AIRforschen
Precise weather forecasts are essential for safe traffic flows, efficient use of renewable energies and the management of extreme weather events. The quality of the forecasts depends crucially on the frequency and distribution of meteorological measurements. Most measurements are taken either from the ground or at very high altitudes (for example by commercial aircraft at an altitude of over 10 km). Therefore, there are large observation gaps in the planetary boundary layer (up to approx. 2 km altitude), although this layer in particular is very relevant for weather events.
The "AIRforschen" project aims to close these gaps by integrating general aviation aircraft (for example from air sports clubs and rescue services), travelling in the planetary boundary layer, into the data collection. General aviation in Germany is characterized by a high density of airfields (400 for general aviation compared to 40 for commercial aviation) and a high number of aircraft movements: 80% of all flights and 95% of all registered aircraft in Germany can be attributed to general aviation. This means that general aviation aircraft offer ideal platforms for weather measurements in the planetary boundary layer.
The main objective of the project is to utilise general aviation flight movements as platforms for weather measurements. Tapping into this previously unused data source will ultimately make it possible to improve weather forecasts and thus contribute to increased safety against natural disasters and more efficient management of aviation, transport and energy supply.
In the course of the project, a sensor kit will be developed that can be easily and inexpensively installed on aircraft. The sensor kit records weather data and sends it anonymously to a central database via the pilots' smartphones. The collected data is analyzed for anomalies and compressed using machine learning methods. A smartphone app and a website are also being developed in the project to transfer the data and facilitate dialogue between the project participants. The collected data will ultimately be fed into weather models, where it will contribute to the improvement of weather forecasts and the development of new weather services.
The improved weather forecasts can be beneficial in numerous applications. These include, for example:
- Safety: Better protection against weather-related natural disasters.
- Transport: Better management of traffic flow under different weather conditions.
- Energy supply: Better planning of renewable energy production.
In this project, the DLR Institute of Data Science is contributing its expertise in the field of accessing and analysing aviation data. Within the project, the institute is responsible for project management, the creation of a user community, the coordination of app and website development and the development of software for anomaly detection and data compression. The institute is working together with the following partners from science, industry and public administration:
All information about the project:
Project duration: 08/2024 - 07/2027