gov.noaa.idp:Global Precipitation Analysis via CMORPH
eng; USA
utf8
dataset
NOAA IDP GIS Support Team
DOC/NOAA/NWS/NCEP/IDP-GIS > National Oceanic & Atmospheric Administration > IDP-GIS
Position Type
9 999-999-9999
City
State
99999
USA
idp.gis.support@noaa.gov
Monday-Friday, 8am-4pm Eastern Time
pointOfContact
2016-05-19T15:40:04+00:00
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
CMORPH Analysis
Global precipitation analysis
2016-01-01
revision
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 IR data. At present we incorporate precipitation estimates 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. With regard
to spatial resolution, although the preciptation estimates are available on a grid with a spacing of 8 km (at the equator), the resolution of the individual satellite-derived estimates is
coarser than that - more on the order of 12 x 15 km or so. The finer "resolution" is obtained via interpolation. In effect, IR data are used as a means to transport the microwave-derived
precipitation features during periods when microwave data are not available at a location. Propagation vector matrices are produced by computing spatial lag correlations on successive images
of geostationary satellite IR which are then used to propagate the microwave derived precipitation estimates. This process governs the movement of the precipitation features only. At a
given location, the shape and intensity of the precipitation features in the intervening half hour periods between microwave scans are determined by performing a time-weighting interpolation
between microwave-derived features that have been propagated forward in time from the previous microwave observation and those that have been propagated backward in time from the following
microwave scan. We refer to this latter step as "morphing" of the features.
How the data should be used
ongoing
Pingping Xie;Robert Joyce
DOC/NOAA/NWS/Climate Prediction Center > National Oceanic & Atmospheric Administration
position here
9 999-999-9999
City
ST
99999
USA
Pingping.Xie@noaa.gov;Robert.Joyce@noaa.gov
Fix next business day, Monday-Friday, 8am-4pm Eastern Time
custodian
atmosphere,united states of america,monitoring,precipitation,meteorological hazards,global precipitation,microwave satellite,infrared,geostationary satellite,climatology,meteorology,natural hazards,environmental impacts,
drought,precipitation,atmospheric phenomena,water management,precipitation anomaly
theme
Geographic keywords
place
eng;USA
climatologyMeteorologyAtmosphere
modeled period
9999-99-99
9999-99-99
Additional information goes here|||||
CMORPH Analysis
9999
publication
Pingping Xie;Robert Joyce
DOC/NOAA/NWS/Climate Prediction Center > National Oceanic & Atmospheric Administration
Pingping.Xie@noaa.gov;Robert.Joyce@noaa.gov
Monday-Friday, 8am-4pm Eastern Time
custodian
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 IR data. At present we incorporate precipitation estimates 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. With regard
to spatial resolution, although the preciptation estimates are available on a grid with a spacing of 8 km (at the equator), the resolution of the individual satellite-derived estimates is
coarser than that - more on the order of 12 x 15 km or so. The finer "resolution" is obtained via interpolation. In effect, IR data are used as a means to transport the microwave-derived
precipitation features during periods when microwave data are not available at a location. Propagation vector matrices are produced by computing spatial lag correlations on successive images
of geostationary satellite IR which are then used to propagate the microwave derived precipitation estimates. This process governs the movement of the precipitation features only. At a
given location, the shape and intensity of the precipitation features in the intervening half hour periods between microwave scans are determined by performing a time-weighting interpolation
between microwave-derived features that have been propagated forward in time from the previous microwave observation and those that have been propagated backward in time from the following
microwave scan. We refer to this latter step as "morphing" of the features.
DATA ANALYSIS AND VISUALIZATION > GEOGRAPHIC INFORMATION SYSTEMS > WEB-BASED GEOGRAPHIC INFORMATION SYSTEMS
DATA MANAGEMENT/DATA HANDLING > DATA SEARCH AND RETRIEVAL
DATA ANALYSIS AND VISUALIZATION > VISUALIZATION/IMAGE PROCESSING
theme
None
None
ArcGIS Map Service
10.2.2
1
-180
180
-60
60
tight
Web Page for the service
N/A
http
Web Browser
Location for the resource page of the service
information
ArcGIS for Server REST endpoint for cached map service
Place to put the URL of the Rest endpoint for the service
http
ArcGIS Map Service
Name of cached map service
General description of Service
information
Dynamic Map Service
https://idpgis.ncep.noaa.gov/arcgis/rest/services/NWS_Climate_Outlooks/cpc_cmorph_dly_025deg/MapServer
http
ArcGIS Map Service
Global Precipitation Analysis via CMORPH
Estimates of precipitation based on satellite measurements of clouds and temperature
information
WMS Get Capabilities
http
Open Geospatial Consortium Web Map Service (WMS)
cpc_cmorph_dly_025deg
Capabilities document for Open Geospatial Consortium compliant Web Map Service
information
WFS Get Capabilities
URL for capabilities document
http
Open Geospatial Consortium Web Feature Service (WFS)
Name of WFS document
Capabilities document for Open Geospatial Consortium compliant Web Feature Service
information
NOAA IDP GIS Support Team
DOC/NOAA/NWS/NCEP/IDP-GIS > National Oceanic & Atmospheric Administration > IDP-GIS
9 999-999-9999
city name
State
99999
USA
idp.gis.support@noaa.gov
http://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/CMORPH_DLY/
http
Download
distributor
zip file; geo-tiffs
9999
http://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/CMORPH_DLY/
http
This ISO metadata record was created using the 'Check and Save to File' (with form validation) function of the GRIIDC ISO 19115-2 Metadata Editor on 2016-05-17T21:49:46+00:00