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Global Probable Maximum Precipitation (PMP) Datasets

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Owners:		This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type:	Resource
Storage:	The size of this resource is 323.5 MB
Created:	May 04, 2022 at 2:19 a.m.
Last updated:	Oct 13, 2023 at 3:48 p.m.
Citation:	See how to cite this resource
Content types:	Geographic Raster Content

Sharing Status:	Public
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Downloads:	1391
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Abstract

The Probable Maximum Precipitation (PMP) Datasets in Geotiff format at the 0.5-hr, 1-hr, 2-hr, 3-hr, 6-hr, 12-hr, 24-hr, 2-day, and 3-day are statistically derived based on World Meteorological Organization (WMO)’s endorsed Hershfield PMP estimation technique using IMERG’s 30-min precipitation dataset. The Google Earth Engine’s script for assessing and interacting with the datasets is also provided.

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Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

Place/Area Name:

Semi Global

North Latitude

75.0992°

East Longitude

179.4475°

South Latitude

-56.2256°

West Longitude

-179.2498°

Temporal

Start Date:
End Date:

Content

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Data Services

The following web services are available for data contained in this resource. Geospatial Feature and Raster data are made available via Open Geospatial Consortium Web Services. The provided links can be copied and pasted into GIS software to access these data. Multidimensional NetCDF data are made available via a THREDDS Data Server using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to support additional data types.

Web Map Service

https://geoserver.hydroshare.org/geoserver/HS-9bed05f68ad444e8ad371d9db001007a/wms?request=GetCapabilities

Web Coverage Service

https://geoserver.hydroshare.org/geoserver/HS-9bed05f68ad444e8ad371d9db001007a/wcs?request=GetCapabilities

Credits

Funding Agencies

This resource was created using funding from the following sources:

Agency Name	Award Title	Award Number
Kansas Applied Remote Sensing (KARS)

How to Cite

Ekpetere, K., J. Coll, X. Li, J. Kastens, D. B. Mechem (2023). Global Probable Maximum Precipitation (PMP) Datasets, HydroShare, http://www.hydroshare.org/resource/9bed05f68ad444e8ad371d9db001007a

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/

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