Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-10-4477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review and perspective paper
| Highlight paper
| 
06 Dec 2017
Review and perspective paper | Highlight paper |
| 06 Dec 2017
DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models
University of California, Davis, Davis, CA, USA
Christiane Jablonowski
University of Michigan, Ann Arbor, MI, USA
James Kent
University of South Wales, Pontypridd, Wales, UK
Peter H. Lauritzen
National Center for Atmospheric Research, Boulder, CO, USA
Ramachandran Nair
National Center for Atmospheric Research, Boulder, CO, USA
Kevin A. Reed
Stony Brook University, Stony Brook, NY, USA
Colin M. Zarzycki
National Center for Atmospheric Research, Boulder, CO, USA
David M. Hall
University of Colorado, Boulder, Boulder, CO, USA
Don Dazlich
Colorado State University, Fort Collins, CO, USA
Ross Heikes
Colorado State University, Fort Collins, CO, USA
Celal Konor
Colorado State University, Fort Collins, CO, USA
David Randall
Colorado State University, Fort Collins, CO, USA
Thomas Dubos
Laboratoire de Météorologie Dynamique, Institut Pierre-Simon Laplace (IPSL), Paris, France
Yann Meurdesoif
Laboratoire de Météorologie Dynamique, Institut Pierre-Simon Laplace (IPSL), Paris, France
Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ, USA
Lucas Harris
Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ, USA
Christian Kühnlein
European Center for Medium-Range Weather Forecasting (ECMWF), Reading, UK
Vivian Lee
Environment and Climate Change Canada (ECCC), Dorval, Québec, Canada
Abdessamad Qaddouri
Environment and Climate Change Canada (ECCC), Dorval, Québec, Canada
Claude Girard
Environment and Climate Change Canada (ECCC), Dorval, Québec, Canada
Marco Giorgetta
Max Planck Institute for Meteorology, Hamburg, Germany
Daniel Reinert
Deutscher Wetterdienst (DWD), Offenbach am Main, Germany
Joseph Klemp
National Center for Atmospheric Research, Boulder, CO, USA
Sang-Hun Park
Yonsei University, Seoul, South Korea
William Skamarock
National Center for Atmospheric Research, Boulder, CO, USA
Hiroaki Miura
University of Tokyo, Bunkyo, Tokyo, Japan
Tomoki Ohno
Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa, Japan
Ryuji Yoshida
RIKEN AICS/Kobe University, Kobe, Japan
Robert Walko
University of Miami, Coral Gables, FL, USA
Alex Reinecke
Naval Research Laboratory, Monterey, CA, USA
Kevin Viner
Naval Research Laboratory, Monterey, CA, USA
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This article is included in the Encyclopedia of Geosciences
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Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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This article is included in the Encyclopedia of Geosciences
Joseph Mouallem, Sergey Malyshev, Zhihong Tan, Elena Shevliakova, Kun Gao, Lucas Harris, Rusty Benson, William Cooke, Niki Zadeh, and Lauren Chilutti
Geosci. Model Dev., 19, 8427–8446, https://doi.org/10.5194/gmd-19-8427-2026, https://doi.org/10.5194/gmd-19-8427-2026, 2026
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This article is included in the Encyclopedia of Geosciences
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This article is included in the Encyclopedia of Geosciences
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Geosci. Model Dev., 19, 7415–7455, https://doi.org/10.5194/gmd-19-7415-2026, https://doi.org/10.5194/gmd-19-7415-2026, 2026
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This article is included in the Encyclopedia of Geosciences
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EGUsphere, https://doi.org/10.5194/egusphere-2026-3568, https://doi.org/10.5194/egusphere-2026-3568, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This article is included in the Encyclopedia of Geosciences
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This article is included in the Encyclopedia of Geosciences
Jung Choi, Jiwoo Lee, Kristin Chang, Paul A. Ullrich, Peter J. Gleckler, and Sang-Yoon Jun
Geosci. Model Dev., 19, 6189–6206, https://doi.org/10.5194/gmd-19-6189-2026, https://doi.org/10.5194/gmd-19-6189-2026, 2026
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This article is included in the Encyclopedia of Geosciences
Ségolène Crossouard, Soulivanh Thao, Thomas Dubos, Masa Kageyama, Mathieu Vrac, and Yann Meurdesoif
Geosci. Model Dev., 19, 5907–5931, https://doi.org/10.5194/gmd-19-5907-2026, https://doi.org/10.5194/gmd-19-5907-2026, 2026
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Current atmospheric models are limited by the computational time required for physical processes, known as physical parameterizations. To address this, we developed neural network-based emulators to replace these parameterizations in the IPSL climate model, using a simplified aquaplanet setup and a realistic configuration. We found that incorporating some physical knowledge, such as latent variables, into the learning process can improve predictions.
This article is included in the Encyclopedia of Geosciences
Xiaorui Zhang, Yuyang Han, Siyu Chen, Xiadong An, Chen Sheng, Wansuo Duan, Xi Chen, Qinglong You, Xingyue Hao, Ziqi Qiu, Zhihan Zhang, Zicheng Zhuang, and Meng Gao
Atmos. Chem. Phys., 26, 9207–9219, https://doi.org/10.5194/acp-26-9207-2026, https://doi.org/10.5194/acp-26-9207-2026, 2026
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This study examines how snow cover over the Tibetan Plateau and oceanic conditions influence air quality in China during winter. By analyzing weather data and pollution levels, we found that variations in snow cover affect weather patterns linked to fine particulate matter pollution. Our results emphasize the need to consider both snow and ocean influences in air quality predictions, aiming to improve forecasting models and support better public health and environmental management strategies.
This article is included in the Encyclopedia of Geosciences
Timothy C. Andrews, Christiane Jablonowski, Owen K. Hughes, and Thomas M. Bendall
EGUsphere, https://doi.org/10.5194/egusphere-2026-2293, https://doi.org/10.5194/egusphere-2026-2293, 2026
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This work describes a new test case for evaluating and comparing models for numerical weather prediction, as part of the Dynamical Core Model Intercomparison Project (DCMIP). We present two versions of this test: First is gap flow through a mountain chain, and second is vortex shedding behind a mountain. We apply these tests to four numerical models, with different modelling decisions being reflected in the simulation comparisons.
This article is included in the Encyclopedia of Geosciences
Giuliana Pallotta, Shiheng Duan, Celine Bonfils, Jiwoo Lee, Seth Goodnight, and Paul Ullrich
EGUsphere, https://doi.org/10.48550/arXiv.2604.06567, https://doi.org/10.48550/arXiv.2604.06567, 2026
Short summary
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Deep-learning Earth system models (DL-ESMs) offer a computationally efficient alternative to traditional Earth system models, but their suitability for Earth system applications requires rigorous evaluation. We apply the PCMDI Metrics Package to assess ACE2 and NeuralGCM using climatology, variability, monsoon, and precipitation diagnostics, providing one of the first systematic Earth system model evaluations of DL-ESMs.
This article is included in the Encyclopedia of Geosciences
Jishi Zhang, Jean-Christophe Golaz, Matthew Vincent Signorotti, Hsiang-He Lee, Peter Bogenschutz, Minda Monteagudo, Paul Aaron Ullrich, Robert S. Arthur, Stephen Po-Chedley, Philip Cameron-Smith, and Jean-Paul Watson
Geosci. Model Dev., 19, 4513–4545, https://doi.org/10.5194/gmd-19-4513-2026, https://doi.org/10.5194/gmd-19-4513-2026, 2026
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We ran a convection-permitting model with regional mesh refinement (3.25 km and 800 m) to simulate present-day wind and solar capacity factors over California, coupling it to an energy generation model. The high-resolution models captured realistic seasonal and diurnal cycles, with wind markedly better than a 25 km model and solar outperforming a 3 km operational forecast. We highlight the critical role of resolution, modeling assumptions, and data reliability in renewable energy assessment.
This article is included in the Encyclopedia of Geosciences
Nijiko Inoue, Tamaki Suematsu, Hiroaki Miura, and Daehyun Kim
EGUsphere, https://doi.org/10.5194/egusphere-2026-2626, https://doi.org/10.5194/egusphere-2026-2626, 2026
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Models struggle to reproduce the Madden–Julian Oscillation (MJO), a major tropical storm. Thus, tools for evaluating MJO simulation are essential. Here, we implement in Python, an MJO diagnostic tool developed in 2009. We also reassessed the original methods and clarified ambiguities in the original package. A new diagnostic that evaluates the Walker circulation associated with the MJO is introduced. The resulting package is a reproducible and accessible framework for evaluating MJO simulations.
This article is included in the Encyclopedia of Geosciences
Joseph P. Hollowed, Christiane Jablonowski, Thomas Ehrmann, Diana Bull, Benjamin Wagman, and Benjamin Hillman
Atmos. Chem. Phys., 26, 6889–6908, https://doi.org/10.5194/acp-26-6889-2026, https://doi.org/10.5194/acp-26-6889-2026, 2026
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Large volcanic eruptions introduce huge quantities of aerosols into the stratosphere. Volcanic aerosols heat the stratosphere, thereby altering the global circulation of air. This research uses simulations of the 1991 Mt. Pinatubo eruption to study the resulting circulation changes, and the dynamical processes which govern them. We find that stratospheric composition is altered by increased tropical vertical motion, and that the seasonal cycle of the global circulation is significantly dampened.
This article is included in the Encyclopedia of Geosciences
Mei Chong, Shengkai Wang, Xi Chen, Yuan Liang, Bing Pu, Shian-Jiann Lin, Zhi Liang, and Yimin Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-628, https://doi.org/10.5194/essd-2025-628, 2026
Preprint under review for ESSD
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The wind speed needed to lift dust from surfaces governs the highest uncertainty in emission models, making it the root cause of dust forecasting errors. We developed iDust-ut, a global threshold dataset by fusing ground observations, satellite data, and reanalysis products. Tests with the iDust model show doubled severe dust storm prediction accuracy. The dataset works directly in any model with built-in adaptation for wind biases, substantially improving operational dust forecasting worldwide.
This article is included in the Encyclopedia of Geosciences
Vincent E. Larson, Zhun Guo, Benjamin A. Stephens, Colin Zarzycki, Gerhard Dikta, Yun Qian, and Shaocheng Xie
Geosci. Model Dev., 18, 9767–9790, https://doi.org/10.5194/gmd-18-9767-2025, https://doi.org/10.5194/gmd-18-9767-2025, 2025
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Global models of the atmosphere contain errors that lead to inaccurate simulations. A software tool ("QuadTune") is presented that attempts to mitigate errors related to suboptimal parameter values. It also displays diagnostic plots that provide hints about where structural errors might lie in the model.
This article is included in the Encyclopedia of Geosciences
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
Geosci. Model Dev., 18, 6461–6478, https://doi.org/10.5194/gmd-18-6461-2025, https://doi.org/10.5194/gmd-18-6461-2025, 2025
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We introduce a new high-resolution model that couples the atmosphere and ocean to better simulate extreme weather events. It combines the Geophysical Fluid Dynamics Laboratory (GFDL) advanced atmospheric and ocean models with a powerful coupling system that enables robust and efficient two-way interactions. Simulations show that the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model represents a key step toward improving extreme weather forecasts.
This article is included in the Encyclopedia of Geosciences
Joseph P. Hollowed, Christiane Jablonowski, Thomas Ehrmann, Diana Bull, Benjamin Wagman, and Benjamin Hillman
Atmos. Chem. Phys., 25, 11025–11049, https://doi.org/10.5194/acp-25-11025-2025, https://doi.org/10.5194/acp-25-11025-2025, 2025
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Simulations of the 1991 Mt. Pinatubo eruption are used to study how radiative heating by volcanic aerosols alters stratospheric winds. We found that heating of the tropical stratosphere by volcanic aerosols drives increased wind speeds in the midlatitude vortex region. A theoretical framework is then used to identify the dynamical origin of these enhanced winds, which we find to be a combination of a strengthened global circulation and a modification of large-scale atmospheric waves.
This article is included in the Encyclopedia of Geosciences
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
This article is included in the Encyclopedia of Geosciences
Yushi Morioka, Eric Maisonnave, Sébastien Masson, Clement Rousset, Luis Kornblueh, Marco Giorgetta, Masami Nonaka, and Swadhin K. Behera
EGUsphere, https://doi.org/10.5194/egusphere-2025-2258, https://doi.org/10.5194/egusphere-2025-2258, 2025
Preprint archived
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Ocean mesoscale eddies, which have a horizontal scale with an order of 100 km, play a prominent role in global ocean heat transport that regulates Earth climate. Here we newly develop an eddy-permitting climate model to demonstrate that the increased ocean model resolution improves representation of air-sea interaction in the western and eastern boundary current regions, while the improved sea ice model physics benefit realistic simulation of sea ice variability.
This article is included in the Encyclopedia of Geosciences
Nicolai Krieger, Heini Wernli, Michael Sprenger, and Christian Kühnlein
Weather Clim. Dynam., 6, 447–469, https://doi.org/10.5194/wcd-6-447-2025, https://doi.org/10.5194/wcd-6-447-2025, 2025
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This study investigates the Laseyer, a local windstorm in a narrow Swiss valley characterized by strong southeasterly winds during northwesterly ambient flow. Using large-eddy simulations (LESs) with 30 m grid spacing, this is the first study to reveal that the extreme gusts in the valley are caused by an amplifying interplay of two recirculation regions. Modifying terrain and ambient wind conditions affects the windstorm's intensity and highlights the importance of topographic details in LES.
This article is included in the Encyclopedia of Geosciences
Alexander Lojko, Andrew C. Winters, Annika Oertel, Christiane Jablonowski, and Ashley E. Payne
Weather Clim. Dynam., 6, 387–411, https://doi.org/10.5194/wcd-6-387-2025, https://doi.org/10.5194/wcd-6-387-2025, 2025
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Convective storms can produce intense anticyclonically rotating vortices (~10 km) defined by negative potential vorticity (NPV), which can elongate to larger scales (~1000 km). Our composite analysis shows that elongated NPV frequently occurs along the western North Atlantic tropopause, where we observed it enhancing jet stream kinematics. Elongated NPV may impinge on aviation turbulence and weather forecasting despite its small-scale origin.
This article is included in the Encyclopedia of Geosciences
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
This article is included in the Encyclopedia of Geosciences
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
This article is included in the Encyclopedia of Geosciences
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
This article is included in the Encyclopedia of Geosciences
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
This article is included in the Encyclopedia of Geosciences
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 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.
This article is included in the Encyclopedia of Geosciences
Colin M. Zarzycki, Benjamin D. Ascher, Alan M. Rhoades, and Rachel R. McCrary
Nat. Hazards Earth Syst. Sci., 24, 3315–3335, https://doi.org/10.5194/nhess-24-3315-2024, https://doi.org/10.5194/nhess-24-3315-2024, 2024
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We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, in climate data. Analyzing the Susquehanna River basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.
This article is included in the Encyclopedia of Geosciences
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
This article is included in the Encyclopedia of Geosciences
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
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To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
This article is included in the Encyclopedia of Geosciences
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
This article is included in the Encyclopedia of Geosciences
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
This article is included in the Encyclopedia of Geosciences
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
This article is included in the Encyclopedia of Geosciences
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
This article is included in the Encyclopedia of Geosciences
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
This article is included in the Encyclopedia of Geosciences
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
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Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
This article is included in the Encyclopedia of Geosciences
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
This article is included in the Encyclopedia of Geosciences
Min-Seop Ahn, Paul A. Ullrich, Peter J. Gleckler, Jiwoo Lee, Ana C. Ordonez, and Angeline G. Pendergrass
Geosci. Model Dev., 16, 3927–3951, https://doi.org/10.5194/gmd-16-3927-2023, https://doi.org/10.5194/gmd-16-3927-2023, 2023
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We introduce a framework for regional-scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics and apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier-generation models and have been slightly improved in CMIP6.
This article is included in the Encyclopedia of Geosciences
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
This article is included in the Encyclopedia of Geosciences
Abhishekh Kumar Srivastava, Paul Aaron Ullrich, Deeksha Rastogi, Pouya Vahmani, Andrew Jones, and Richard Grotjahn
Geosci. Model Dev., 16, 3699–3722, https://doi.org/10.5194/gmd-16-3699-2023, https://doi.org/10.5194/gmd-16-3699-2023, 2023
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Stakeholders need high-resolution regional climate data for applications such as assessing water availability and mountain snowpack. This study examines 3 h and 24 h historical precipitation over the contiguous United States in the 12 km WRF version 4.2.1-based dynamical downscaling of the ERA5 reanalysis. WRF improves precipitation characteristics such as the annual cycle and distribution of the precipitation maxima, but it also displays regionally and seasonally varying precipitation biases.
This article is included in the Encyclopedia of Geosciences
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
This article is included in the Encyclopedia of Geosciences
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, https://doi.org/10.5194/gmd-16-2719-2023, https://doi.org/10.5194/gmd-16-2719-2023, 2023
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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.
This article is included in the Encyclopedia of Geosciences
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
This article is included in the Encyclopedia of Geosciences
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
This article is included in the Encyclopedia of Geosciences
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
This article is included in the Encyclopedia of Geosciences
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
This article is included in the Encyclopedia of Geosciences
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
This article is included in the Encyclopedia of Geosciences
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
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This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
This article is included in the Encyclopedia of Geosciences
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, https://doi.org/10.5194/gmd-15-6985-2022, 2022
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This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
This article is included in the Encyclopedia of Geosciences
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
This article is included in the Encyclopedia of Geosciences
Joseph Mouallem, Lucas Harris, and Rusty Benson
Geosci. Model Dev., 15, 4355–4371, https://doi.org/10.5194/gmd-15-4355-2022, https://doi.org/10.5194/gmd-15-4355-2022, 2022
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The single-nest capability in GFDL's dynamical core, FV3, is upgraded to support multiple same-level and telescoping nests. Grid nesting adds a refined grid over an area of interest to better resolve small-scale flow features necessary to accurately predict special weather events such as severe storms and hurricanes. This work allows concurrent execution of multiple same-level and telescoping multi-level nested grids in both global and regional setups.
This article is included in the Encyclopedia of Geosciences
Kai-Yuan Cheng, Lucas M. Harris, and Yong Qiang Sun
Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, https://doi.org/10.5194/gmd-15-1097-2022, 2022
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This paper presents the implementation of container technology for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model that can be used as a global, a global–nest, and a regional model for weather-to-seasonal prediction. Container technology makes SHiELD cross-platform and easy to use, which opens opportunities for collaborative research and development. The performance and scalability of the containerized SHiELD are evaluated and discussed.
This article is included in the Encyclopedia of Geosciences
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
This article is included in the Encyclopedia of Geosciences
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Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems...
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