Challenges and design choices for global weather and climate models based on machine learning von Dueben, Peter D, Bauer, Peter

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WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting von Rasp, Stephan, Dueben, Peter D., Scher, Sebastian, Weyn, Jonathan A., Mouatadid, Soukayna, Thuerey, Nils

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Bridging observations, theory and numerical simulation of the ocean using machine learning von Sonnewald, Maike, Lguensat, Redouane, Jones, Daniel C, Dueben, Peter D, Brajard, Julien, Balaji, V

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The digital revolution of Earth-system science von Bauer, Peter, Dueben, Peter D, Hoefler, Torsten, Quintino, Tiago, Schulthess, Thomas C, Wedi, Nils P

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Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting von Chantry, Matthew, Hatfield, Sam, Dueben, Peter, Polichtchouk, Inna, Palmer, Tim

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A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts von Harris, Lucy, McRae, Andrew T. T., Chantry, Matthew, Dueben, Peter D., Palmer, Tim N.

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Machine Learning Emulation of 3D Cloud Radiative Effects von Meyer, David, Hogan, Robin J., Dueben, Peter D., Mason, Shannon L.

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Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks von Hatfield, Sam, Chantry, Matthew, Dueben, Peter, Lopez, Philippe, Geer, Alan, Palmer, Tim

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Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing von Zeman, Christian, Wedi, Nils P., Dueben, Peter D., Ban, Nikolina, Schar, Christoph

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Mixed‐Precision for Linear Solvers in Global Geophysical Flows von Ackmann, Jan, Dueben, Peter D., Palmer, Tim, Smolarkiewicz, Piotr K.

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A Baseline for Global Weather and Climate Simulations at 1 km Resolution von Wedi, Nils P., Polichtchouk, Inna, Dueben, Peter, Anantharaj, Valentine G., Bauer, Peter, Boussetta, Souhail, Browne, Philip, Deconinck, Willem, Gaudin, Wayne, Hadade, Ioan, Hatfield, Sam, Iffrig, Olivier, Lopez, Philippe, Maciel, Pedro, Mueller, Andreas, Saarinen, Sami, Sandu, Irina, Quintino, Tiago, Vitart, Frederic

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Machine Learning Emulation of Urban Land Surface Processes von Meyer, David, Grimmond, Sue, Dueben, Peter, Hogan, Robin, Reeuwijk, Maarten

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Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System von Laloyaux, Patrick, Kurth, Thorsten, Dueben, Peter Dominik, Hall, David

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WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models von Rasp, Stephan, Hoyer, Stephan, Merose, Alexander, Langmore, Ian, Battaglia, Peter, Russell, Tyler, Sanchez‐Gonzalez, Alvaro, Yang, Vivian, Carver, Rob, Agrawal, Shreya, Chantry, Matthew, Ben Bouallegue, Zied, Dueben, Peter, Bromberg, Carla, Sisk, Jared, Barrington, Luke, Bell, Aaron, Sha, Fei

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Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI von Chantry, Matthew, Christensen, Hannah, Dueben, Peter, Palmer, Tim

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A discontinuous/continuous low order finite element shallow water model on the sphere von Düben, Peter D., Korn, Peter, Aizinger, Vadym

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ESA-ECMWF Report on recent progress and research directions in machine learning for Earth System observation and prediction von Schneider, Rochelle, Bonavita, Massimo, Geer, Alan, Arcucci, Rossella, Dueben, Peter, Vitolo, Claudia, Le Saux, Bertrand, Demir, Begüm, Mathieu, Pierre-Philippe

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On the use of programmable hardware and reduced numerical precision in earth‐system modeling von Düben, Peter D., Russell, Francis P., Niu, Xinyu, Luk, Wayne, Palmer, T. N.

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Deep learning for post-processing ensemble weather forecasts von Gronquist, Peter, Yao, Chengyuan, Ben-Nun, Tal, Dryden, Nikoli, Dueben, Peter, Li, Shigang, Hoefler, Torsten

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TRU-NET: a deep learning approach to high resolution prediction of rainfall von Adewoyin, Rilwan A., Dueben, Peter, Watson, Peter, He, Yulan, Dutta, Ritabrata

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