Revolution at Sonnblick: AI measures aerosols for the climate in real time!

Revolution at Sonnblick: AI measures aerosols for the climate in real time!

At the Sonnblick Observatory, which is located at around 3,100 meters above sea level in the Hohe Tauern, a new measuring system is being introduced that analyzes bioaerosols using artificial intelligence (AI). Loud Small newspaper Bioaerosols are tiny, naturally occurring particles in the air, such as pollen, fungal spores and bacteria, whose type and concentration have a decisive influence on the weather, climate and vegetation. This is particularly relevant given that such aerosols also determine the formation of clouds and precipitation and are therefore of great importance for climate research.

The traditional methods for measuring pollen, which are based on pollen traps, require manual evaluation and can therefore cause time delays in data provision. The new technology at the Sonnblick Observatory, on the other hand, enables automated differentiation between different types of aerosols, which significantly speeds up the evaluation. Julia Burkart, the project manager and physicist at Geosphere Austria, confirms that through the use of AI, the measurement data should be available online in almost real time.

Relevance for climate research

The meanings of these aerosol measurements are diverse. Long-term changes in the type and number of aerosols can have significant impacts on rainfall and snowfall conditions. These findings are crucial for the development of climate models, especially in times when climate change is leading to changes in high alpine regions. The research aims to study in detail the effects of climate change on the concentration and type of pollen, fungal spores and other bioaerosols.

The role of AI in climate research is also the subject of a lecture by Christopher Kadow, a climate information scientist at the German Climate Computing Center. In his lecture entitled “Artificial intelligence reconstructs the climate”. OeAW explains how AI is used to complement historical climate data and thus close gaps in the data sets. Advanced technologies are used here that can be used, for example, for upscaling processing of climate data or for virtually repairing defective rain radar data.

AI and its future in climate research

The transformative impact of AI on climate research is also reflected in its ability to predict extreme weather events more precisely. A report from Tech Zeitgeist highlights that companies like Google DeepMind and OpenAI are leaders in developing new AI models that can analyze large amounts of data faster and more precisely than traditional climate models. These advances not only promote the analysis of CO₂ emissions, but also enable faster calculation of climate simulations, which in many cases even minimize sources of error.

However, these technologies also raise ethical questions. The question of who has access to the data and how it is used to advantage is becoming increasingly important, as uneven data distribution can lead to biases in predictions. Transparency in AI models is therefore required to prevent misuse and misinterpretation of data. The responsible use of these technologies will therefore be crucial for the future of climate research.