Projects per year
Dr Peer Nowack uses numerical models and machine learning to address key challenges in climate science, atmospheric physics, and atmospheric chemistry. In particular, he is interested in methods to understand and reduce uncertainty in regional climate change projections, the development of computationally efficient parameterizations for the latest generation of Earth system models, seasonal forecasting, extreme weather events in a changing climate, and air pollution.
- Ceppi and Nowack. Observational evidence that cloud feedback amplifies global warming. PNAS 118, e2026290118 (2021).
- Nowack et al. Causal networks for climate model evaluation and constrained projections. Nature Communications 11, 1415 (2020).
- Runge, Nowack et al. Detecting and quantifying causal associations in large nonlinear time series datasets. Science Advances 5, eaau4996 (2019).
- Nowack et al. Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations. Environmental Research Letters 13, 104016 (2018).
- Nowack et al. On the role of ozone feedback in the ENSO amplitude response under global warming. Geophysical Research Letters 44, 3858-3866 (2017).
- Nowack et al. Stratospheric ozone changes under solar geoengineering: implications for UV exposure and air quality. Atmospheric Chemistry and Physics 16, 4191-4203 (2016).
- Nowack et al. A large ozone-circulation feedback and its implications for global warming assessments. Nature Climate Change 5, 41-45 (2015).
Link to Google Scholar.
Chemistry, data science, machine learning, climate science.
|01/2020 -||Lecturer in Atmospheric Chemistry and Data Science, University of East Anglia.|
|2017 -2021||Imperial College Research Fellow, Department of Physics / Data Science Institute, Imperial College London.|
|2016-2017||Postdoctoral Research Associate, Department of Chemistry, University of Cambridge.|
|01-03/2017||ASI Data Science Fellowship, CMC Markets, London.|
|2016||PhD, Department of Chemistry, University of Cambridge.|
|2012||BSc, Interdisciplinary Sciences: Physics, Chemistry, Computer Science, ETH Zurich, Switzerland.|
Key Research Interests
- Machine learning
- Atmospheric chemistry and physics
- Air pollution
- Extreme weather
- Climate sensitivity
- Causality algorithms
- Climate change
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Doctor of Philosophy, University of Cambridge
Award Date: 1 Oct 2016
Bachelor of Science, ETH Zürich
Award Date: 1 Oct 2012
Imperial College Research Fellow, Imperial College London
1 Aug 2017 → 31 Jul 2021
Dive into details
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- 1 Active
A machine learning approach to quantify meteorological drivers of ozone pollution in China from 2015 to 2019Weng, X., Forster, G. & Nowack, P., 29 Jun 2022, In: Atmospheric Chemistry and Physics. 22, 12, p. 8385-8402 18 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile
Watson-Parris, D., Rao, Y., Olivie, D., Seland, Ø., Nowack, P., Camps-Valls, G., Stier, P., Bouabid, S., Dewey, M., Fons, E., Gonzalez, J., Harder, P., Jeggle, K., Lenhardt, J., Manshausen, P., Novitasari, M., Ricard, L. & Roesch, C., 1 Sep 2022, (Accepted/In press) In: Journal of Advances in Modeling Earth Systems. e2021MS002954.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile1 Downloads (Pure)
& 1 others, , 15 Mar 2022, online: arXiv Computers and Society, p. 1-49.
Research output: Working paper
Thomas, C., Voulgarakis, A., Lim, G., Haigh, J. & Nowack, P., 12 Jul 2021, In: Weather and Climate Dynamics. 2, 3, p. 581-608 28 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile18 Downloads (Pure)
Nowack, P., Zeng, G., Zhang, J., Bodeker, G., Burrows, S. M., Cameron-Smith, P., Cugnet, D., Danek, C., Deushi, M., Horowitz, L. W., Kubin, A. & 11 others, , 31 Mar 2021, In: Atmospheric Chemistry and Physics. 21, 6, p. 5015-5061 47 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile18 Citations (Scopus)4 Downloads (Pure)
Press / Media
A new approach to analyse satellite measurements of Earth’s cloud cover reveals that clouds are very likely to enhance global heating, according to new research led by UEA.
19/07/21 → 21/07/21
56 items of Media coverage
Press/Media: Press / Media