• Ansmann, A., U. Wandinger, M. Riebesell, C. Weitkamp, and W. Michaelis. 1992. Independent measurements of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar. Appl. Opt. 3:71137131.

    • Search Google Scholar
    • Export Citation
  • Baedi, R. J. P., J. J. M. de Wit, H. W. J. Russchenberg, J. S. Erkelens, and J. P. V. Poiares Baptista. 2000. Estimating effective radius and liquid water content from radar and lidar based on the CLARE’98 data-set. Phys. Chem. Earth 25:10571062.

    • Search Google Scholar
    • Export Citation
  • Battan, L. J. 1973. Radar Observations of the Atmosphere. University of Chicago Press, 324 pp.

  • Cess, R. D. Coauthors 1990. Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res. 95:1660116615.

    • Search Google Scholar
    • Export Citation
  • Cess, R. D. Coauthors 1996. Cloud feedback in atmospheric general circulation models: An update. J. Geophys. Res. 101:1279112794.

  • Delanoë, J., A. Protat, J. Testud, D. Bouniol, A. J. Heymsfield, A. Bansemer, P. R. A. Brown, and R. M. Forbes. 2005. Statistical properties of the normalized ice particle size distribution. J. Geophys. Res. 110.D10201, doi:10.1029/2004JD005405.

    • Search Google Scholar
    • Export Citation
  • Donovan, D. P. and A. C. A. P. van Lammeren. 2001. Cloud effective particle size and water content profile retrievals using combined lidar and radar observations. Part 1: Theory and simulations. J. Geophys. Res. 106:2742527448.

    • Search Google Scholar
    • Export Citation
  • Donovan, D. P. Coauthors 2001. Cloud effective particle size and water content profile retrievals using combined lidar and radar observations. Part 2: Comparison with IR radiometer and in-situ measurements of ice clouds. J. Geophys. Res. 106:2744927464.

    • Search Google Scholar
    • Export Citation
  • Eloranta, E. W. 1998. A practical model for the calculation of multiply scattered lidar returns. Appl. Opt. 37:24642472.

  • Flamant, P. H., V. Noël, H. Chepfer, M. Quante, O. Danne, V. Giraud, and J. Pelon. 2000. Particle sizes in cirrus cloud during the Carl’99 campaign: 29 April and 14 May case studies. Extended Abstracts, Int. Radiation Symp., St. Petersburg, Russia, Research Institute of Physics.

  • Francis, P. N. 1999. A summary of the clouds microphysics data collected during CLARE’98 by the UKMO C-130 aircraft. Proc ESTEC Int. Workshop WPP-170, Noordwijk, Netherlands, ESTEC, 13–14.

    • Search Google Scholar
    • Export Citation
  • Francis, P. N., A. Jones, R. W. Saunders, K. P. Shine, A. Slingo, and Z. Sun. 1994. An observational and theoretical study of the radiative properties of cirrus: Some results from ICE’89. Quart. J. Roy. Meteor. Soc. 120:809848.

    • Search Google Scholar
    • Export Citation
  • Francis, P. N., P. Hignett, and A. Macke. 1998. The retrieval of cirrus cloud properties from aircraft multi-spectral reflectance measurements during EUCREX’93. Quart. J. Roy. Meteor. Soc. 124:12731291.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J. and J. L. Parrish. 1978. A computational technique for increasing the effective sample volume of the PMS two-dimensional particle size spectrometer. J. Appl. Meteor. 17:15661571.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, P. R. Field, S. L. Durden, J. L. Stith, J. E. Dye, W. Hall, and C. A. 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. 59:34573491.

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

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., P. N. Francis, H. Flentje, A. Illingworth, M. Quante, and J. Pelon. 2003. Characteristics of mixed-phase clouds. Part 1: Lidar, radar and aircraft observations from CLARE’98. Quart. J. Roy. Meteor. Soc. 129:20892116.

    • Search Google Scholar
    • Export Citation
  • Illingworth, A. J. all CLARE Participants 1999. Overview of the flights and datasets. CLARE’98 Cloud Lidar and Radar Experiment, Proc. ESTEC Int. Workshop WPP-170, Noordwijk, Netherlands, ESTEC, 17–24.

  • Intrieri, J. M., W. L. Eberhard, and G. L. Stephens. 1990. Preliminary comparison of lidar and radar backscatter as a means of assessing cirrus radiative properties. Preprints, Seventh Conf. on Atmospheric Radiation, San Francisco, CA, Amer. Meteor. Soc., 354–356.

  • Intrieri, J. M., G. L. Stephens, W. L. Eberhard, and T. Uttal. 1993. A method for determining cirrus cloud particles sizes using lidar and radar backscatter technique. J. Appl. Meteor. 32:10741082.

    • Search Google Scholar
    • Export Citation
  • Klett, J. D. 1981. Stable analytical inversion solution for processing lidar returns. Appl. Opt. 20:211220.

  • Kumagai, H., H. Horie, H. Kuroiwa, H. Okamoto, and S. Iwasaki. 2000. Retrieval of cloud microphysics using 95-GHz cloud radar and microwave radiometer. Proc. SPIE 4152:364371.

    • Search Google Scholar
    • Export Citation
  • Lhermitte, R. 1987. A 94-GHz doppler radar for cloud observations. J. Atmos. Oceanic Technol. 4:3648.

  • Mace, G. G., T. P. Ackerman, P. Minnis, and D. F. Young. 1998a. Cirrus layer microphysical properties derived from surface-based millimeter radar and infrared interferometer. J. Geophys. Res. 103:2320723216.

    • Search Google Scholar
    • Export Citation
  • Mace, G. G., K. Sassen, S. Kinne, and T. P. Ackermann. 1998b. An examination of cirrus cloud characteristics using data from millimetre wave radar and lidar: The 24 April SUCCESS case study. Geophys. Res. Lett. 25:11331136.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., T. Uttal, J. B. Snider, and R. A. Kropfli. 1992. Estimation of ice clouds parameters from ground-based infrared radiometer and radar measurements. J. Geophys. Res. 97:1156711574.

    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M. and A. J. Heymsfield. 1998. The definition and significance of an effective radius for ice clouds. J. Atmos. Sci. 55:20392052.

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

    • Search Google Scholar
    • Export Citation
  • Okamoto, H., S. Iwasaki, M. Yasui, H. Horie, H. Kuroiva, and H. Kumagai. 2003. An algorithm, for retrieval of cloud microphysics using 95-GHz cloud radar and lidar. J. Geophys. Res. 108.4226, doi:10.1029/2001JD001225.

    • Search Google Scholar
    • Export Citation
  • Paltridge, G. W. 1974. Global cloud cover and earth surface temperature. J. Atmos. Sci. 31:15711576.

  • Pazmany, A. L., R. E. McIntosh, R. D. Kelly, and G. Vali. 1994. An airborne 95 GHz dual polarization radar for cloud studies. IEEE Trans. Geosci. Remote Sens. 1:731739.

    • Search Google Scholar
    • Export Citation
  • Pelon, J. Coauthors 2001. Final report of investigation of cloud by ground-based and airborne radar and lidar (CARL). European Commission DGXII Contract PL970567, 39 pp.

  • Protat, A., C. Tinel, and J. Testud. 2002. Dynamic properties of water and ice clouds from dual-beam airborne cloud radar data: The Carl’2000 and Carl’2001 validation campaigns. Proc. of the 11th Cloud Physics Conf., Ogden, UT, Amer. Meteor. Soc., CD-ROM, P5.18.

  • Riedi, J., M. Doutriaux-Boucher, P. Goloub, and P. Couvert. 2000. Global distribution of cloud top phase from POLDER/ADEOS I. Geophys. Res. Lett. 27:17071710.

    • Search Google Scholar
    • Export Citation
  • Sauvage, L., H. Chepfer, V. Trouillet, P. H. Flamant, G. Brogniez, J. Pelon, and F. Albers. 1999. Remote sensing of cirrus radiative properties during EUCREX’94. Case study of 17 April 1994. Part 1: Observations. Mon. Wea. Rev. 127:504519.

    • Search Google Scholar
    • Export Citation
  • Testud, J., P. Amayenc, X. Dou, and T. Tani. 1996. Tests of rain profiling algorithms for a spaceborne radar using raincell models and real data precipitation fields. J. Atmos. Oceanic Technol. 13:426453.

    • Search Google Scholar
    • Export Citation
  • Testud, J., S. Oury, R. A. Black, P. Amayenc, and X. Dou. 2001. The concept of “normalized” distribution to describe raindrop spectra: A tool for cloud physics and cloud remote sensing. J. Appl. Meteor. 40:11181140.

    • Search Google Scholar
    • Export Citation
  • Tinel, C. 2002. Restitution des propriétés microphysiques et radiatives des nuages froids et mixtes à partir des données du système RALI (Radar-Lidar) (Retrieval of microphysical and radiative parameters of ice and mixed-phased clouds from the RALI system). Ph.D. thesis, University Paris 7, 237 pp.

  • Tinel, C., J. Testud, A. Guyot, and K. Caillault. 2000. Cloud parameter retrieval for combined remote sensing observations. Phys. Chem. Earth 25:10631067.

    • Search Google Scholar
    • Export Citation
  • Uttal, T., R. A. Kropfli, W. L. Ebenhard, and J. M. Intrieri. 1990. Observations of mid-latitude, continental cirrus clouds using a 3.2 cm radar: Comparisons with 10.6 μm lidar observations. Preprints, Seventh Conf. on Atmospheric Radiation, San Francisco, CA, Amer. Meteor. Soc., 349–353.

  • Van de Hulst, H. C. 1957. Light Scattering by Small Particles. John Wiley and Sons, 470 pp.

  • Wang, Z. and K. Sassen. 2002. Cirrus cloud microphysical property retrieval using lidar and radar measurements. Part 1: Algorithm description and comparison with in situ data. J. Appl. Meteor. 41:218229.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 187 91 0
PDF Downloads 122 67 0

The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy

View More View Less
  • a Centre d’études Terrestre et Planétaires, Institut Pierre Simon Laplace, Paris, France
  • | b Service d’Aéronomie, Institut Pierre Simon Laplace, Paris, France
  • | c Department of Meteorology, University of Reading, Reading, United Kingdom
  • | d Centre d’études Terrestre et Planétaires, Institut Pierre Simon Laplace, Paris, France
Restricted access

Abstract

Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

* Current affiliation: Centre National d’études Spatiales, Toulouse, France

Corresponding author address: Claire Tinel, CNES, DCT/SI/MO–BPI 811, 18 av. Edouard Belin, 31401 Toulouse Cedex 9, France. claire.tinel@cnes.fr

Abstract

Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

* Current affiliation: Centre National d’études Spatiales, Toulouse, France

Corresponding author address: Claire Tinel, CNES, DCT/SI/MO–BPI 811, 18 av. Edouard Belin, 31401 Toulouse Cedex 9, France. claire.tinel@cnes.fr

Save