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Conference Paper

Measuring weather data with a self-build low-cost sensor

Authors

Sobottke,  Vincent
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Schoster,  Daniela
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Rust,  Henning
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Böttcher,  Christopher
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Lehmke,  Jonas
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Ulrich,  Jana
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Otto,  Marco
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Meier,  Fred
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Sobottke, V., Schoster, D., Rust, H., Böttcher, C., Lehmke, J., Ulrich, J., Otto, M., Meier, F. (2023): Measuring weather data with a self-build low-cost sensor, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4159


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021598
Abstract
Considering the fast urban growth and the rapid increase of the city population, urban areas are constantly changing. Additionally, the spatial heterogeneity of Berlin leads to a pronounced spatial variability of meteorological variables, which is impossible to capture with the existing network of urban measuring stations. Therefore, the Open Urban Climate Observatory Berlin aims to establish an open meteorological measurement network by involving the urban society, e.g. allotment gardeners, who maintain the measuring devices especially developed for this purpose. With this extension of the classical measurement network and a recently installed high-resolution precipitation radar for Berlin, a new data basis becomes available to answer relevant questions for the urban community.In order to improve the quality of this data set, we apply a range of methods from the fields of Statistics and Machine Learning to filter faulty measurements and calibrate measurements using publicly available data from stations of the German-Weather-Service (DWD) and the network itself. In collaboration with the citizens, research questions will be developed and addressed and the potential of possible applications will be explored during workshops. In this process, citizens will be supported by scientific staff with technology and knowledge about the urban climate. Ideally, the results will serve as a basis for the development of applications, e.g. a digital watering assistant that provides watering recommendations optimized for plant growth and resource utilization based on local measurements and appropriately processed precipitation forecasts.We will report on the current status of the project and some preliminary results of data analysis.