Skip to main content
Log in

Observational diagnosis of cloud phase in the winter Antarctic atmosphere for parameterizations in climate models

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instruments for the period 2000–2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months (June, July, and August) reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0°C. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ∼20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs (≫ −40°C) for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ackerman, S. A., K. I. Strabala, W. P. Menzel, R. A. Frey, C. C. Moeller, and L. E. Gumley, 1998: Discriminating clear-sky from clouds with MODIS. J. Geophys. Res., 103(D24), 32141–32157.

    Article  Google Scholar 

  • Baum, B. A., P. F. Soulen, K. I. Strabala, M. D. King, S. A. Ackerman, W. P. Menzel, and P. Yang, 2000: Remote sensing of cloud properties using MODIS airborne simulator imagery during SUCCESS, 2, Cloud thermodynamic phase. J. Geophys. Res., 105, 11781–11792.

    Article  Google Scholar 

  • Baum, B. A., P. Yang, A. J. Heymsfield, S. Platnick, M. D. King, Y. X. Hu, and S. T. Bedka, 2005: Bulk scattering properties for the remote sensing of ice clouds. Part II: Narrowband models. J. Appl. Meteor., 44, 1896–1911.

    Article  Google Scholar 

  • Chiriaco, M., and Coauthors, 2007: Comparison of CALIPSO-like, LaRC, and MODIS retrievals of icecloud properties over SIRTA in France and Florida during CRYSTAL-FACE. J. Appl. Meteor. Climatol., 46, 249–272.

    Article  Google Scholar 

  • Choi, Y.-S., C.-H. Ho, M.-H. Ahn, and Y.-S. Kim, 2005: Enhancement of the consistency of MODIS thin cirrus with cloud phase by adding 1.6 µm reflectance. Int. J. Remote Sens., 26, 4669–4680.

    Article  Google Scholar 

  • Choi, Y.-S., C.-H. Ho, J. Kim, and R. S. Lindzen, 2010: Satellite retrievals of (quasi-) spherical particles at cold temperatures. Geophys. Res. Lett., 37, L05703.

    Article  Google Scholar 

  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). National Center for Atmospheric Research, Boulder, Colorado, 214pp.

    Google Scholar 

  • Curry, J. A., F. G. Meyer, L. F. Radke, C. A. Brock, and E. E. Ebert, 1990: Occurrence and characteristics of lower tropospheric ice crystal in the Arctic. Int. J. Climatol., 10, 749–764.

    Article  Google Scholar 

  • Curry, J. A., W. B. Rossow, D. Randall, and J. L. Schramm, 1996: Overview of Arctic cloud and radiation characteristics. J. Climate, 9, 1731–1764.

    Article  Google Scholar 

  • Del Genio, A. D., M.-S. Yao, W. Kovari, and K. K.-W. Lo, 1996: A prognostic cloud water parameterization for global climate models. J. Climate, 9, 270–304.

    Article  Google Scholar 

  • Doutriaux-Boucher, M., and J. Quaas, 2004: Evaluation of cloud thermodynamic phase parameterizations in the LMDZ GCM by using POLDER satellite data. Geophys. Res. Lett., 31, L06126, doi: 10.1029/2003GL019095.

    Article  Google Scholar 

  • Giraud, V., O. Thouron, J. Riedi, and P. Goloub, 2001: Analysis of direct comparison of cloud top temperature and infrared split window signature against independent retrievals of cloud thermodynamic phase. Geophys. Res. Lett., 28, 983–986.

    Article  Google Scholar 

  • Gultepe, I., and G. A. Isaac, 1997: Liquid water content and temperature relationship from aircraft observations and its applicability to GCMs. J. Climate, 10, 446–452.

    Article  Google Scholar 

  • Ho, C.-H., M.-D. Chou, M. Suarez, and K.-M. Lau, 1998: Effect of ice cloud on GCM climate simulations. Geophys. Res. Lett., 25, 71–74.

    Article  Google Scholar 

  • Holland, M. M., and C. M. Bitz, 2003: Polar amplification of climate change in coupled models. Climate Dyn., 21, 221–232.

    Article  Google Scholar 

  • Houze, R. A., 1993: Cloud Dynamics. Academic Press, San Diego, 573pp.

    Google Scholar 

  • Hu, Y.-X., D. Winker, P. Yang, B. Baum, L. Poole, and L. Vann, 2001: Identification of cloud phase from PICASSO-CENA lidar depolarization: A multiple scattering sensitivity study. Journal of Quantitative Spectroscopy and Radiative Transfer, 70, 569–579.

    Article  Google Scholar 

  • Hu, Y.-X., and Coauthors, 2009: CALIPSO/CALIOP cloud phase discrimination algorithm. J. Atmos. Oceanic Technol., 26, 2293–2309.

    Article  Google Scholar 

  • IPCC, 2007: Climate change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996pp.

    Google Scholar 

  • King, M. D., S. Platnick, P. A. Hubanks, G. T. Arnold, E. G. Moody, G. Wind, and B. Wind, 2006: Collection 005 change summary for the MODIS cloud optical property (06_OD) algorithm, 23pp. [Available online at http://modisatmos.gsfc.nasa.gov/C005_Changes/C005_CloudOpticalProperties_ver311.pdf.]

  • Lee, M.-I., I.-S. Kang, J.-K. Kim, and B. E. Mapes, 2001: Influence of cloud-radiation interaction on simulating tropical intraseasonal oscillation with an atmospheric general circulation model. J. Geophys. Res., 106, 14219–14233.

    Article  Google Scholar 

  • Li, J.-L., and Coauthors, 2005: Comparisons of EOS MLS cloud ice measurements with ECMWF analyses and GCM simulations: Initial results. Geophys. Res. Lett., 32, L18710, doi: 10.1029/2005GL023788.

    Article  Google Scholar 

  • Li, J.-L., J. H. Jiang, D. E. Waliser, and A. M. Tompkins, 2007: Assessing consistency between EOS MLS and ECMWF analyzed and forecast estimates of cloud ice. Geophys. Res. Lett., 34, L08701, doi: 10.1029/2006GL029022.

    Article  Google Scholar 

  • Liou, K. N., 2002: An Introduction to Atmospheric Radiation. 2nd ed., Elsevier, New York, 228–231.

    Google Scholar 

  • Liu, Z., M. A. Vaughan, D. M. Winker, C. A. Hostetler, L. R. Poole, D. Hlavka, W. Hart, and M. McGill, 2004: Use of probability distribution functions for discriminating between cloud and aerosol in lidar backscatter data. J. Geophys. Res., 109, D15202, doi: 10.1029/2004JD004732.

    Article  Google Scholar 

  • Liu, Z., A. H. Omar, Y. Hu, M. A. Vaughan, and D. M. Winker, 2005: CALIOP algorithm theoretical basis document—Part 3: Scene classification algorithms. Release 1.0, PC-SCI-202, NASA Langley Research Center, Hampton, VA, 56pp. [Available online at http://www-calipso.larc.nasa.gov/resources/pdfs/PC-SCI-202_Part3_v1.0.pdf.]

    Google Scholar 

  • Madonna, L. A., C. M. Sciulli, L. N. Canjar, and G. M. Pound, 1961: Low-temperature cloud-chamber studies on water vapour. Proc. Phys. Soc., 78, 1218–1222.

    Article  Google Scholar 

  • Mason, B. J., 1952: The spontaneous crystallization of supercooled water. Quart. J. Roy. Meteor. Soc., 78, 22–27.

    Article  Google Scholar 

  • Menzel, W. P., R. A. Frey, B. A. Baum, and H. Zhang, 2006: Cloud top properties and cloud phase algorithm theoretical basis document. MODIS Algorithm Theoretical Basis document (NASA), 56pp. [Available online at http://modisatmos.gsfc.nasa.gov/docs/MOD06CT:MYD06CTATBDC005.pdf.]

  • Nasiri, S. L., and B. H. Kahn, 2008: Limitations of bispectral infrared cloud phase determination and potential for improvement. J. Appl. Meteor. Climatol., 47, 2895–2910.

    Article  Google Scholar 

  • Noel, V., A. Hertzog, H. Chepfer, and D. M. Winker, 2008: Polar stratospheric clouds over Antarctica from the CALIPSO spaceborne lidar. J. Geophys. Res., 113, D02205.

    Article  Google Scholar 

  • Omar, A. H., and C. S. Gardner, 2001: Observations by the Lidar In-Space Technology Experiment (LITE) of high-altitude cirrus clouds over the equator in regions exhibiting extreme cold temperatures. J. Geophys. Res., 106, 1227–1236.

    Article  Google Scholar 

  • Platnick, S., M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum, J. C. Riedi, and R. A. Frey, 2003: The MODIS cloud products: Algorithms and examples from Terra. IEEE Trans. Geosci. Remote Sens., 41, 456–473.

    Google Scholar 

  • Pruppacher, H., 1995: A new look at homogeneous ice nucleation in supercooled water drops. J. Atmos. Sci., 52, 1924–1933.

    Article  Google Scholar 

  • Pruppacher, H., and J. Klett, 1997: Microphysics of Clouds and Precipitation. Kluwer Academic Publishers, Netherlands, 486pp.

    Google Scholar 

  • Rogers, R. R., and M. K. Yau, 1989: A Short Course in Cloud Physics. Pergamon Press Inc., Oxford, 293pp.

    Google Scholar 

  • Rossow, W. B., A. W. Walker, and L. C. Garder, 1993: Comparison of ISCCP and other cloud amounts. J. Climate, 6, 2394–2418.

    Article  Google Scholar 

  • 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, 697–711.

    Article  Google Scholar 

  • Smith, R. N., 1990: A scheme for predicting layer clouds and their water content in a general circulation model. Quart. J. Roy. Meteorol. Soc., 116, 435–460.

    Article  Google Scholar 

  • Strabala, K. I., S. A. Ackerman, and W. P. Menzel, 1994: Cloud properties inferred from 8–12-µm data. J. Appl. Meteor., 33, 212–229.

    Article  Google Scholar 

  • Tsushima, Y., and Coauthors, 2006: Importance of the mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study. Climate Dyn., 27, 113–126.

    Article  Google Scholar 

  • Uttal, T., and Coauthors, 2002: Surface heat budget of the Arctic Ocean. Bull. Amer. Meteor. Soc., 83, 255–275.

    Article  Google Scholar 

  • Vavrus, S., 2004: The impact of cloud feedbacks on Arctic climate under greenhouse forcing. J. Climate, 17, 603–615.

    Article  Google Scholar 

  • Verlinde, J., and Coauthors, 2007: The mixed-phase arctic cloud experiment. Bull. Amer. Meteor. Soc., 88, 205–221.

    Article  Google Scholar 

  • Weidle, F., and H. Wernli, 2008: Comparison of ERA40 cloud top phase with POLDER-1 observations. J. Geophys. Res., 113, D05209, doi: 10.1029/2007JD009234.

    Article  Google Scholar 

  • Winker, D. M., W. H. Hunt, and M. J. McGill, 2007: Initial performance assessment of CALIOP. Geophys. Res. Lett., 34, L19803, doi: 10.1029/2007GL030135.

    Article  Google Scholar 

  • Yang, P., L. Zhang, G. Hong, S. L. Nasiri, B. A. Baum, H. L. Huang, M. D. King, and S. Platnick, 2007: Differences between collection 4 and 5 MODIS ice cloud optical/microphysical products and their impact on radiative forcing simulations. IEEE Trans. Geosci. Remote Sens., 45, 2886–2899.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yong-Sang Choi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Choi, YS., Ho, CH., Kim, SW. et al. Observational diagnosis of cloud phase in the winter Antarctic atmosphere for parameterizations in climate models. Adv. Atmos. Sci. 27, 1233–1245 (2010). https://doi.org/10.1007/s00376-010-9175-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-010-9175-3

Key words

Navigation