Rain Cell Africa aims to promote and develop an innovating estimation of rain based on cellular networks. It relies on commercial microwave links from cellular telephone networks to detect and quantify rainfall. The method exploits radio wave attenuation caused by rain. Based on the loss of signal between backhaul antennas, rainfall can be accurately monitored throughout the network. In Africa, where the mobile phone network is dense and growing, this technique offers an unprecedented potential.
Rainfall monitoring based on commercial terrestrial microwave links has been tested for the first time in Africa, in Burkina Faso ( Doumounia et al, 2014 ). Following this first success, other case studies have been carried out in West and Central African countries.
Rain Cell Africa vise à promouvoir et développer une méthode d'estimation des pluies innovante grâce aux réseaux de téléphonie mobile. Elle est basée sur l'atténuation du signal radio transmis entre deux antennes par la pluie et tire profit de liaisons micro-ondes commerciaux pour détecter et estimer la quantité de pluie. En Afrique où les réseaux de téléphonie mobile sont denses et en expansion, cette technique offre un potentiel très élevé.
La méthode Rain Cell a été testée avec succès pour la première fois en Afrique, au Burkina Faso ( Doumounia et al, 2014 ). Depuis, plusieurs études ont été menées dans divers pays d'Afrique de l'Ouest et d'Afrique Centrale.
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

1 to 5 of 5 Results
Mar 15, 2021 - Rain Cell project in Mali
Alcoba Kait, Matias; Noumaguel, Nogmana; Cazenave, Frederic, 2021, "Rainfall dataset of the May 16 2019 flood event in Bamako, Mali", https://doi.org/10.23708/ZI0ONV, DataSuds, V1, UNF:6:NIECVHQc45Z8Ir42IELI/Q== [fileUNF]
On May 16 2019, an intense rainfall event led to devastating floods in Bamako, Mali. The Early Flood Warning System (EWS) Rain Cell app Bamako was partially operational. 6 rain gauges, spread over the city, recorded and sent rainfall intensities in real time. This text file conta...
Mar 10, 2021 - Rain Cell project in Mali
Bouvier, Christophe; Chahinian, Nanée; Alcoba Kait, Matias; Dembélé, N'dji dit Jacques; Cazenave, Frédéric, 2021, "Simulated peak flow for the May 16 2019 flood event in Bamako, Mali", https://doi.org/10.23708/PDLP9F, DataSuds, V1
On May 16 2019, an intense rainfall event led to devastating floods in Bamako (Mali). The Rain Cell app Bamako was partially operational, with 6 rain gauges recording and sending in real time rainfall over the city of Bamako. This raster file in ASCII ESRI format contains peakflo...
Mar 9, 2021 - Rain Cell project in Mali
Bouvier, Christophe; Chahinian, Nanée; Alcoba Kait, Matias; Dembélé, N'dji dit Jacques; Cazenave, Frédéric, 2021, "Simulated overbank flow for the May 16 2019 flood event in Bamako, Mali", https://doi.org/10.23708/RXSSDX, DataSuds, V1
On May 16 2019, an intense rainfall event led to devastating floods in Bamako (Mali). The Rain Cell app Bamako was partially operational, with 6 rain gauges recording and sending in real time rainfall over the city of Bamako. This raster file in ASCII ESRI format contains peakflo...
Mar 5, 2021 - Rain Cell project in Mali
Dembele, N'dji dit Jacques, 2021, "Experience feedback (REX) of the May 16 2019 flood event in Bamako, Mali", https://doi.org/10.23708/CL3VFS, DataSuds, V1
On May 16 2019, an intense rainfall event led to devastating floods in Bamako, Mali. In the immediate aftermath of the flood event, the Laboratoire Hommes-Peuplements–Environments (Labo-HoPE research laboratory) collected data about the flooding process and mechanism as well as t...
Rain Cell project in Mali logo
Mar 4, 2021
IRD has developed the RainCell app Bamako project, an Early Flood Warning System (EWS) for the city of Bamako. The project was carried out in partnership with the Civil Protection of Mali (DGPC ), MALI-METEO and the National Hydraulic Directorate (DNH ). Funded by the Korean Gree...
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.