Global Probable Maximum Precipitation (PMP) Datasets
| Authors: | |
|---|---|
| Owners: | Kenneth Okechukwu Ekpetere |
| Type: | Resource |
| Storage: | The size of this resource is 359.5 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 Geographic Raster Content Geographic Raster Content Geographic Raster Content Geographic Raster Content Geographic Raster Content Geographic Raster Content Geographic Raster Content Geographic Raster Content |
| Sharing Status: | Public |
|---|---|
| Views: | 1761 |
| Downloads: | 1550 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
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.
Subject Keywords
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: | 01/01/2000 |
|---|---|
| End Date: | 12/31/2023 |
Leaflet Map data © OpenStreetMap contributors
Content
This resource contains links to external content. Linked content is
NOT stored in HydroShare, and we can't guarantee its availability, quality, or
security.
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.
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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