
Open data
|
Deployed on AWS
The Rain over Africa (RoA) dataset consists of spaceborn estimates of precipitation of Rain over Africa using only geostationary imagery and obtained through a convolutional and quantile regression neural network. The dataset also contains some uncertainty estimates.
Overview
The Rain over Africa (RoA) dataset consists of spaceborn estimates of precipitation of Rain over Africa using only geostationary imagery and obtained through a convolutional and quantile regression neural network. The dataset also contains some uncertainty estimates.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
How can we make this page better?
Tell us how we can improve this page, or report an issue with this product.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- RoA expected rain rate and quantiles at levels 5%, 16%, 25%, 50%, 75%, 84%, and 95% in Zarr format
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::rainoverafrica
- AWS region
- us-west-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://rainoverafrica/
- Description
- Notifications for new Rain over Africa data
- Resource type
- SNS topic
- Amazon Resource Name (ARN)
- arn:aws:sns:us-west-2:261854712492:rainoverafrica-object_created
- AWS region
- us-west-2
Resources
Vendor resources
Support
How to cite
Rain over Africa was accessed on DATE from https://registry.opendata.aws/roa .
License
Similar products
Accelerate your cloud transformation across Africa with Console Connect CloudRouter-a software-defined multi-cloud networking solution that provides direct, high-performance access to AWS from key markets throughout the continent. Designed to overcome connectivity and latency challenges, Console Connect enables enterprises, governments, and service providers to move data seamlessly and securely between AWS, other cloud providers, data centers, and enterprise networks.
HyperTrack provides the building blocks to automate on-demand jobs and workforce. Our APIs and SDKs for planning, assigning, tracking, and verification learn from ground truth data to improve operational KPIs including job completion rate, workforce reliability, productivity, and on-time delivery.
Secure enterprise video and podcast streaming purpose-built for Moodle and Totara LMS. AWS-powered with multi-region data residency, AI transcription, adaptive HLS delivery, and learning analytics.

Digital Earth Africa (DE Africa) provides free and open access to a copy of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) monthly and daily products over Africa. The CHIRPS rainfall maps are produced and provided by the Climate Hazards Center in collaboration with the US Geological Survey, and use both rain gauge and satellite observations.
The CHIRPS-2.0 Africa Monthly dataset is regularly indexed to DE Africa from the CHIRPS monthly data. The CHIRPS-2.0 Africa Daily dataset is likewise indexed from the CHIRPS daily data. Both products have been converted to cloud-opitmized GeoTIFFs, and can be accessed through DE Africa’s Open Data Cube. This means the full archive of CHIRPS daily and monthly rainfall can be easily used for inspection or analysis across DE Africa platforms, including the user-interactive DE Africa Map.
For more information on the dataset, see the CHIRPS website.