Observed Self-Similarity of Precipitation Regimes over the Tropical Oceans

Gregory S. Elsaesser Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Christian D. Kummerow Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Tristan S. L’Ecuyer Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Yukari N. Takayabu Center for Climate System Research, University of Tokyo, Kashiwa, Chiba, and Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Kanagawa, Japan

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Shoichi Shige Department of Aerospace Engineering, Osaka Prefecture University, Osaka, Japan

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Abstract

A K-means clustering algorithm was used to classify Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) scenes within 1° square patches over the tropical (15°S–15°N) oceans. Three cluster centroids or “regimes” that minimize the Euclidean distance metric in a five-dimensional space of standardized variables were sought [convective surface rainfall rate; ratio of convective rain to total rain; and fractions of convective echo profiles with tops in three fixed height ranges (<5, 5–9, and >9 km)]. Independent cluster computations in adjacent ocean basins return very similar clusters in terms of PR echo-top distributions, rainfall, and diabatic heating profiles. The clusters consist of shallow convection (SHAL cluster), with a unimodal distribution of PR echo tops and composite diabatic heating rates of ∼2 K day−1 below 3 km; midlevel convection (MID-LEV cluster), with a bimodal distribution of PR echo tops and ∼5 K day−1 heating up to about 7 km; and deeper convection (DEEP cluster), with a multimodal distribution of PR echo tops and >20 K day−1 heating from 5 to 10 km. Each contributes roughly 20%–40% in terms of total tropical rainfall, but with MID-LEV clusters especially enhanced in the Indian and Atlantic sectors, SHAL relatively enhanced in the central and east Pacific, and DEEP most prominent in the western Pacific. While the clusters themselves are quite similar in rainfall and heating, specific cloud types defined according to the PR echo top and surface rainfall rate are less similar and exhibit systematic differences from one cluster to another, implying that the degree to which precipitation structures are similar decreases when one considers individual precipitating clouds as repeating tropical structures instead of larger-scale cluster ensembles themselves.

* Current affiliation: Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, Kitashirakawa-Oiwake-cho, Sakyo-ku, Kyoto, Japan

Corresponding author address: Gregory Elsaesser, Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523-1371. Email: elsaesser@atmos.colostate.edu

Abstract

A K-means clustering algorithm was used to classify Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) scenes within 1° square patches over the tropical (15°S–15°N) oceans. Three cluster centroids or “regimes” that minimize the Euclidean distance metric in a five-dimensional space of standardized variables were sought [convective surface rainfall rate; ratio of convective rain to total rain; and fractions of convective echo profiles with tops in three fixed height ranges (<5, 5–9, and >9 km)]. Independent cluster computations in adjacent ocean basins return very similar clusters in terms of PR echo-top distributions, rainfall, and diabatic heating profiles. The clusters consist of shallow convection (SHAL cluster), with a unimodal distribution of PR echo tops and composite diabatic heating rates of ∼2 K day−1 below 3 km; midlevel convection (MID-LEV cluster), with a bimodal distribution of PR echo tops and ∼5 K day−1 heating up to about 7 km; and deeper convection (DEEP cluster), with a multimodal distribution of PR echo tops and >20 K day−1 heating from 5 to 10 km. Each contributes roughly 20%–40% in terms of total tropical rainfall, but with MID-LEV clusters especially enhanced in the Indian and Atlantic sectors, SHAL relatively enhanced in the central and east Pacific, and DEEP most prominent in the western Pacific. While the clusters themselves are quite similar in rainfall and heating, specific cloud types defined according to the PR echo top and surface rainfall rate are less similar and exhibit systematic differences from one cluster to another, implying that the degree to which precipitation structures are similar decreases when one considers individual precipitating clouds as repeating tropical structures instead of larger-scale cluster ensembles themselves.

* Current affiliation: Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, Kitashirakawa-Oiwake-cho, Sakyo-ku, Kyoto, Japan

Corresponding author address: Gregory Elsaesser, Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523-1371. Email: elsaesser@atmos.colostate.edu

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

  • Berg, W., C. D. Kummerow, and C. Morales, 2002: Differences between east and west Pacific rainfall systems. J. Climate, 15 , 36593672.

    • Search Google Scholar
    • Export Citation
  • Boccippio, D. J., W. A. Petersen, and D. J. Cecil, 2004: The tropical convective spectrum. Part I: Archetypal vertical structures. J. Climate, 18 , 27442769.

    • Search Google Scholar
    • Export Citation
  • Caine, S., C. Jakob, S. Siems, and P. May, 2009: Objective classification of precipitating convective regimes using a weather radar in Darwin, Australia. Mon. Wea. Rev., 137 , 15851600.

    • Search Google Scholar
    • Export Citation
  • Houze Jr., R. A., 1997: Stratiform precipitation in regions of convection: A meteorological paradox? Bull. Amer. Meteor. Soc., 78 , 21792196.

    • Search Google Scholar
    • Export Citation
  • Houze Jr., R. A., and A. K. Betts, 1981: Convection in GATE. Rev. Geophys. Space Phys., 19 , 541576.

  • Iguchi, T., T. Kozu, R. Meneghini, J. Awaka, and K. Okamoto, 2000: Rain-profiling algorithm for the TRMM precipitation radar. J. Appl. Meteor., 39 , 20382052.

    • 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
  • 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 , 23972418.

    • Search Google Scholar
    • Export Citation
  • L’Ecuyer, T. S., and G. L. Stephens, 2003: The tropical oceanic energy budget from the TRMM perspective. Part I: Algorithm and uncertainties. J. Climate, 16 , 19671985.

    • Search Google Scholar
    • Export Citation
  • L’Ecuyer, T. S., and G. L. Stephens, 2007: The tropical oceanic energy budget from the TRMM perspective. Part II: Evaluating GCM representations of the sensitivity of regional energy and water cycles to the 1998–99 ENSO cycle. J. Climate, 20 , 45484571.

    • Search Google Scholar
    • Export Citation
  • L’Ecuyer, T. S., and G. McGarragh, 2010: A 10-yr climatology of tropical radiative heating and its vertical structure from TRMM observations. J. Climate, 23 , 519541.

    • Search Google Scholar
    • Export Citation
  • Luo, Z., G. Y. Liu, G. L. Stephens, and R. H. Johnson, 2009: Terminal versus transient cumulus congestus: A CloudSat perspective. Geophys. Res. Lett., 36 , L05808. doi:10.1029/2008GL036927.

    • Search Google Scholar
    • Export Citation
  • Mapes, B., S. Tulich, J. Lin, and P. Zuidema, 2006: The mesoscale convection life-cycle: Building block or prototype for large-scale tropical waves? Dyn. Atmos. Oceans, 42 , 329.

    • Search Google Scholar
    • Export Citation
  • Masunaga, H., and C. D. Kummerow, 2006: Observations of tropical precipitating clouds ranging from shallow to deep convective systems. Geophys. Res. Lett., 33 , L16805. doi:10.1029/2006GL026547.

    • Search Google Scholar
    • Export Citation
  • 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
  • Shige, S., Y. N. Takayabu, W-K. Tao, and D. E. Johnson, 2004: Spectral retrieval of latent heating profiles from TRMM PR data. Part I: Development of a model-based algorithm. J. Appl. Meteor., 43 , 10951113.

    • Search Google Scholar
    • Export Citation
  • Shige, S., Y. N. Takayabu, W-K. Tao, and C-L. Shie, 2007: Spectral retrieval of latent heating profiles from TRMM PR data. Part II: Algorithm improvement and heating estimates over tropical ocean regions. J. Appl. Meteor. Climatol., 46 , 10981124.

    • Search Google Scholar
    • Export Citation
  • Short, D. A., and K. Nakamura, 2000: TRMM radar observations of shallow precipitation over the tropical oceans. J. Climate, 13 , 41074124.

    • Search Google Scholar
    • Export Citation
  • Warren, S. G., C. J. Hahn, and J. London, 1985: Simultaneous occurrence of different cloud types. J. Climate Appl. Meteor., 24 , 658667.

    • Search Google Scholar
    • Export Citation
  • Yanai, M., S. Esbensen, and J-H. Chu, 1973: Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets. J. Atmos. Sci., 30 , 611627.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., S. Klein, G. G. Mace, and J. Boyle, 2007: Cluster analysis of tropical clouds using CloudSat data. Geophys. Res. Lett., 34 , L12813. doi:10.1029/2007GL029336.

    • Search Google Scholar
    • Export Citation
  • Zuidema, P., and B. Mapes, 2008: Cloud vertical structure observed from space and ship over the Bay of Bengal and the eastern tropical Pacific. J. Meteor. Soc. Japan, 86A , 205218.

    • Search Google Scholar
    • Export Citation
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