Advances in Atmospheric Sciences

, Volume 31, Issue 4, pp 926–937 | Cite as

Application of aircraft observations over Beijing in cloud microphysical property retrievals from CloudSat

  • Lei Wang
  • Chengcai Li
  • Zhigang Yao
  • Zengliang Zhao
  • Zhigang Han
  • Qiang Wei


Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure. The cloud lognormal size distributions derived from 12 flights over Beijing, China, in 2008–09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals. We present the distribution parameters of stratiform cloud droplet (diameter <500 μm and <1500 μm) and discuss the effect of large particles on distribution parameter fitting. Based on three retrieval schemes with different lognormal size distribution parameters, the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations. The results showed that the liquid water content (LWC) retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006. We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009. The CloudSat cloud water path (CWP) retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) data. The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP. These results strongly suggest that it is necessary to consider particles with diameters greater than 50 μm in CloudSat LWC retrievals.

Key words

CloudSat liquid water content a priori data aircraft observations 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Austin, R. T., 2007: Level 2B radar-only cloud water content (2BCWC-RO) process description document. CloudSat project report, 24 pp. [Available online at]Google Scholar
  2. Austin, R. T., and G. L. Stephens, 2001: Retrieval of stratus cloud microphysical parameters using millimeter-wave radar and visible optical depth in preparation for CloudSat: 1. Algorithm formulation. J. Geophysi. Res., 106(D22), 2 8233–28242.CrossRefGoogle Scholar
  3. Austin, R. T., A. J. Heymsfield, and G. L. Stephens, 2009: Retrieval of ice cloud microphysical parameters using the Cloud-Sat millimeter-wave radar and temperature. J. Geophys. Res., 114, D00A23, doi: 10.1029/2008jd010049.Google Scholar
  4. Barker, H. W., A. V. Korolev, D. R. Hudak, J. W. Strapp, K. B. Strawbridge, and M. Wolde, 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, doi: 10.1029/2008JD009971.Google Scholar
  5. Brunke, M. A., S. P. de Szoeke, P. Zuidema, and X. Zeng, 2010: A comparisons of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck. Atmos. Chem. Phys., 10, 6527–6536.CrossRefGoogle Scholar
  6. Cober, S. G., G. A. Isaac, and J. W. Strapp, 2001: Characterizations of aircraft icing environments that include supercooled large drops. J. Appl. Meteor., 40, 1984–2002.CrossRefGoogle Scholar
  7. Comstock, K. K., R. Wood, S. E. Yuter, and C. S. Bretherton, 2004: Reflectivity and rain rate in and below drizzling stratocumulus. Quart. J. Roy. Meteor. Soc., 130, 2891–2918.CrossRefGoogle Scholar
  8. de La Torre Juárez, M., B. Kahn, and E. Fetzer, 2009: Cloud-type dependencies of MODIS and AMSR-E liquid water path differences. Atmospheric Chemistry And Physics Discussions, 9, 3367–3399.CrossRefGoogle Scholar
  9. Dong, X. Q., P. Minnis, B. Xi, S. Sun-Mack, and Y. Chen, 2008: Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site. J. Geophys. Res., 113, doi: 10.1029/2007JD008438.Google Scholar
  10. Feng, W. W., Z. G. Yao, Z. G. Han, and Z. L. Zhao, 2009: Simulation analysis on microphysical parameters retrieval of liquid water clouds with satellite-based millimeter-wave radar. Journal of PLA University of Science and Technology: Natural Science Edition, 10, 95–102. (in Chinese)Google Scholar
  11. Guo, X. L., D. H. Fu, and Z. X. Hu, 2013: Progress in cloud physics, precipitation, and weather modification during 2008–2012. Chinese J. Atmos. Sci., 37, 351–363. (in Chinese)Google Scholar
  12. Kahn, B. H., and Coauthors, 2008: Cloud type comparisons of AIRS, CloudSat, and CALIPSO cloud height and amount. Atmospheric Chemistry and Physics, 8, 1231–1248.CrossRefGoogle Scholar
  13. Knollenberg, R. G., 1976: Three new instruments for cloud physics measurements: The 2-D spectrometer, the forward scattering spectrometer probe, and the active scattering aerosol spectrometer. Intel. Conf. on Cloud Physics, American Meteorological Society, July 1976, 554–561.Google Scholar
  14. Li, J. L. F., and Coauthors, 2008: Comparisons of satellites liquid water estimates to ECMWF and GMAO analyses, 20th century IPCC AR4 climate simulations, and GCM simulations. Geophys. Res. Lett., 35, doi: 10.1029/2008GL035427.Google Scholar
  15. Matrosov, S. Y., T. Uttal, and D. A. Hazen, 2004: Evaluation of radar reflectivity-based estimates of water content in stratiform marine clouds. J. Appl. Meteor., 43, 405–419.CrossRefGoogle Scholar
  16. Miles, N. L., J. Verlinde, and E. E. Clothiaux, 2000: Cloud droplet size distributions in low-level stratiform clouds. J. Atmos. Sci., 57, 295–311.CrossRefGoogle Scholar
  17. Morrison, H., and A. Gettelman, 2008: A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, version 3 (CAM3). Part I: Description and numerical tests. J. Climate, 21, 3642–3659.CrossRefGoogle Scholar
  18. Noh, Y. J., C. J. Seaman, T. H. Vonder Haar, D. R. Hudak, and P. Rodriguez, 2011: Comparisons and analyses of aircraft and satellite observations for wintertime mixed-phase clouds. J. Geophys. Res., 116, doi: 10.1029/2010JD015420.Google Scholar
  19. Partain, P., 2007: Cloudsat MODIS-AUX auxiliary data process description and interface control document. Cooperative Institute for Research in the Atmosphere, Colorado State University, 23 pp.Google Scholar
  20. Peng, J., H. Zhang, and X. Y. Shen, 2013: Analysis of vertical structure of clouds in East Asia with cloudSat data. Chinese J. Atmos. Sci., 37, 91–100. (in Chinese)Google Scholar
  21. Platnick, S., M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum, J. C. Riedi, and R. A. Frey, 2003: The MODIS cloud products: algorithms and examples from terra. IEEE Transactions on Geoscience and Remote Sensing, 41, 459–473.CrossRefGoogle Scholar
  22. Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science, 243, 57–63.CrossRefGoogle Scholar
  23. Rodgers, C. D., 1976: Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation. Rev. Geophys., 14, 609–624.CrossRefGoogle Scholar
  24. Seethala, C., and Á. Horváth, 2010: Global assessment of AMSRE and MODIS cloud liquid water path retrievals in warm oceanic clouds. J. Geophys. Res., 115, doi: 10.1029/2009JD012662.Google Scholar
  25. 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, 1771–1790.CrossRefGoogle Scholar
  26. Vidaurre, G., and J. Hallett, 2009: Ice and water content of stratiform mixed-phase cloud. Quar. J. Roy. Meteor. Soc., 135, 1292–1306.CrossRefGoogle Scholar
  27. Wang, L., C. C. Li, Z. L. Zhao, Z. G. Yao, Z. G. Han, and Q. Wei, 2014: The Application of the 2D habit classification in cloud microphysics analysis. Chinese J. Atmos. Sci., 38(2), 201–202. (in Chinese)Google Scholar
  28. Wang, S. H., Z. G. Han, Z. G. Yao, Z. L. Zhao, and X. Jie, 2011: Analysis on Cloud vertical structure over China and its neighborhood based on cloudSat data. Plateau Meteorology, 30, 38–52. (in Chinese)Google Scholar
  29. Wang, Y. F., H. C. Lei, Y. X. Wu, W. A. Xiao, and X. Q. Zhang, 2005: Size distributions of the water drops in the warm layer of stratiform clouds in Yanan. Journal of Nanjing Insitute of Meteorology, 28, 787–793. (in Chinese)Google Scholar
  30. Yan, C. F., and W. K. Chen, 1990: The stratus cloud droplet number/size distributions and spectral parameters calculation. J. Appl. Meteor., 1, 352–359. (in Chinese)Google Scholar
  31. Yang, D. S., and P. C. Wang, 2012: Tempo-spatial distribution characteristics of cloud particle size over China during Summer. Climatic and Environmental Research, 17, 433–443. (in Chinese)Google Scholar
  32. Zhao, Z. L., J. T. Mao, Q. Wei, Y. J. Ying, L. Wang, Z. G. Han, and C. C. Li, 2010: A study of vertical structure of spring stratiform clouds in Northwest China. Meteorological Monthly, 36, 71–77. (in Chinese)Google Scholar

Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Lei Wang
    • 1
  • Chengcai Li
    • 1
  • Zhigang Yao
    • 2
  • Zengliang Zhao
    • 2
  • Zhigang Han
    • 2
  • Qiang Wei
    • 2
  1. 1.Department of Atmospheric and Oceanic Sciences, School of PhysicsPeking UniversityBeijingChina
  2. 2.Beijing Institute of Applied MeteorologyBeijingChina

Personalised recommendations