Validation and Development of Melting Layer Models Using Constraints by Active/Passive Microwave Observations of Rain and the Wind-Roughened Ocean Surface

Shannon T. Brown Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan

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Christopher S. Ruf Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan

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Abstract

A physically based method is developed to estimate the microphysical structure of the melting layer in stratiform rain using airborne observations by a dual-frequency radar and a 10.7-GHz radiometer. The method employs a nonlinear optimal estimation approach to find two parameters of the gamma drop size distribution (DSD) at each radar range gate from the Ku/Ka-band reflectivities. The DSD profile is used to determine the atmospheric absorption/extinction profile, which enables the surface contribution to the measured brightness temperature to be estimated. The surface wind speed is estimated from the surface emissivity by inverting the forward model, which relates the two. Retrievals in stratiform precipitation require a model to describe the thermodynamic and electromagnetic properties of melting hydrometeors. The melting layer can contribute a majority of the total atmospheric absorption, making it a key component for accurate retrievals in stratiform rain. Several melting layer models were evaluated based on their fit to the dual-frequency reflectivity measurements in the melting layer. A candidate model is selected and tuned to match the radar measurements. The melting layer model is then incorporated into the full forward model for the brightness temperature observed by the radiometer. The surface wind speed assumed in the forward model is forced by the radiometer observations. If the actual surface wind speed is known, this approach provides a powerful constraint on the possible melting layer model. A case study is presented from an airborne campaign over areas of precipitation off the coast of Vancouver Island, British Columbia, Canada. The estimated wind speeds are found to be uncorrelated with the reflectivity and their average value is within 1 m s−1 of that retrieved in a clear area adjacent to the rain.

* Current affiliation: Jet Propulsion Laboratory, Pasadena, California

Corresponding author address: Shannon Brown, Jet Propulsion Laboratory, 4800 Oak Grove Drive, M/S 168-314, Pasadena, CA 91109. Email: shannon.t.brown@jpl.nasa.gov

Abstract

A physically based method is developed to estimate the microphysical structure of the melting layer in stratiform rain using airborne observations by a dual-frequency radar and a 10.7-GHz radiometer. The method employs a nonlinear optimal estimation approach to find two parameters of the gamma drop size distribution (DSD) at each radar range gate from the Ku/Ka-band reflectivities. The DSD profile is used to determine the atmospheric absorption/extinction profile, which enables the surface contribution to the measured brightness temperature to be estimated. The surface wind speed is estimated from the surface emissivity by inverting the forward model, which relates the two. Retrievals in stratiform precipitation require a model to describe the thermodynamic and electromagnetic properties of melting hydrometeors. The melting layer can contribute a majority of the total atmospheric absorption, making it a key component for accurate retrievals in stratiform rain. Several melting layer models were evaluated based on their fit to the dual-frequency reflectivity measurements in the melting layer. A candidate model is selected and tuned to match the radar measurements. The melting layer model is then incorporated into the full forward model for the brightness temperature observed by the radiometer. The surface wind speed assumed in the forward model is forced by the radiometer observations. If the actual surface wind speed is known, this approach provides a powerful constraint on the possible melting layer model. A case study is presented from an airborne campaign over areas of precipitation off the coast of Vancouver Island, British Columbia, Canada. The estimated wind speeds are found to be uncorrelated with the reflectivity and their average value is within 1 m s−1 of that retrieved in a clear area adjacent to the rain.

* Current affiliation: Jet Propulsion Laboratory, Pasadena, California

Corresponding author address: Shannon Brown, Jet Propulsion Laboratory, 4800 Oak Grove Drive, M/S 168-314, Pasadena, CA 91109. Email: shannon.t.brown@jpl.nasa.gov

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  • Atlas, D., Srivastava C. , and Sekhon S. , 1973: Doppler radar characteristics of precipitation at vertical incidence. Rev. Geophys. Space Phys., 11 , 135.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barthazy, E., Heinrich W. , and Waldvogel A. , 1998: Size distribution of hydrometers through the melting layer. Atmos. Res., 47–48 , 193208.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., Kummerow C. , Shin D. , and Williams C. , 2003: Constraining microwave brightness temperatures by radar brightband observations. J. Atmos. Oceanic Technol., 20 , 856871.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauer, P., Baptista J. , and Iulis M. , 1999: The effect of the melting layer on the microwave emission of clouds over the ocean. J. Atmos. Sci., 56 , 852867.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bohren, C., and Battan L. , 1982: Radar backscattering of microwaves by spongy ice spheres. J. Atmos. Sci., 39 , 26232628.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dou, X., Testud J. , Amayenc P. , and Black R. , 1999: The concept of a normalized gamma distribution to descibe raindrop spectra and its use to parameterize rain relations. Preprints, 29th Int. Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc., 625–628.

  • Fabry, F., and Szyrmer W. , 1999: Modeling of the melting layer. Part II: Electromagnetic. J. Atmos. Sci., 56 , 35933600.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goodberlet, M., Swift C. , and Wilkerson J. , 1990: Ocean surface wind speed measurements of the Special Sensor Microwave/Imager (SSM/I). IEEE. Trans. Geosci. Remote Sens., 28 , 823828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grecu, M., and Anagnostou E. , 2002: Use of passive microwave observations in a radar rainfall-profiling algorithm. J. Appl. Meteor., 41 , 702715.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, T., and Rosmond T. , 1991: The description of the Navy Operational Global Atmospheric Prediction System’s spectral forecast model. Mon. Wea. Rev., 119 , 17861815.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hollinger, J., 1970: Passive microwave measurements of the sea surface. J. Geophys. Res., 75 , 52095213.

  • Im, E., Durden S. , Sadowy G. , and Li L. , 2002: Rainfall observations by the airborne dual-frequency precipitation radar during CAMEX-4. Proc. 2002 IGARSS, Toronto, ON, Canada, IEEE, 281–283.

  • Klaassen, W., 1988: Radar observations and simulation of the melting layer of precipitation. J. Atmos. Sci., 45 , 37413753.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Locatelli, J., and Hobbs P. , 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res., 98 , 27572765.

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

  • Maxwell Garnet, J., 1904: Colours in metal glasses and in metallic films. Philos. Trans. Roy. Soc. London., A203 , 385420.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meneghini, T., and Liao L. , 1996: Comparisons of cross sections for melting hydrometeors as derived from dielectric mixing formulas and a numerical method. J. Appl. Meteor., 35 , 16581670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meneghini, T., and Liao L. , 2000: Effective dielectric constants of mixed-phase hydrometeors. J. Atmos. Oceanic Technol., 17 , 628640.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., Zhang R. , and Pitter R. L. , 1990: Mass-dimensional relationships for ice particles and the influence and riming on snowfall rates. J. Appl. Meteor., 29 , 153163.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitra, S., Vohl O. , Ahr M. , and Pruppacher R. , 1990: A wind tunnel and theoretical study of the melting behavior of atmospheric ice particles. Part IV: Experiment and theory for snow flakes. J. Atmos. Sci., 47 , 584591.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Olson, W., Bauer P. , Viltard N. , Johnson D. , Tao W. , Meneghini R. , and Liao L. , 2001: A melting-layer model for passive/active microwave remote sensing applications. Part I: Model formulation and comparison with observations. J. Appl. Meteor., 40 , 11451163.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pandey, P., and Kakar R. , 1982: An empirical microwave emissivity model for a foam-covered sea. IEEE J. Oceanic Eng., 7 , 135140.

  • Rinehart, R., 1997: Radar for Meteorologists. Rinehart Publications, 149 pp.

  • Rodgers, C., 2000: Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific, 238 pp.

  • Rogers, R. R., and Yau M. K. , 1996: A Short Course in Cloud Physics. 3d ed. Butterworth-Heinemann, 290 pp.

  • Ruf, C., and Principe C. , 2003: X-band lightweight rainfall radiometer first light. Proc. 2003 IGARSS, Toulouse, France, IEEE, 1701–1703.

  • Ruf, C., and Coauthors, 2002: Lightweight rainfall radiometer STAR aircraft sensor. Proc. 2002 IGARSS, Toronto, ON, Canada, IEEE, 850–852.

  • Rutledge, S., and Hobbs P. , 1983: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part VIII: A model for the “seeder-feeder” process in warm-frontal rainbands. J. Atmos. Sci., 40 , 11861206.

    • Search Google Scholar
    • Export Citation
  • Sekhon, R., and Srivastava R. , 1970: Snow size spectra and radar reflectivity. J. Atmos. Sci., 27 , 299307.

  • Stogryn, A., 1972: The emissivity of sea foam at microwave frequencies. J. Geophys. Res., 77 , 16581666.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tao, W., and Simpson J. , 1993: Goddard Cumulus Ensemble Model. Part I: Model description. Terr. Atmos. Oceanic Sci., 4 , 3572.

  • Tripoli, G. J., 1992: A nonhydrostatic mesoscale model designed to simulate scale interaction. Mon. Wea. Rev., 120 , 13421359.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Uhlhorn, E., and Black P. , 2003: Verification of remotely sensed sea surface winds in hurricanes. J. Atmos. Oceanic Technol., 20 , 99116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ulaby, F., Moore R. K. , and Fung A. K. , 1981: Microwave interaction with atmospheric constituents. Microwave Remote Sensing: Active and Passive, Vol. I, Fundamentals and Radiometry, Artech House, 256–343.

  • Ulaby, F., Moore R. K. , and Fung A. K. , 1986: Appendix E. Microwave Remote Sensing: Active and Passive, Vol. III, From Theory to Applications, Artech House, 2020–2022.

  • Ulbrich, C., 1983: Natural variations in the analytical form of the raindrop size distribution. J. Climate Appl. Meteor., 22 , 17641775.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viltard, N., Kummerow C. , Olson W. , and Hong Y. , 2000: Combined use of the radar and radiometer of TRMM to estimate the influence of drop size distribution on rain retrievals. J. Appl. Meteor., 39 , 21032114.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weissman, D., Bourassa M. , and Tongue J. , 2002: Effects of rain rate and wind magnitude on sea winds scatterometer wind speed errors. J. Atmos. Oceanic Technol., 19 , 738746.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Willis, P., 1984: Functional fits to some observed drop size distributions and parameterization of rain. J. Atmos. Sci., 41 , 16481661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Willis, P., and Heymsfield A. , 1989: Structure of the melting layer in mesoscale convective system stratiform precipitation. J. Atmos. Sci., 46 , 20082025.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wusheng, J., and Wang P. , 1999: Ventilation coefficients for falling ice crystals in the atmosphere at low-intermediate Reynolds numbers. J. Atmos. Sci., 56 , 829836.

    • Crossref
    • Search Google Scholar
    • Export Citation
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