Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6601-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6601-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
02 Sep 2022
Methods for assessment of models |
| 02 Sep 2022
| 02 Sep 2022
Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models
Mathematics and Computational Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
Jorge E. Guerra
OU/CIMMS, NOAA National Severe Storms Laboratory, Norman, OK, USA
Xiangmin Jiao
Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11704, USA
Paul Kuberry
Center for Computing Research, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87125, USA
Yipeng Li
Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY 11704, USA
Paul Ullrich
Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
David Marsico
Department of Mathematics, University of California, Davis, CA 95616, USA
Robert Jacob
Mathematics and Computational Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
Pavel Bochev
Center for Computing Research, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87125, USA
Philip Jones
Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
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Jung Choi, Jiwoo Lee, Kristin Chang, Paul A. Ullrich, Peter J. Gleckler, and Sang-Yoon Jun
EGUsphere, https://doi.org/10.5194/egusphere-2026-958, https://doi.org/10.5194/egusphere-2026-958, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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As climate risks grow, society needs reliable predictions for the coming years and decades. We developed a framework to collectively compare climate prediction systems and examine their performances on global temperature, rainfall, and sea ice. As a complementary to traditional analyses, our new framework offers tracking evolution of model performance in simulation time, helping scientists and stakeholders better understand strengths and limits of decadal climate prediction.
Hongyu Chen, Paul A. Ullrich, Julian Panetta, David Marsico, Moritz Hanke, Rajeev Jain, Chengzhu Zhang, and Robert L. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2026-636, https://doi.org/10.5194/egusphere-2026-636, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Accurate data transfer between different grids is essential in climate and weather modeling. This study analyzes the geometric operations that underpin such transfers on the spherical Earth, identifies gaps and limitations in current methods, and introduces improved algorithms to ensure accuracy, reliability, and performance for next-generation modeling and data analysis systems.
Xiaojian Zheng, Yan Feng, David Painemal, Meng Zhang, Shaocheng Xie, Zhujun Li, Robert Jacob, and Bethany Lusch
Atmos. Chem. Phys., 25, 17473–17499, https://doi.org/10.5194/acp-25-17473-2025, https://doi.org/10.5194/acp-25-17473-2025, 2025
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This study used satellite observations and climate model simulations to examine how aerosols affect marine clouds over the Eastern North Atlantic. Cloud responses to aerosols differed significantly across meteorological regimes. The model captured overall trends but exaggerated cloud responses, performing better for shallower than deeper clouds. The results highlight the need to untangle aerosol effects from meteorology and improve cloud process representation in climate models.
Naser Mahfouz, Hassan Beydoun, Johannes Mülmenstädt, Noel Keen, Adam C. Varble, Luca Bertagna, Peter Bogenschutz, Andrew Bradley, Matthew W. Christensen, T. Conrad Clevenger, Aaron Donahue, Jerome Fast, James Foucar, Jean-Christophe Golaz, Oksana Guba, Walter Hannah, Benjamin Hillman, Robert Jacob, Wuyin Lin, Po-Lun Ma, Yun Qian, Balwinder Singh, Christopher Terai, Hailong Wang, Mingxuan Wu, Kai Zhang, Andrew Gettelman, Mark Taylor, L. Ruby Leung, Peter Caldwell, and Susannah Burrows
Atmos. Chem. Phys., 25, 15105–15120, https://doi.org/10.5194/acp-25-15105-2025, https://doi.org/10.5194/acp-25-15105-2025, 2025
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Our study assesses the aerosol effective radiative forcing in a global cloud-resolving atmosphere model at ultra-high resolution. We demonstrate that global aerosol forcing signal can be robustly reproduced across resolutions when aerosol activation processes are carefully parameterized. Further, we argue that simplified prescribed aerosol schemes will open the door for further process/mechanism studies under controlled conditions.
Mark R. Petersen, Xylar S. Asay-Davis, Alice M. Barthel, Carolyn Branecky Begeman, Siddhartha Bishnu, Steven R. Brus, Philip W. Jones, Hyun-Gyu Kang, Youngsung Kim, Azamat Mametjanov, Brian O’Neill, Kieran K. Ringel, Katherine M. Smith, Sarat Sreepathi, Luke P. Van Roekel, and Maciej Waruszewski
EGUsphere, https://doi.org/10.5194/egusphere-2025-3500, https://doi.org/10.5194/egusphere-2025-3500, 2025
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Ocean models are used to predict currents, temperature, and salinity of the earth’s oceans, much like weather forecasting. As supercomputer hardware changes with evolving technology, models must be updated, and sometimes rewritten. Here we document Omega, a new ocean model that was designed to run on the world’s fastest supercomputers. Testing shows that Omega accurately solves the model equations, and runs efficiently on many different computer architectures, including exascale computers.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-3947, https://doi.org/10.5194/egusphere-2025-3947, 2025
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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.
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathaniel Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Mederios, Enrico Scoccimarro, Jeremy Walton, Philip Kershaw, André L. Marquez, Malcolm J. Roberts, Eleanor O’Rourke, Elisabeth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
EGUsphere, https://doi.org/10.5194/egusphere-2025-2685, https://doi.org/10.5194/egusphere-2025-2685, 2025
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As Earth system models become more complex, rapid and comprehensive evaluation through comparison with observational data is necessary. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require fast analysis. This paper describes a new Rapid Evaluation Framework (REF) that was developed for the Assessment Fast Track that will be run at the Earth System Grid Federation (ESGF) to inform the community about the performance of models.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Paul A. Ullrich, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed
Geosci. Model Dev., 14, 5023–5048, https://doi.org/10.5194/gmd-14-5023-2021, https://doi.org/10.5194/gmd-14-5023-2021, 2021
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TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets. Version 2.1 of TE now provides extensive support for nodal and areal features. This paper describes the algorithms that have been added to the TE framework since version 1.0 and gives several examples of how these can be combined to produce composite algorithms for evaluating and understanding atmospheric features.
Cited articles
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis, NOAA Technical Memorandum NESDIS
NGDC-24, https://doi.org/10.7289/V5C8276M, 2009. a, b
Balaji, V., Anderson, J., Held, I., Winton, M., Durachta, J., Malyshev, S., and
Stouffer, R. J.: The Exchange Grid: A mechanism for data exchange between
Earth System components on independent grids, in: Parallel Computational
Fluid Dynamics 2005, edited by: Deane, A., Ecer, A., McDonough, J., Satofuka,
N., Brenner, G., Emerson, D. R., Periaux, J., and Tromeur-Dervout, D.,
Elsevier, Amsterdam, 179–186,
https://doi.org/10.1016/B978-044452206-1/50021-5, 2006. a
Barth, T. and Jespersen, D.: The design and application of upwind schemes on
unstructured meshes, in: 27th Aerospace sciences meeting, 366 pp.,
https://doi.org/10.2514/6.1989-366, 1989. a
Berger, M., Murman, S. M., and Aftosmis, M. J.: Analysis of Slope Limiters on
Irregular Grids, in: Proceedings of the 43rd AIAA Aerospace Sciences Meeting,
AIAA2005-0490, AIAA, Reno, NV, 2005. a
Blanchard, G. and Loubere, R.: High-Order Conservative Remapping with a
posteriori MOOD stabilization on polygonal meshes, Comput. Fluids, 136, 83–103, https://doi.org/10.1016/j.compfluid.2016.06.002,
2016. a
Breitkopf, P., Rassineux, A., Touzot, G., and Villon, P.: Explicit form and
efficient computation of MLS shape functions and their derivatives,
Int. J. Numer. Meth. Eng., 48, 451–466,
2000. a
Brewer, M. L., Diachin, L. F., Knupp, P. M., Leurent, T., and Melander, D. J.:
The Mesquite Mesh Quality Improvement Toolkit, in: Proceedings of the 12th International Meshing Roundtable, IMR 2003,
Santa Fe, New Mexico, USA, 14–17 September 2003. a
Buhmann, M.: A new class of radial basis functions with compact support, Math.
Comput., 70, 307–318, 2001. a
Chesshire, G. and Henshaw, W. D.: A scheme for conservative interpolation on
overlapping grids, SIAM J. Sci. Comput., 15, 819–845, 1994. a
Collins, N., Theurich, G., DeLuca, C., Suarez, M., Trayanov, A., Balaji, V.,
Li, P., Yang, W., Hill, C., and Da Silva, A.: Design and implementation of
components in the Earth System Modeling Framework, Int. J.
High Perform. C., 19, 341–350, 2005. a
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017. a, b
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for earth
system modeling developed for CCSM4 and CESM1, Int. J.
High Perform. C., 26, 31–42,
https://doi.org/10.1177/1094342011428141, 2012. a
de Boor, C.: Quasiinterpolants and approximation power of multivariate splines,
in: Computation of curves and surfaces, Springer, 313–345, 1990. a
Dukowicz, J. K. and Baumgardner, J. R.: Incremental Remapping as a
Transport/Advection Algorithm, J. Comput. Phys., 160, 318– 335, https://doi.org/10.1006/jcph.2000.6465, 2000. a
E3SM Project: Energy Exascale Earth System Model (E3SM),
https://doi.org/10.11578/E3SM/dc.20180418.36, 2018. a, b
Edwards, H. C., Trott, C. R., and Sunderland, D.: Kokkos: Enabling manycore
performance portability through polymorphic memory access patterns, J.
Parallel Distr. Com., 74, 3202–3216,
https://doi.org/10.1016/j.jpdc.2014.07.003, 2014. a
Farrell, P. and Maddison, J.: Conservative interpolation between volume meshes
by local Galerkin projection, Comput. Method. Appl. M., 200,
89–100, 2011. a
Flyer, N. and Wright, G. B.: Transport schemes on a sphere using radial basis
functions, J. Comput. Phys., 226, 1059–1084, 2007. a
Fornberg, B. and Flyer, N.: The Gibbs phenomenon for radial basis functions, in:
The Gibbs Phenomenon in Various Representations and Applications, Potsdam, NY: Sampling Publishing,
201–224, 2007. a
Garimella, R., Kucharik, M., and Shashkov, M.: An efficient linearity and bound
preserving conservative interpolation (remapping) on polyhedral meshes,
Comput. Fluids, 36, 224–237, 2007. a
Gottlieb, D. and Shu, C.-W.: On the Gibbs phenomenon and its resolution, SIAM
Rev., 39, 644–668, 1997. a
Gross, B., Trask, N., Kuberry, P., and Atzberger, P.: Meshfree methods on
manifolds for hydrodynamic flows on curved surfaces: A Generalized Moving
Least-Squares (GMLS) approach, J. Comput. Phys., 409,
109340, https://doi.org/10.1016/j.jcp.2020.109340, 2020. a, b, c
Guerra, J. and Mahadevan, V.: Satellite datasets used for MIRA workflows, Zenodo [data set],
https://doi.org/10.5281/zenodo.5172792, 2021. a, b, c
Hanke, M., Redler, R., Holfeld, T., and Yastremsky, M.: YAC 1.2.0: new aspects for coupling software in Earth system modelling, Geosci. Model Dev., 9, 2755–2769, https://doi.org/10.5194/gmd-9-2755-2016, 2016. a, b, c, d
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P., Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: The
community earth system model: a framework for collaborative research, B. Am.
Meterol. Soc., 94, 1339–1360, https://doi.org/10.1175/BAMS-D-12-00121.1, 2013. a, b
Jalali, A. and Gooch, C. F. O.: Higher-Order Finite Volume Solution Reconstruction on Highly Anisotropic Meshes, in: 21st AIAA Computational Fluid Dynamics
Conference, San Diego, https://doi.org/10.2514/6.2013-2565,
2013. a
Jerri, A. J.: The Gibbs Phenomenon in Fourier Analysis, Splines and Wavelet
Approximations, Mathematics and Its Applications, Springer, 446, 340 pp., https://doi.org/10.1007/978-1-4757-2847-7, 2013. a, b
Jiao, X. and Heath, M. T.: Overlaying surface meshes, part I: Algorithms,
Int. J. Comput. Geom. Ap., 14, 379–402, 2004b. a
Jiao, X. and Heath, M. T.: Overlaying surface meshes, part II: Topology
preservation and feature matching, Int. J. Comput. Geom. Ap., 14, 403–419,
2004c. a
Jiao, X. and Wang, D.: Reconstructing high-order surfaces for meshing, Eng.
Comput., 28, 361–373, 2012. a
Joldes, G. R., Chowdhury, H. A., Wittek, A., Doyle, B., and Miller, K.:
Modified moving least squares with polynomial bases for scattered data
approximation, Appl. Math. Comput., 266, 893–902, 2015. a
Joppich, W. and Kürschner, M.: MpCCI – a tool for the simulation of
coupled applications, Concurr. Comp.-Pract. E., 18, 183–192, 2006. a
Kageyama, A. and Sato, T.: “Yin-Yang grid”: An overset grid in spherical
geometry, Geochem. Geophy. Geosy., 5, Q09005,
https://doi.org/10.1029/2004GC000734, 2004. a
Kritsikis, E., Aechtner, M., Meurdesoif, Y., and Dubos, T.: Conservative interpolation between general spherical meshes, Geosci. Model Dev., 10, 425–431, https://doi.org/10.5194/gmd-10-425-2017, 2017. a, b, c
Kuberry, P., Bosler, P., and Trask, N.: Compadre Toolkit,
https://doi.org/10.11578/dc.20190411.1, 2019. a
Larson, J., Jacob, R., and Ong, E.: The model coupling toolkit: a new
Fortran90 toolkit for building multiphysics parallel coupled models, Int.
J. High Perform. C., 19, 277–292, 2005. a
Lauritzen, P. H. and Thuburn, J.: Evaluating advection/transport schemes using
interrelated tracers, scatter plots and numerical mixing diagnostics,
Q. J. Roy. Meteor. Soc., 138, 906–918, 2012. a
Lauritzen, P. H., Nair, R. D., and Ullrich, P. A.: A conservative
semi-Lagrangian multi-tracer transport scheme (CSLAM) on the cubed-sphere
grid, J. Comput. Phys., 229, 1401–1424, 2010. a
Liu, L., Zhang, C., Li, R., Wang, B., and Yang, G.: C-Coupler2: a flexible and user-friendly community coupler for model coupling and nesting, Geosci. Model Dev., 11, 3557–3586, https://doi.org/10.5194/gmd-11-3557-2018, 2018. a, b
Mirzaei, D., Schaback, R., and Dehghan, M.: On generalized moving least squares
and diffuse derivatives, IMA J. Numer. Anal., 32, 983–1000,
https://doi.org/10.1093/imanum/drr030, 2012. a
Nair, R. D. and Jablonowski, C.: Moving vortices on the sphere: A test case for
horizontal advection problems, Mon. Weather Rev., 136, 699–711, 2008. a
Nayroles, B., Touzot, G., and Villon, P.: Generalizing the finite element
method: Diffuse approximation and diffuse elements, Comput. Mech.,
10, 307–318, https://doi.org/10.1007/BF00364252, 1992. a
Norman, M. R. and Nair, R. D.: Inherently conservative nonpolynomial-based
remapping schemes: Application to semi-Lagrangian transport, Mon. Weather
Rev., 136, 5044–5061, 2008. a
Petersen, M.: MPAS-Ocean V6 Run Directories, Zenodo [code], https://doi.org/10.5281/zenodo.1252437,
2018. a
Platnick, S., Ackerman, S. A., King, M. D., Meyer, K., Menzel, W. P., Holz,
R. E., Baum, B. A., and Yang, P.: MODIS atmosphere L2 cloud product (06_L2),
NASA MODIS Adaptive Processing System [data set], https://doi.org/10.5067/MODIS/MYD06_L2.006,
2020. a, b
Rider, W. J.: Reconsidering remap methods, Int. J. Numer.
Meth. Fl., 76, 587–610, https://doi.org/10.1002/fld.3950,
2014. a
Ringler, T. D., Thuburn, J., Klemp, J. B., and Skamarock, W. C.: A unified
approach to energy conservation and potential vorticity dynamics for
arbitrarily-structured C-grids, J. Comput. Phys., 229,
3065–3090, 2010. a
Royer, J.-F.: Correction of negative mixing ratios in spectral models by global
horizontal borrowing, Mon. Weather Rev., 114, 1406–1410, 1986. a
Skamarock, W. C. and Gassmann, A.: Conservative Transport Schemes for Spherical
Geodesic Grids: High-Order Flux Operators for ODE-Based Time Integration,
Mon. Weather Rev., 139, 2962–2975, https://doi.org/10.1175/MWR-D-10-05056.1,
2011. a
Skamarock, W. C. and Menchaca, M.: Conservative Transport Schemes for Spherical
Geodesic Grids: High-Order Reconstructions for Forward-in-Time Schemes,
Mon. Weather Rev., 138, 4497–4508, https://doi.org/10.1175/2010MWR3390.1, 2010. a
Smith, M. J., Cesnik, C. E., and Hodges, D. H.: Evaluation of some data
transfer algorithms for noncontiguous meshes, J. Aerospace
Eng., 13, 52–58, 2000. a
Suchde, P. and Kuhnert, J.: A meshfree generalized finite difference method for
surface PDEs, Comput. Math. Appl., 78, 2789–2805,
https://doi.org/10.1016/j.camwa.2019.04.030, 2019. a, b
Tautges, T. J. and Caceres, A.: Scalable parallel solution coupling for
multiphysics reactor simulation, in: Journal of Physics: Conference Series,
vol. 180, 012017, IOP Publishing, 2009. a
Taylor, M., Edwards, J., Thomas, S., and Nair, R.: A mass and energy conserving
spectral element atmospheric dynamical core on the cubed-sphere grid,
J. Phys. Conf. Ser., 78, 012074, https://doi.org/10.1088/1742-6596/78/1/012074,
2007. a
Thuburn, J., Ringler, T. D., Skamarock, W. C., and Klemp, J. B.: Numerical
representation of geostrophic modes on arbitrarily structured C-grids,
J. Comput. Phys., 228, 8321–8335, 2009. a
Townsend, A., Wilber, H., and Wright, G. B.: Computing with functions in
spherical and polar geometries I. The sphere, SIAM J. Sci.
Comput., 38, C403–C425, 2016. a
Valcke, S., Piacentini, A., and Jonville, G.: Benchmarking Regridding Libraries
Used in Earth System Modelling, Math. Comput. Appl.,
27, https://doi.org/10.3390/mca27020031, 2022. a, b
Wendland, H.: Scattered data approximation, Cambridge university
press, vol. 17, https://doi.org/10.1017/CBO9780511617539, 2004. a
Wieczorech, M. A. and Meschede, M.: SHTools – Tools for working with
spherical harmonics, Geochem. Geophy. Geosy., 19, 2574–2592,
https://doi.org/10.1029/2018GC007529, 2018. a
Wimmers, A. J. and Velden, C. S.: Seamless Advective Blending of Total
Precipitable Water Retrievals from Polar-Orbiting Satellites, J.
Appl. Meteorol. Clim., 50, 1024–1036,
https://doi.org/10.1175/2010JAMC2589.1, 2011.
a, b
Zender, C. S.: Analysis of self-describing gridded geoscience data with netCDF
Operators (NCO), Environ. Modell. Softw., 23, 1338–1342,
https://doi.org/10.1016/j.envsoft.2008.03.004, 2008. a
Zerroukat, M., Wood, N., and Staniforth, A.: A monotonic and positive–definite
filter for a Semi-Lagrangian Inherently Conserving and Efficient (SLICE)
scheme, Q. J. Roy. Meteor. Soc., 131,
2923–2936, 2005. a
Zerroukat, M., Wood, N., and Staniforth, A.: The parabolic spline method
(PSM) for conservative transport problems, Int. J. Numer. Meth. Fl., 51,
1297–1318, 2006. a
Short summary
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.
Coupled Earth system models require transfer of field data between multiple components with...
