Overview
Total precipitation (PTOT) from the CHIRPS v3.0 monthly Africa product, delivered as per-pixel monthly Cloud Optimized GeoTIFFs and per-year rolling 3-month (seasonal) sums, 1981 to present. The monthly files hold the same values as CHIRPS on the same 0.05° grid, with the -9999 sentinel masked and overviews added. The seasonal sums cover the twelve rolling tri-month windows (JFM, FMA, …, DJF) and are derived from the monthly files.
Important note
Seasonal windows are labelled by the calendar year in which the window ends (DJF_2020 = Dec 2019 to Feb 2020). Edge windows that the record cannot cover in full are absent (NDJ and DJF 1981; windows ending after the latest monthly file).
Quick start
import rioxarray
url = "https://digital-atlas.s3.amazonaws.com/domain=climate/type=observational/source=chirps-chirts-era5/region=africa/processing=monthly/variable=PTOT/PTOT-1981-01.tif"
da = rioxarray.open_rasterio(url, masked=True)library(terra)
url <- "/vsicurl/https://digital-atlas.s3.amazonaws.com/domain=climate/type=observational/source=chirps-chirts-era5/region=africa/processing=monthly/variable=PTOT/PTOT-1981-01.tif"
r <- rast(url)Intended uses
- monthly and seasonal rainfall totals and anomalies over Africa
- comparing seasonal rainfall across ENSO phases or analogue years
- rainfall context for drought, vegetation and flood indicators
Not recommended for
Why: Only monthly totals and 3-month sums are published here.
Use instead: The CHIRPS v3 daily archive (catalog record chirps-v3-daily).
Access & use
Files, endpoints, and worked examples for each distribution.
Data
Per-pixel monthly precipitation totals, one COG per month.
Format: Cloud-Optimized GeoTIFF — best for single-file downloads, visualisation, and traditional GIS tools
List of files 544 filesDownload CSV
Individual file
https://digital-atlas.s3.amazonaws.com/domain=climate/type=observational/source=chirps-chirts-era5/region=africa/processing=monthly/variable=PTOT/PTOT-1981-01.tif
Usage examples
import rioxarray
url = "https://digital-atlas.s3.amazonaws.com/domain=climate/type=observational/source=chirps-chirts-era5/region=africa/processing=monthly/variable=PTOT/PTOT-1981-01.tif"
da = rioxarray.open_rasterio(url, masked=True)
# Clip a window (East Africa)
window = da.rio.clip_box(
minx=28, miny=-12, maxx=52, maxy=18
)
# ...or sample a single point
point = da.sel(x=36.8, y=-1.3, method="nearest")library(terra)
url <- "/vsicurl/https://digital-atlas.s3.amazonaws.com/domain=climate/type=observational/source=chirps-chirts-era5/region=africa/processing=monthly/variable=PTOT/PTOT-1981-01.tif"
r <- rast(url)
# Clip a window (East Africa)
window <- crop(r, ext(28, 52, -12, 18))
# ...or sample a single point
point <- extract(r, cbind(36.8, -1.3))Other access methods
File pattern: variable={variable}/{variable}-{time}.tif
Per-year rolling 3-month precipitation sums, one COG per season x year.
Format: Cloud-Optimized GeoTIFF — best for single-file downloads, visualisation, and traditional GIS tools
File indexes
CDH inventoryhttps://raw.githubusercontent.com/CGIAR-Climate-Data-Hub/cdh-catalog/main/records/africa-precipitation-monthly-seasonal/seasonal-files.csvDownload
Seasonal file inventory
| variable | season | year | href |
|---|---|---|---|
| PTOT | JFM | 1981 | PTOT_JFM_1981_sum.tif |
| PTOT | FMA | 1981 | PTOT_FMA_1981_sum.tif |
| PTOT | MAM | 1981 | PTOT_MAM_1981_sum.tif |
| PTOT | AMJ | 1981 | PTOT_AMJ_1981_sum.tif |
| PTOT | MJJ | 1981 | PTOT_MJJ_1981_sum.tif |
First 5 files of the list
Usage examples
import pandas as pd
# One row per file: href (its full URL) and its value on each dimension
files = pd.read_csv("https://raw.githubusercontent.com/CGIAR-Climate-Data-Hub/cdh-catalog/main/records/africa-precipitation-monthly-seasonal/seasonal-files.csv")# One row per file: href (its full URL) and its value on each dimension
files <- read.csv("https://raw.githubusercontent.com/CGIAR-Climate-Data-Hub/cdh-catalog/main/records/africa-precipitation-monthly-seasonal/seasonal-files.csv")# One row per file: href (its full URL) and its value on each dimension
curl -s "https://raw.githubusercontent.com/CGIAR-Climate-Data-Hub/cdh-catalog/main/records/africa-precipitation-monthly-seasonal/seasonal-files.csv" | headOther access methods
Data dictionary
What each file holds. A layout describes how the data is stored in a file: its variables, the dimensions they vary over, and any keys.
File layouts
In every file
Variables
| Variable | Type | Unit | Description |
|---|---|---|---|
| PTOT | float32 | mm | Total precipitation over the period (calendar month, or 3-month seasonal sum). |
Dimensions
0.05 deg (~5.5 km, CHIRPS native).
Grid spacing: 0.05 degree
Only in monthly
Dimensions
Month of the monthly totals (YYYY-MM); the {time} token of the monthly asset.
Range: 1981-01 – 2026-04, monthly
Only in seasonal
Dimensions
Rolling 3-month window named by the initials of its months (JFM = Jan-Mar ... DJF = Dec-Feb). Each value covers three months; NDJ and DJF span the year boundary and are labelled by the year in which they end.
JFMFMAMAMAMJMJJJJAJASASOSONONDNDJDJF
Year in which a seasonal window ends.
Range: 1981 – 2026, annual
Technical metadata
The full spatial, temporal, and modeling detail behind the summaries elsewhere on this page.
Spatial
- CRS
- EPSG:4326
- Extent (W S E N)
- [-20, -40, 55, 40]
- Coverage
- Africa
- Grid spacing
- 3 arc-minutes (~5.6 km at the equator)
Temporal
- Start
- 1981-01
- End
- open (present)
Provenance
Ordered processing steps, from source to publication.
- source
CHIRPS v3.0 monthly precipitation totals, Africa window (station + infrared blend).
- monthly-cog
Each monthly GeoTIFF rewritten as a COG with internal overviews, -9999 masked to NaN. Same grid and values as the source.
- seasonal-sum
Per-year tri-month sums over the twelve seasonal windows, written as COGs with overviews.
How to cite
Please cite the dataset and any associated peer-reviewed publications.
P. Steward, C. Funk, P. Peterson, M. Landsfeld (2026) Monthly and seasonal precipitation from CHIRPS v3 (Africa), Africa Agriculture Adaptation Atlas. Version 1. Alliance of Bioversity International and CIAT. Accessed through the CGIAR Climate Action Data Hub, https://cgiar-climate-data-hub.github.io/catalog/africa-precipitation-monthly-seasonal_1/.
BibTeX
@misc{africa_precipitation_monthly_seasonal_2026,
title = {Monthly and seasonal precipitation from CHIRPS v3 (Africa), Africa Agriculture Adaptation Atlas},
author = {Steward, P. and Funk, C. and Peterson, P. and Landsfeld, M.},
year = {2026},
version = {1},
publisher = {Alliance of Bioversity International and CIAT},
note = {Accessed through the CGIAR Climate Action Data Hub, https://cgiar-climate-data-hub.github.io/catalog/africa-precipitation-monthly-seasonal_1/}
}Attribution
Reproduce this credit line wherever you reuse the data.
Derived from CHIRPS v3, Climate Hazards Center, UC Santa Barbara.
Contacts
Who produced this dataset, and who to reach about it.