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1. Towards Specialized Supercomputers for Climate Sciences: Computational Requirements of the Icosahedral Nonhydrostatic Weather and Climate Model

Author

Hoefler, Torsten, Calotoiu, Alexandru, Dipankar, Anurag, Schulthess, Thomas, Lapillonne, Xavier, and Fuhrer, Oliver

Subjects
Physics - Atmospheric and Oceanic Physics, Computer Science - Hardware Architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Physics - Computational Physics
Abstract

We discuss the computational challenges and requirements for high-resolution climate simulations using the Icosahedral Nonhydrostatic Weather and Climate Model (ICON). We define a detailed requirements model for ICON which emphasizes the need for specialized supercomputers to accurately predict climate change impacts and extreme weather events. Based on the requirements model, we outline computational demands for km-scale simulations, and suggests machine learning techniques to enhance model accuracy and efficiency. Our findings aim to guide the design of future supercomputers for advanced climate science.

Published
2024

2. Earth Virtualization Engines -- A Technical Perspective

Author

Hoefler, Torsten, Stevens, Bjorn, Prein, Andreas F., Baehr, Johanna, Schulthess, Thomas, Stocker, Thomas F., Taylor, John, Klocke, Daniel, Manninen, Pekka, Forster, Piers M., Kölling, Tobias, Gruber, Nicolas, Anzt, Hartwig, Frauen, Claudia, Ziemen, Florian, Klöwer, Milan, Kashinath, Karthik, Schär, Christoph, Fuhrer, Oliver, and Lawrence, Bryan N.

Subjects
Physics - Atmospheric and Oceanic Physics, Computer Science - Artificial Intelligence, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Computers and Society, Physics - Physics and Society
Abstract

Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change. EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of climate projections. At their core, EVEs offer a federated data layer that enables simple and fast access to exabyte-sized climate data through simple interfaces. In this article, we summarize the technical challenges and opportunities for developing EVEs, and argue that they are essential for addressing the consequences of climate change.

Published
2023

3. Productive Performance Engineering for Weather and Climate Modeling with Python

Author

Ben-Nun, Tal, Groner, Linus, Deconinck, Florian, Wicky, Tobias, Davis, Eddie, Dahm, Johann, Elbert, Oliver D., George, Rhea, McGibbon, Jeremy, Trümper, Lukas, Wu, Elynn, Fuhrer, Oliver, Schulthess, Thomas, and Hoefler, Torsten

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Earth system models are developed with a tight coupling to target hardware, often containing specialized code predicated on processor characteristics. This coupling stems from using imperative languages that hard-code computation schedules and layout. We present a detailed account of optimizing the Finite Volume Cubed-Sphere Dynamical Core (FV3), improving productivity and performance. By using a declarative Python-embedded stencil domain-specific language and data-centric optimization, we abstract hardware-specific details and define a semi-automated workflow for analyzing and optimizing weather and climate applications. The workflow utilizes both local and full-program optimization, as well as user-guided fine-tuning. To prune the infeasible global optimization space, we automatically utilize repeating code motifs via a novel transfer tuning approach. On the Piz Daint supercomputer, we scale to 2,400 GPUs, achieving speedups of up to 3.92x over the tuned production implementation at a fraction of the original code.

Published
2022

4. Domain-Specific Multi-Level IR Rewriting for GPU

Author

Gysi, Tobias, Müller, Christoph, Zinenko, Oleksandr, Herhut, Stephan, Davis, Eddie, Wicky, Tobias, Fuhrer, Oliver, Hoefler, Torsten, and Grosser, Tobias

Subjects
Computer Science - Programming Languages
Abstract

Traditional compilers operate on a single generic intermediate representation (IR). These IRs are usually low-level and close to machine instructions. As a result, optimizations relying on domain-specific information are either not possible or require complex analysis to recover the missing information. In contrast, multi-level rewriting instantiates a hierarchy of dialects (IRs), lowers programs level-by-level, and performs code transformations at the most suitable level. We demonstrate the effectiveness of this approach for the weather and climate domain. In particular, we develop a prototype compiler and design stencil- and GPU-specific dialects based on a set of newly introduced design principles. We find that two domain-specific optimizations (500 lines of code) realized on top of LLVM's extensible MLIR compiler infrastructure suffice to outperform state-of-the-art solutions. In essence, multi-level rewriting promises to herald the age of specialized compilers composed from domain- and target-specific dialects implemented on top of a shared infrastructure., Comment: 12 pages, 16 figures

Published
2020

6. Prospects for Kilometer-Scale Climate Models

Author

Schär, Christoph, Fuhrer, Oliver, Arteaga, Andrea, Ban, Nikolina, Charpilloz, Christophe, Di Girolamo, Salvatore, Hentgen, Laureline, Hoefler, Torsten, Lapillonne, Xavier, Leutwyler, David, Osterried, Katherine, Panosetti, Davide, Rüdisühli, Stefan, Schlemmer, Linda, Schulthess, Thomas, Sprenger, Michael, Ubbiali, Stefano, and Wernli, Heini

Published
2021

9. Kilometer-Scale Climate Models : Prospects and Challenges

Author

Schär, Christoph, Fuhrer, Oliver, Arteaga, Andrea, Ban, Nikolina, Charpilloz, Christophe, Di Girolamo, Salvatore, Hentgen, Laureline, Hoefler, Torsten, Lapillonne, Xavier, Leutwyler, David, Osterried, Katherine, Panosetti, Davide, Rüdisühli, Stefan, Schlemmer, Linda, Schulthess, Thomas C., Sprenger, Michael, Ubbiali, Stefano, and Wernli, Heini

Published
2020

10. Domain Decomposition Coupling of FV4 and DDFV for Numerical Weather Prediction

Author

Fuhrer, Oliver, Gander, Martin J., Moody, Sandie, Barth, Timothy J., Series Editor, Griebel, Michael, Series Editor, Keyes, David E., Series Editor, Nieminen, Risto M., Series Editor, Roose, Dirk, Series Editor, Schlick, Tamar, Series Editor, Haynes, Ronald, editor, MacLachlan, Scott, editor, Cai, Xiao-Chuan, editor, Halpern, Laurence, editor, Kim, Hyea Hyun, editor, Klawonn, Axel, editor, and Widlund, Olof, editor

Published
2020
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12. Earth Virtualization Engines (EVE)

Author

Stevens, Bjorn, Adami, Stefan, Ali, Tariq, Anzt, Hartwig, Aslan, Zafer, Attinger, Sabine, Bäck, Jaana, Baehr, Johanna, Bauer, Peter, Bernier, Natacha, Bishop, Bob, Bockelmann, Hendryk, Bony, Sandrine, Brasseur, Guy, Bresch, David N., Breyer, Sean, Brunet, Gilbert, Buttigieg, Pier Luigi, Cao, Junji, Castet, Christelle, Cheng, Yafang, Dey Choudhury, Ayantika, Coen, Deborah, Crewell, Susanne, Dabholkar, Atish, Dai, Qing, Doblas-Reyes, Francisco, Durran, Dale, El Gaidi, Ayoub, Ewen, Charlie, Exarchou, Eleftheria, Eyring, Veronika, Falkinhoff, Florencia, Farrell, David, Forster, Piers M., Frassoni, Ariane, Frauen, Claudia, Fuhrer, Oliver, Gani, Shahzad, Gerber, Edwin, Goldfarb, Debra, Grieger, Jens, Gruber, Nicolas, Hazeleger, Wilco, Herken, Rolf, Hewitt, Chris, Hoefler, Torsten, Hsu, Huang Hsiung, Jacob, Daniela, Jahn, Alexandra, Jakob, Christian, Jung, Thomas, Kadow, Christopher, Kang, In Sik, Kang, Sarah, Kashinath, Karthik, Kleinen-Von Königslöw, Katharina, Klocke, Daniel, Kloenne, Uta, Klöwer, Milan, Kodama, Chihiro, Kollet, Stefan, Kölling, Tobias, Kontkanen, Jenni, Kopp, Steve, Koran, Michal, Kulmala, Markku, Lappalainen, Hanna, Latifi, Fakhria, Lawrence, Bryan, Lee, June Yi, Lejeun, Quentin, Lessig, Christian, Li, Chao, Lippert, Thomas, Luterbacher, Jürg, Manninen, Pekka, Marotzke, Jochem, Matsouoka, Satoshi, Merchant, Charlotte, Messmer, Peter, Michel, Gero, Michielsen, Kristel, Miyakawa, Tomoki, Müller, Jens, Munir, Ramsha, Narayanasetti, Sandeep, Ndiaye, Ousmane, Nobre, Carlos, Oberg, Achim, Oki, Riko, Özkan-Haller, Tuba, Palmer, Tim, Posey, Stan, Prein, Andreas, Primus, Odessa, Pritchard, Mike, Pullen, Julie, Putrasahan, Dian, Quaas, Johannes, Raghavan, Krishnan, Ramaswamy, Venkatachalam, Rapp, Markus, Rauser, Florian, Reichstein, Markus, Revi, Aromar, Saluja, Sonakshi, Satoh, Masaki, Schemann, Vera, Schemm, Sebastian, Schnadt Poberaj, Christina, Schulthess, Thomas, Senior, Cath, Shukla, Jagadish, Singh, Manmeet, Slingo, Julia, Sobel, Adam, Solman, Silvina, Spitzer, Jenna, Stier, Philip, Stocker, Thomas, Strock, Sarah, Su, Hang, Taalas, Petteri, Taylor, John, Tegtmeier, Susann, Teutsch, Georg, Tompkins, Adrian, Ulbrich, Uwe, Vidale, Pier Luigi, Wu, Chien Ming, Xu, Hao, Zaki, Najibullah, Zanna, Laure, Zhou, Tianjun, Ziemen, Florian, Stevens, Bjorn, Adami, Stefan, Ali, Tariq, Anzt, Hartwig, Aslan, Zafer, Attinger, Sabine, Bäck, Jaana, Baehr, Johanna, Bauer, Peter, Bernier, Natacha, Bishop, Bob, Bockelmann, Hendryk, Bony, Sandrine, Brasseur, Guy, Bresch, David N., Breyer, Sean, Brunet, Gilbert, Buttigieg, Pier Luigi, Cao, Junji, Castet, Christelle, Cheng, Yafang, Dey Choudhury, Ayantika, Coen, Deborah, Crewell, Susanne, Dabholkar, Atish, Dai, Qing, Doblas-Reyes, Francisco, Durran, Dale, El Gaidi, Ayoub, Ewen, Charlie, Exarchou, Eleftheria, Eyring, Veronika, Falkinhoff, Florencia, Farrell, David, Forster, Piers M., Frassoni, Ariane, Frauen, Claudia, Fuhrer, Oliver, Gani, Shahzad, Gerber, Edwin, Goldfarb, Debra, Grieger, Jens, Gruber, Nicolas, Hazeleger, Wilco, Herken, Rolf, Hewitt, Chris, Hoefler, Torsten, Hsu, Huang Hsiung, Jacob, Daniela, Jahn, Alexandra, Jakob, Christian, Jung, Thomas, Kadow, Christopher, Kang, In Sik, Kang, Sarah, Kashinath, Karthik, Kleinen-Von Königslöw, Katharina, Klocke, Daniel, Kloenne, Uta, Klöwer, Milan, Kodama, Chihiro, Kollet, Stefan, Kölling, Tobias, Kontkanen, Jenni, Kopp, Steve, Koran, Michal, Kulmala, Markku, Lappalainen, Hanna, Latifi, Fakhria, Lawrence, Bryan, Lee, June Yi, Lejeun, Quentin, Lessig, Christian, Li, Chao, Lippert, Thomas, Luterbacher, Jürg, Manninen, Pekka, Marotzke, Jochem, Matsouoka, Satoshi, Merchant, Charlotte, Messmer, Peter, Michel, Gero, Michielsen, Kristel, Miyakawa, Tomoki, Müller, Jens, Munir, Ramsha, Narayanasetti, Sandeep, Ndiaye, Ousmane, Nobre, Carlos, Oberg, Achim, Oki, Riko, Özkan-Haller, Tuba, Palmer, Tim, Posey, Stan, Prein, Andreas, Primus, Odessa, Pritchard, Mike, Pullen, Julie, Putrasahan, Dian, Quaas, Johannes, Raghavan, Krishnan, Ramaswamy, Venkatachalam, Rapp, Markus, Rauser, Florian, Reichstein, Markus, Revi, Aromar, Saluja, Sonakshi, Satoh, Masaki, Schemann, Vera, Schemm, Sebastian, Schnadt Poberaj, Christina, Schulthess, Thomas, Senior, Cath, Shukla, Jagadish, Singh, Manmeet, Slingo, Julia, Sobel, Adam, Solman, Silvina, Spitzer, Jenna, Stier, Philip, Stocker, Thomas, Strock, Sarah, Su, Hang, Taalas, Petteri, Taylor, John, Tegtmeier, Susann, Teutsch, Georg, Tompkins, Adrian, Ulbrich, Uwe, Vidale, Pier Luigi, Wu, Chien Ming, Xu, Hao, Zaki, Najibullah, Zanna, Laure, Zhou, Tianjun, and Ziemen, Florian

Abstract

To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.

Published
2024

13. Earth Virtualization Engines (EVE)

Author

Faculteit Geowetenschappen, Stevens, Bjorn, Adami, Stefan, Ali, Tariq, Anzt, Hartwig, Aslan, Zafer, Attinger, Sabine, Bäck, Jaana, Baehr, Johanna, Bauer, Peter, Bernier, Natacha, Bishop, Bob, Bockelmann, Hendryk, Bony, Sandrine, Brasseur, Guy, Bresch, David N., Breyer, Sean, Brunet, Gilbert, Buttigieg, Pier Luigi, Cao, Junji, Castet, Christelle, Cheng, Yafang, Dey Choudhury, Ayantika, Coen, Deborah, Crewell, Susanne, Dabholkar, Atish, Dai, Qing, Doblas-Reyes, Francisco, Durran, Dale, El Gaidi, Ayoub, Ewen, Charlie, Exarchou, Eleftheria, Eyring, Veronika, Falkinhoff, Florencia, Farrell, David, Forster, Piers M., Frassoni, Ariane, Frauen, Claudia, Fuhrer, Oliver, Gani, Shahzad, Gerber, Edwin, Goldfarb, Debra, Grieger, Jens, Gruber, Nicolas, Hazeleger, Wilco, Herken, Rolf, Hewitt, Chris, Hoefler, Torsten, Hsu, Huang Hsiung, Jacob, Daniela, Jahn, Alexandra, Jakob, Christian, Jung, Thomas, Kadow, Christopher, Kang, In Sik, Kang, Sarah, Kashinath, Karthik, Kleinen-Von Königslöw, Katharina, Klocke, Daniel, Kloenne, Uta, Klöwer, Milan, Kodama, Chihiro, Kollet, Stefan, Kölling, Tobias, Kontkanen, Jenni, Kopp, Steve, Koran, Michal, Kulmala, Markku, Lappalainen, Hanna, Latifi, Fakhria, Lawrence, Bryan, Lee, June Yi, Lejeun, Quentin, Lessig, Christian, Li, Chao, Lippert, Thomas, Luterbacher, Jürg, Manninen, Pekka, Marotzke, Jochem, Matsouoka, Satoshi, Merchant, Charlotte, Messmer, Peter, Michel, Gero, Michielsen, Kristel, Miyakawa, Tomoki, Müller, Jens, Munir, Ramsha, Narayanasetti, Sandeep, Ndiaye, Ousmane, Nobre, Carlos, Oberg, Achim, Oki, Riko, Özkan-Haller, Tuba, Palmer, Tim, Posey, Stan, Prein, Andreas, Primus, Odessa, Pritchard, Mike, Pullen, Julie, Putrasahan, Dian, Quaas, Johannes, Raghavan, Krishnan, Ramaswamy, Venkatachalam, Rapp, Markus, Rauser, Florian, Reichstein, Markus, Revi, Aromar, Saluja, Sonakshi, Satoh, Masaki, Schemann, Vera, Schemm, Sebastian, Schnadt Poberaj, Christina, Schulthess, Thomas, Senior, Cath, Shukla, Jagadish, Singh, Manmeet, Slingo, Julia, Sobel, Adam, Solman, Silvina, Spitzer, Jenna, Stier, Philip, Stocker, Thomas, Strock, Sarah, Su, Hang, Taalas, Petteri, Taylor, John, Tegtmeier, Susann, Teutsch, Georg, Tompkins, Adrian, Ulbrich, Uwe, Vidale, Pier Luigi, Wu, Chien Ming, Xu, Hao, Zaki, Najibullah, Zanna, Laure, Zhou, Tianjun, Ziemen, Florian, Faculteit Geowetenschappen, Stevens, Bjorn, Adami, Stefan, Ali, Tariq, Anzt, Hartwig, Aslan, Zafer, Attinger, Sabine, Bäck, Jaana, Baehr, Johanna, Bauer, Peter, Bernier, Natacha, Bishop, Bob, Bockelmann, Hendryk, Bony, Sandrine, Brasseur, Guy, Bresch, David N., Breyer, Sean, Brunet, Gilbert, Buttigieg, Pier Luigi, Cao, Junji, Castet, Christelle, Cheng, Yafang, Dey Choudhury, Ayantika, Coen, Deborah, Crewell, Susanne, Dabholkar, Atish, Dai, Qing, Doblas-Reyes, Francisco, Durran, Dale, El Gaidi, Ayoub, Ewen, Charlie, Exarchou, Eleftheria, Eyring, Veronika, Falkinhoff, Florencia, Farrell, David, Forster, Piers M., Frassoni, Ariane, Frauen, Claudia, Fuhrer, Oliver, Gani, Shahzad, Gerber, Edwin, Goldfarb, Debra, Grieger, Jens, Gruber, Nicolas, Hazeleger, Wilco, Herken, Rolf, Hewitt, Chris, Hoefler, Torsten, Hsu, Huang Hsiung, Jacob, Daniela, Jahn, Alexandra, Jakob, Christian, Jung, Thomas, Kadow, Christopher, Kang, In Sik, Kang, Sarah, Kashinath, Karthik, Kleinen-Von Königslöw, Katharina, Klocke, Daniel, Kloenne, Uta, Klöwer, Milan, Kodama, Chihiro, Kollet, Stefan, Kölling, Tobias, Kontkanen, Jenni, Kopp, Steve, Koran, Michal, Kulmala, Markku, Lappalainen, Hanna, Latifi, Fakhria, Lawrence, Bryan, Lee, June Yi, Lejeun, Quentin, Lessig, Christian, Li, Chao, Lippert, Thomas, Luterbacher, Jürg, Manninen, Pekka, Marotzke, Jochem, Matsouoka, Satoshi, Merchant, Charlotte, Messmer, Peter, Michel, Gero, Michielsen, Kristel, Miyakawa, Tomoki, Müller, Jens, Munir, Ramsha, Narayanasetti, Sandeep, Ndiaye, Ousmane, Nobre, Carlos, Oberg, Achim, Oki, Riko, Özkan-Haller, Tuba, Palmer, Tim, Posey, Stan, Prein, Andreas, Primus, Odessa, Pritchard, Mike, Pullen, Julie, Putrasahan, Dian, Quaas, Johannes, Raghavan, Krishnan, Ramaswamy, Venkatachalam, Rapp, Markus, Rauser, Florian, Reichstein, Markus, Revi, Aromar, Saluja, Sonakshi, Satoh, Masaki, Schemann, Vera, Schemm, Sebastian, Schnadt Poberaj, Christina, Schulthess, Thomas, Senior, Cath, Shukla, Jagadish, Singh, Manmeet, Slingo, Julia, Sobel, Adam, Solman, Silvina, Spitzer, Jenna, Stier, Philip, Stocker, Thomas, Strock, Sarah, Su, Hang, Taalas, Petteri, Taylor, John, Tegtmeier, Susann, Teutsch, Georg, Tompkins, Adrian, Ulbrich, Uwe, Vidale, Pier Luigi, Wu, Chien Ming, Xu, Hao, Zaki, Najibullah, Zanna, Laure, Zhou, Tianjun, and Ziemen, Florian

Published
2024

19. Earth Virtualization Engines: A Technical Perspective

Author

Hoefler, Torsten, primary, Stevens, Bjorn, additional, Prein, Andreas F., additional, Baehr, Johanna, additional, Schulthess, Thomas, additional, Stocker, Thomas F., additional, Taylor, John, additional, Klocke, Daniel, additional, Manninen, Pekka, additional, Forster, Piers M., additional, Kölling, Tobias, additional, Gruber, Nicolas, additional, Anzt, Hartwig, additional, Frauen, Claudia, additional, Ziemen, Florian, additional, Klöwer, Milan, additional, Kashinath, Karthik, additional, Schär, Christoph, additional, Fuhrer, Oliver, additional, and Lawrence, Bryan N., additional

Published
2023
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20. Productive Performance Engineering for Weather and Climate Modeling with Python

Author

Ben-Nun, Tal, primary, Groner, Linus, additional, Deconinck, Florian, additional, Wicky, Tobias, additional, Davis, Eddie, additional, Dahm, Johann, additional, Elbert, Oliver D., additional, George, Rhea, additional, McGibbon, Jeremy, additional, Trümper, Lukas, additional, Wu, Elynn, additional, Fuhrer, Oliver, additional, Schulthess, Thomas, additional, and Hoefler, Torsten, additional

Published
2022
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23. Pace v0.2: a Python-based performance-portable atmospheric model.

Author

Dahm, Johann, Davis, Eddie, Deconinck, Florian, Elbert, Oliver, George, Rhea, McGibbon, Jeremy, Wicky, Tobias, Wu, Elynn, Kung, Christopher, Ben-Nun, Tal, Harris, Lucas, Groner, Linus, and Fuhrer, Oliver

Subjects
SUPERCOMPUTERS, ATMOSPHERIC models, PYTHON programming language, MOORE'S law, SOFTWARE productivity, MACHINE learning, FORTRAN
Abstract

Progress in leveraging current and emerging high-performance computing infrastructures using traditional weather and climate models has been slow. This has become known more broadly as the software productivity gap. With the end of Moore's law driving forward rapid specialization of hardware architectures, building simulation codes on a low-level language with hardware-specific optimizations is a significant risk. As a solution, we present Pace, an implementation of the nonhydrostatic FV3 dynamical core and GFDL cloud microphysics scheme which is entirely Python-based. In order to achieve high performance on a diverse set of hardware architectures, Pace is written using the GT4Py domain-specific language. We demonstrate that with this approach we can achieve portability and performance, while significantly improving the readability and maintainability of the code as compared to the Fortran reference implementation. We show that Pace can run at scale on leadership-class supercomputers and achieve performance speeds 3.5–4 times faster than the Fortran code on GPU-accelerated supercomputers. Furthermore, we demonstrate how a Python-based simulation code facilitates existing or enables entirely new use cases and workflows. Pace demonstrates how a high-level language can insulate us from disruptive changes, provide a more productive development environment, and facilitate the integration with new technologies such as machine learning. [ABSTRACT FROM AUTHOR]

Published
2023
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27. Domain-Specific Multi-Level IR Rewriting for GPU

Author

Gysi, Tobias, primary, Müller, Christoph, additional, Zinenko, Oleksandr, additional, Herhut, Stephan, additional, Davis, Eddie, additional, Wicky, Tobias, additional, Fuhrer, Oliver, additional, Hoefler, Torsten, additional, and Grosser, Tobias, additional

Published
2021
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30. Effects of terrain-following vertical coordinates on simulation of stratus clouds in numerical weather prediction models

Author

Westerhuis, Stephanie, Fuhrer, Oliver, Bhattacharya, Ritthik, Schmidli, Jürg, and Bretherton, Christopher

Subjects
stratus cloud, complex orography, terrain‐following coordinates, COSMO model, numerical diffusion
Abstract

Many numerical weather prediction models employ terrain-following vertical coordinates. As a consequence, over orography, flat tops of stratus clouds are intersected by the vertical coordinate surfaces. We conduct idealised two-dimensional simulations of a stratus cloud with the COSMO model to study the effect of such sloping vertical coordinate surfaces. The evolution of the stratus cloud above a flat surface within a horizontally homogeneous atmosphere serves as a reference. During night-time, the cloud thickens, driven by radiative cooling at the cloud top. Adding a sinusoidal perturbation to the vertical coordinate surfaces reduces the growth of the stratus cloud. With strong perturbations, the cloud starts to dissipate. The physical processes in the two simulations are identical, hence this behaviour is purely driven by numerical diffusion. The cloud is similarly thinned when sinusoidal orographic features are introduced. The reduction depends on the amplitude and wavelength of the perturbations and hills. Increasing the horizontal resolution partly mitigates the numerical diffusion. However, this is a very costly measure for an operational weather model. We suggest conducting further research on a new vertical coordinate with additional local smoothing of the orographic signal., Quarterly Journal of the Royal Meteorological Society, 147 (734), ISSN:0035-9009, ISSN:1477-870X

Published
2021

31. fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model

Author

McGibbon, Jeremy, primary, Brenowitz, Noah D., additional, Cheeseman, Mark, additional, Clark, Spencer K., additional, Dahm, Johann P. S., additional, Davis, Eddie C., additional, Elbert, Oliver D., additional, George, Rhea C., additional, Harris, Lucas M., additional, Henn, Brian, additional, Kwa, Anna, additional, Perkins, W. Andre, additional, Watt-Meyer, Oliver, additional, Wicky, Tobias F., additional, Bretherton, Christopher S., additional, and Fuhrer, Oliver, additional

Published
2021
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33. Pace v0.1: A Python-based Performance-Portable Implementation of the FV3 Dynamical Core.

Author

Dahm, Johann, Davis, Eddie, Deconinck, Florian, Elbert, Oliver, George, Rhea, McGibbon, Jeremy, Wicky, Tobias, Wu, Elynn, Kung, Christopher, Ben-Nun, Tal, Harris, Lucas, Groner, Linus, and Fuhrer, Oliver

Subjects
PYTHON programming language, HIGH performance computing, ATMOSPHERIC models, MOORE'S law, SUPERCOMPUTERS, GRAPHICS processing units
Abstract

Progress in leveraging current and emerging high-performance computing infrastructures using traditional weather and climate models has been slow. This has become known more broadly as the software productivity gap. With the end of Moore's Law driving forward rapid specialization of hardware architectures, building simulation codes on a low-level language with hardware specific optimizations is a significant risk. As a solution, we present Pace, an implementation of the nonhydrostatic FV3 dynamical core which is entirely Python-based. In order to achieve high performance on a diverse set of hardware architectures, Pace is written using the GT4Py domain-specific language. We demonstrate that with this approach we can achieve portability and performance, while significantly improving the readability and maintainability of the code as compared to the Fortran reference implementation. We show that Pace can run at scale on leadership-class supercomputers and achieve performance speeds 3.5–4 times faster than the Fortran code on GPU-accelerated supercomputers. Furthermore, we demonstrate how a Python-based simulation code facilitates existing or enables entirely new use-cases and workflows. Pace demonstrates how a high-level language can insulate us from disruptive changes, provide a more productive development environment, and facilitate the integration with new technologies such as machine learning. [ABSTRACT FROM AUTHOR]

Published
2022
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34. Dynamics of orographically triggered banded convection in sheared moist orographic flows

Author

Fuhrer, Oliver and Schar, Christoph

Subjects
Convection (Meteorology) -- Research, Shear flow -- Observations, Topographical drawing -- Research, Gravity waves -- Observations, Earth sciences, Science and technology
Abstract

Shallow orographic convection embedded in an unstable cap cloud can organize into convective bands. Previous research has highlighted the important role of small-amplitude topographic variations in triggering and organizing banded convection. Here, the underlying dynamical mechanisms are systematically investigated by conducting three-dimensional simulations of moist flows past a two-dimensional mountain ridge using a cloud-resolving numerical model. Most simulations address a sheared environment to account for the observed wind profiles. Results confirm that small-amplitude topographic variations can enhance the development of embedded convection and anchor quasi-stationary convective bands to a fixed location in space. The resulting precipitation patterns exhibit tremendous spatial variability, since regions receiving heavy rainfall can be only kilometers away from regions receiving little or no rain. In addition, the presence of banded convection has important repercussions on the area-mean precipitation amounts. For the experimental setup here, the gravity wave response to small-amplitude topographic variations close to the upstream edge of the cap cloud (which is forced by the larger-scale topography) is found to be the dominant triggering mechanism. Small-scale variations in the underlying topography are found to force the location and spacing of convective bands over a wide range of scales. Further, a self-sufficient mode of unsteady banded convection is investigated that does not dependent on external perturbations and is able to propagate against the mean flow. Finally, the sensitivity of model simulations of banded convection with respect to horizontal computational resolution is investigated. Consistent with predictions from a linear stability analysis, convective bands of increasingly smaller scales arc favored as the horizontal resolution is increased. However, small-amplitude topographic roughness is found to trigger banded convection and to control the spacing and location of the resulting bands. Thereby, the robustness of numerical simulations with respect to an increase in horizontal resolution is increased in the presence of topographic variations.

Published
2007

36. Embedded cellular convection in moist flow past topography

Author

Fuhrer, Oliver and Schar, Christoph

Subjects
Clouds -- Research, Mountains -- Research, Rain and rainfall -- Research, Earth sciences, Science and technology
Abstract

Marginally unstable air masses impinging upon a mountain ridge may lead to the development of a nominally stratiform orographic cloud with shallow embedded convection. Rainfall amounts and distribution are then strongly influenced by the convective dynamics. In this study, the transition from purely stratiform orographic precipitation to flow regimes with embedded convection is systematically investigated. To this end, idealized cloud-resolving numerical simulations of moist flow past a two-dimensional mountain ridge are performed in a three-dimensional domain. A series of simulations with increasing upstream potential instability shows that the convective dynamics may significantly increase precipitation amounts, intensity, and efficiency, to an extent that cannot be replicated by two-dimensional simulations. Under conditions of uniform upstream flow, the embedded convection is of the cellular type. It is demonstrated that simple stability measures of the upstream profile are poor predictors for the occurrence and depth of embedded convection. A linear stability analysis is performed to understand the linear growth of the developing convective instabilities. Embedded convection results if the growth rates of convective instabilities are compatible with the advective time scale (the time an air parcel spends inside the orographic cloud) and the microphysical time scale (time for rain production and fallout). Individual convective updrafts are anchored to the mean flow. Additional simulations serve to demonstrate that the development of embedded convection and associated precipitation may strongly depend on small-amplitude upstream perturbations. Such perturbations enhance the efficacy of the convective circulations and lead to overall stronger precipitation. The potential implications of this result for the predictability of quantitative precipitation are also discussed.

Published
2005

40. Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

Author

Fuhrer, Oliver, Chadha, Tarun, Hoefler, Torsten, Kwasniewski, Grzegorz, Lapillonne, Xavier, Leutwyler, David, Lüthi, Daniel, Osuna, Carlos, Schär, Christoph, Schulthess, Thomas C., and Vogt, Hannes

Abstract

The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth – the dominant bottleneck of climate codes – is being used.

Published
2019

41. SMARTCARB – Use of satellite measurements of auxiliary reactive trace gases for fossil fuel carbon dioxide emission estimation

Author

Kuhlmann, Gerrit, Clément, Valentin, Marshall, Julia, Fuhrer, Oliver, Broquet, Grégoire, Schnadt-Poberaj, Christina, Löscher, Armin, Meijer, Yasjka, and Brunner, Dominik

Abstract

Final report of the SMARTCARB project that investigated the potential of a future constellation of CO2 satellites with imaging capability in combination with CO and NO2 observations to quantify the CO2 emissions from large cities and power plants. The project was funded by the European Space Agency (contract no. 4000119599/16/NL/FF/mg).

Published
2019
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42. The SWALDRIC project

Author

Schär, Christoph, Telišman Prtenjak, Maja, Fuhrer, Oliver, Grisogono, Branko, Strelec Mahović, Nataša, Ban, Nikolina, Güttler, Ivan, Horvath, Kristian, Večenaj, Željko, Babić, Karmen, Belušić Vozila, Andreina, Mikuš Jurković, Petra, Jelić, Damjan, and Malečić, Barbara

Subjects
olujno vrijeme, tuča, CRM
Abstract

Severe convective storms are a primary cause of catastrophic loss through property damage and life-threatening weather conditions. These events are characterized by the presence of heavy convective storms, lightning that can initiate wildfires, strong and damaging winds (e.g., wind gusts), as well as heavy rain that can cause flash floods and hail. Due to sparse observations and inability of conventional climate models to represent these local weather phenomena, our understanding of severe weather events and their response to a changing climate is still very limited. Advances in computational power and recent developments in atmospheric modeling have enabled the use of climate models at kilometer scale horizontal resolutions. These so-called convection-resolving models (CRMs) resolve deep convective events such as thunderstorms and rain showers. Such models have been used for numerical weather forecasting purposes for over a decade. Although these models improve the simulation of heavy precipitation, their application for climate studies and the analysis of severe convective events, like lightning, hail and severe winds, has been very limited. The SWALDRIC project investigate severe weather events over Europe, with a specific focus on the Alpine and Adriatic region. The main goals of the study are to better understand severe weather events, to evaluate their representation in weather and climate models, and to investigate their response to climate change. Key elements of the proposal are: The exploitation of a unique Croatian hail-pad data set, the exploration and intercomparison of a wide range of different atmospheric (weather and climate) modeling systems, and the use of kilometer-scale pan-European decade-long simulations using the first regional climate modeling framework able to run entirely on Graphics Processing Units (COSMO-GPU).

Published
2019

43. Accounting for the vertical distribution of emissions in atmospheric CO2 simulations

Author

Brunner, Dominik, Kuhlmann, Gerrit, Marshall, Julia, Clement, Valentin, Fuhrer, Oliver, Broquet, Grégoire, Löscher, Armin, and Meijer, Yasjka

Abstract

Inverse modeling of anthropogenic and biospheric CO2 fluxes from ground-based and satellite observations critically depends on the accuracy of atmospheric transport simulations. Previous studies emphasized the impact of errors in simulated winds and vertical mixing in the planetary boundary layer, whereas the potential importance of releasing emissions not only at the surface but distributing them in the vertical was largely neglected. Accounting for elevated emissions may be critical, since more than 50 % of CO2 in Europe is emitted by large point sources such as power plants and industrial facilities. In this study, we conduct high-resolution atmospheric simulations of CO2 with the mesoscale Consortium for Small-scale Modeling model extended with a module for the simulation of greenhouse gases (COSMO-GHG) over a domain covering the city of Berlin and several coal-fired power plants in eastern Germany, Poland and Czech Republic. By including separate tracers for anthropogenic CO2 emitted only at the surface or according to realistic, source-dependent profiles, we find that releasing CO2 only at the surface overestimates near-surface CO2 concentrations in the afternoon on average by 14 % in summer and 43 % in winter over the selected model domain. Differences in column-averaged dry air mole XCO2 fractions are smaller, between 5 % in winter and 8 % in summer, suggesting smaller yet non-negligible sensitivities for inversion modeling studies assimilating satellite rather than surface observations. The results suggest that the traditional approach of emitting CO2 only at the surface is problematic and that a proper allocation of emissions in the vertical deserves as much attention as an accurate simulation of atmospheric transport., Atmospheric Chemistry and Physics, 19 (7), ISSN:1680-7375, ISSN:1680-7367

Published
2019

44. The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

Author

Müller, Andreas, primary, Deconinck, Willem, additional, Kühnlein, Christian, additional, Mengaldo, Gianmarco, additional, Lange, Michael, additional, Wedi, Nils, additional, Bauer, Peter, additional, Smolarkiewicz, Piotr K., additional, Diamantakis, Michail, additional, Lock, Sarah-Jane, additional, Hamrud, Mats, additional, Saarinen, Sami, additional, Mozdzynski, George, additional, Thiemert, Daniel, additional, Glinton, Michael, additional, Bénard, Pierre, additional, Voitus, Fabrice, additional, Colavolpe, Charles, additional, Marguinaud, Philippe, additional, Zheng, Yongjun, additional, Van Bever, Joris, additional, Degrauwe, Daan, additional, Smet, Geert, additional, Termonia, Piet, additional, Nielsen, Kristian P., additional, Sass, Bent H., additional, Poulsen, Jacob W., additional, Berg, Per, additional, Osuna, Carlos, additional, Fuhrer, Oliver, additional, Clement, Valentin, additional, Baldauf, Michael, additional, Gillard, Mike, additional, Szmelter, Joanna, additional, O'Brien, Enda, additional, McKinstry, Alastair, additional, Robinson, Oisín, additional, Shukla, Parijat, additional, Lysaght, Michael, additional, Kulczewski, Michał, additional, Ciznicki, Milosz, additional, Piątek, Wojciech, additional, Ciesielski, Sebastian, additional, Błażewicz, Marek, additional, Kurowski, Krzysztof, additional, Procyk, Marcin, additional, Spychala, Pawel, additional, Bosak, Bartosz, additional, Piotrowski, Zbigniew P., additional, Wyszogrodzki, Andrzej, additional, Raffin, Erwan, additional, Mazauric, Cyril, additional, Guibert, David, additional, Douriez, Louis, additional, Vigouroux, Xavier, additional, Gray, Alan, additional, Messmer, Peter, additional, Macfaden, Alexander J., additional, and New, Nick, additional

Published
2019
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46. Porting the COSMO Weather Model to Manycore CPUs

Author

Thaler, Felix, primary, Moosbrugger, Stefan, additional, Osuna, Carlos, additional, Bianco, Mauro, additional, Vogt, Hannes, additional, Afanasyev, Anton, additional, Mosimann, Lukas, additional, Fuhrer, Oliver, additional, Schulthess, Thomas C., additional, and Hoefler, Torsten, additional

Published
2019
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