CLOUDSAT Reflectivity Product


Yuying Zhang (LLNL) and Roger Marchand (UW)



Launched in late April 2006,CloudSat ( is orbiting in formation with other NASA spacecraft in the A-Train, and the orbit is Sun synchronous with the overpass occurring around 0130/1330 local time. The 94-GHz nadir-looking radar on CloudSat, with the estimated minimum detectable signal of -30 dBZ (at the start of the missing and now approaching -25 dBZ), probes the vertical structure of clouds and precipitation simultaneously within a 1.4 km across-track by 1.8 km along-track footprint. The radar has a range resolution of approximately 480 m, and the return power is oversampled for a range gate spacing of 240 m.

The CloudSat Reflectivity Data are generated from the Level 2 GEOPROF product (Mace et al., 2008; Marchand et al., 2008; by the efforts from Dr. Yuying Zhang at LLNL and Dr. Roger Marchand at UW. The CFAD data are on a 2degree-by-2degree lat-lon grid with a 480m vertical resolution consistent with the COSP outputs. Similar to COSP, the dBZ values are binned by each 5 dBZ in the range of -50 dBZ to 25 dBZ. Regarding the CloudSat radar detection threshold, the radar has a good detection with radar reflectivity larger than -25 dBZe, and the data between -25 dBZe and -30 dBZe can also be used with caution since in principal the values in this dBZ bin should be biased low. In order to take ground contamination and topography into account, we also provide missing data fraction. Please refer to the Quality Statement (CloudSat_CFAD_dataset_quality_statement.pdf) for a more detailed description of this data product. Monthly mean data from June 2006 through November 2010 are provided with one data file per year. The CloudSat data product contains four types of data files:

  • cfadDbze94(time,dbze,alt40,latitude,longitude) ---- Joint Histogram of Equivalent Reflectivity factor and Height above sea level
  • clt_cloudsat(time,latitude,longitude) ---- Total Cloud Coverage seen by CloudSat
  • overpasses(time,latitude,longitude) ---- Number of CloudSat profiles collected in each lat/lon gridbox for the statistics
  • missingdatafraction(time,alt40,latitude,longitude) ---- Missing data fraction due to the effects of ground clutter and surface elevation
  • Note that the monthly mean data are created only based on a limited number of samples since the ground track repeats every 16 days. Furthermore, the CloudSat radar only generates a curtain or two-dimensional cross section through the atmosphere as the satellite moves along its orbital trajectory. Therefore multi-year seasonal mean is recommended because it provides a better representation of cloud statistics. The multi-year seasonal mean can be easily calculated from the monthly data and the radar overpass numbers should be used to weight the mean calculations.



    - Zhang , Y., S. A. Klein, J. Boyle, and G. G. Mace, 2010: Evaluation of tropical cloud and precipitation statistics of Community Atmosphere Model version 3 using CloudSat and CALIPSO data, J. Geophys. Res., 115, D12205, doi:10.1029/2009JD012006.

    - Marchand, R. T., J. Haynes, G.G. Mace, T.Ackerman, G.Stephens, "A comparison of simulated cloud radar output from the multiscalemodeling framework global climate model with CloudSat cloud radar observations", JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114, D00A20, doi:10.1029/2008JD009790, 2009.

    - Marchand, R. T., G. G. Mace, and T. P. Ackerman, 2008: Hydrometeor detection using CloudSat-an earth orbiting 94 GHz cloud radar. J. Atmos. Oceanic. Technol., 25, 519-533, doi: 10.1175/2007JTECHA1006.1.

    - Mace, G. G., et al., 2009: A description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data, J. Geophys. Res., 114, D00A26.


    Exemple of plot:



    Ftp CMOR data access: CloudSat_Reflectivity CMOR


    Matlab routine: CloudSat.m



    Please contact Dr. Yuying Zhang and Roger Marchand if you have any question or comments about CloudSat dataset.



    Thanks are due to Dr. Jay Mace (UU) for providing the Level 2 GEOPROF product and Dr. Steve Klein (LLNL) for his very valuable comments and suggestions to this product.