Employing Cluster Analysis to Detect Significant Cloud 3D RT Effect Indicators

Michael J. Foster Space Science and Engineering Center, Department of Atmospheric and Oceanic Sciences, University of Wisconsin—Madison, Madison, Wisconsin

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Dana E. Veron College of Marine and Earth Studies, University of Delaware, Newark, Delaware

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Abstract

Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate models do not currently incorporate methods of identifying situations where this contribution is substantial. This work represents an effort to identify atmospheric conditions conducive to the formation of cloud field configurations that significantly affect shortwave radiative fluxes. Once identified, these characteristics may form the basis of a parameterization that accounts for radiative impact of complex cloud fields. A k-means clustering algorithm is applied to observed cloud properties taken from the Atmospheric Radiation Measurement Program tropical western Pacific sites to identify specific cloud regimes. Results from a stand-alone stochastic model, which statistically represents shortwave radiative transfer through broken cloud fields, are compared with those of a plane-parallel model. The aggregate scenes in each regime are examined to measure the bias in shortwave flux calculations due to neglected cloud field morphology. The results from the model comparison and cluster analysis suggest that cloud fraction, vertical wind shear, and spacing between cloudy layers are all important indicators of complex cloud field geometry and that these criteria are most often met in cloud regimes characterized by moderate to strong convection. The cluster criteria are applied to output from the Community Climate System Model (version 3.0) and it is found that the presence of persistent high cirrus cloud in model simulations inhibits identification of specific cloud regimes.

Corresponding author address: Michael J. Foster, 1225 West Dayton Street, Madison, WI 53706. Email: mfoster@aos.wisc.edu

Abstract

Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate models do not currently incorporate methods of identifying situations where this contribution is substantial. This work represents an effort to identify atmospheric conditions conducive to the formation of cloud field configurations that significantly affect shortwave radiative fluxes. Once identified, these characteristics may form the basis of a parameterization that accounts for radiative impact of complex cloud fields. A k-means clustering algorithm is applied to observed cloud properties taken from the Atmospheric Radiation Measurement Program tropical western Pacific sites to identify specific cloud regimes. Results from a stand-alone stochastic model, which statistically represents shortwave radiative transfer through broken cloud fields, are compared with those of a plane-parallel model. The aggregate scenes in each regime are examined to measure the bias in shortwave flux calculations due to neglected cloud field morphology. The results from the model comparison and cluster analysis suggest that cloud fraction, vertical wind shear, and spacing between cloudy layers are all important indicators of complex cloud field geometry and that these criteria are most often met in cloud regimes characterized by moderate to strong convection. The cluster criteria are applied to output from the Community Climate System Model (version 3.0) and it is found that the presence of persistent high cirrus cloud in model simulations inhibits identification of specific cloud regimes.

Corresponding author address: Michael J. Foster, 1225 West Dayton Street, Madison, WI 53706. Email: mfoster@aos.wisc.edu

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  • Anderberg, M. R., 1973: Cluster Analysis for Applications. Academic Press, 359 pp.

  • Boville, B. A., P. J. Rasch, J. J. Hack, and J. R. McCaa, 2006: Representation of clouds and precipitation processes in the Community Atmosphere Model version 3 (CAM3). J. Climate, 19 , 21842198.

    • Search Google Scholar
    • Export Citation
  • Briegleb, B. P., 1992: Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model. J. Geophys. Res., 97 , 76037612.

    • Search Google Scholar
    • Export Citation
  • Byrne, R. N., R. C. J. Somerville, and B. Subasilar, 1996: Broken-cloud enhancement of solar radiation absorption. J. Atmos. Sci., 53 , 878886.

    • Search Google Scholar
    • Export Citation
  • Cahalan, R. F., 1994: Bounded cascade clouds albedo and effective thickness. Nonlinear Processes Geophys., 1 , 156167.

  • Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000: Objective determination of cloud heights and radar reflectivities using a combination of active remote sensors at the ARM CART sites. J. Appl. Meteor., 39 , 645665.

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2006: The formulation and atmospheric simulation of the Community Atmospheric Model Version 3 (CAM3). J. Climate, 19 , 21442161.

    • Search Google Scholar
    • Export Citation
  • Foster, M. J., and D. E. Veron, 2008: Evaluating the stochastic approach to shortwave radiative transfer in the tropical western Pacific. J. Geophys. Res., 113 , D22205. doi:10.1029/2007JD009581.

    • Search Google Scholar
    • Export Citation
  • Gordon, N. D., J. R. Norris, C. P. Weaver, and S. A. Klein, 2005: Cluster analysis of cloud regimes and characteristic dynamics of midlatitude synoptic systems in observations and a model. J. Geophys. Res., 110 , D15S17. doi:10.1029/2004JD005027.

    • Search Google Scholar
    • Export Citation
  • Jakob, C., and G. Tselioudis, 2003: Objective identification of cloud regimes in the tropical western Pacific. Geophys. Res. Lett., 30 , 2082. doi:10.1029/2003GL018367.

    • Search Google Scholar
    • Export Citation
  • Jakob, C., G. Tselioudis, and T. Hume, 2005: The radiative, cloud, and thermodynamic properties of the major tropical western Pacific cloud regimes. J. Climate, 18 , 12031215.

    • Search Google Scholar
    • Export Citation
  • Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11 , 11311149.

    • Search Google Scholar
    • Export Citation
  • Kollias, P., E. E. Clothiaux, B. A. Albrecht, M. A. Miller, K. P. Moran, and K. L. Johnson, 2005: The Atmospheric Radiation Measurement program cloud profiling radars: An evaluation of signal processing and sampling strategies. J. Atmos. Oceanic Technol., 22 , 930948.

    • Search Google Scholar
    • Export Citation
  • Lane, D. E., K. Goris, and R. C. J. Somerville, 2002: Radiative transfer through broken cloud fields: Observations and model validation. J. Climate, 15 , 29212933.

    • Search Google Scholar
    • Export Citation
  • Lane-Veron, D. E., and R. C. J. Somerville, 2004: Stochastic theory of radiative transfer through generalized cloud fields. J. Geophys. Res., 109 , D18113. doi:10.1029/2004JD004524.

    • Search Google Scholar
    • Export Citation
  • Long, C. N., T. P. Ackerman, K. L. Gaustad, and J. N. S. Cole, 2006: Estimation of fractional sky cover from broadband shortwave radiometer measurements. J. Geophys. Res., 111 , D11204. doi:10.1029/2005JD006475.

    • Search Google Scholar
    • Export Citation
  • Malvagi, F., R. N. Byrne, G. C. Pomraning, and R. C. J. Somerville, 1993: Stochastic radiative transfer in a partially cloudy atmosphere. J. Atmos. Sci., 50 , 21462158.

    • Search Google Scholar
    • Export Citation
  • McClatchey, R. A., R. W. Fenn, J. E. A. Selby, F. E. Volz, and J. S. Garing, 1972: Optical properties of the atmosphere. 3rd ed. Environmental Research Paper 411, Air Force Cambridge Research Laboratories, 113 pp.

    • Search Google Scholar
    • Export Citation
  • Naud, C. M., A. Del Genio, G. G. Mace, S. Benson, E. E. Clothiaux, and P. Kollias, 2008: Impact of dynamics and atmospheric state on cloud vertical overlap. J. Climate, 21 , 17581770. doi:10.1175/2007JCLI1828.1.

    • Search Google Scholar
    • Export Citation
  • Pincus, R., and S. A. Klein, 2000: Unresolved spatial variability and microphysical process rates in large-scale models. J. Geophys. Res., 105 , 2705927065.

    • Search Google Scholar
    • Export Citation
  • Potter, P. L., and R. D. Cess, 2004: Testing the impact of clouds on the radiation budgets of 19 atmospheric general circulation models. J. Geophys. Res., 109 , D02106. doi:10.1029/2003JD004018.

    • Search Google Scholar
    • Export Citation
  • Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 589–662.

    • Search Google Scholar
    • Export Citation
  • Redelsperger, J. L., D. B. Parsons, and F. Guichard, 2002: Recovery processes and factors limiting cloud-top height following the arrival of a dry intrusion observed during TOGA COARE. J. Atmos. Sci., 59 , 24382457.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., and R. A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80 , 22612287.

  • Rossow, W. B., G. Tselioudis, A. Polak, and C. Jakob, 2005: Tropical climate described as a distribution of weather states indicated by distinct mesoscale cloud property mixtures. Geophys. Res. Lett., 32 , L21812. doi:10.1029/2005GL024584.

    • Search Google Scholar
    • Export Citation
  • Stokes, G. M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) Program: Programmatic background and design of the Cloud and Radiation Test Bed. Bull. Amer. Meteor. Soc., 75 , 12011221.

    • Search Google Scholar
    • Export Citation
  • Williams, K. D., C. A. Senior, A. Slingo, and J. F. B. Mitchell, 2005: Towards evaluating cloud response to climate change using clustering technique identification of cloud regimes. Climate Dyn., 24 , 701719.

    • Search Google Scholar
    • Export Citation
  • Wiscombe, W. J., and J. W. Evans, 1977: Exponential-sum fitting of radiative transmission functions. J. Comput. Phys., 24 , 416444.

  • Zhang, G. J., 2009: Effects of entrainment on convective available potential energy and closure assumptions in convection parameterization. J. Geophys. Res., 114 , D07109. doi:10.1029/2008JD010976.

    • Search Google Scholar
    • Export Citation
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