Use of Passive Microwave Observations in a Radar Rainfall-Profiling Algorithm

Mircea Grecu Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut

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Emmanouil N. Anagnostou Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut

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Abstract

A physically based methodology to incorporate passive microwave observations in a “rain-profiling algorithm” is developed for space- or airborne radars at frequencies exhibiting attenuation. The rain-profiling algorithm deploys a formulation for reflectivity attenuation correction that is mathematically equivalent to that of Hitschfeld and Bordan. In this formulation, the reflectivity–hydrometeor content (or rainfall rate) and reflectivity–attenuation relationships are expressed as a function of one variable in the drop size distribution parameterization, namely, the multiplicative factor in a normalized gamma distribution. The multiplicative factor parameter, mean cloud water content, and one parameter describing the precipitation phase are estimated in a Bayesian framework. This involves the minimization of differences between the 10-, 19-, 37-, and 85-GHz brightness temperature values predicted by a plane-parallel multilayer radiative transfer model and those observed by space- or airborne radiometers. A variational approach is devised to perform the minimization. The methodology is first tested using data simulated using a cloud model and is subsequently applied to coincident airborne brightness temperature and radar profile observations originating in the Kwajalein Experiment of the Tropical Rainfall Measuring Mission (TRMM). Results suggest improvements in rain estimation induced by the inclusion of the brightness temperature information in the retrieval framework if consistent modeling and quantification of errors are performed. Recommendations regarding the application of the method to TRMM satellite observations are formulated based on the findings of the study.

Corresponding author address: Dr. Emmanouil N. Anagnostou, Civil and Environmental Engineering, U-37, University of Connecticut, Storrs, CT 06269-2037. manos@engr.uconn.edu

Abstract

A physically based methodology to incorporate passive microwave observations in a “rain-profiling algorithm” is developed for space- or airborne radars at frequencies exhibiting attenuation. The rain-profiling algorithm deploys a formulation for reflectivity attenuation correction that is mathematically equivalent to that of Hitschfeld and Bordan. In this formulation, the reflectivity–hydrometeor content (or rainfall rate) and reflectivity–attenuation relationships are expressed as a function of one variable in the drop size distribution parameterization, namely, the multiplicative factor in a normalized gamma distribution. The multiplicative factor parameter, mean cloud water content, and one parameter describing the precipitation phase are estimated in a Bayesian framework. This involves the minimization of differences between the 10-, 19-, 37-, and 85-GHz brightness temperature values predicted by a plane-parallel multilayer radiative transfer model and those observed by space- or airborne radiometers. A variational approach is devised to perform the minimization. The methodology is first tested using data simulated using a cloud model and is subsequently applied to coincident airborne brightness temperature and radar profile observations originating in the Kwajalein Experiment of the Tropical Rainfall Measuring Mission (TRMM). Results suggest improvements in rain estimation induced by the inclusion of the brightness temperature information in the retrieval framework if consistent modeling and quantification of errors are performed. Recommendations regarding the application of the method to TRMM satellite observations are formulated based on the findings of the study.

Corresponding author address: Dr. Emmanouil N. Anagnostou, Civil and Environmental Engineering, U-37, University of Connecticut, Storrs, CT 06269-2037. manos@engr.uconn.edu

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  • Bauer, P., A. Khain, A. Pokrovsky, R. Meneghini, C. Kummerow, F. Marzano, and J. P. V. Poiares Baptista. 2000. Combined cloud–microwave radiative transfer modeling of stratiform rainfall. J. Atmos. Sci. 57:10821104.

    • Search Google Scholar
    • Export Citation
  • Byrd, R. H., P. H. Lu, J. Nocedal, and C. Y. Zhu. 1995. A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Comput. 16:11901208.

    • Search Google Scholar
    • Export Citation
  • Durden, S. L., E. Im, F. K. Li, W. Ricketts, A. Tanner, and W. Wilson. 1994. ARMAR. An airborne rain-mapping radar. J. Atmos. Oceanic Technol. 11:727737.

    • Search Google Scholar
    • Export Citation
  • Giering, R. and T. Kaminski. 1998. Recipes for adjoint code construction. ACM Trans. Math. Software 24:437474.

  • Haddad, Z. S., E. Im, S. L. Durden, and S. Hensley. 1996. Stochastic filtering of rain profiles using radar, surface-referenced radar, or combined radar–radiometer measurements. J. Appl. Meteor. 35:229242.

    • Search Google Scholar
    • Export Citation
  • Harris, D. and E. Foufoula-Georgiou. 2001. Subgrid variability and stochastic downscaling of modeled clouds: Effects on radiative transfer computations for rainfall retrieval. J. Geophys. Res. 106:1034910362.

    • Search Google Scholar
    • Export Citation
  • Hitschfeld, W. and J. Bordan. 1954. Errors inherent in the radar measurement of rainfall at attenuating wavelengths. J. Meteor. 11:5867.

    • 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. J. Atmos. Oceanic Technol. 11:15071516.

    • 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. 39:20382052.

    • Search Google Scholar
    • Export Citation
  • Kozu, T. and T. Iguchi. 1999. Nonuniform beamfilling correction for spaceborne radar rainfall measurement: Implications from TOGA COARE radar data analysis. J. Atmos. Oceanic Technol. 16:17221735.

    • Search Google Scholar
    • Export Citation
  • Liebe, H. J. 1985. An updated model for millimeter wave propagation in moist air. Radio Sci. 20:10691089.

  • Lin, H., M. Xin, C. Wei, Y. Hao, and S. Zou. 1985. Ground-based remote sensing of LWC in cloud and rainfall by a combined dual-wavelength radar–radiometer system. Adv. Atmos. Sci. 2:93103.

    • Search Google Scholar
    • Export Citation
  • Magono, C. and T. Nakamura. 1965. Aerodynamic studies of falling snowflakes. J. Meteor. Soc. Japan 43:139147.

  • Marzano, F. S., A. Mugnai, G. Panegrossi, N. Pierdicca, E. A. Smith, and J. Turk. 1999. Bayesian estimation of precipitating cloud parameters from combined measurements of spaceborne microwave radiometer and radar. IEEE Trans. Geosci. Remote Sens. 37:596613.

    • Search Google Scholar
    • Export Citation
  • Marzoug, M. and P. Amayenc. 1991. Improved range-profiling algorithm of rainfall rate from a spaceborne radar with path-integrated attenuation constraint. IEEE Trans. Geosci. Remote Sens. 29:690703.

    • Search Google Scholar
    • Export Citation
  • Meneghini, R. and D. Atlas. 1986. Simultaneous ocean cross section and rainfall measurements from space with nadir-looking radar. J. Atmos. Oceanic Technol. 3:400413.

    • Search Google Scholar
    • Export Citation
  • Meneghini, R., H. Kumagai, J. R. Wang, T. Iguchi, and T. Kozu. 1997. Microphysical retrievals over stratiform rain using measurements from an airborne dual-wavelength radar-radiometer. IEEE Trans. Geosci. Remote Sens. 35:487506.

    • Search Google Scholar
    • Export Citation
  • Meneghini, R., T. Iguchi, T. Kozu, L. Liao, K. Okamoto, J. A. Jones, and J. Kwiatkowski. 2000. Use of the surface reference technique for path attenuation estimates from the TRMM precipitation radar. J. Appl. Meteor. 39:20532070.

    • Search Google Scholar
    • Export Citation
  • Olson, W. S., C. D. Kummerow, G. M. Heymsfield, and L. Giglio. 1996. A method for combined passive–active microwave retrievals of cloud and precipitation profiles. J. Appl. Meteor. 35:17631789.

    • Search Google Scholar
    • Export Citation
  • Roberti, L., J. Haferman, and C. Kummerow. 1994. Microwave radiative-transfer through horizontally inhomogeneous precipitating clouds. J. Geophys. Res. 99 (D8),:1670716718.

    • Search Google Scholar
    • Export Citation
  • Schols, J. L. and J. A. Weinman. 1994. Retrieval of hydrometeor distributions over the ocean from airborne single-frequency radar and multi-frequency radiometric measurements. Atmos. Res. 34:329346.

    • Search Google Scholar
    • Export Citation
  • Smith, E. A., X. Xiang, A. Mugnai, and G. J. Tripoli. 1994. Design of an inversion-based precipitation profile retrieval algorithm using an explicit cloud model for initial guess microphysics. Meteor. Atmos. Phys. 54:5378.

    • Search Google Scholar
    • Export Citation
  • Smith, E. A., F. J. Turk, M. R. Farrar, A. Mugnai, and X. W. Xiang. 1997. Estimating 13.8-GHz path-integrated attenuation from 10.7-GHz brightness temperatures for the TRMM combined PR-TMI precipitation algorithm. J. Appl. Meteor. 36:365388.

    • Search Google Scholar
    • Export Citation
  • Spencer, R. W., R. E. Hood, F. J. LaFontaine, E. A. Smith, R. Platt, J. Galliano, V. L. Griffin, and E. Lobl. 1994. High-resolution imaging of rain systems with the advanced microwave precipitation radiometer. J. Atmos. Oceanic Technol. 11:849857.

    • Search Google Scholar
    • Export Citation
  • Szyrmer, W. and I. Zawadzki. 1999. Modeling of the melting layer. Part I: Dynamics and microphysics. J. Atmos. Sci. 56:35733592.

  • Tani, T. and P. Amayenc. 1998. Comparison of rain-profiling methods from ARMAR data in TOGA COARE with a view to a possible use with the TRMM radar. J. Appl. Meteor. 37:16001618.

    • Search Google Scholar
    • Export Citation
  • Tao, W. K. and J. Simpson. 1993. Goddard Cumulus Ensemble model. Part I: Model description. TAO 4:3572.

  • Testud, J., S. Oury, and P. Amayenc. 2000a. The concept of “normalized” distribution to describe raindrop spectra: A tool for hydrometeor remote sensing. Phys. Chem. Earth B25:897902.

    • Search Google Scholar
    • Export Citation
  • Testud, J., E. Le Bouar, E. Obligis, and M. Ali-Mehenni. 2000b. The rain profiling algorithm applied to polarimetric weather radar. J. Atmos. Oceanic Technol. 17:332356.

    • Search Google Scholar
    • Export Citation
  • Weinman, J. A., R. Meneghini, and K. Nakamura. 1990. Retrieval of precipitation profiles from airborne radar and passive radiometer measurements: Comparison with dual-frequency radar measurements. J. Appl. Meteor. 29:981993.

    • Search Google Scholar
    • Export Citation
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