Articles under review
Bjorn Stevens, Masaki Satoh, Ludovic Auger, Joachim Biercamp, Christopher Bretherton, Xi Chen, Peter Düben, Falko Judt, Marat Khairoutdinov, Daniel Klocke, Chihiro Kodama, Luis Kornblueh, Shian-Jiann Lin, William Putman, Shibuya Ryosuke, Philipp Neumann, Nicolas Röber, Bennoit Vannier, Pier-Luigi Vidale, Nils Wedi, Linjiong Zhou. DYAMOND: The DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Submitted to Progress in Earth and Planetary Science, 2019.
Sam Hatfield, Matthew Chantry, Peter Dueben, Tim Palmer. Accelerating high-resolution weather and climate models with deep-learning hardware. Submitted to PASC, 2019.
 Milan Kloewer, Peter D. Dueben, Tim Palmer. Posits as an alternative to floats for weather and climate models. Accepted in CoNGA, 2019.
 Aneesh C. Subramanian, Stephan Juricke, Peter D. Dueben and Tim Palmer. A Stochastic Representation of Sub-Grid Uncertainty for Dynamical Core Development. Accepted in Bulletin of the American Meteorological Society, 2019.
 Peter D. Dueben. A new number format for ensemble simulations. Accepted in Journal of Advances in Modeling Earth Systems, 2018
 Peter D. Dueben, Martin Leutbecher and Peter Bauer. New methods for data storage of model output from ensemble simulations. Accepted in Monthly Weather Review, 2018
 Matthew Chantry, Tobias Thornes, Peter D. Dueben and Tim Palmer. Scale-selective precision for weather and climate forecasting. Accepted in Monthly Weather Review, 2018
 Philipp Neumann, Peter D. Dueben, Panagiotis Adamidis, Peter Bauer, Matthias Brueck, Luis Kornblueh, Daniel Klocke, Bjorn Stevens, Nils Wedi and Joachim Biercamp. Assessing the scales in numerical weather and climate predictions: Will Exascale be the rescue? Accepted in Philosophical Transactions of the Royal Society A, 2018
 Peter D. Dueben and Peter Bauer. Challenges and design choices for global weather and climate models based on machine learning. Geoscientific Model Development, 11, 10, 3999-4009, 2018
 Samuel Edward Hatfield, Peter D. Dueben, Matthew Chantry, Keiichi Kondo, Takemasa Miyoshi, Tim Palmer. Choosing the optimal numerical precision for data assimilation in the presence of model error. Journal of Advances in Modeling Earth Systems, 10, 2177-2191, 2018
 Tobias Thornes, Peter Dueben, Tim Palmer. A Power Law for Reduced Precision at Small Spatial Scales: Experiments with an SQG Model. Quarterly Journal of the Royal Meteorological Society, 144:1179-1188, 2018
 Samuel Edward Hatfield, Aneesh Subramanian, Tim Palmer, Peter D. Dueben. Improving weather forecast skill through reduced precision data assimilation. Monthly Weather Review, 146 (1), 49-62, 2018
 Francis P. Russell, Peter D. Dueben, Xinyu Niu, Wayne Luk, T.N. Palmer. Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures. Computer Physics Communications, 221, 160-173, 2017
 Targett, JS, Dueben, X, Luk, W. Validationg optimisations for chaotic simulations, Field Programmable Logic and Application (FPL), 2017
 Andrew Dawson and Peter D. Dueben. rpe v5: An emulator for reduced floating-point precision in large numerical simulations. Geoscientific Model Development, 10 (6), 2221-2230, 2017
 Stephen Jeffress, Peter D. Dueben, T.N. Palmer. Bitwise Efficiency in Chaotic Models. Proceedings A of the Royal Society A, 473 (2205), 20170144, 2017
 Peter D. Dueben and A. Dawson. An approach to secure weather and climate models against hardware faults. Journal of Advances in Modeling Earth Systems, 9 (1), 501-513, 2017
 Peter D. Dueben, A. Subramanian, A. Dawson and T. N. Palmer. A study of reduced precision to make superparametrisation more competitive using a hardware emulator in the OpenIFS model. Journal of Advances in Modeling Earth Systems, 9 (1), 566-584, 2017
 Andrew Dawson, Peter D. Dueben, David MacLeod and Tim Palmer. Reliable low precision simulations in land surface models. Climate Dynamics, 1-10, 2017.
 Tobias Thornes, Peter D. Dueben, and Tim Palmer. On the use of scale-dependent precision in Earth System modelling. Quarterly Journal of the Royal Meteorological Society, 143: 897-908, 2017
 Filip Váňa, Peter D. Dueben, Simon Lang, Tim Palmer, Martin Leutbecher, Deborah Salmond, and Glenn Carver. Single precision in weather forecasting models. Monthly Weather Review, 145 (2), 495-502, 2017
 Peter D. Dueben, Francis P. Russell, Xinyu Niu, Wayne Luk, and T. N. Palmer. On the use of programmable hardware and reduced numerical precision in earth-system modeling. Journal of Advances in Modeling Earth Systems, 7(3):1393–1408, 2015
 Peter D. Dueben and Stamen I. Dolaptchiev. Rounding errors may be beneficial for simulations of atmospheric flow: Results from the forced 1D Burgers equation. Theoretical and Computational Fluid Dynamics, 29(4):311–328, 2015
 Peter D. Dueben, Jeremy Schlachter, Parishkrati, Sreelatha Yenugula, John Augustine, Christian Enz, K. Palem, and T. N. Palmer. Opportunities for energy efficient computing: A study of inexact general purpose processors for high-performance and big-data applications. Design Automation and Test in Europe (DATE), pages 764–769, 2015
 Francis P. Russell, Peter D. Dueben, Xinyu Niu, Wayne Luk, and T.N. Palmer. Architectures and precision analysis for modelling atmospheric variables with chaotic behaviour. IEEE 23rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 171–178, 2015
 James Targett, Stephen Jeffress, Xinyu Niu, Francis Russell, Peter D. Dueben, and Wayne Luk. Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations. Proceedings of the International Conference on Field Programmable Technology (FPT), 2015
 Peter D. Dueben and T. N. Palmer. Benchmark tests for numerical weather forecasts on inexact hardware. Monthly Weather Review, 142:3809–3829, 2014
 Peter D. Dueben, Jaume Joven, Avinash Lingamneni, Hugh McNamara, Giovanni De Micheli, Krishna V. Palem, and T. N. Palmer. On the use of inexact, pruned hardware in atmospheric modelling. Philosophical Transactions of the Royal Society A, 372(2018), 2014
 Peter D. Dueben and Peter Korn. Atmosphere and ocean modeling on grids of variable resolution - a 2d case study. Monthly Weather Review, 142:1997–2017, 2014
 Tim Palmer, Peter D. Dueben, and Hugh McNamara. Stochastic modelling and energy-efficient computing for weather and climate prediction. Philosophical Transactions of the Royal Society A, 372(2018), 2014
 Peter D. Dueben, Hugh McNamara, and T.N. Palmer. The use of imprecise processing to improve accuracy in weather & climate prediction. Journal of Computational Physics, 271(0):2–18, 2014.
 Peter D. Dueben, Peter Korn, and Vadym Aizinger. A discontinuous/continuous low order finite element shallow water model on the sphere. Journal of Computational Physics, 231(6):2396–2413, 2012
 Peter D. Dueben, D. Homeier, G. Münster, K. Jansen, and D. Mesterhazy. Monte Carlo approach to turbulence. 27. International Symposium on Lattice Field Theory, Beijing, China, 41, 2009
 Peter D. Dueben, D. Homeier, K. Jansen, D. Mesterhazy, G. Münster, and C. Urbach. Monte Carlo simulations of the randomly forced burgers equation. Europhysics Letters, 84(4):40002, 2008
Main and co-authors of deliverables 2.2, 2.6, 2.7 and 2.8 of the ESiWACE H2020 project.
Peter D. Dueben, Michail Diamantakis, Simon Lang, Sami Saarinen, Irina Sandu, Nils Wedi and Tomas
Wilhelmson. Progress in using single precision in the IFS. ECMWF Newsletter, 2018.
Peter D. Dueben. Speeding up weather forecasts by using single precision computer calculations. ECMWF Science blog, 2018.
Filip Vana, Glenn Carver, Peter D. Dueben, Simon Lang, Tim Palmer, Martin Leutbecher, and Deborah Salmond. Single-precision IFS. ECMWF Newsletter, 148, 2016
Glenn Carver and Peter D. Dueben. Third OpenIFS user meeting held at ECMWF. ECMWF Newsletter, 144, 2015
Peter D. Dueben, Stephen Jeffress, and T. N. Palmer. Inexact hardware for numerical simulations of weather and climate: What is possible, why it is useful and how to do it. Proceedings of the Emerging Technology Conference (EMIT) 2015, 2015
Peter D. Dueben and Peter Korn. A study on boundary separation in an idealized ocean model. arXiv:1507.03080, 2015
Peter D. Dueben and Peter Korn. The representation of boundary currents in a finite element shallow water model. arXiv:1502.00784, 2015