Humidity variability revealed by a sounding array and its implications for cloud representation in GCMs

Journal of Geophysical Research

Volumn 119, Issue 17, 2014, Pages 10499-10514

  Lin, Yanluan ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85018214651     PISSN: 01480227     EISSN: 21562202     Source Type: Journal    
DOI: 10.1002/2014JD021837     Document Type: Article

References (41)

1. Ackerman, T. P., and G. Stokes (2003), The atmospheric radiation measurement program, Phys. Today, 56, 38–45, doi:10.1063/1.1554135.
2. Bechtold, P., C. Fravalo, and J. P. Pinty (1992), A model of marine boundary-layer cloudiness for mesoscale applications, J. Atmos. Sci., 49, 1723–1744.
3. Bony, S., and K. A. Emanuel (2001), A parameterization of the cloudiness associated with cumulus convection: Evaluation using TOGA COARE data, J. Atmos. Sci., 58, 3158–3183.
4. Chaboureau, J. P., and P. Bechtold (2002), A simple cloud parameterization derived from cloud resolving model data: Diagnostic and prognostic applications, J. Atmos. Sci., 59, 2362–2372.
5. Couvreux, F., F. Guichard, V. Masson, and J.-L. Redelsperge (2007), Negative water vapour skewness and dry tongues in the convective boundary layer: Observations and large-eddy simulation budget analysis, Boundary Layer Meteorol., 123, 269–294.
6. 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.
7. Fridlind, A. M., et al. (2012), A comparison of TWP-ICE observational data with cloud-resolving model results, J. Geophys. Res., 117, D05204, doi:10.1029/2011JD016595.
8. Golaz, J.-C., V. E. Larson, and W. R. Cotton (2002), A PDF-based model for boundary layer clouds. Part I: Method and model description, J. Atmos. Sci., 59, 3540–3551.
9. Grützun, V., J. Quaas, C. J. Morcrette, and F. Ament (2013), Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?, J. Geophys. Res Atmos., 118, 10,507–10,517, doi:10.1002/jgrd.50813.
10. Heymsfield, A. J., L. M. Miloshevich, C. Twohy, G. Sachse, and S. Oltmans (1998), Upper-tropospheric relative humidity observations and implications for cirrus ice nucleation, Geophys. Res. Lett., 25, 1343–1346, doi:10.1029/98GL01089.
11. Kahn, B. H., and J. Teixeira (2009), A global climatology of temperature and water vapor variance scaling from the atmospheric infrared sounder, J. Clim., 20, 5558–5576, doi:10.1175/2009JCLI2934.1.
12. Klein, S. A., R. Pincus, C. Hannay, and K.-M. Xu (2005), How might a statistical cloud scheme be coupled to a mass-flux convection scheme?, J. Geophys. Res., 110, D15S06, doi:10.1029/2004JD005017.
13. 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. Atmos., 118, 1329–1342, doi:10.1002/jgrd.50141.
14. Le Treut, H., and Z.-X. Li (1991), Sensitivity of an atmospheric general circulation model to prescribed SST changes: Feedback effects associated with the simulation of cloud optical properties, Clim. Dyn., 5, 175–187.
15. Lenderink, G., and A. P. Siebesma (2000), Combining the mass flux approach with a statistical cloud scheme, in Proceedings of the 14th Symposium on Boundary Layers and Turbulence, Aspen, CO, pp. 66–69, Am. Meteorol. Soc., Boston, Mass.
16. Lin, Y., et al. (2012), TWP-ICE global atmospheric model intercomparison: Convection responsiveness and resolution impact, J. Geophys. Res., 117, D09111, doi:10.1029/2011JD017018.
17. Lohmann, U., N. McFarlane, L. Levkov, K. Abdella, and F. Albers (1999), Comparing different cloud schemes of a single column model by using mesoscale forcing and nudging technique, J. Clim., 12, 438–461.
18. May, P. T., J. H. Mather, G. Vaughan, C. Jakob, G. M. McFarquhar, K. N. Bower, and G. G. Mace (2008), The tropical warm pool international cloud experiment, Bull. Am. Meteorol. Soc., 89(5), 629–645.
19. Mellor, G. L. (1977), The Gaussian cloud model relations, J. Atmos. Sci., 34, 356–358.
20. Molod, A. (2012), Constraints on the profiles of total water PDF in AGCMs from AIRS and a high-resolution model, J. Clim., 25, 8341–8352.
21. Naumann, A. K., A. Seifert, and J. P. Mellado (2013), A refined statistical cloud closure using double-Gaussian probability density functions, Geosci. Model Dev. Discuss., 6, 1085–1125.
22. Perraud, E., F. Couvreux, S. Malardel, C. Lac, V. Masson, and O. Thouron (2011), Evaluation of statistical distributions for the parameterization of subgrid boundary-layer clouds, Boundary Layer Meteorol., 140, 263–294.
23. Petch, J. C., and M. E. B. Gray (2001), Sensitivity studies using a cloud resolving model simulation of the tropical west Pacific, Q. J. R. Meteorol. Soc., 127(577), 2287–2306.
24. Peters, M. E., and C. S. Bretherton (2006), Structure of tropical variability from a vertical mode perspective, Theor. Comput. Fluid. Dyn., 20, 501–524.
25. Price, J. D. (2001), A study on boundary layer humidity distributions and errors in parameterised cloud fraction, Q. J. R. Meteorol. Soc., 127, 739–759.
26. Price, J. D., and R. Wood (2002), Comparison of probability density functions for total specific humidity and saturation deficit humidity, and consequences for cloud parameterization, Q. J. R. Meteorol. Soc., 128, 2059–2072.
27. Quaas, J. (2012), Evaluating the critical relative humidity as a measure of subgrid-scale variability of humidity in general circulation model cloud cover parameterizations using satellite data, J. Geophys. Res., 117, D09208, doi:10.1029/2012JD017495.
28. Sherwood, S. C., R. Roca, T. M. Weckwerth, and N. G. Andronova (2010), Tropospheric water vapor, convection and climate, Rev. Geophys., 48, RG2001, doi:10.1029/2009RG00030.
29. Smith, R. N. (1990), A scheme for predicting layer clouds and their water content in a general circulation model, Q. J. R. Meteorol. Soc., 116, 435–460, doi:10.1002/qj.49711649210.
30. Sommeria, G., and J. W. Deardorff (1997), Subgrid-scale condensation in models of nonprecipitating clouds, J. Atmos. Sci., 34, 344–355.
31. Sundqvist, H. (1978), A parameterization scheme for non-convective condensation including prediction of cloud water content, Q. J. R. Meteorol. Soc., 104, 677–690.
32. Sundqvist, H., E. Berge, and J. E. Kristjánsson (1989), Condensation and cloud parameterization studies with a mesoscale numerical weather prediction model, Mon. Weather Rev., 117, 1641–1657.
33. Tompkins, A. (2002), A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in large-scale model and its use to diagnose cloud cover, J. Atmos. Sci., 59, 1917–1942.
34. Tompkins, A. M. (2003), Impact of temperature and humidity variability on cloud cover assessed using aircraft data, Q. J. R. Meteorol. Soc., 129, 2151–2170.
35. Tompkins, A. M., K. Gierens, and G. Radel (2007), Ice supersaturation in the ECMWF integrated forecast system, Q. J. R. Meteorol. Soc., 133, 53–63, doi:10.1002/qj.14.
36. Watanabe, M., S. Emori, M. Satoh, and H. Miura (2009), A PDF based hybrid prognostic cloud scheme for general circulation models, Clim. Dyn., 33, 795–816.
37. Weber, T., J. Quaas, and P. Räisänen (2011), Evaluation of the subgrid scale variability scheme for water vapor and cloud condensate in the ECHAM5 model using satellite data, Q. J. R. Meteorol. Soc., 137, 2079–2091, doi:10.1002/qj.887.
38. Wood, R., and P. R. Field (2000), Relationship between total water, condensed water, and cloud fraction in stratiform clouds examined using aircraft data, J. Atmos. Sci., 57, 1888–1905.
39. Xie, S., T. Hume, C. Jakob, S. A. Klein, R. B. McCoy, and M. Zhang (2010), Observed large-scale structures and diabatic heating and drying profiles during TWP-ICE, J. Clim., 23(1), 57–79, doi:10.1175/2009JCLI3071.1.
40. Xu, K.-M., and S. K. Krueger (1991), Evaluation of cloudiness parameterizations using a cumulus ensemble model, Mon. Weather Rev., 119, 342–367.
41. Zhu, P., and P. Zuidema (2009), On the use of PDF schemes to parameterize sub-grid clouds, Geophys. Res. Lett., 36, L05807, doi:10.1029/2008GL036817.