Summary
Dr Peer Nowack is an Imperial College Research Fellow at the Grantham Institute, the Department of Physics and the Data Science Institute. He uses numerical models and machine learning to address key challenges in climate science and atmospheric physics. 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.
Keywords
- Machine learning
- Numerical models
- Climate sensitivity
- Atmospheric composition
- Air pollution
- Atmospheric physics
- Earth observations
- Big data
- Causality algorithms
PHD OPPORTUNITIES for 2020
A new PhD project (supervised by Dr Nowack) at the University of East Anglia is currently open for applications: Environmental data science: a new machine learning approach to study the influence of climate change on extreme weather
PROJECT LINKS
- Electric Vehicle Fleet Optimisation for Lowering Vehicle Emissions (EVOLVE)
- Science and Solutions for a Changing Planet DTP
Biography
- Independent Research Fellow, Imperial College London. Since 08/2017.
- Postdoctoral Research Associate, Department of Chemistry, University of Cambridge. 2016 - 2017
- ASI Data Science Fellowship, CMC Markets, London. Development of machine learning models to measure the dependence of business performance on market volatility and to identify new business opportunities. 01/2017 - 03/2017
- PhD, Department of Chemistry, University of Cambridge. Numerical simulations of ozone changes in the atmosphere: impacts on projections of climate sensitivity, the El Niño Southern Oscillation and solar geoengineering. 2012 - 2016
- BSc exchange programme, University of Cambridge.
Bachelor thesis and 3rd-4th year lecture courses. 2010 - 2011 - BSc in Interdisciplinary Sciences (Physics, Computer Science, Chemistry), ETH Zurich, Switzerland. 2008 - 2012
Selected Publications
Journal Articles
Runge J, Nowack P, Kretschmer M, et al., 2019, Detecting and quantifying causal associations in large nonlinear time series datasets, Science Advances, Vol:5, ISSN:2375-2548, Pages:1-15
Nowack PJ, Braesicke P, Haigh J, et al., 2018, Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations, Environmental Research Letters, Vol:13, ISSN:1748-9326
Nowack PJ, 2018, The impact of stratospheric ozone feedbacks on climate sensitivity estimates, Journal of Geophysical Research: Atmospheres, Vol:123, ISSN:2169-897X, Pages:4630-4641
Nowack PJ, Braesicke P, Abraham NL, et al., 2017, On the role of ozone feedback in the ENSO amplitude response under global warming, Geophysical Research Letters, Vol:44, ISSN:0094-8276, Pages:3858-3866
Nowack PJ, Abraham NL, Braesicke P, et al., 2016, Stratospheric ozone changes under solar geoengineering: implications for UV exposure and air quality, Atmospheric Chemistry and Physics, Vol:16, ISSN:1680-7316, Pages:4191-4203
Nowack PJ, Abraham NL, Maycock AC, et al., 2015, A large ozone-circulation feedback and its implications for global warming assessments, Nature Climate Change, Vol:5, ISSN:1758-678X, Pages:41-45