Editorial Type:
Article
Article Type:
Research Article

Critical Assessment of Microphysical Assumptions within TRMM Radiometer Rain Profile Algorithm Using Satellite, Aircraft, and Surface Datasets from KWAJEX

Steven T. Fiorino Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio

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Eric A. Smith NASA Goddard Space Flight Center, Greenbelt, Maryland

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Print Publication:
01 May 2006
DOI:
https://doi.org/10.1175/JAM2336.1
Page(s):
754–786
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Abstract

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager precipitation profile retrieval algorithm (2a12) assumes cloud model–derived vertically distributed microphysics as part of the radiative transfer–controlled inversion process to generate rain-rate estimates. Although this algorithm has been extensively evaluated, none of the evaluation approaches has explicitly examined the underlying microphysical assumptions through a direct intercomparison of the assumed cloud-model microphysics with in situ, three-dimensional microphysical observations. The main scientific objective of this study is to identify and overcome the foremost model-generated microphysical weaknesses in the TRMM 2a12 algorithm through analysis of (a) in situ aircraft microphysical observations; (b) aircraft- and satellite-based passive microwave measurements; (c) ground-, aircraft-, and satellite-based radar measurements; (d) synthesized satellite brightness temperatures and radar reflectivities; (e) radiometer-only profile algorithm retrievals; and (f) radar-only profile or volume algorithm retrievals. Results indicate the assumed 2a12 microphysics differs most from aircraft-observed microphysics where either ground or aircraft radar–derived rain rates exhibit the greatest differences with 2a12-retrieved rain rates. An emission–scattering coordinate system highlights the 2a12 algorithm's tendency to match high-emission/high-scattering observed profiles to high-emission/low-scattering database profiles. This is due to a lack of mixed-phase-layer ice hydrometeor scatterers in the cloud model–generated profiles as compared with observed profiles. Direct comparisons between aircraft-measured and model-generated 2a12 microphysics suggest that, on average, the radiometer algorithm's microphysics database retrieves liquid and ice water contents that are approximately 1/3 the size of those observed at levels below 10 km. Also, the 2a12 rain-rate retrievals are shown to be strongly influenced by the 2a12's convective fraction specification. A proposed modification of this factor would improve 2a12 rain-rate retrievals; however, fundamental changes to the cloud radiation model's ice parameterization are necessary to overcome the algorithm's tendency to produce mixed-phase-layer ice hydrometeor deficits.

Corresponding author address: Eric A. Smith, Goddard Space Flight Center, Code 613.6, Greenbelt, MD 20771. Email: eric.a.smith@nasa.gov

Abstract

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager precipitation profile retrieval algorithm (2a12) assumes cloud model–derived vertically distributed microphysics as part of the radiative transfer–controlled inversion process to generate rain-rate estimates. Although this algorithm has been extensively evaluated, none of the evaluation approaches has explicitly examined the underlying microphysical assumptions through a direct intercomparison of the assumed cloud-model microphysics with in situ, three-dimensional microphysical observations. The main scientific objective of this study is to identify and overcome the foremost model-generated microphysical weaknesses in the TRMM 2a12 algorithm through analysis of (a) in situ aircraft microphysical observations; (b) aircraft- and satellite-based passive microwave measurements; (c) ground-, aircraft-, and satellite-based radar measurements; (d) synthesized satellite brightness temperatures and radar reflectivities; (e) radiometer-only profile algorithm retrievals; and (f) radar-only profile or volume algorithm retrievals. Results indicate the assumed 2a12 microphysics differs most from aircraft-observed microphysics where either ground or aircraft radar–derived rain rates exhibit the greatest differences with 2a12-retrieved rain rates. An emission–scattering coordinate system highlights the 2a12 algorithm's tendency to match high-emission/high-scattering observed profiles to high-emission/low-scattering database profiles. This is due to a lack of mixed-phase-layer ice hydrometeor scatterers in the cloud model–generated profiles as compared with observed profiles. Direct comparisons between aircraft-measured and model-generated 2a12 microphysics suggest that, on average, the radiometer algorithm's microphysics database retrieves liquid and ice water contents that are approximately 1/3 the size of those observed at levels below 10 km. Also, the 2a12 rain-rate retrievals are shown to be strongly influenced by the 2a12's convective fraction specification. A proposed modification of this factor would improve 2a12 rain-rate retrievals; however, fundamental changes to the cloud radiation model's ice parameterization are necessary to overcome the algorithm's tendency to produce mixed-phase-layer ice hydrometeor deficits.

Corresponding author address: Eric A. Smith, Goddard Space Flight Center, Code 613.6, Greenbelt, MD 20771. Email: eric.a.smith@nasa.gov

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Journal of Applied Meteorology and Climatology

  • Adler, R. F., G. J. Huffman, and P. R. Keehn, 1994: Global tropical rain estimates from microwave adjusted geosynchronous IR data. Remote Sens. Rev, 11 , 125–152.

    • Search Google Scholar
    • Export Citation

  • Ferraro, R. R., and G. F. Marks, 1995: The development of SSM/I rain-rate retrieval algorithms using ground based radar measurements. J. Atmos. Oceanic Technol, 12 , 755–770.

    • Search Google Scholar
    • Export Citation

  • Fiorino, S. T., 2002: Investigation of microphysical assumptions in TRMM radiometer's rain profile algorithm using KWAJEX satellite, aircraft, and surface data sets. Ph.D. dissertation, The Florida State University, 104 pp.

  • Flatau, P. J., G. J. Tripoli, J. Verlinde, and W. R. Cotton, 1989: The CSU-RAMS cloud microphysical module: General theory and code documentation. Dept. of Atmospheric Science, Colorado State University Paper 451, 88 pp.

  • Grabowski, W. W., 2003: Impact of cloud microphysics on convective–radiative quasi equilibrium revealed by cloud-resolving convective parameterization. J. Climate, 16 , 3463–3475.

    • Search Google Scholar
    • Export Citation

  • Haddad, Z. S., E. A. Smith, C. D. Kummerow, T. Iguchi, M. R. Farrar, S. L. Durden, M. Alves, and W. S. Olson, 1997: The TRMM “Day-1” radar/radiometer combined rain-profiling algorithm. J. Meteor. Soc. Japan, 75 , 799–809.

    • Search Google Scholar
    • Export Citation

  • Hagen, M., and S. E. Yuter, 2003: Relations between radar reflectivity, liquid water content, and rainfall rate during the MAP-SOP. Quart. J. Roy. Meteor. Soc, 129 , 477–493.

    • Search Google Scholar
    • Export Citation

  • Heymsfield, A. J., A. Bansemer, P. R. Field, S. L. Durden, J. Stith, J. E. Dye, W. Hall, and T. Grainger, 2002: Observations and parameterizations of particle size distributions in deep tropical cirrus and stratiform precipitating clouds: Results from in situ observations in TRMM field campaigns. J. Atmos. Sci, 59 , 3457–3491.

    • Search Google Scholar
    • Export Citation

  • Hong, Y., C. D. Kummerow, and W. S. Olson, 1999: Separation of convective and stratiform precipitation using microwave brightness temperature. J. Appl. Meteor, 38 , 1195–1213.

    • Search Google Scholar
    • Export Citation

  • Hou, A. Y., S. Q. Zhang, A. M. da Silva, and W. S. Olson, 2000: Improving assimilated global datasets using TMI rainfall and columnar moisture observations. J. Climate, 13 , 4180–4195.

    • Search Google Scholar
    • Export Citation

  • Iguchi, T., and R. Meneghini, 1994: Intercomparison of single-frequency methods for retrieving a vertical rain profile from airborne or spaceborne radar data. J. Atmos. Oceanic Technol, 11 , 1507–1511.

    • Search Google Scholar
    • Export Citation

  • Iguchi, T., T. Kozu, R. Meneghini, J. Awaka, and K. Okamoto, 2000: Rain-profiling algorithm for the TRMM precipitation radar. J. Appl. Meteor, 39 , 2038–2052.

    • Search Google Scholar
    • Export Citation

  • Kingsmill, D. E., and Coauthors, 2004: TRMM common microphysics products: A tool for evaluating spaceborne precipitation retrieval algorithms. J. Appl. Meteor, 43 , 1598–1618.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C. D., 1998: Beamfilling errors in passive microwave retrievals. J. Appl. Meteor, 37 , 1837–1858.

  • Kummerow, C., and K. Okamoto, 1999: Space-borne remote sensing of precipitation from TRMM. Review of Radio Science (1996–1999), W. Ross Stone, Ed., Oxford University Press, 487–502.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C. D., W. S. Olson, and L. Giglio, 1996: A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. IEEE Trans. Geosci. Remote Sens, 34 , 1213–1232.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C., and Coauthors, 2000: The status of the Tropical Rainfall Measuring Mission (TRMM) after two years in orbit. J. Appl. Meteor, 39 , 1965–1982.

    • Search Google Scholar
    • Export Citation

  • Lang, S., W-K. Tao, J. Simpson, and B. Ferrier, 2003: Modeling of convective–stratiform precipitation processes: Sensitivity to partitioning methods. J. Appl. Meteor, 42 , 505–527.

    • Search Google Scholar
    • Export Citation

  • Liu, G., and J. A. Curry, 1992: Retrieval of precipitation from satellite microwave measurement using both emission and scattering. J. Geophys. Res, 97 , 9959–9974.

    • Search Google Scholar
    • Export Citation

  • Liu, G., and J. A. Curry, 1998: An investigation of the relationship between emission and scattering signals in SSM/I data. J. Atmos. Sci, 55 , 1628–1643.

    • Search Google Scholar
    • Export Citation

  • Marshall, J. S., and W. Mc K. Palmer, 1948: The distribution of raindrops with size. J. Meteor, 5 , 165–166.

  • Meneghini, R., T. Iguchi, T. Kozu, L. Liao, K. Okamoto, J. Jones, and J. Kwiatkowski, 2000: Use of the surface reference technique for path attenuation estimates from the TRMM Precipitation Radar. J. Appl. Meteor, 39 , 2053–2070.

    • Search Google Scholar
    • Export Citation

  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. Kluwer Academic, 954 pp.

  • Smith, E. A., and T. D. Hollis, 2002: Performance evaluation of level 2 TRMM rain profile algorithms by intercomparison and hypothesis testing. Cloud Systems, Hurricanes, and the Tropical Rainfall Measuring Mission (TRMM): A Tribute to Dr. Joanne Simpson, Meteor. Monogr., No. 59, Amer. Meteor. Soc., 207–222.

  • Smith, E. A., F. J. Turk, M. R. Farrar, A. Mugnai, and X. Xiang, 1997: Estimating 13.8-GHz path-integrated attenuation from 10.7-GHz brightness temperatures for TRMM combined PR–TMI precipitation algorithm. J. Appl. Meteor, 36 , 365–388.

    • Search Google Scholar
    • Export Citation

  • Smith, E. A., and Coauthors, 1998: Results of WetNet PIP-2 Project. J. Atmos. Sci, 55 , 1483–1536.

  • Smith, E. A., and Coauthors, 2005: International Global Precipitation Measurement (GPM) Program and Mission: An overview. Measuring Precipitation from Space: EURAINSAT and the Future, V. Levizzani, P. Bauer, and F. J. Turk, Eds., Springer Verlag, in press.

    • Search Google Scholar
    • Export Citation

  • Spencer, R. W., H. M. Goodman, and R. E. Hood, 1989: Precipitation retrieval over land and ocean with the SSM/I: Identification and characteristics of the scattering signal. J. Atmos. Oceanic Technol, 6 , 254–273.

    • Search Google Scholar
    • Export Citation

  • Steiner, M., R. A. Houze Jr., and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor, 34 , 1978–2007.

    • Search Google Scholar
    • Export Citation

  • Stith, J. L., J. E. Dye, A. Bansemer, A. J. Heymsfield, C. A. Grainger, W. A. Petersen, and R. Cifelli, 2002: Microphysical observations of tropical clouds. J. Appl. Meteor, 41 , 97–117.

    • Search Google Scholar
    • Export Citation

  • Wilheit, T. T., A. T. C. Chang, M. S. V. Rao, E. B. Rodgers, and J. S. Theon, 1977: Satellite technique for quantitatively mapping rainfall rates over the oceans. J. Appl. Meteor, 16 , 551–560.

    • Search Google Scholar
    • Export Citation

  • Wilheit, T. T., A. T. C. Chang, and L. S. Chiu, 1991: Retrieval of monthly rainfall indices from microwave radiometric measurements using probability distribution functions. J. Atmos. Oceanic Technol, 8 , 118–136.

    • Search Google Scholar
    • Export Citation

  • Wilheit, T. T., and Coauthors, 1994: Algorithms for the retrieval of rainfall from passive microwave measurements. Remote Sens. Rev, 11 , 163–194.

    • Search Google Scholar
    • Export Citation

  • Yuter, S. E., and R. A. Houze Jr., 1997: Measurements of raindrop size distributions over the Pacific warm pool and implications for Z–R relations. J. Appl. Meteor, 36 , 847–867.

    • Search Google Scholar
    • Export Citation

  • Yuter, S. E., R. A. Houze Jr., E. A. Smith, T. T. Wilheit, and E. Zipser, 2005: Physical characterization of tropical oceanic convection observed in KWAJEX. J. Appl. Meteor, 44 , 385–415.

    • Search Google Scholar
    • Export Citation
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