Evaluating Light Rain Drop Size Estimates from Multiwavelength Micropulse Lidar Network Profiling

Simone Lolli Joint Center for Earth Systems Technology, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Ellsworth J. Welton NASA Goddard Space Flight Center, Greenbelt, Maryland

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James R. Campbell Naval Research Laboratory, Monterey, California

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Abstract

This paper investigates multiwavelength retrievals of median equivolumetric drop diameter D0 suitable for drizzle and light rain, through collocated 355-/527-nm Micropulse Lidar Network (MPLNET) observations collected during precipitation occurring 9 May 2012 at the Goddard Space Flight Center (GSFC) project site. By applying a previously developed retrieval technique for infrared bands, the method exploits the differential backscatter by liquid water at 355 and 527 nm for water drops larger than ≈50 μm. In the absence of molecular and aerosol scattering and neglecting any transmission losses, the ratio of the backscattering profiles at the two wavelengths (355 and 527 nm), measured from light rain below the cloud melting layer, can be described as a color ratio, which is directly related to D0. The uncertainty associated with this method is related to the unknown shape of the drop size spectrum and to the measurement error. Molecular and aerosol scattering contributions and relative transmission losses due to the various atmospheric constituents should be evaluated to derive D0 from the observed color ratio profiles. This process is responsible for increasing the uncertainty in the retrieval. Multiple scattering, especially for UV lidar, is another source of error, but it exhibits lower overall uncertainty with respect to other identified error sources. It is found that the total error upper limit on D0 approaches 50%. The impact of this retrieval for long-term MPLNET monitoring and its global data archive is discussed.

Corresponding author address: Simone Lolli, NASA Goddard Space Flight Center, Mail Code 612, Greenbelt, MD 20771. E-mail: simone.lolli@nasa.gov

Abstract

This paper investigates multiwavelength retrievals of median equivolumetric drop diameter D0 suitable for drizzle and light rain, through collocated 355-/527-nm Micropulse Lidar Network (MPLNET) observations collected during precipitation occurring 9 May 2012 at the Goddard Space Flight Center (GSFC) project site. By applying a previously developed retrieval technique for infrared bands, the method exploits the differential backscatter by liquid water at 355 and 527 nm for water drops larger than ≈50 μm. In the absence of molecular and aerosol scattering and neglecting any transmission losses, the ratio of the backscattering profiles at the two wavelengths (355 and 527 nm), measured from light rain below the cloud melting layer, can be described as a color ratio, which is directly related to D0. The uncertainty associated with this method is related to the unknown shape of the drop size spectrum and to the measurement error. Molecular and aerosol scattering contributions and relative transmission losses due to the various atmospheric constituents should be evaluated to derive D0 from the observed color ratio profiles. This process is responsible for increasing the uncertainty in the retrieval. Multiple scattering, especially for UV lidar, is another source of error, but it exhibits lower overall uncertainty with respect to other identified error sources. It is found that the total error upper limit on D0 approaches 50%. The impact of this retrieval for long-term MPLNET monitoring and its global data archive is discussed.

Corresponding author address: Simone Lolli, NASA Goddard Space Flight Center, Mail Code 612, Greenbelt, MD 20771. E-mail: simone.lolli@nasa.gov
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  • Beard, K. V., 1976: Terminal velocity and shape of cloud and precipitation drops aloft. J. Atmos. Sci., 33, 851864.

  • Bennartz, R., and Coauthors, 2013: July 2012 Greenland melt extent enhanced by low-level liquid clouds. Nature, 496, 8386, doi:10.1038/nature12002.

    • Search Google Scholar
    • Export Citation
  • Bohren, C. F., and Huffman D. R. , 1983: Absorption and Scattering of Light by Small Particles. John Wiley and Sons, 530 pp.

  • Campbell, J. R., and Shiobara M. , 2008: Glaciation of a mixed-phase boundary layer cloud at a coastal arctic site as depicted in continuous lidar measurements. Polar Sci., 2, 121127.

    • Search Google Scholar
    • Export Citation
  • Campbell, J. R., Hlavka D. L. , Welton E. J. , Flynn C. J. , Turner D. D. , Spinhirne J. D. , Scott V. S. , and Hwang I. H. , 2002: Full-time, eye-safe cloud and aerosol lidar observation at Atmospheric Radiation Measurement Program sites: Instrument and data processing. J. Atmos. Oceanic Technol., 19, 431442.

    • Search Google Scholar
    • Export Citation
  • Campbell, J. R., Welton E. J. , Spinhirne J. D. , Ji Q. , Tsay S.-C. , Piketh S. J. , Barenbrug M. , and Holben B. N. , 2003: Micropulse lidar observations of tropospheric aerosols over northeastern South Africa during the ARREX and SAFARI 2000 dry season experiments. J. Geophys. Res., 108, 8497, doi:10.1029/2002JD002563.

    • Search Google Scholar
    • Export Citation
  • Campbell, J. R., Sassen K. , and Welton E. J. , 2008: Elevated cloud and aerosol layer retrievals from micropulse lidar signal profiles. J. Atmos. Oceanic Technol., 25, 685700.

    • Search Google Scholar
    • Export Citation
  • COESA, 1976: U.S. Standard Atmosphere, 1976. NOAA, 227 pp.

  • Di Girolamo, P., Summa D. , Cacciani M. , Norton E. G. , Peters G. , and Dufournet Y. , 2012: Lidar and radar measurements of the melting layer: Observations of dark and bright band phenomena. Atmos. Chem. Phys., 12, 41434157.

    • Search Google Scholar
    • Export Citation
  • Fernald, F. G., 1984: Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 23, 652653.

  • Frisch, A. S., Fairall C. W. , and Snider J. B. , 1995: Measurement of stratus cloud and drizzle parameters in ASTEX with a Kα-band Doppler radar and a microwave radiometer. J. Atmos. Sci., 52, 27882799.

    • Search Google Scholar
    • Export Citation
  • Harrison, E. F., Minnis P. , Barkstrom B. R. , Ramanathan V. , Cess R. D. , and Gibson G. G. , 1990: Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J. Geophys. Res., 95 (D11), 18 68718 704.

    • Search Google Scholar
    • Export Citation
  • Hoff, R., and Boesenberg J. , 2008: GAW Aerosol Lidar Observations Network (GALION). Preprints, Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, New Orleans, LA, Amer. Meteor. Soc., 5.2. [Available online at https://ams.confex.com/ams/88Annual/techprogram/paper_131629.htm.]

  • Lolli, S., Sauvage L. , Stachlewska I. , and Coulter R. , 2008: Assessment of the EZ LIDAR and micro pulse lidar (MPL) performances at ARM Southern Great Plains (SGP) Central Facility for the measurement of clouds and aerosols. Geophysical Research Abstracts, Vol. 10, Abstract EGU2008–A-11091. [Available online at http://www.cosis.net/abstracts/EGU2008/11091/EGU2008-A-11091.pdf.]

    • Search Google Scholar
    • Export Citation
  • Lolli, S., Sauvage L. , Loaec S. , and Lardier M. , 2011: EZ lidar: A new compact autonomous eye-safe scanning aerosol lidar for extinction measurements and PBL height detection. Validation of the performances against other instruments and intercomparison campaigns. Opt. Pura Apl., 44, 3341.

    • Search Google Scholar
    • Export Citation
  • Lynch, D. K., and Livingston W. , 2001: Color and Light in Nature. 2nd ed. Cambridge University Press, 277 pp.

  • O’Connor, E. J., Illingworth A. J. , and Hogan R. J. , 2004: A technique for autocalibration of cloud lidar. J. Atmos. Oceanic Technol., 21, 777786.

    • Search Google Scholar
    • Export Citation
  • O’Connor, E. J., Hogan R. J. , and Illingsworth A. J. , 2005: Retrieving stratocumulus drizzle parameters using Doppler radar and lidar. J. Appl. Meteor., 44, 1427.

    • Search Google Scholar
    • Export Citation
  • Russell, P., Swissler T. , and McCormick M. , 1979: Methodology for error analysis and simulation of lidar aerosol measurements. Appl. Opt., 18, 37833797.

    • Search Google Scholar
    • Export Citation
  • Sassen, K., 1978: Backscattering cross sections for hydrometeors: Measurements at 6328 Å. Appl. Opt., 17, 804806.

  • Sassen, K., and Cho B. S. , 1992: Subvisual–thin cirrus lidar dataset for satellite verification and climatological research. J. Appl. Meteor., 31, 12751285.

    • Search Google Scholar
    • Export Citation
  • Sassen, K., Campbell J. R. , Zhu J. , Kollias P. , Shupe M. , and Williams C. , 2005: Lidar and triple-wavelength Doppler radar measurements of the melting layer: A revised model for dark- and brightband phenomena. J. Appl. Meteor., 44, 301312.

    • Search Google Scholar
    • Export Citation
  • Sassen, K., Matrosov S. , and Campbell J. , 2007: CloudSat spaceborne 94 GHz radar bright bands in the melting layer: An attenuation-driven upside-down lidar analog. Geophys. Res. Lett., 34, L16818, doi:10.1029/2007GL030291.

    • Search Google Scholar
    • Export Citation
  • Slingo, A., and Slingo J. M. , 1991: Response of the National Center for Atmospheric Research Community Climate Model to improvements in the representation of clouds. J. Geophys. Res., 96 (D9), 15 34115 357.

    • Search Google Scholar
    • Export Citation
  • Spinhirne, J. D., 1993: Micro pulse lidar. IEEE Trans. Geosci. Remote Sens., 31, 4855.

  • Spinhirne, J. D., Rall J. A. R. , and Scott V. S. , 1995: Compact eye safe lidar systems. Rev. Laser Eng., 23, 112118.

  • Welton, E. J., and Campbell J. R. , 2002: Micropulse lidar signal uncertainties. J. Atmos. Oceanic Technol., 19, 20892094.

  • Welton, E. J., Campbell J. R. , Spinhrine J. D. , and Scott III V. S. , 2001: Global monitoring of clouds and aerosols using a network of micropulse lidar systems. Lidar Remote Sensing for Industry and Environment Monitoring, U. N. Singh, T. Itabe, N. Sugimoto, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 4153), 151–158.

  • Welton, E. J., and Coauthors, 2002: Measurements of aerosol vertical profiles and optical properties during INDOEX 1999 using micropulse lidars. J. Geophys. Res., 107, 8019, doi:10.1029/2000JD000038.

    • Search Google Scholar
    • Export Citation
  • Westbrook, C. D., Hogan R. J. , O’Connor E. J. , and Illingworth A. J. , 2010: Estimating drizzle drop size and precipitation rate using two-colour lidar measurements. Atmos. Meas. Tech., 3, 671681, doi:10.5194/amt-3-671-2010.

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

    • Search Google Scholar
    • Export Citation
  • Wolf, S., and Voshchinnikov N. V. , 2004: Mie scattering by ensembles of particles with very large size parameters. Comput. Phys. Commun., 162, 113123.

    • Search Google Scholar
    • Export Citation
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