Ferdinand Briegel

Ferdinand Briegel, M.Sc.
Doctoral student and research assistant

Werthmannstrasse 10
79085 Freiburg
Room 00.002

Biography

Ferdinand Briegel studied Environmental Science and Hydrology at the University of Freiburg from 2012 to 2016 (Bachelor of Science). From 2016 to 2019 he studied Environmental Science with the elective track Environmental Modelling and GIS (Master of Science).  From June 2020 to December 2020 he worked as a research assistant in the urbisphere project (database management) at the Chair of Environmental Meteorology at the University of Freiburg. In January 2021 his doctoral research in the I4C project, also at the Chair of Environmental Meteorology, started.

Research interests

In his master's thesis, he developed a new approach to partition net CO2 fluxes into respiration and photosynthesis based on deep learning. 

In his PhD thesis, a multi-scale deep learning model for the prediction of thermal stress in urban areas will be developed. In the first step, physical meso- and microscale models will be coupled and subsequently approximated by deep learning. Furthermore, the key factors for reducing the thermal stress on the different scale levels will be determined.

Current Research Projects

• I4C - Intelligence for Cities (KI-Leuchttürme, BMU)

Publications

Articles in peer-reviewed journals

• Briegel F, Wehrle J, Schindler D, Christen A, 2024: High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning, Geoscientific Model Development, 17, 1667–1688.
• Briegel F,  Makansi O, Brox T, Matzarakis A, Christen, A, 2023: Modelling long-term thermal comfort conditions in urban environments using a deep convolutional encoder-decoder as a computational shortcut. Urban Climate, 47, 101359.

• Lee S-C, Christen A, Black TA, Jassal RS, Briegel F, Nesic Z, 2021: Combining flux variance similarity partitioning with artificial neural networks to gap-fill measurements of net ecosystem production of a Pacific Northwest Douglas-fir stand. Agricultural and Forest Meteorology, 303, 108382.

• Briegel F, Lee S-C, Black TA, Jassal RS, Christen A, 2020: Factors controlling long-term carbon dioxide exchange between a Douglas- fir stand and the atmosphere identified using an artificial neural network approach. Ecological Modelling, 435, 109266.

Conference contributions

• Briegel F, Schrodi S, Wehrle J, Sulzer M, Brox T, Schindler D, Christen A, 2023: Downscaling of climate change scenario ensembles to city-wide and high-resolution thermal comfort maps using deep learning. 41st Annual Conference AK Klima 2023, Tübingen, Germany, 12–14 Oct 2023.

• Plein M, Feigel G, Zeeman M, Briegel F, Dormann C, Christen A, 2023: A sensor network for real-time monitoring and modelling of street-level heat exposure in Freiburg, Germany. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023.
• Zeeman M, Benjamins K, Briegel F, Drouin M-A, Feigel G, Fenner D, Kotthaus S, Hilland R, Meier F, Morrison W, Plein M, Metzger S, Reddy K, Chrysoulakis N, Grimmond S, Christen A, 2023: A modular data management approach for environmental observation campaigns in multiple cities. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023.
• Feigel G, Plein M, Zeeman M, Briegel F, Christen A, 2023: A compact and customisable street-level sensor system for real-time weather monitoring and outreach in Freiburg, Germany. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023.

• Briegel F, Makansi O, Brox T, Christen A, 2022: Modelling mean radiant temperature in complex urban areas using a convolutional network approach. Poster. Beating the Heat 2022, Bern, Switzerland, 16 Sep. 2022.

• Briegel F, Makansi O, Brox T, Christen A, 2022: Modelling T_mrt in a complex urban environment using a convolutional encoder-decoder network. Poster. IAUC Virtual Poster Conference, 30. Aug - 1 Sep. 2022.
• Briegel F, Makansi O, Brox T, Matzarakis A, Christen A, 2022: Modelling mean radiant temperature in complex urban areas using a convolutional network approach. EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022.

• Schlögl S, Briegel F, Gutbrod KG, 2020: High resolution meteorological station network in Swiss Cities: City Weather Monitoring and operational forecasts. Symposium on Challenges in Applied Human Biometeorology, Freiburg, Germany, 02.-03. Mar. 2020.