The Evaluation of CloudSat and CALIPSO Ice Microphysical Products Using Ground-Based Cloud Radar and Lidar Observations

A. Protat Centre for Australian Weather and Climate Research, Melbourne, Victoria, Australia, and Laboratoire Atmosphère, Milieux, et Observations Spatiales (LATMOS), Vélizy, France

Search for other papers by A. Protat in
Current site
Google Scholar
PubMed
Close
,
J. Delanoë University of Reading, Reading, United Kingdom

Search for other papers by J. Delanoë in
Current site
Google Scholar
PubMed
Close
,
E. J. O’Connor University of Reading, Reading, United Kingdom

Search for other papers by E. J. O’Connor in
Current site
Google Scholar
PubMed
Close
, and
T. S. L’Ecuyer Colorado State University, Fort Collins, Colorado

Search for other papers by T. S. L’Ecuyer in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

Corresponding author address: Alain Protat, Centre for Australian Weather and Climate Research, 700 Collins St., Docklands, Melbourne, VIC 3008, Australia. Email: a.protat@bom.gov.au

Abstract

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

Corresponding author address: Alain Protat, Centre for Australian Weather and Climate Research, 700 Collins St., Docklands, Melbourne, VIC 3008, Australia. Email: a.protat@bom.gov.au

Save
  • Austin, R. T., and Stephens G. L. , 2001: Retrieval of stratus cloud microphysical parameters using millimeter-wave radar and visible optical depth in preparation for CloudSat. 1. Algorithm formulation. J. Geophys. Res., 106 , 2823328242.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Austin, R. T., Heymsfield A. J. , and Stephens G. L. , 2009: Retrieval of ice cloud microphysical parameters using the CloudSat millimeter wave radar and temperature. J. Geophys. Res., 114 , D00A23. doi:10.1029/2008JD010049.

    • Search Google Scholar
    • Export Citation
  • Barker, H. W., Korolev A. V. , Hudak D. R. , Strapp J. W. , Strawbridge K. B. , and Wolde M. , 2008: A comparison between CloudSat and aircraft data for a multilayer, mixed phase cloud system during the Canadian CloudSat-CALIPSO Validation Project. J. Geophys. Res., 113 , D00A16. doi:10.1029/2008JD009971.

    • Search Google Scholar
    • Export Citation
  • Benedetti, A., Stephens G. L. , and Haynes J. M. , 2003: Ice cloud microphysics retrievals from millimeter radar and visible optical depth using an estimation theory approach. J. Geophys. Res., 108 , 4335. doi:10.1029/2002JD002693.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bodas-Salcedo, A., Webb M. J. , Brooks M. E. , Ringer M. A. , Williams K. D. , Milton S. F. , and Wilson D. R. , 2008: Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities. J. Geophys. Res., 113 , D00A13. doi:10.1029/2007JD009620.

    • Search Google Scholar
    • Export Citation
  • Bony, S., and Coauthors, 2006: How well do we understand and evaluate climate change feedback processes? J. Climate, 19 , 34453482.

  • Brown, P. R. A., and Francis P. N. , 1995: Improved measurements of the ice water content in cirrus using a total-water probe. J. Atmos. Oceanic Technol., 12 , 410414.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Comstock, J. M., Ackerman T. P. , and Mace G. G. , 2002: Ground-based lidar and radar remote sensing of tropical cirrus clouds at Nauru Island: Cloud statistics and radiative impacts. J. Geophys. Res., 107 , 4714. doi:10.1029/2002JD002203.

    • Search Google Scholar
    • Export Citation
  • Delanoë, J., and Hogan R. J. , 2008: A variational scheme for retrieving ice cloud properties from combined radar, lidar and infrared radiometer. J. Geophys. Res., 113 , D07204. doi:10.1029/2007JD009000.

    • Search Google Scholar
    • Export Citation
  • Delanoë, J., and Hogan R. J. , 2010: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds. J. Geophys. Res., in press.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delanoë, J., Protat A. , Bouniol D. , Heymsfield A. , Bansemer A. , and Brown P. , 2007: The characterization of ice cloud properties from doppler radar measurements. J. Appl. Meteor. Climatol., 46 , 16821698.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dufresne, J-L., and Bony S. , 2008: An assessment of the primary sources of spread of global warming estimates from coupled atmosphere–ocean models. J. Climate, 21 , 51355144.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., 2007: On measurements of small ice particles in clouds. Geophys. Res. Lett., 34 , L23812. doi:10.1029/2007GL030951.

  • Heymsfield, A. J., and Miloshevich L. M. , 2003: Parameterizations for the cross-sectional area and extinction of cirrus and stratiform ice cloud particles. J. Atmos. Sci., 60 , 936956.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., Bansemer A. , Field P. R. , Durden S. L. , Stith J. , Dye J. E. , Hall W. , and Grainger T. , 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., Winker D. , and van Zadelhoff G-J. , 2005: Extinction-ice water content-effective radius algorithms for CALIPSO. Geophys. Res. Lett., 32 , L10807. doi:10.1029/2005GL022742.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and Coauthors, 2008: Testing IWC retrieval methods using radar and ancillary measurements with in situ data. J. Appl. Meteor. Climatol., 47 , 135163.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., 2006: Fast approximate calculation of multiply scattered lidar returns. Appl. Opt., 45 , 59845992.

  • Hogan, R. J., and Illingworth A. J. , 2003: Parameterizing ice cloud inhomogeneity and the overlap of inhomogeneities using cloud radar data. J. Atmos. Sci., 60 , 756767.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., Donovan D. P. , Tinel C. , Brooks M. A. , Illingworth A. J. , and Poiares Baptista J. P. V. , 2006a: Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds. J. Atmos. Oceanic Technol., 23 , 211227.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., Mittermaier M. P. , and Illingworth A. J. , 2006b: The retrieval of ice water content from radar reflectivity factor and temperature and its use in the evaluation of a mesoscale model. J. Appl. Meteor. Climatol., 45 , 301317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Illingworth, A. J., and Coauthors, 2007: CLOUDNET—Continuous evaluation of cloud profiles in seven operational models using ground-based observations. Bull. Amer. Meteor. Soc., 88 , 883898.

    • Search Google Scholar
    • Export Citation
  • L’Ecuyer, T. S., Wood N. B. , Haladay T. , Stephens G. L. , and Stackhouse P. W. Jr., 2008: Impact of clouds on atmospheric heating based on the R04 CloudSat fluxes and heating rates data set. J. Geophys. Res., 113 , D00A15. doi:10.1029/2008JD009951.

    • Search Google Scholar
    • Export Citation
  • Liu, C. L., and Illingworth A. J. , 2000: Toward more accurate retrievals of ice water content from radar measurement of clouds. J. Appl. Meteor., 39 , 11301146.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mace, G. G., Heymsfield A. J. , and Poellot M. , 2002: On retrieving the microphysical properties of cirrus clouds using the moments of the millimetre-wavelength Doppler spectrum. J. Geophys. Res., 107 , 4815. doi:10.1029/2001JD001308.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mace, G. G., Benson S. , and Vernon E. , 2006: Cirrus clouds and the large-scale atmospheric state: Relationships revealed by six years of ground-based data. J. Climate, 19 , 32573278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., Korolev A. V. , and Heymsfield A. J. , 2002: Profiling cloud ice mass and particle characteristic size from Doppler radar measurements. J. Atmos. Oceanic Technol., 19 , 10031018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., Um J. , Freer M. , Baumgardner D. , Kok G. L. , and Mace G. , 2007: Importance of small ice crystals to cirrus properties: Observations from the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Geophys. Res. Lett., 34 , L13803. doi:10.1029/2007GL029865.

    • Search Google Scholar
    • Export Citation
  • Okamoto, H., Iwasaki S. , Yasui M. , Horie H. , Kuroiwa H. , and Kumagai H. , 2003: An algorithm for retrieval of cloud microphysics using 95-GHz cloud radar and lidar. J. Geophys. Res., 108 , 4226. doi:10.1029/2001JD001225.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Potter, G. L., and Cess R. D. , 2004: Testing the impact of clouds on the radiation budgets of 19 atmospheric general circulation models. J. Geophys. Res., 109 , D02106. doi:10.1029/2003JD004018.

    • Search Google Scholar
    • Export Citation
  • Protat, A., Armstrong A. , Haeffelin M. , Morille Y. , Pelon J. , Delanoë J. , and Bouniol D. , 2006: Impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA. Geophys. Res. Lett., 33 , L11805. doi:10.1029/2005GL025340.

    • Search Google Scholar
    • Export Citation
  • Protat, A., Delanoë J. , Bouniol D. , Heymsfield A. J. , Bansemer A. , and Brown P. , 2007: Evaluation of ice water content retrievals from cloud radar reflectivity and temperature using a large airborne in situ microphysical database. J. Appl. Meteor. Climatol., 46 , 557572.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Protat, A., and Coauthors, 2009: Assessment of CloudSat reflectivity measurements and ice cloud properties using ground-based and airborne cloud radar observations. J. Atmos. Oceanic Technol., 26 , 17171741.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Protat, A., Delanoë J. , Plana-Fattori A. , May P. T. , and O’Connor E. J. , 2010: The statistical properties of tropical ice clouds generated by the West African and Australian monsoons, from ground-based radar-lidar observations. Quart. J. Roy. Meteor. Soc., 136 , 345363. doi:10.1002/qj.490.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sassen, K., and Cho B. S. , 1992: Subvisual-thin cirrus lidar dataset for satellite verification and climatological research. J. Appl. Meteor., 31 , 12751285.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sassen, K., Wang Z. , and Liu D. , 2008: Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements. J. Geophys. Res., 113 , D00A12. doi:10.1029/2008JD009972.

    • Search Google Scholar
    • Export Citation
  • Sato, K., and Okamoto H. , 2006: Characterization of Ze and LDR of nonspherical and inhomogeneous ice particles for 95-GHz cloud radar: Its implication to microphysical retrievals. J. Geophys. Res., 111 , D22213. doi:10.1029/2005JD006959.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., Tsay S-C. , Stackhouse P. W. , and Flatau P. J. , 1990: The relevance of the microphysical and radiative properties of cirrus clouds to climate and climatic feedback. J. Atmos. Sci., 47 , 17421754.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and Coauthors, 2002: The CloudSat mission and the A train: A new dimension of space-based observations of clouds and precipitation. Bull. Amer. Meteor. Soc., 83 , 17711790.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and Coauthors, 2008: CloudSat mission: Performance and early science after the first year of operation. J. Geophys. Res., 113 , D00A18. doi:10.1029/2008JD009982.

    • Search Google Scholar
    • Export Citation
  • Stith, J. L., Dye J. E. , Bansemer A. , Heymsfield A. J. , Grainger C. A. , Petersen W. A. , and Cifelli R. , 2002: Microphysical observations of tropical clouds. J. Appl. Meteor., 41 , 97117.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stith, J. L., Haggerty J. A. , Heymsfield A. , and Grainger C. A. , 2004: Microphysical characteristics of tropical updrafts in clean conditions. J. Appl. Meteor., 43 , 779794.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stokes, G. M., and Schwartz S. E. , 1994: The Atmospheric Radiation Measurement (ARM) program: Programmatic background and design of the cloud and radiation test bed. Bull. Amer. Meteor. Soc., 75 , 12011221.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tanelli, S., Durden S. L. , Im E. , Pak K. S. , Reinke D. G. , Partain P. , Haynes J. M. , and Marchand R. T. , 2008: CloudSat’s cloud profiling radar after 2 years in orbit: Performance, external calibration, and processing. Geoscience and Remote Sensing. IEEE Trans. Geosci. Remote Sens., 46 , 35603573.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tinel, C., Testud J. , Pelon J. , Hogan R. J. , Protat A. , Delanoë J. , and Bouniol D. , 2005: The retrieval of ice-cloud properties from cloud radar and lidar synergy. J. Appl. Meteor., 44 , 860875.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Waliser, D., and Coauthors, 2009: Cloud ice: A climate model challenge with signs and expectations of progress. J. Geophys. Res., 114 , D00A21. doi:10.1029/2008JD010015.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woods, C. P., Waliser D. E. , Li J-L. , Austin R. T. , Stephens G. L. , and Vane D. G. , 2008: Evaluating CloudSat ice water content retrievals using a cloud-resolving model: Sensitivities to frozen particle properties. J. Geophys. Res., 113 , D00A11. doi:10.1029/2008JD009941.

    • Search Google Scholar
    • Export Citation
  • Wu, D. L., and Coauthors, 2009: Comparisons of global cloud ice from MLS, CloudSat, and correlative data sets. J. Geophys. Res., 114 , D00A24. doi:10.1029/2008JD009946.

    • Search Google Scholar
    • Export Citation
  • Young, S. A., and Vaughan M. A. , 2009: The retrieval of profiles of particulate extinction from Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) data: Algorithm description. J. Atmos. Oceanic Technol., 26 , 11051119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuter, S. E., and Houze R. A. Jr., 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon. Wea. Rev., 123 , 19411963.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 640 323 31
PDF Downloads 299 88 1