NOAA CPC Morphing Technique (CMORPH) Global Precipitation Analyses Version 0.x

NOTE: This dataset has been superseded by CMORPH version 1.0, which is available in RDA dataset ds502.2 [https://rda.ucar.edu/datasets/ds502.2/]. Users are advised to transition to this updated dataset.

This dataset contains version 0.x of the NOAA CPC MORPHing technique (CMORPH) global precipitation analyses covering the period June 2014-present. Version 0.x comprises the original CMORPH precipitation analyses that CPC has been generating since CMORPH became operational in December 2002, and is generated using an improving algorithm with inputs of evolving versions. Older CMORPH version 0.x data (prior to June 2014) may be accessed from RDA dataset ds502.0 [http://rda.ucar.edu/datasets/ds502.0/].

CMORPH 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.

To Access Resource:

Questions? Email Resource Support Contact:

  • Thomas Cram
    tcram@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  2014-06-01T00:00:00Z
    End:  2023-07-24T21:00:00Z

Keywords

Resource Type dataset
Temporal Range Begin 2014-06-01T00:00:00Z
Temporal Range End 2023-07-24T21:00:00Z
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links

Related Resource #1 : NOAA CPC CMORPH Precipitation Page

Related Resource #2 : CMORPH v0.x data at NOAA/CPC

Additional Information N/A
Resource Format NCEP_CPC_CMORPH025 (Binary)
NetCDF (Binary)
Standardized Resource Format NetCDF
Binary
Asset Size 5206 MB
Legal Constraints

Use of this dataset is subject to UCAR's Terms of Use, except that commercial use is generally not prohibited.


Access Constraints Registration on the RDA web site is a requirement for access to the data.
Software Implementation Language N/A

Resource Support Name Thomas Cram
Resource Support Email tcram@ucar.edu
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email rdahelp@ucar.edu
Metadata Contact Organization NCAR Research Data Archive

Author Climate Prediction Center, National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2015-01-06
Digital Object Identifier (DOI) https://doi.org/10.5065/D60R9MF6
Alternate Identifier ds502.1
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress onGoing
Metadata Date 2024-01-03T15:11:43-07:00
Metadata Record Identifier edu.ucar.rda::ds502.1
Metadata Language eng; USA
Suggested Citation Climate Prediction Center, National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce. (2015). NOAA CPC Morphing Technique (CMORPH) Global Precipitation Analyses Version 0.x. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/D60R9MF6. Accessed 24 April 2024.

Harvest Source