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