Research

Here you can find my research as research publications in journals, a seminar talk, my conference contributions and public science communication.

Publications

S. Kesselheim, A. Herten, K. Krajsek., J. Ebert, J. Jitsev, M. Cherti, M. Langguth, B. Gong, S. Stadtler, A. Mozaffari, G. Cavallaro, R. Sedona, A. Schug, A. Strube, R. Kamath, M. G. Schultz, M. Riedel and T. Lippert. JUWELS Booster–A Supercomputer for Large-Scale AI Research International Conference on High Performance Computing (pp. 453-468). Springer, Cham. https://arxiv.org/pdf/2108.11976.pdf, Jahr: 2021


C. Betancourt, T. Stomberg, R. Roscher, M. G. Schultz, S. Stadtler. AQ-Bench: a benchmark dataset for machine learning on global air quality metrics. Earth System Science Data
https://doi.org/10.5194/essd-13-3013-2021, 2021


M. G. Schultz, C. Betancourt, B. Gong, F. Kleinert, M. Langguth, L. H. Leufen, A. Mozzafari, S. Stadtler. Can deep learning beat numerical weather prediction? Philosophical Transactions of the Royal Society A
https://doi.org/10.1098/rsta.2020.0097, 2021


S. Stadtler, D. Simpson, S. Schröder, D. Taraborrelli, A. Bott, and M. Schultz. Ozone impacts of gas-aerosol uptake in global chemistry transport models. Atmospheric Chemistry and Physics,
https://doi.org/10.5194/acp-18-3147-2018, 2018.


S. Stadtler, T. Kühn, S. Schröder, D. Taraborrelli, M. G. Schultz, and H. Kokkola. Isoprene derived secondary organic aerosol in the global aerosol chemistry climate model ECHAM6.3- HAM2.3MOZ1.0. Geoscientific Model Development,
https://doi.org/10.5194/gmd-11-3235-2018, 2018.


M. G. Schultz, S. Stadtler, S. Schröder, D. Taraborrelli, A. Henrot, N. Kaffashzadeh, B. Franco, S. Ferrachat, C. Siegenthaler-Le Drian, U. Lohmann, D. Neubauer, S. Wahl, H. Kokkola, T. Kuehn, P. Stier, D. Kinnison, G. Tyndall, and J. Orlando. The chemistry climate model ECHAM6.3-HAM2.3MOZ1.0. Geoscientific Model Development,
https://doi.org/10.5194/gmd-11-1695-2018, 2018.


H. Kokkola, T. Kühn, A. Laakso, T. Bergman, K. Lehtinen, T. Mielonen, A. Arola, S. Stadtler, H. Korhonen, S. Ferrachat, U. Lohmann, D. Neubauer, I. Tegen, C. Siegenthaler-Le Drian, M. G. Schultz, I. Bey, P. Stier, and S. Romakkaniemi SALSA2.0: The sectional aerosol module of the aerosol-chemistry-climate model ECHAM6.3.0-HAM2.1-MOZ1.0. Geoscientific Model Development
https://doi.org/10.5194/gmd-11-3833-2018, 2018


Talks

As an atmospheric scientist, I think it is unsatisfying to derive air quality with a black-box model. To be able to trust my machine learning model, I need to understand how the model makes predictions. Especially, do the trained machine learning models fit our current understanding of atmospheric chemistry? We use two different architectures, a Random Forest and a shallow Neural Network. In this talk, I speak about how we used explainable machine learning to understand the differences between two conceptually different algorithms.

Conferences

S. Stadtler, J. Kowalski, M. Abel, R. Roscher, S. Crewell, B. Gräler, S. Kollet, M. Schultz. KI: STE Project-AI Strategy for Earth System Data. Oral pico presentation in EGU General Assembly Conference, April 2021, online.


S. Stadtler, T. Kühn, S. Schröder, D. Taraborrelli, M. G. Schultz, and H. Kokkola. Isoprene derived secondary organic aerosol in ECHAM6-HAMMOZ. Oral presentation at the ECHAM6-HAMMOZ Workshop, March 2017, Zürich, Switzerland


S. Stadtler, T. Kühn, S. Schröder, D. Taraborrelli, M. G. Schultz, and H. Kokkola. Isoprene derived secondary organic aerosol in a global aerosol chemistry climate model. Poster presentation at the EGU, April 2017, Vienna, Austria


S. Stadtler, T. Kühn, S. Schröder, D. Taraborrelli, M. G. Schultz, and H. Kokkola. Isoprene derived secondary organic aerosol in a global chemistry climate model (ECHAM6-HAMMOZ). Poster presentation at the AeroCom Workshop, October 2017, Helsinki, Finland.


S. Stadtler, S. Schröder, D. Taraborrelli, and M. Schultz. The impact of heterogeneous reactions on tropospheric ozone. Oral presentation at the ECHAM-HAMMOZ Workshop, March 2016, Zürich, Switzerland.


S. Stadtler, D. Simpson, S. Schröder, D. Taraborrelli, A. Bott, and M. Schultz. Heterogeneous Chemistry in Global Chemistry Transport Models. Oral presentation at the EGU, April 2016, Vienna, Austria.

conference-talk
Copyright: Forschungszentrum Jülich

Public Outreach

KI gegen den Klimawandel: Bundesumweltministerin Svenja Schulze im Forschungszentrum

Jülich, 28. Juni 2021 – Bundesumweltministerin Svenja Schulze machte auf ihrer Sommerreise heute Station im Forschungszentrum Jülich. Im Zentrum des Besuchs standen Informationen über energieeffizientes Supercomputing und der Einsatz Künstlicher Intelligenz (KI) für den Klima- und Umweltschutz. Die Jülicher Forscherinnen und Forscher wollen Methoden der KI nutzen, um Gefahren durch den Klimawandel frühzeitig zu erkennen. Mit JUWELS können sie dafür auf einen äußerst energieeffizienten und den aktuell schnellsten Superrechner Europas zurückgreifen.

meeting-with-environment-minister
Copyright: Forschungszentrum Jülich / Ralf-Uwe Limbach

Source: FZ-Jülich