The growth of air transport demand expected over the next decades, along with the increasing frequency and intensity of extreme weather events, such as heavy rainfalls and severe storms due to climate change, will pose a tough challenge for air traffic management systems, with implications for flight safety, delays and passengers. In this context, the Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project has a dual aim, first to investigate if very short-range high-resolution weather forecast, including data assimilation, can improve the predictive capability of these events, and then to understand if such forecasts can be suitable for air traffic management purposes. The intense squall line that affected Malpensa, the major airport by passenger traffic in northern Italy, on 11 May 2019 is selected as a benchmark. Several numerical experiments are performed with a Weather Research and Forecasting (WRF) model using two assimilation techniques, 3D-Var in WRF Data Assimilation (WRFDA) system and a nudging scheme for lightning, in order to improve the forecast accuracy and to evaluate the impact of assimilated different datasets. To evaluate the numerical simulations performance, three different verification approaches, object-based, fuzzy and qualitative, are used. The results suggest that the assimilation of lightning data plays a key role in triggering the convective cells, improving both location and timing. Moreover, the numerical weather prediction (NWP)-based nowcasting system is able to produce reliable forecasts at high spatial and temporal resolution. The timing was found to be suitable for helping Air Traffic Management (ATM) operators to compute alternative landing trajectories.

The single polarization C-Band weather radar network of the Meteorological Service of Catalonia covers the entire region (32,000 km²), which allows it to apply a series of corrections that improve preliminary estimations of the rainfall field (hourly and daily). In addition, an automatic re-processing using automatic weather stations helps to incorporate ground-based information. The last process of the quantitative precipitation estimation (QPE) is running the end-product again eight days later, when the data have been reviewed and corrected in the case of detecting anomalies in the radar or gauge data. These corrections are applied operationally, with the fields generated and stored automatically. The QPE fields are generated in the GeoTIFF format, allowing easy use with multiple applications and simplifying processes such as quality control. In this way, the analysis of a 10 year period of GeoTIFF QPE daily data compared with ground rainfall values is introduced. The results help to understand different points regarding the functioning of the network such as the dependance on the type of precipitation and the seasonality. In addition, the description of a heavy rainfall episode (22 October 2019) shows the variations and improvements in the different products. The main conclusions refer to how using GeoTIFF combined with point data (rain gauges), it is possible to ensure simple but effective quality control of an operational radar network.

Urban floods repeatedly threaten Barcelona, damaging the city infrastructure and endangering the safety of the population. The urban planning of the city, the socioeconomic distribution, its topography, and the characteristics of precipitation systems translate into these flood events having a heterogeneous effect across the city. It means that the coping capacity has a strong dependence on local factors that must be considered when management plans are developed by the municipality. This work aims to contribute to the better knowledge of precipitation structures associated with heavy rainfall events and floods in Barcelona based on radar data and an urban rain gauge network. Radar data have been provided by the Meteorological Service of Catalonia (SMC), while precipitation data, impact data, and early warnings, have been provided by Barcelona Cicle de l’Aigua S.A. (BCASA), for the period 2013–2018. A new radar-based methodology has been developed to identify convective rainfall structures from radar reflectivity volumes (CAPPI and TOP products) to make the analysis easier. The high computing speed of the procedure allows efficient analysis of a large set of convective cells without scarifying temporal resolution of radar data. Both rainfall fields (radar and rain gauge, respectively) have been compared. Then through the identified rainfall convective structures, thunderstorm hotspots have been identified. Considering an alert indicator from BCASA and the reported incidents, episodes with the highest impact have been analysed in depth. Results show 207 significant rainfall episodes in the ROI for the six years, which are mainly concentrated between September and November. The fact that significant episodes are usually produced by highly convective rain corroborates the advantage of using radar images as a tool to detect any maxima even when no rain gauge is there. In 64 of the episodes, the level of pre-alert was achieved with a maximum frequency between August and September. The proposed algorithm shows more than 8000 centroids of convective cells from 189 cases. Whilst maximum surface reflectivity over 45 dBZ is more prone to occur near the coastline, the centroids of storm cells tend to concentrate more inland. The final objective is to improve the actions taken by the organisation responsible for managing urban floods, which have seen Barcelona recognised as a model city for flood resilience by the United Nations.

In the H2020 project “Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM” (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During project runtime, traffic days with extreme weather events in the Po Valley were analyzed, an arrival manager was extended with a module for 4D diversion trajectory calculation, two display variants for severe weather conditions in an air traffic controller primary display were developed, and the airport Milano Malpensa was modelled for an air traffic simulation. On the meteorological side, three new forecasting techniques were developed to better nowcast weather events affecting tactical air traffic operations and used to automatically organize arrival traffic. Additionally, short-range weather forecasts with high spatial resolution were elaborated using radar-based nowcasting and a numerical weather prediction model with data assimilation. This nowcast information was integrated into the extended arrival manager for the sequencing and guiding of approaching aircraft even in adverse weather situations. The combination of fast and reliable weather nowcasts with a guidance support system enables severe weather diversion coordination in combination with a visualization of its dynamics on traffic situation displays.

Flash floods repeatedly threaten Barcelona, damaging the city infrastructure and endangering the safety of the population. The city’s urban planning and socioeconomic distribution, associated with the topography and other geographic factors, means that these flood events do not affect the entire city in the same way. This is a key point for surveillance and emergency tasks, which need some patterns and models to improve response capacity. This work aims to gain a better understanding of such events, to add valuable information on how to predict and manage these situations. For this purpose, both radar and ground observational data have been combined to identify the most important precipitation episodes in Barcelona between 2013 and 2018. To make the analysis easier, a new algorithm has been developed to determine the thunderstorm hotspots. Episodes with a higher impact have been analysed in depth. The final objective is to improve the actions taken by the organisation responsible for managing urban floods, which have seen Barcelona recognised as a model city for flood resilience by the United Nations.

Floods are the natural hazards that cause the most damage and affect the most people in Spain. However, the response of the population and the actions they take before, during and after the emergency can be inappropriate due to inaccurate risk perception and preparation. This paper presents an analysis of the floods of 22–23 October 2019 in the upper area of the Francolí watershed (Catalonia, NE Spain), with the aim of analysing how to improve public perception and impact estimation through citizen science. To this end, a campaign (FLOODUP-Francolí) was organised together with a local institution that helped to engage participants. This consisted of a kick-off conference, a period of participation through tools adapted to the virtual format, including a questionnaire, and a face-to-face conference to present the results. The detailed analysis of the actions taken in the emergency allowed the identification of key aspects to improve flood prevention, response and recovery processes: clarity and consistency of communication, channels of communication, the timing of warnings, the preparedness of the population and the existence of agreed-upon self-protection protocols. Finally, this study demonstrates the contribution of citizen science initiatives in the field of natural hazards to improving community resilience and historical memory.