Atmospheric Water Datasets

from the clouds and precipitation group at Chalmers University of Technology

Rain over Africa

Resources

Description

Background

Satellites are the only way to continuously monitor rainfall across all of Africa. However, current methods for estimating rain from space can take a long time because they combine data from multiple sources.

We introduced Rain over Africa (RoA) in this publication, a new public method that can provide near-real-time precipitation estimates for Africa. The approach works by downloading a Meteosat image and processing it with an artificial neural network trained on precipitation estimates from the calibration satellite in the Global Precipitation Measurement (GPM) mission. Note that GPM, despite being a constellation of satellites, has less continuous coverage of Africa than Meteosat.

We found that RoA estimates show good agreement with estimates from dedicated precipitation sensors. Moreover, while the latter are available every few hours at best, RoA estimates can be updated every 15 minutes. This makes RoA valuable for disaster preparedness and water management. Additionally, RoA provides practical probabilities of rain to help predict different scenarios, delivered as precipitation quantiles.

The dataset

We are offering many years of RoA precipitation estimates via the Registry of Open Data on AWS at registry.opendata.aws/roa.

The data is stored as Zarr files in the following structure:

s3://rainoverafrica/
├── README.txt
└── data/
    ⋮
    ├── roa_2023.zarr/
    └── roa_2024.zarr/

We create one Zarr file per year and follow the pattern roa_YYYY.zarr. We are uploading the data in batches.

If you need to explore further the directory tree, you can use the AWS CLI or fsspec's s3fs.

More documentation can be found at https://github.com/SEE-GEO/roa.

Contact: amell@chalmers.se.