Data Publications

NOAA CPC Morphing Technique (CMORPH) Global Precipitation Analyses

hasData_Center_Short_Name
  • UCAR/NCAR/CISL/DSS
hasDataset_Online_Resource
hasDataset_Title
  • NOAA CPC Morphing Technique (CMORPH) Global Precipitation Analyses
hasEntry_ID
  • NCAR_DS502.0
hasReference
  • Joyce, R.J., J.E. Janowiak, P.A. Arkin, and P. Xie, 2004: CMORPH: A Method That Produces Global Precipitation Estimates From Data At High Spatial And Temporal Resolution. J. Hydrometeor, 5, 487-503, URL: http://journals.ametsoc.org/doi/abs/10.1175/1525-7541%282004%29005%3C0487:CAMTPG%3E2.0.CO%3B2. Kummerow, C., Y. Hong, W.S. Olson, S. Yang, R.F. Adler, J. McCollum, R. Ferraro, G. Petty, D-B. Shin, and T.T. Wilheit, 2001: The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors. J. Appl. Meteor., 40, 1801-1820, URL: http://journals.ametsoc.org/doi/abs/10.1175/1520-0450%282001%29040%3C1801:TEOTGP%3E2.0.CO%3B2. Ferraro, R.R., F. Weng, N.C. Grody, and L. Zhao, 2000: Precipitation Characteristics Over Land From the NOAA-15 AMSU Sensor. Geophys. Res. Lett., 27(17), 2669-2672 (DOI: 10.1029/2000GL011665), URL: http://www.agu.org/journals/gl/v027/i017/2000GL011665/. Ferraro, R.R., 1997: Special Sensor Microwave Imager Derived Global Rainfall Estimates For Climatological Applications. J. Geophys. Res., 102, 16715-16735 (DOI: 10.1029/97JD01210), URL: http://www.agu.org/journals/jd/v102/iD14/97JD01210/.
hasSummary
  • CMORPH (CPC MORPHing technique) produces global precipitation analyses at very high spatial and temporal resolution. This technique uses precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively, and whose features are transported via spatial propagation information that is obtained entirely from geostationary satellite infrared data. Precipitation estimates are derived from the passive microwaves aboard the DMSP 13, 14 and 15 (SSM/I), the NOAA-15, 16, 17 and 18 (AMSU-B), and AMSR-E and TMI aboard NASA's Aqua and TRMM spacecraft, respectively. These estimates are generated by algorithms of Ferraro (1997) for SSM/I, Ferraro et al. (2000) for AMSU-B and Kummerow et al. (2001) for TMI. Note that this technique is not a precipitation estimation algorithm but a means by which estimates from existing microwave rainfall algorithms can be combined. Therefore, this method is extremely flexible such that any precipitation estimates from any microwave satellite source can be incorporated.
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