Page Summary
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CHIRPS is a 30+ year quasi-global rainfall dataset incorporating satellite imagery and in-situ station data.
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The dataset provides gridded rainfall time series at 0.05° resolution for trend analysis and seasonal drought monitoring.
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The dataset is available from 1981 to 2025 with a cadence of 1 Custom_time_unit.
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The dataset is in the public domain and its use is governed by the specified Terms of Use.
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The dataset includes a precipitation band with values in mm/pentad.
- Dataset Availability
- 1981-01-01T00:00:00Z–2025-11-26T00:00:00Z
- Dataset Provider
- UCSB/CHG
- Cadence
- 1 Custom_time_unit
- Tags
Description
Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring.
Bands
Pixel Size 5566 meters
Bands
| Name | Units | Min | Max | Pixel Size | Description |
|---|---|---|---|---|---|
precipitation
|
mm/pentad | 0* | 1072.43* | meters | Precipitation |
Image Properties
Image Properties
| Name | Type | Description |
|---|---|---|
|
month
|
DOUBLE | Month |
|
pentad
|
DOUBLE | Pentad |
|
year
|
DOUBLE | Year |
Terms of Use
Terms of Use
This datasets are in the public domain. To the extent possible under law, Pete Peterson has waived all copyright and related or neighboring rights to Climate Hazards Center Infrared Precipitation with Stations (CHIRPS).
Citations
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Funk, Chris, Pete Peterson, Martin Landsfeld, Diego Pedreros, James Verdin, Shraddhanand Shukla, Gregory Husak, James Rowland, Laura Harrison, Andrew Hoell & Joel Michaelsen. "The climate hazards infrared precipitation with stations-a new environmental record for monitoring extremes". Scientific Data 2, 150066. doi:10.1038/sdata.2015.66 2015.
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee . ImageCollection ( 'UCSB-CHG/CHIRPS/PENTAD' ) . filter ( ee . Filter . date ( '2018-05-01' , '2018-05-05' )); var precipitation = dataset . select ( 'precipitation' ); var precipitationVis = { min : 0 , max : 112 , palette : [ '001137' , '0aab1e' , 'e7eb05' , 'ff4a2d' , 'e90000' ], }; Map . setCenter ( 17.93 , 7.71 , 2 ); Map . addLayer ( precipitation , precipitationVis , 'Precipitation' );
