GMD - Editor's choice

GMD - Editor's choice
Editor's choice
14 Apr 2026
The Destination Earth digital twin for climate change adaptation
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Costanza Anerdi, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo-Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Kesari Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
Geosci. Model Dev., 19, 2821–2848,
2026
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The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of global climate projections. It produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
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Editorial statement
Destination Earth is a breakthrough in the fidelity and scale of climate simulation. The simulation data this makes available, and the recurrent simulation approach to working with the vast quantity of data generated by very high resolution climate simulations, will change this field for ever. The result will be more accurate and fine-grained climate science far better able to inform policy and decision-making than has hitherto been possible.
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07 Apr 2026
The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7)
Detlef P. Van Vuuren, Brian C. O'Neill, Claudia Tebaldi, Benjamin M. Sanderson, Louise P. Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh M. N. Fall, Katja Frieler, Matthew J. Gidden, Laila K. Gohar, Annika Högner, Andrew D. Jones, Jarmo Kikstra, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camilla Mathison, Shahbaz Mehmood, Zebedee Nicholls, Luciana F. Prado, Qiang Zhang, Steven K. Rose, Alex C. Ruane, Marit Sandstad, Carl-Friedrich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna A. Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha S. Vishwanathan, Tokuta Yokohata, Marco Zecchetto, and Tilo Ziehn
Geosci. Model Dev., 19, 2627–2656,
2026
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We propose a set of seven plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
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Editorial statement
This article describes the design of the next version of emission scenarios that will be used for the 7th phase of the Coupled Model Intercomparison Project, which in turn will be used for the 7th Assessment Report of the Intergovernmental Panel on Climate Change. It provides the story lines for the creation of the emission scenarios and therefore it envisions future trajectories of policies and energy use. Models in CMIP 7 will use these scenarios to run simulations of future climate change using the scenarios as the main forcing. The authors carefully considered all community comments and maintained an open approach to develop these scenarios.
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12 Feb 2026
NorESM2–DIAM: a coupled model for investigating global and regional climate-economy interactions
Jenny Bjordal, Anthony A. Smith Jr., Henri Cornec, and Trude Storelvmo
Geosci. Model Dev., 19, 1337–1365,
2026
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We introduce NorESM2-DIAM (Norwegian Earth System Model version 2-Disaggregated Integrated Assessment Model), a first-of-its-kind tool linking a climate model with a high-resolution economic model to study how climate change, internal variability, and economic activity interact across the world. The model reveals strong regional differences and large annual swings in economic impacts, offers insights for climate policy discussions, and provides a strong foundation for future model development.
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Editorial statement
Earth System Models are highly sophisticated computer models of the physical, chemical and biological processes that make up our planet. They are a key tool in predicting the climate change. Integrated Assessment Models tie physical changes in the climate to economic and social effects. Traditionally, Earth System Models (ESM) and Integrated Assessment Models (IAM) are loosely coupled through a static, unidirectional, asynchronous way. The work presented by this paper develops a novel framework that couples an ESM and a spatially disaggregated IAM in a dynamic, bidirectonal and synchronous way. This work represents a significant advance towards tight, bi-directional coupling between the Earth and Human systems. The tools developed here provide a blueprint for future studies seeking to identify precisely who is affected, where, and when by climate change—an essential step toward designing politically feasible and effective policies.
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23 Jan 2026
Operational numerical weather prediction with ICON on GPUs (version 2024.10)
Xavier Lapillonne, Daniel Hupp, Fabian Gessler, André Walser, Andreas Pauling, Annika Lauber, Benjamin Cumming, Carlos Osuna, Christoph Müller, Claire Merker, Daniel Leuenberger, David Leutwyler, Dmitry Alexeev, Gabriel Vollenweider, Guillaume Van Parys, Jonas Jucker, Lukas Jansing, Marco Arpagaus, Marco Induni, Marek Jacob, Matthias Kraushaar, Michael Jähn, Mikael Stellio, Oliver Fuhrer, Petra Baumann, Philippe Steiner, Pirmin Kaufmann, Remo Dietlicher, Ralf Müller, Sergey Kosukhin, Thomas C. Schulthess, Ulrich Schättler, Victoria Cherkas, and William Sawyer
Geosci. Model Dev., 19, 755–772,
2026
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The ICON climate and numerical weather prediction model was fully ported to Graphical Processing Units (GPUs) using OpenACC compiler directives, covering all components required for operational weather prediction. The GPU port together with several performance optimizations led to a speed-up of 5.6× when comparing to traditional Central Processing Units (CPUs) . Thanks to this adaptation effort, MeteoSwiss became the first national weather service to run the ICON model operationally on GPUs.
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Editorial statement
Increasingly, new supercomputers depend on GPUs for the vast bulk of their processing power. This makes the effective exploitation of GPUs an imperative across geoscientific modelling. This paper presents the port of a full numerical weather prediction system to GPU. It provides an excellent example of how such a port can be achieved in practice while delivering significant performance benefits. As such, this work offers particularly valuable guidance for the wider modelling community.
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15 Jan 2026
The ISIMIP groundwater sector: a framework for ensemble modeling of global change impacts on groundwater
Robert Reinecke, Tanjila Akhter, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Wim Thiery, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
Geosci. Model Dev., 19, 523–542,
2026
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Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
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Editorial statement
Groundwater has long been a neglected dimension of hydrological cycle--both in large scale hydrological models and in global change research and models. Inclusion of a groundwater sector in ISIMIP is an important step toward bringing groundwater to the forefront of global change discussions.
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15 Dec 2025
Feedback-based sea level rise impact modelling for integrated assessment models with FRISIAv1.0
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
Geosci. Model Dev., 18, 10017–10052,
2025
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We present FRISIA version 1.0, a model for emulating sea level rise (SLR) and representing SLR impacts and adaptation in integrated assessment models (IAMs). FRISIA includes previously uncaptured coastal socio-economic feedback and a diverse set of impact strains, thereby improving the represenation of SLR impacts in IAMs. Here we describe the baseline behaviour of FRISIA, explore the effects of the additional feedback and showcase the coupling of FRISIA to an IAM.
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Editorial statement
Sea-level rise is a crucial concern, and a central channel through which climate change impacts human and natural systems. The FRISIA model introduced in this paper allows calculating sea-level rise and associated macro-economic damages as a function of climate forcers and socio-economic developments. It is designed to be coupled with other models, such as process-detailed Integrated Assessment Models, and therefore expcted to be of substantial value to the broader scientific community.
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23 Oct 2025
nextGEMS: entering the era of kilometer-scale Earth system modeling
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
Geosci. Model Dev., 18, 7735–7761,
2025
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The Next Generation of Earth Modeling Systems project (nextGEMS) developed two Earth system models that use horizontal grid spacing of 10 km and finer, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS simulated the Earth System climate over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
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Editorial statement
Kilometre-scale global climate models are pivotal for delivering nuanced regional climate insights and informing climate action, though they face the formidable challenge of balancing computational demands with the precision required to simulate complex subgrid processes. This paper is one of the landmarks in climate modelling, demonstrating the potential of kilometre-scale models to enhance regional climate understanding. It overcomes computational hurdles to achieve high-resolution simulations, crucial for capturing mesoscale phenomena. The authors' transparent exploration of challenges and successes makes this a vital read for climate scientists, offering insights into the future of climate modelling and its applications in climate action.
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10 Oct 2025
A dilatant visco-elasto-viscoplasticity model with globally continuous tensile cap: stable two-field mixed formulation
Anton A. Popov, Nicolas Berlie, and Boris J. P. Kaus
Geosci. Model Dev., 18, 7035–7058,
2025
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We present a simple plasticity model that can be used for robust modeling of strain localization in both shear and tensile failure regimes. The new model overcomes the difficulty related to combining these regimes and enables for particularly simple and reliable numerical implementation, which delivers regularized solutions that are insensitive to mesh resolution. We describe algorithmic details and demonstrate the applications to a number of relevant strain localization problems.
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Editorial statement
The paper by Popov et al. provides a comprehensive insight into overcoming challenges related to modelling the brittle-ductile transition in materials. This study offers a detailed description and bridges to similar concepts used beyond the geosciences, such as in engineering.
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01 Oct 2025
An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment
John P. Dunne, Helene T. Hewitt, Julie M. Arblaster, Frédéric Bonou, Olivier Boucher, Tereza Cavazos, Beth Dingley, Paul J. Durack, Birgit Hassler, Martin Juckes, Tomoki Miyakawa, Matt Mizielinski, Vaishali Naik, Zebedee Nicholls, Eleanor O'Rourke, Robert Pincus, Benjamin M. Sanderson, Isla R. Simpson, and Karl E. Taylor
Geosci. Model Dev., 18, 6671–6700,
2025
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The seventh phase of the Coupled Model Intercomparison Project (CMIP7) coordinates efforts to answer key and timely climate science questions and facilitate delivery of relevant multi-model simulations for prediction and projection; characterization, attribution, and process understanding; and vulnerability, impact, and adaptation analysis. Key to the CMIP7 design are the mandatory Diagnostic, Evaluation and Characterization of Klima and optional Assessment Fast Track experiments.
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Editorial statement
The Coupled Model Intercomparison Project lies at the core of global climate prediction. This paper details the Coupled Model Intercomparison Project phase 7 (CMIP7) and its Fast Track initiative. By transitioning into a continuous climate modeling program with enhanced coordination and federated planning, CMIP7 aims to address key climate questions more effectively. The expansion of the Diagnostic, Evaluation, and Characterization of Klima (DECK) experiments—including the addition of historical simulations, effective radiative forcing assessments, and CO₂-emissions-driven experiments—strengthens the foundation for climate model evaluation and projection. Additionally, the AR7 Fast Track ensures timely delivery of critical climate simulation data to support the upcoming 7th Intergovernmental Panel on Climate Change Assessment Report. This paper highlights how these advancements in experimental protocols and infrastructure support not only scientific understanding but also inform policy-making and climate services, ultimately contributing to global efforts in climate adaptation and mitigation.
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05 Sep 2025
flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO
emissions
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724,
2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
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Editorial statement
As a core contribution to CMIP7, this paper offers an idealized yet insightful projection of climate system behavior during the net-zero transition. Its policy relevance is clear, as it effectively links human-driven emission mitigation efforts with their climatic consequences.
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27 Aug 2025
GPTCast: a weather language model for precipitation nowcasting
Gabriele Franch, Elena Tomasi, Rishabh Wanjari, Virginia Poli, Chiara Cardinali, Pier Paolo Alberoni, and Marco Cristoforetti
Geosci. Model Dev., 18, 5351–5371,
2025
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Our research introduces GPTCast, a novel method for very short term precipitation forecasting using radar data. By applying advanced machine learning techniques inspired by large language models, we developed a system that generates accurate and realistic weather predictions. We trained the model using 6 years of radar data from northern Italy, demonstrating its superior performance over leading ensemble extrapolation methods.
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Editorial statement
The application of machine learning techniques to weather forecasting is an exceptionally promising area for this technology. This paper presents an LLM nowcasting tool which outperforms existing technology for short term precipitation forecasting. This is an exciting demonstrator of the possibilities of this novel approach.
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01 Aug 2025
A Bayesian framework for inferring regional and global change from stratigraphic proxy records (StratMC v1.0)
Stacey Edmonsond and Blake Dyer
Geosci. Model Dev., 18, 4759–4788,
2025
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The chemistry of sedimentary rocks is used to reconstruct past changes in Earth's climate and biogeochemical cycles. Reconstructing global change requires merging stratigraphic proxy records from many locations, each of which may be incomplete, time-uncertain, and influenced by both global and local processes. StratMC uses Bayesian modeling to see through this complexity, building more accurate and testable reconstructions of global change from stratigraphic data.
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Editorial statement
This paper represents a major step forward in understanding Earth history proxy records and how to model and correlate records, as illustrated by examples in the paper. The work presented here should have direct implications in the field of reconstructing Earth history from paleo proxy records but also beyond with a wide range of possible applications.
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25 Jul 2025
asQ: parallel-in-time finite element simulations using ParaDiag for geoscientific models and beyond
Joshua Hope-Collins, Abdalaziz Hamdan, Werner Bauer, Lawrence Mitchell, and Colin Cotter
Geosci. Model Dev., 18, 4535–4569,
2025
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Effectively using modern supercomputers requires massively parallel algorithms. Time-parallel algorithms calculate the system state (e.g. the atmosphere) at multiple times simultaneously and have exciting potential but are tricky to implement and still require development. We have developed software to simplify implementing and testing the ParaDiag algorithm on supercomputers. We show that for some atmospheric problems it can enable faster or more accurate solutions than traditional techniques.
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Editorial statement
Parallelization is important for speeding up complex geoscientific
models. In addition to spatial parallelization, several parallel-in-time
(PinT) methods have been developed. This paper introduces the reader to
PinT methods for hyperbolic and geophysical models, and it presents the
asQ library which facilitates the implementation of
diagonalization-based (ParaDiag) methods.
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09 Dec 2024
Evaluating downscaled products with expected hydroclimatic co-variances
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681,
2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
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Editorial statement
This paper addresses the conditions in which GCM and downscaled solutions diverge for targeted processes under historical and future climate conditions. Downscaling is a crucial part of making climate model outputs useable by the wider science and policy community. Understanding the properties and limitations of downscaling should hence be of interest far beyond the model development community.
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30 Oct 2024
A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593,
2024
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By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
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Editorial statement
Operational avalanche forecasting has so far been done almost exclusively by human forecasters. For the first time, an automated machine learning approach allows to reach forecasting skills close to human forecasters.
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28 Oct 2024
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512,
2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
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Editorial statement
This multi-model inter-comparison presents a state-of-the-art assessment of Latin America for the first time which is a region often ignored in air quality studies.
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30 Apr 2024
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445,
2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
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Editorial statement
Coastal erosion is a process with widespread human impact. This well-written paper explains the NEWTS coastal erosion model in terms which will be accessible for geoscientists and beyond. It is recommended reading for anyone with an interest in this application area.
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16 Apr 2024
HydroFATE (v1): a high-resolution contaminant fate model for the global river system
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899,
2024
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Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
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Editorial statement
This paper is significant for both the geoscience community and the general public. For geoscientists, the novel HydroFATE model provides an innovative tool to estimate and track the presence of household and pharmaceutical contaminants in the world's river systems, aiding in global pollution studies and environmental planning. For the public and media, it highlights the widespread issue of water contamination from commonly used substances, illustrating their potential impacts on environmental and public health. HydroFATE can inform decision-making across sectors - from water testing prioritization by local governments to ecological considerations by pharmaceutical companies, making it a compelling narrative for the media. The antibiotic sulfamethoxazole's use as a test case further links this work to global health discussions on antibiotic resistance.
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15 Mar 2024
Minimum-variance-based outlier detection method using forward-search model error in geodetic networks
Utkan M. Durdağ
Geosci. Model Dev., 17, 2187–2196,
2024
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This study introduces a novel approach to outlier detection in geodetic networks, challenging conventional and robust methods. By treating outliers as unknown parameters within the Gauss–Markov model and exploring numerous outlier combinations, this approach prioritizes minimal variance and eliminates iteration dependencies. The mean success rate (MSR) comparisons highlight its effectiveness, improving the MSR by 40–45 % for multiple outliers.
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Editorial statement
Robust outlier detection is a challenge for all areas of science that deal with real data. Here, the author describes a new approach to this in the field of geodesy, but does so in a readable and accessible way. It will therefore be valuable reading for those beyond that field.
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21 Dec 2023
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489,
2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
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Editorial statement
This manuscript provides a novel and comprehensive assessment of uncertainty associated with sea level rise. The model description is thorough and it is applied to a number of possible scenarios. The conclusions are important for framing future discussions on sea level rise.
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16 Nov 2023
Universal differential equations for glacier ice flow modelling
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687,
2023
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We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
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Editorial statement
The integration of neural networks into PDE solvers to simulate systems for which the PDE models are incomplete is a key advance at the cutting edge of geoscientific modelling. The approach presented here is applicable far beyond the realm of ice modelling, and will be of interest to model developers and users across geoscience and beyond.
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06 Oct 2023
Emulating lateral gravity wave propagation in a global chemistry–climate model (EMAC v2.55.2) through horizontal flux redistribution
Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchař, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern
Geosci. Model Dev., 16, 5561–5583,
2023
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The columnar approach of gravity wave (GW) schemes results in dynamical model biases, but parallel decomposition makes horizontal GW propagation computationally unfeasible. In the global model EMAC, we approximate it by GW redistribution at one altitude using tailor-made redistribution maps generated with a ray tracer. More spread-out GW drag helps reconcile the model with observations and close the 60°S GW gap. Polar vortex dynamics are improved, enhancing climate model credibility.
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Editorial statement
Grave wave (GW) parameterisations currently used in state-of-the-art weather and climate models are based on a purely columnar approach, which does not allow for any horizontal propagation of GWs and has been identified as potential source of systematic biases in the simulation of middle atmospheric dynamics. The study by Eichinger and colleagues presents now a computationally efficient method to emulate the effects of lateral propagation of orographic GWs in climate models by horizontal momentum flux redistribution using redistribution maps derived from a GW ray-tracing model. The presented approach is an important step towards a better representation of orographic GWs in climate models, which might improve long-standing problems in atmospheric modelling.
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02 Aug 2023
The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450,
2023
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Editorial statement
Short summary
We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
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Editorial statement
This paper investigates an impactful topic, is easily digestible to non-scientists, is well written, has nice visuals, uses novel objective identification methods and has well documented and accessible code.
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31 Jul 2023
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366,
2023
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Editorial statement
Short summary
This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
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Editorial statement
Sea level rise represents one of the most compelling aspects of anthropogenic climate change. The potential social and economic impacts are enormous, with little that can be done to mitigate them. It is therefore of critical importance that we are able to correctly anticipate these impacts in advance. This study presents a new, open-source platform that integrates numerical modelling with socioeconomic and physical datasets, whilst also allowing for the uncertainty in climate change projections. This tool therefore allows for new and improved estimates of the global costs of future sea level rise and is likely to be of widespread interest.
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17 May 2023
Pace v0.2: a Python-based performance-portable atmospheric model
Johann Dahm, Eddie Davis, Florian Deconinck, Oliver Elbert, Rhea George, Jeremy McGibbon, Tobias Wicky, Elynn Wu, Christopher Kung, Tal Ben-Nun, Lucas Harris, Linus Groner, and Oliver Fuhrer
Geosci. Model Dev., 16, 2719–2736,
2023
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Editorial statement
Short summary
It is hard for scientists to write code which is efficient on different kinds of supercomputers. Python is popular for its user-friendliness. We converted a Fortran code, simulating Earth's atmosphere, into Python. This new code auto-converts to a faster language for processors or graphic cards. Our code runs 3.5–4 times faster on graphic cards than the original on processors in a specific supercomputer system.
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Editorial statement
Achieving both performance and portability in a whole dynamical core implemented in a high-productivity language such as Python is an eye-opening result which rebuts some widely held assumptions in the geoscientific modelling community. This is a paper which everyone who writes geoscientific models should read.
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