Citizen observations via smartphone in Belgium: data collection and applications

The detection and prediction of very local weather effects, like wind gusts or hail storms, remains a challenging issue in meteorology. Especially in the case of severe storms, there is often a lack of detailed ground truth data to assess the precise conditions of the event. One promising approach to supplement the information obtained with the classical instruments like radar and satellite, is the collection of citizen weather reports through smartphones. In August 2019, the Royal Meteorological Institute of Belgium (RMIB) added such a reporting feature in its smartphone app. Currently the database of citizen reports holds more than two and a half million records. Since May 2022, the app users are also able to add a photo to their observation.

In this presentation, we describe the general concept of the app feature and how the quality control of the reports and the filtering of the photos are organised. Then, we give some general statistics of the aggregated dataset. We will show that this unconventional observation system brings uncommon sources of uncertainties and biases related to the human nature of the observations. The collected data have already been exploited in several use cases at RMIB, such as the verification of the official weather warnings and the forecasts per commune as sent out by the weather office. We will further focus on the verification of the operational radar-based hail detection algorithm used at RMIB. Among all reported observations, 23 % concern precipitation (rain, snow or hail) and 0.7 % hail. We will examine the extent to which such a dataset allows evaluating the performance of the algorithm in terms of probability of correct and false detections. These applications show that the citizen observations are an extremely valuable new source of very localised information for many applications in research and operations at RMIB.