- High-resolution weather and climate simulations.
- High-performance computing for weather and climate models.
- Machine learning for weather and climate predictions.
- Model error, model uncertainty and predictability of chaotic systems.
- New hardware for computational fluid dynamics such as field programmable gate arrays, machine learning accelerators, and stochastic processors.
- Reduced numerical precision and hardware faults.
EDUCATION AND WORK EXPERIENCE
- 2022 - today: Head of the Earth System Modelling Section at the European Centre for Medium Range Weather Forecasts (ECMWF)
- 2019 - 2022: Coordinator of Machine Learning and AI activities at ECMWF.
- 2017 - 2022: Royal Society University Research Fellow in the Research Department of ECMWF.
- 2016 - 2017: Scientist working in the Research Department of ECMWF on the ESiWACE project, Reading, UK.
- 2012 - 2016: Postdoctoral Research Assistant working with Tim Palmer at the sub-department for Atmospheric, Oceanic and Planetary Physics, University of Oxford, UK. Postdoctoral MCR Member of Jesus College.
- 2009 - 2012: PhD supervised by Peter Korn and Jochem Marotzke at the Max Planck Institute for Meteorology, Hamburg, Germany. Thesis: “Finite element methods, grid refinement, and boundary currents in geophysical modeling”. Member of the International Max Planck Research School on Earth System Modelling.
- 2004 - 2009: Diploma in Physics supervised by Dirk Homeier and Gernot Münster at the Institute for Theoretical Physics, Westfälische Wilhelms-Universität, Münster, Germany.
TEACHING EXPERIENCE
- 2021: Lecturer at a Machine Learning Crash-Course for CESOC.
- 2017 - today: Lecturer at training courses at ECMWF.
- 2020: Lecturer at the Summer School on "Effective HPC for Climate and Weather", Reading, UK.
- 2016: Lecturer at the ISSAOS 2016 summer school on "Advanced Programming Techniques for the Earth System Science" hosted by the Gran Sasso Science Institute in L’Aquila, Italy.
- 2016: Organiser and Lecturer at the "Chaos and Uncertainty in Weather Forecasts" advanced course for PhD students of the Environmental Research Doctoral Training Partnership at the University of Oxford.
- 2013 - 2016: Tutor for the "Fluid Flows, Fluctuations and Complexity" course for undergraduate students in Physics at New College and Somerville College, University of Oxford.
- 2011 - 2015: Lecturer at the "Introduction to Earth System Science and Modelling" course for PhD students at the International Max Planck Research School on Earth System Modelling.
- 2007 - 2009: Tutor for undergraduate students in Physics at the University of Münster, Germany.
STUDENT SUPERVISION
- 2017 - 2022: PhD supervisor (together with Tim Palmer) of the PhD project of Milan Klöwer at the University of Oxford.
- 2018 - 2021: PhD supervisor (together with Pavel Berloff) of the PhD project of Niraj Agarwal at Imperial College London.
- 2017 - 2018: Supervisor of Master Projects at the University of Bristol and Imperial College London.
- 2015 - 2019: PhD supervisor (together with Tim Palmer) of the PhD project of Samuel Hatfield at the University of Oxford.
- 2014 - 2018: PhD supervisor (together with Tim Palmer) of the PhD project of Tobias Thornes at the University of Oxford.
- 2015: Evaluator of MPhys projects at the Department of Physics, University of Oxford.
- 2013 - 2014: Supervisor of MPhys Projects in the Department of Physics, University of Oxford.
AWARDS, PROPOSALS AND GRANTS
- 2021: Coordinator of the MAELSTROM EuroHPC Joint Undertaking project which involves seven partners within Europe and a budget of 4,3 million Euro.
- 2021: Co-Author of the AI4Copernicus ICT proposal.
- 2018-today: Work-package leader of the ESiWACE-2 Centre of Excellence H2020 project (www.esiwace.eu).
- 2020 and 2021: Co-Pi of an US INCITE grant to perform seasonal predictions with IFS at 1.45 km resolution for a full season on Summit - the second fastest supercomputer in the world (PI Nils Wedi). The simulation of 2020 has won the "Reader's Choice Best Use of HPC in Physical Science" by HPCwire in 2020.
- 2020: Best Paper Award at ICLR2020.
- 2020: Co-Pi of an Alan Turing Institute pilot project for a six-months Postdoctoral Research Assistant position at Warwick University (PI Ritabrata Dutta).
- 2019: Best Paper Award at PASC2019.
- 2018: Co-author of the ExtremeEarth Preparatory Project proposal for the preparation of a EU Flagship proposal on high-resolution modeling of weather, climate and solid Earth (http://www.extremeearth.eu/).
- 2017: Royal Society University Research Fellowship on "Uncertainty in Earth System Modelling".
- 2016: Main author of an accepted proposal for a three year Postdoctoral Research Assistant position, funded by the Office of Naval Research (PI Tim Palmer).
- 2016: Principal Investigator of a special project worth 45 million billing units at the high-performance computing centre of ECMWF.
- 2015: Main author of an accepted proposal for a four-month Postdoctoral Research Assistant position, funded by the Recover network (PI Tim Palmer).
- 2015: Award for Excellence from the Department of Physics at the University of Oxford.
SELECTION OF TALKS IN 2020 (mostly virtual):
Invited talk at AI for Good Discovery; invited talk at KI NRW AI Monday; invited talk at the IARAI conference; invited seminar speaker at IFAB; invited seminar speaker at AWI; invited seminar speaker at EUMETSAT; invited seminar speaker at ATOS; invited talk at GTC2021; invited talk at KGML2021; invited talk at the EWGLAM workshop; invited talk at the ESiWACE HPC summer school; invited talk at a Dagstuhl workshop; invited talk at the University Bayreuth; invited talk at the University of Tuebingen; invited seminar talk at Oak Ridge National Laboratory; invited talk at the Cambridge Environmental Data Science Group; invited seminar talk at the NCI TechTake; invited talk at Imperial College London; invited talk at AARMS
SCIENTIFIC REVIEWER
Peter has written referee reports for articles in the following scientific journals:
Bulletin of the American Meteorological Society, Geoscience Communication, Geosciences, Geoscientific Model Development, IEEE Transactions on Parallel and Distributed Systems, International Journal of High Performance Computing Applications, Journal of Advances in Modeling Earth Systems, Journal of Applied Meteorology and Climatology, Journal of Computational Physics, Nature Communications, Nonlinear Processes in Geophysics, Nonlinearity, Monthly Weather Review, Science Advances, Scientific Data, Tellus A, Weather and Climate Dynamics, and Weather and Forecasting.
- 2023
- Matthew Chantry, Peter Ukkonen, Robin Hogan, Peter Dueben (February 2023) Emulating radiative transfer in a numerical weather prediction model. DOI: 10.5194/egusphere-egu23-3256
- Margarita Choulga, Tom Kimpson, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, Tim Palmer (February 2023) Deep Learning for Verification of Earth's surfaces. DOI: 10.5194/egusphere-egu23-8777
- Gianpaolo Balsamo, Florence Rabier, Magdalena Balmaseda, Peter Bauer, Andy Brown, Peter Dueben, Steve English, Tony McNally, Florian Pappenberger, Irina Sandu, Jean-Noël Thepaut, Nils Wedi (February 2023) Recent progress and outlook for the ECMWF Integrated Forecasting System. DOI: 10.5194/egusphere-egu23-13110
- 2022
- David Meyer, Robin J. Hogan, Peter D. Dueben, Shannon L. Mason (March 2022) Machine Learning Emulation of 3D Cloud Radiative Effects, Journal of Advances in Modeling Earth Systems n. 3. DOI: 10.1029/2021MS002550
- Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall (January 2022) Deep learning to estimate model biases in an operational NWP assimilation system. DOI: 10.1002/essoar.10510309.1
- David Meyer, Sue Grimmond, Peter Dueben, Robin Hogan, Maarten van Reeuwijk (March 2022) Machine Learning Emulation of Urban Land Surface Processes, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2021MS002744
- Jan Ackmann, Peter Dominik Dueben, Tim N Palmer, Piotr K. Smolarkiewicz (April 2022) Mixed-precision for Linear Solvers in Global Geophysical Flows. DOI: 10.1002/essoar.10511194.1
- Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, Tim Palmer (December 2022) Deep Learning for Verification of Earth-System Parametrisation of Water Bodies. DOI: 10.5194/egusphere-2022-1177
- Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall (July 2022) Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2022MS003016
- Milan Klöwer, Miha Razinger, Juan J. Dominguez, Peter D. Düben, Tim Palmer (March 2022) Compressing atmospheric data into its real information content. DOI: 10.5194/egusphere-egu22-3109
- Zied Ben Bouallègue, Fenwick Cooper, Matthew Chantry, Peter Dueben, Peter Bechtold, irina sandu (May 2022) Statistical modelling of 2m temperature and 10m wind speed forecast errors, ECMWF Technical Memoranda n. 896. DOI: 10.21957/vdcccja3f
- Jan Ackmann, Peter D. Dueben, Tim Palmer, Piotr K. Smolarkiewicz (October 2022) Mixed‐Precision for Linear Solvers in Global Geophysical Flows, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2022MS003148
- Lucy Harris, Andrew T. T. McRae, Matthew Chantry, Peter D. Dueben, Tim N. Palmer (October 2022) A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2022MS003120
- Milan Klöwer, Samuel Hatfield, Matteo Croci, Peter D. Düben, Tim Palmer (March 2022) Fluid simulations accelerated with 16 bits: Approaching 4x speedup on A64FX by squeezing ShallowWaters.jl into Float16. DOI: 10.5194/egusphere-egu22-3095
- 2021
- Simon T. K. Lang, Andrew Dawson, Michail Diamantakis, Peter Dueben, Samuel Hatfield, Martin Leutbecher, Tim Palmer, Fernando Prates, Christopher D. Roberts, Irina Sandu, Nils Wedi (October 2021) More accuracy with less precision, Quarterly Journal of the Royal Meteorological Society n. 741, pp. 4358-4370. DOI: 10.1002/qj.4181
- Milan Klöwer, Sam Hatfield, Matteo Croci, Peter Düben, Tim Palmer (August 2021) Fluid simulations accelerated with 16 bit: Approaching 4x speedup on A64FX by squeezing ShallowWaters.jl into Float16. DOI: 10.1002/essoar.10507472.2
- Niraj Agarwal, D. Kondrashov, P. Dueben, E. Ryzhov, P. Berloff (September 2021) A Comparison of Data‐Driven Approaches to Build Low‐Dimensional Ocean Models, Journal of Advances in Modeling Earth Systems n. 9. DOI: 10.1029/2021MS002537
- Samuel Edward Hatfield, Matthew Chantry, Peter Dominik Dueben, Philippe Lopez, Alan Jon Geer, Tim N Palmer (February 2021) Building tangent-linear and adjoint models for data assimilation with neural networks. DOI: 10.1002/essoar.10506310.1
- Mark John Rodwell, Michail Diamantakis, Peter Dueben, Martin Janousek, Simon Lang, Inna Polichtchouk, Fernando Prates, Chris Roberts, Filip Vána (July 2021) IFS upgrade provides more skilful ensemble forecasts, ECMWF Newsletter, issue 168, pp. 18-23. DOI: 10.21957/m830hnz27r
- Peter Dueben, Umberto Modigliani, Alan Geer, Stephan Siemen, Florian Pappenberger, Peter Bauer, Andy Brown, Martin Palkovic, Baudouin Raoult, Nils Wedi, Vasileios Baousis (January 2021) Machine learning at ECMWF: A roadmap for the next 10 years, ECMWF Technical Memoranda n. 878. DOI: 10.21957/ge7ckgm
- Jan Ackmann, Peter Düben, Tim Palmer, Piotr Smolarkiewicz (March 2021) Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows. DOI: 10.5194/egusphere-egu21-5507
- Christian Zeman, Nils P. Wedi, Peter D. Dueben, Nikolina Ban, Christoph Schär (February 2021) Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing. DOI: 10.5194/gmd-2021-31
- Matthew Chantry, Hannah Christensen, Peter Dueben, Tim Palmer (April 2021) Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences n. 2194, pp. 20200083. DOI: 10.1098/rsta.2020.0083
- Peter Grönquist, Chengyuan Yao, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Shigang Li, Torsten Hoefler (April 2021) Deep learning for post-processing ensemble weather forecasts, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences n. 2194, pp. 20200092. DOI: 10.1098/rsta.2020.0092
- Sam Hatfield, Kristian Mogensen, Peter Dueben, Nils Wedi, Michail Diamantakis (March 2021) Operational Single-Precision Earth-System Modelling at ECMWF. DOI: 10.5194/egusphere-egu21-733
- David Meyer, Robin J. Hogan, Peter D. Dueben, Shannon L. Mason (March 2021) Machine Learning Emulation of 3D Cloud Radiative Effects. DOI: 10.5194/egusphere-egu21-3342
- Matthew Chantry, Sam Hatfield, Peter Duben, Inna Polichtchouk, Tim Palmer (March 2021) Machine learning emulation of gravity wave drag in numerical weather forecasting. DOI: 10.5194/egusphere-egu21-7678
- Thomas Rackow, Nils Wedi, Kristian Mogensen, Peter Dueben, Helge F. Goessling, Jan Hegewald, Christian Kühnlein, Lorenzo Zampieri, Thomas Jung (March 2021) DYAMOND-II simulations with IFS-FESOM2. DOI: 10.5194/egusphere-egu21-9672
- Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, Roberto Ribas (April 2021) Systematic detection of local CH<sub>4</sub> anomalies by combining satellite measurements with high-resolution forecasts, Atmospheric Chemistry and Physics. DOI: 10.5194/acp-21-5117-2021
- Falko JUDT, Daniel KLOCKE, Rosimar RIOS-BERRIOS, Benoit VANNIERE, Florian ZIEMEN, Ludovic AUGER, Joachim BIERCAMP, Christopher BRETHERTON, Xi CHEN, Peter DÜBEN, Cathy HOHENEGGER, Marat KHAIROUTDINOV, Chihiro KODAMA, Luis KORNBLUEH, Shian-Jiann LIN, Masuo NAKANO, Philipp NEUMANN, William PUTMAN, Niklas RÖBER, Malcolm ROBERTS, Masaki SATOH, Ryosuke SHIBUYA, Bjorn STEVENS, Pier Luigi VIDALE, Nils WEDI, Linjiong ZHOU (March 2021) Tropical Cyclones in Global Storm-Resolving Models, Journal of the Meteorological Society of Japan. Ser. II n. 3, pp. 579-602. DOI: 10.2151/jmsj.2021-029
- Maike Sonnewald, Redouane Lguensat, Daniel C Jones, Peter D Dueben, Julien Brajard, V Balaji (July 2021) Bridging observations, theory and numerical simulation of the ocean using machine learning, Environmental Research Letters n. 7, pp. 073008. DOI: 10.1088/1748-9326/ac0eb0
- Sam Hatfield, Matthew Chantry, Peter Dueben, Philippe Lopez, Alan Geer, Tim Palmer (September 2021) Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks, Journal of Advances in Modeling Earth Systems n. 9. DOI: 10.1029/2021MS002521
- 2020
- Peter Düben (July 2020) Review "Necessary conditions for algorithmic tuning of weather prediction models using OpenIFS as an example". DOI: 10.5194/gmd-2020-56-RC1
- Hatfield S., McRae A., Palmer T., Düben P. (March 2020) Single-precision in the tangent-linear and adjoint models of incremental 4D-VAr, Monthly Weather Review. DOI: 10.1175/MWR-D-19-0291.1
- Cooper F.C., Düben P.D., Denis C., Dawson A., Ashwin P. (March 2020) The relationship between numerical precision and forecast lead time in the Lorenz'95 system, Monthly Weather Review. DOI: 10.1175/MWR-D-18-0200.1
- Saffin L., Hatfield S., Düben P., Palmer T. (March 2020) Reduced-precision parametrization: lessons from an intermediate-complexity atmospheric model, Quarterly Journal of the Royal Meteorological Society. DOI: 10.1002/qj.3754
- Peter Bauer, Tiago Quintino, Nils Wedi, Antonino Bonanni, Marcin Chrust, Willem Deconinck, Michail Diamantakis, Peter Dueben, Stephen English, Johannes Flemming, Paddy Gillies, Ioan Hadade, James Hawkes, Mike Hawkins, Olivier Iffrig, Christian Kühnlein, Michael Lange, Peter Lean, Olivier Marsden, Andreas Müller, Sami Saarinen, Domokos Sarmany, Michael Sleigh, Simon Smart, PIOTR SMOLARKIEWICZ, Daniel Thiemert, Giovanni Tumolo, Christian Weihrauch, Cristiano Zanna, Pedro Maciel (March 2020) The ECMWF Scalability Programme: Progress and Plans, ECMWF Technical Memoranda n. 857. DOI: 10.21957/gdit22ulm
- Peter Düben, Nils Wedi, Sami Saarinen, Christian Zeman (March 2020) Global simulations of the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting System. DOI: 10.5194/egusphere-egu2020-19344
- Stephan Rasp, Peter D. Dueben, Sebastian Scher, Jonathan A. Weyn, Soukayna Mouatadid, Nils Thuerey (November 2020) WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting, Journal of Advances in Modeling Earth Systems n. 11. DOI: 10.1029/2020MS002203
- Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, Roberto Ribas (September 2020) Systematic detection of local CH<sub>4</sub> emissions anomalies combining satellite measurements and high-resolution forecasts. DOI: 10.5194/acp-2020-550
- Nils P. Wedi, Inna Polichtchouk, Peter Dueben, Valentine G. Anantharaj, Peter Bauer, Souhail Boussetta, Philip Browne, Willem Deconinck, Wayne Gaudin, Ioan Hadade, Sam Hatfield, Olivier Iffrig, Philippe Lopez, Pedro Maciel, Andreas Mueller, Sami Saarinen, Irina Sandu, Tiago Quintino, Frederic Vitart (November 2020) A Baseline for Global Weather and Climate Simulations at 1 km Resolution, Journal of Advances in Modeling Earth Systems n. 11. DOI: 10.1029/2020MS002192
- M. Klöwer, P. D. Düben, T. N. Palmer (October 2020) Number Formats, Error Mitigation, and Scope for 16‐Bit Arithmetics in Weather and Climate Modeling Analyzed With a Shallow Water Model, Journal of Advances in Modeling Earth Systems n. 10. DOI: 10.1029/2020MS002246
- 2019
- Hatfield S., Chantry M., Düben P., Palmer T. (March 2019) Accelerating high-resolution weather models with deep-learning hardware, Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2019. DOI: 10.1145/3324989.3325711
- Stevens B., Satoh M., Auger L., Biercamp J., Bretherton C.S., Chen X., Düben P., Judt F., Khairoutdinov M., Klocke D., Kodama C., Kornblueh L., Lin S.-J., Neumann P., Putman W.M., Röber N., Shibuya R., Vanniere B., Vidale P.L., Wedi N., Zhou L. (March 2019) DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains, Progress in Earth and Planetary Science. DOI: 10.1186/s40645-019-0304-z
- Neumann P., Düben P., Adamidis P., Bauer P., Brück M., Kornblueh L., Klocke D., Stevens B., Wedi N., Biercamp J. (March 2019) Assessing the scales in numerical weather and climate predictions: Will exascale be the rescue?, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. DOI: 10.1098/rsta.2018.0148
- Peter Düben (November 2019) Review. DOI: 10.5194/gc-2019-22-RC1
- Peter Düben (July 2019) Review of Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model. DOI: 10.5194/gmd-2019-136-RC1
- Peter Düben (April 2019) Review "Scalability and some optimization of the Finite-volumE Sea ice-Ocean Model, Version 2.0 (FESOM2)". DOI: 10.5194/gmd-2018-334-RC1
- Peter Düben (March 2019) Review of "How to use mixed precision in Ocean Models". DOI: 10.5194/gmd-2019-20-RC1
- Peter Düben (March 2019) Review of weather and climate forecasting with neural networks. DOI: 10.5194/gmd-2019-53-RC1
- Chantry M., Thornes T., Palmer T., Düben P. (March 2019) Scale-selective precision for weather and climate forecasting, Monthly Weather Review. DOI: 10.1175/MWR-D-18-0308.1
- Klöwer M., Düben P.D., Palmer T.N. (March 2019) Posits as an alternative to floats for weather and climate models, ACM International Conference Proceeding Series. DOI: 10.1145/3316279.3316281
- Düben P.D., Leutbecher M., Bauer P. (March 2019) New methods for data storage of model output from ensemble simulations, Monthly Weather Review. DOI: 10.1175/MWR-D-18-0170.1
- Satoh M., Stevens B., Judt F., Khairoutdinov M., Lin S.-J., Putman W.M., Düben P. (March 2019) Global Cloud-Resolving Models, Current Climate Change Reports. DOI: 10.1007/s40641-019-00131-0
- 2018
- Thornes T., Düben P., Palmer T. (March 2018) A power law for reduced precision at small spatial scales: Experiments with an SQG model, Quarterly Journal of the Royal Meteorological Society. DOI: 10.1002/qj.3303
- Hatfield S., Subramanian A., Palmer T., Düben P. (March 2018) Improving weather forecast skill through reduced-precision data assimilation, Monthly Weather Review. DOI: 10.1175/MWR-D-17-0132.1
- Dawson A., Düben P.D., MacLeod D.A., Palmer T.N. (March 2018) Reliable low precision simulations in land surface models, Climate Dynamics. DOI: 10.1007/s00382-017-4034-x
- Peter Dueben, Michail Diamantakis, Simon Lang, Sami Saarinen, irina sandu, Nils Wedi, Tomas Wilhelmsson (October 2018) Progress in using single precision in the IFS, ECMWF Newsletter, issue 157, pp. 26-31. DOI: 10.21957/ps2y9gfa2d
- Peter D. Dueben, Peter Bauer (June 2018) Challenges and design choices for global weather and climate models based on machine learning. DOI: 10.5194/gmd-2018-148
- Sam Hatfield, Peter Düben, Matthew Chantry, Keiichi Kondo, Takemasa Miyoshi, Tim Palmer (September 2018) Choosing the Optimal Numerical Precision for Data Assimilation in the Presence of Model Error, Journal of Advances in Modeling Earth Systems n. 9, pp. 2177-2191. DOI: 10.1029/2018MS001341
- Peter D. Düben (November 2018) A New Number Format for Ensemble Simulations, Journal of Advances in Modeling Earth Systems n. 11, pp. 2983-2991. DOI: 10.1029/2018MS001420
- Peter D. Dueben, Peter Bauer (June 2018) Supplementary material to "Challenges and design choices for global weather and climate models based on machine learning". DOI: 10.5194/gmd-2018-148-supplement
- Peter Düben (August 2018) Response to the first round of reviews. DOI: 10.5194/gmd-2018-148-AC1
- 2017
- Düben P.D., Dawson A. (March 2017) An approach to secure weather and climate models against hardware faults, Journal of Advances in Modeling Earth Systems. DOI: 10.1002/2016MS000816
- Targett J.S., Düben P., Luk W. (March 2017) Validating optimisations for chaotic simulations, 2017 27th International Conference on Field Programmable Logic and Applications, FPL 2017. DOI: 10.23919/FPL.2017.8056793
- Váňa F., Düben P., Lang S., Palmer T., Leutbecher M., Salmond D., Carver G. (March 2017) Single precision in weather forecasting models: An evaluation with the IFS, Monthly Weather Review. DOI: 10.1175/MWR-D-16-0228.1
- Russell F.P., Düben P.D., Niu X., Luk W., Palmer T.N. (March 2017) Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures, Computer Physics Communications. DOI: 10.1016/j.cpc.2017.08.011
- Düben P.D., Subramanian A., Dawson A., Palmer T.N. (March 2017) A study of reduced numerical precision to make superparameterization more competitive using a hardware emulator in the OpenIFS model, Journal of Advances in Modeling Earth Systems. DOI: 10.1002/2016MS000862
- Tobias Thornes, Peter Düben, Tim Palmer (January 2017) On the use of scale-dependent precision in Earth System modelling, Quarterly Journal of the Royal Meteorological Society n. 703, pp. 897-908.
- 2016
- Targett J.S., Niu X., Russell F., Luk W., Jeffress S., Duben P. (March 2016) Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations, 2015 International Conference on Field Programmable Technology, FPT 2015. DOI: 10.1109/FPT.2015.7393152
- Filip Vána, Glenn Carver, Simon Lang, Martin Leutbecher, Deborah Salmond, Peter Dueben, Tim Palmer (March 2016) Single-precision IFS, ECMWF Newsletter, issue 148, pp. 20-23. DOI: 10.21957/avq2i3tp
- Andrew Dawson, Peter Düben (November 2016) rpe v5: An emulator for reduced floating-point precision in large numerical simulations. DOI: 10.5194/gmd-2016-247
- 2015
- Düben P.D., Dolaptchiev S.I. (March 2015) Rounding errors may be beneficial for simulations of atmospheric flow: results from the forced 1D Burgers equation, Theoretical and Computational Fluid Dynamics. DOI: 10.1007/s00162-015-0355-8
- Duben P., Parishkrati, Yenugula S., Augustine J., Palem K., Schlachter J., Enz C., Palmer T.N. (March 2015) Opportunities for energy efficient computing: A study of inexact general purpose processors for high-performance and big-data applications, Proceedings -Design, Automation and Test in Europe, DATE. DOI: 10.7873/date.2015.1116
- Düben P.D., Russell F.P., Niu X., Luk W., Palmer T.N. (March 2015) On the use of programmable hardware and reduced numerical precision in earth-system modeling, Journal of Advances in Modeling Earth Systems. DOI: 10.1002/2015MS000494
- Russell F.P., Düben P.D., Niu X., Luk W., Palmer T.N. (March 2015) Architectures and precision analysis for modelling atmospheric variables with chaotic behaviour, Proceedings - 2015 IEEE 23rd Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2015. DOI: 10.1109/FCCM.2015.52
- 2014
- Düben P.D., McNamara H., Palmer T.N. (March 2014) The use of imprecise processing to improve accuracy in weather & climate prediction, Journal of Computational Physics. DOI: 10.1016/j.jcp.2013.10.042
- Düben P.D., Joven J., Lingamneni A., McNamara H., De Micheli G., Palem K.V., Palmer T.N. (March 2014) On the use of inexact, pruned hardware in atmospheric modelling, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. DOI: 10.1098/rsta.2013.0276
- Düben P.D., Palmer T.N. (March 2014) Benchmark tests for numerical weather forecasts on inexact hardware, Monthly Weather Review. DOI: 10.1175/MWR-D-14-00110.1
- Palmer T., Düben P., McNamara H. (March 2014) Stochastic modelling and energy-efficient computing for weather and climate prediction, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. DOI: 10.1098/rsta.2014.0118
- Düben P.D., Korn P. (March 2014) Atmosphere and ocean modeling on grids of variable resolution-A 2D case study, Monthly Weather Review. DOI: 10.1175/MWR-D-13-00217.1
- 2012
- Düben P.D., Korn P., Aizinger V. (March 2012) A discontinuous/continuous low order finite element shallow water model on the sphere, Journal of Computational Physics. DOI: 10.1016/j.jcp.2011.11.018
- 2009
- Düben P., Homeier D., Jansen K., Mesterhazy D., Münster G. (March 2009) Monte carlo approach to turbulence, Proceedings of Science.
- 2008
- Düben P., Homeier D., Jansen K., Mesterhazy D., Münster G., Urbach C. (March 2008) Monte Carlo simulations of the randomly forced Burgers equation, EPL. DOI: 10.1209/0295-5075/84/40002