ocean circulation and its sensitivity to variations in wind stress. Izv. Atmos. Ocean. Phys. (Engl. Transl.), 38(5), 477-494.
12. Diansky N. A., and E. M. Volodin (2002), Simulation of present-day climate with a coupled Atmosphere-ocean general circulation model. Izv. Atmos. Ocean. Phys. (Engl. Transl.), 38(6), 732-747.
13. Donner, L. J., et al. (2011): The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component of the GFDL coupled model CM3, J. Climate, 24, 3484-3519, doi: 10.1175/2011JCLI3955.1.
14. Dufresne, J.-L., et al. (2013), Climate change projections using the IPSLCM5 Earth System Model: from CMIP3 to CMIP5, Clim. Dyn., doi:10.1007/s00382-012-1636-1.
15. Dufresne, J., J. Quaas, O. Boucher, S. Denvil, and L. Fairhead (2005): Contrasts in the effects on climate of anthropogenic sulfate aerosols between the 20th and the 21st century. Geophys. Res. Lett., 32(21), L21703.
16. Eriksson, P., et al. (2008), Comparison between early Odin-SMR, Aura MLS and CloudSat retrievals of cloud ice mass in the upper tropical troposphere, Atmos. Chem. Phys., 8(7), 1937-1948, doi:10.5194/acp-8-1937-2008.
17. Gettelman, A., E. J. Fetzer, A. Eldering, and F. W. Irion (2006), The Global Distribution of Supersaturation in the Upper Troposphere from the Atmospheric Infrared Sounder. J. Clim., 19, 6089-6103.
18. Gettelman, A., X. Liu, S. J. Ghan, H. Morrison, S. Park, and A. J. Conley (2010), Global simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the Community Atmospheric Model. J. Geophys. Res., 115, D18216, doi:10.1029/2009JD013797.
19. GFDL-AMDT (Geophysical Fluid Dynamics Laboratory Global Atmosphere Model Development Team) (2004), The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 4641-4673.
20. Gregory, D., and P. R. Rowntree, (1990): A mass flux convection scheme with representation of cloud ensemble characteristics and stabilitydependent closure, Mon. Weather Rev., 118, 1483-1506.
21. Haynes, J. M., and G. L. Stephens (2007), Tropical oceanic cloudiness and the incidence of precipitation: Early results from CloudSat, Geophys. Res. Lett., 34, L09811, doi:10.1029/2007GL029335.
22. Heymsfield, A. J., et al. (2008), Testing IWC retrieval methods using radar and ancillary measurements with in situ data, J. Appl. Meteorol. Climatol., 47(1), 135-163, doi:10.1175/2007JAMC1606.1.
23. Hourdin, F., F. M-A Foujols, F. Codron, V. Guemas, J-L Dufresne, S. Bony, S. Denvil, L. Guez, F. Lott, J. Ghettos, P. Braconnot, O. Marti, Y. Meurdesoif, and L. Bopp, (2012), Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model, Climate Dyn., doi: 10.1007/s00382-012-1411-3.
24. Huang, X. L., V. Ramaswamy, and M. Daniel Schwarzkopf (2006), Quantification of the source of errors in AM2 simulated tropical clear-sky outgoing longwave radiation, J. Geophys. Res., 111, D14107, doi:10.1029/ 2005JD006576.
25. Iversen, T., M. Bentsen, I. Bethke, J. B. Debernard, A. Kirkevag, Ø. Seland, H. Drange, J. E. Kristjansson, I. Medhaug, M. Sand, and I. A. Seierstad (2012), The Norwegian Earth System Model, NorESM1-M - Part 2: Climate response and scenario projections, Geosci. Model Dev. Discuss., 5, 2933-2998, doi:10.5194/gmdd-5-2933-2012.
26. Jiang, J. H., H. Su, C. Zhai, and V. Perun, et al. (2012). Evaluation of Cloud and Water Vapor Simulations in CMIP5 Climate Models Using NASA "A-Train" Satellite Observations, J. Geophys. Res., 117, D14105, doi:10.1029/2011JD017237.
27. Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schubert (1999), Trimodal characteristics of tropical convection, J. Climate, 12, 2397-2418.
28. Jones, C. D. et al. (2011), The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543-570, doi:10.1029/ 2011JD017237.
29. Kim, D., A. H. Sobel, A. D. Del Genio, Y. Chen, S. Camargo, M.-S. Yao, M. Kelley, and L. Nazarenko (2012), The tropical subseasonal variability simulated in the NASA GISS general circulation model. J. Climate, 25, 4641-4659, doi:10.1175/JCLI-D-11-00447.1.
30. Kirkevag, A., T. Iversen, Ø. Seland, C. Hoose, J. E. Kristjansson, H. Struthers, A. M. L. Ekman, S. Ghan, J. Griesfeller, E. D. Nilsson, and M. Schulz (2012), Aerosol-climate interactions in the Norwegian Earth System Model - NorESM, Geosci. Model Dev. Discuss., 5, 2599-2685, doi:10.5194/gmdd-5-2599- 2012.
31. Klein, S. A., and D. L. Hartmann (1993), The seasonal cycle of low stratiform clouds, J. Climate, 6, 1587-1606.
32. Klein, S. A., Y. Zhang, M. D. Zelinka, R. Pincus, J. Boyle, and P. J. Gleckler (2013), Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator, J. Geophys. Res., in press, doi:10.1002/jgrd.50141.
33. Lin, J.-L. (2007), The Double-ITCZ Problem in IPCC AR4 Coupled GCMs: Ocean-Atmosphere Feedback Analysis. J. Climate, 20, 4497-4525.
34. Martin, G. M., et al. (2011). The HadGEM2 family of Met Office Unified Model climate configurations. Geosci. Model Dev., 4(723-757), 2011.
35. Mace, G. G., Q. Zhang, M. Vaughan, R. Marchand, G. Stephens, C. Trepte, and D. Winker (2009), A description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data, J. Geophys. Res., 114, D00A26, doi:10.1029/2007JD009755.
36. Randall, D. A., et al. (2007), Climate models and their evaluations, in Climate Change 2007: The Physical Sciences Basis, Contribution of Working Group I to the Fouth Assessment Report of the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., chapter 8, 589-662, Cambridge Univ. Press, U.K.
37. Raval, A., and V. Ramanathan (1989), Observational determination of the greenhouse effect, Nature, 342, 758-762.
38. Rotstayn L. D., Collier MA, Dix MR, Feng Y, Gordon HB, O'Farrell SP, Smith IN, Syktus J. (2010), Improved simulation of Australian climate and ENSO-related climate variability in a GCM with an interactive aerosol treatment. International J. Clim., 30, 1067-1088, doi:10.1002/joc.1952.
39. Rotstayn, L. D., S. J. Jeffrey, M. A. Collier, S. M. Dravitzki, A. C. Hirst, J. I. Syktus, and K. K. Wong (2012), Aerosol-induced changes in summer rainfall and circulation in the Australasian region: a study using single-forcing climate simulations, Atmos. Chem. Phys. Discuss., 12, 5107-5188, doi:10.5194/acpd-12-5107-2012.
40. Sakamato, T. T., et al. (2012) MIROC4h - a new high resolution atmosphereocean coupled general circulation model. J. Meteor. Soc. Japan, Vol. 90, No. 3, 325-359, doi:10.2151/jmsj.2012-301.
41. Su, H., J. H. Jiang, D.G. Vane, and G.L. Stephens (2008), Observed Vertical Structure of Tropical Oceanic Clouds Sorted in Large-scale Regimes, Geophys. Res. Lett., 35, doi:10.1029/2008GL035888.
42. Su, H., J. H. Jiang, J. Teixeira, A. Gettelman, X. Huang, G. Stephens, D. Vane, and V.S. Perun, Comparison of Regime-Sorted Tropical Cloud Profiles Observed by CloudSat with GEOS5 Analyses and Two General Circulation Model Simulations (2011), J. Geophys. Res. 116, D0910, doi:10.1029/2010JD014971.
43. Su, H., and J. H. Jiang (2013), Tropical Clouds and Circulation Changes During the 2006-07 and 2009-10 El Niños, J. Climate, 26, 399-413, doi:http://dx.doi.org/10.1175/JCLI-D-12-00152.1.
44. Taylor, K. E., R. J. Stouffer, and G. A. Meehl (2012), An Overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, doi:10.1175/BAMS-D-11-00094.1.
45. Voldoire, A., et al. (2011), The CNRM-CM5.1 global climate model: Description and basic evaluation, CNRM-CM technical doc, available at http://www.cnrm.meteo.fr/CMIP5/.
46. Volodin, E. M., N. A. Diansky, and A. V. Gusev (2010), Simulating presentday climate with the INMCM4 coupled model of atmospheric and oceanic general circulations, Izv. Atmos. Ocean. Phys., 46, 448-466.
47. von Salzen, K., J. F. Scinocca, N. A. McFarlane, J. Li, J. N. S. Cole, D. Plummer, M. C. Reader, X. Ma, M. Lazare, and L. Solheim (2013), The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Physical processes. Atmosphere-Ocean, doi:10.1080/07055900.2012.755610.
48. Waliser, D. E., et al. (2009), Cloud ice: A climate model challenge with signs and expectations of progress, J. Geophys. Res. 114, D00A21, doi:10.1029/2008JD010015.
49. Watanabe,M., et al. (2010), Improved climate simulation byMIROC5: Mean states, variability, and climate sensitivity, J. Clim., 23, 6312-6335, doi:10.1175/2010JCLI3679.1.
50. Williams K. D., M. A. Ringer, and C. A. Senior (2003), Evaluating the cloud response to climate change and current climate variability. Clim. Dyn., 20, 705-721.
51. Wu, D. L., et al. (2009), Comparisons of global cloud ice from MLS, Cloud-Sat, and correlative data sets, J. Geophys. Res., 113, D00A24, doi:10.1029/2008JD009946.
52. Wu, T., R. Yu, F. Zhang, Z. Wang, M. Dong, L. Wang, X. Jin, D. Chen, L. Li (2010), The Beijing Climate Center for Atmospheric General Circulation Model (BCC-AGCM2.0.1): Description and its performance for the present-day climate, Clim. Dyn., 34, 123-147.
53. Wyant, M. C., C. S. Bretherton, J. T. Bacmeister, J. T. Kiehl, I. M. Held, M. Zhao, S. A. Klein, and B. A. Soden (2006), A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity. Clim. Dyn., 27, 261-279.
54. Yukimoto, S., et al. (2011), Meteorological Research Institute Earth System Model Version 1 (MRI-ESM1) - Model description -. Technical Report of the Meteorological Research Institute, 64, 83pp (available from http://www.mri-jma.go.jp/Publish/Technical/index-en.html).
55. Yukimoto, S., et al. (2012), A new global climate model of the Meteorological Research Institute: MRI-CGCM3 -Model description and basic performance, J. Meteor. Soc. Jpn, 90a, 23-64.
56. Zhang, Y., et al. (2007), Cluster analysis of tropical clouds using CloudSat data, Geophys. Res. Lett., 34, L12813, doi:10.1029/2007GL029336.