Skip to main content
Log in

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

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Austin, R. T., 2007: Level 2B radar-only cloud water content (2BCWC-RO) process description document. CloudSat project report, 24 pp. [Available online at http://www.cloudsat.cira.colostate.edu/ICD/2B-CWC-RO/2B-CWC-ROPD5.1.pdf]

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Rodgers, C. D., 1976: Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation. Rev. Geophys., 14, 609–624.

    Article  Google Scholar 

  • 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.

  • 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.

    Article  Google Scholar 

  • Vidaurre, G., and J. Hallett, 2009: Ice and water content of stratiform mixed-phase cloud. Quar. J. Roy. Meteor. Soc., 135, 1292–1306.

    Article  Google Scholar 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhigang Yao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, L., Li, C., Yao, Z. et al. Application of aircraft observations over Beijing in cloud microphysical property retrievals from CloudSat. Adv. Atmos. Sci. 31, 926–937 (2014). https://doi.org/10.1007/s00376-013-3156-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-013-3156-2

Key words

Navigation