NOAA CPC Morphing Method (CMORPH) Global Precipitation Analyses, Version 1.0 (0.25 degree, 3-hourly resolution)
d502003
NOTE: This dataset has been superseded by the NOAA Climate Data Record (CDR) of CMORPH version 1.0, which is available in RDA dataset ds502.2 [https://rda.ucar.edu/datasets/ds502.2/].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 1.0 of the NOAA CPC MORPHing technique (CMORPH) global precipitation analyses covering the period January 1998-present at 0.25 degree, 3-hourly resolution. Version 1.0 comprises reprocessed data using a fixed algorithm with inputs of the same versions. In contrast, CMORPH Version 0.x is generated using an evolving algorithm with inputs of changing versions over the entire data period. The major differences between Versions 1.0 and 0.x are the following: * Version 1.0 covers the entire TRMM/GPM era from January 1998 to the present, while Version 0.x started from December 2002. * Version 1.0 is generated using a fixed algorithm and inputs of fixed versions to ensure best possible homogeneity, while Version 0.x has been produced using an evolving algorithm and inputs of changing versions, and therefore presents substantial inhomogeneities, especially over the earlier years of its operations (2003-2006). * Version 1.0 include the raw, satellite only precipitation estimates as well as bias corrected and gauge-satellite blended precipitation products, while Version 0.x only has the satellite-only products. 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. CMORPH Version 0.x data may be accessed from RDA datasets ds502.0 (data prior to June 2014) and ds502.1 (June 2014-present).
dataset
https://rda.ucar.edu/datasets/d502003/
protocol: https
applicationProfile: browser
name: Dataset Description
description: Related Link
function: information
https://rda.ucar.edu/datasets/d502003/dataaccess/
protocol: https
applicationProfile: browser
name: Data Access
description: Related Link
function: download
climatologyMeteorologyAtmosphere
dataset
revision
2014-10-16
TRMM > Tropical Rainfall Measuring Mission
Aqua > Earth Observing System, Aqua
revision
2024-07-23
EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION RATE
EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION AMOUNT
revision
2024-07-24
-180
180
59.875
-59.875
1998-01-01T00:00:00Z
2017-07-31T21:00:00Z
publication
2018-05-29
daily
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
(303)-497-1217
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
function: downlaod
pointOfContact
2024-08-04T02:11:09Z