The French Riviera, located in the eastern part of the French Mediterranean coast, has experienced devastating flash floods during the last 10 years. Several of these floods were generated by local and very intense rainfall events, leading to significant material and human losses, especially on small coastal catchments, which often have sparse rain gauge networks and are mostly ungauged in terms of streamflow. For example, the October 2015 event affected the Riou de l’Argentière, Frayère and Brague coastal catchments (respectively 47 km², 21 km² and 72 km² to the sea) with intense rainfall (up to 200 mm in only two hours) characterized by a significant spatial variability (up to two times more precipitation on the downstream part of the catchments). In this context, the estimation of catchment rainfall statistics needs to be performed using datasets with high space and time resolutions. The COMEPHORE dataset is a rainfall observational dataset with hourly and kilometric resolution over the entire French metropolitan territory. It is produced by Météo-France, merging both raingauge and radar observations and currently available from 1997 to 2020. The objective of this study is to explore the COMEPHORE dataset to estimate and gain knowledge on heavy rainfall characteristics over French Riviera coastal catchments. The work focuses on 45 coastal catchments draining more than 10 km² and less 1000 km². Various spatial and temporal descriptors are calculated to describe the intensity and the temporal and spatial dynamics of the precipitation over this Mediterranean region. The temporal evolution of the descriptors is evaluated over the 23 years of available data. Additionally, a focus is made on significant rainfall events observed during the last decades, in order to discuss their frequency, associated weather patterns and their (dis)similarity at the regional scale. Finally, we discuss how the proposed description of the spatial and temporal characteristics of heavy rainfall events affecting the French Riviera can be useful to improve rainfall forecasting, as well as to forecast the associated hydrological responses of the coastal catchments at very short lead times and, ultimately, how it can contribute to reduce losses generated by flash floods.