Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1429-2024
© Author(s) 2024. 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-17-1429-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
16 Feb 2024
Development and technical paper |
| 16 Feb 2024
| 16 Feb 2024
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Sandia National Laboratories, Albuquerque, NM, USA
Mark A. Taylor
Sandia National Laboratories, Albuquerque, NM, USA
Peter A. Bosler
Sandia National Laboratories, Albuquerque, NM, USA
Christopher Eldred
Sandia National Laboratories, Albuquerque, NM, USA
Peter H. Lauritzen
National Center for Atmospheric Research, Boulder, CO, USA
Related authors
Oksana Guba, Arjun Sharma, Mark A. Taylor, Peter A. Bosler, and Erika L. Roesler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3966, https://doi.org/10.5194/egusphere-2025-3966, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
It is important for computational Earth system models to capture interactions between the ocean and the atmosphere accurately. Because of incredible complexity of these interactions, computational models contain simplifications, which may hinder the models' capabilities. Here we focus on detailed analysis of thermodynamic interactions between the ocean and the atmosphere in computational Earth system models. We also provide a framework to show how modeling these interactions can be improved.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-1868, https://doi.org/10.5194/egusphere-2025-1868, 2025
Short summary
Short summary
Our study assesses the aerosol effective radiative forcing in a global cloud-resolving atmosphere model at ultra-high resolution. We demonstrate that global ERFaer 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.
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
Short summary
Short summary
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.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
Short summary
Short summary
Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Oksana Guba, Mark A. Taylor, Andrew M. Bradley, Peter A. Bosler, and Andrew Steyer
Geosci. Model Dev., 13, 6467–6480, https://doi.org/10.5194/gmd-13-6467-2020, https://doi.org/10.5194/gmd-13-6467-2020, 2020
Oscar H. Díaz-Ibarra, Samuel G. Frederick, Jeffrey H. Curtis, Zachary D'Aquino, Peter A. Bosler, Lekha Patel, Cosmin Safta, Matthew West, and Nicole Riemer
EGUsphere, https://doi.org/10.5194/egusphere-2025-4376, https://doi.org/10.5194/egusphere-2025-4376, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed TChem-atm, a new open-source tool for simulating atmospheric chemistry and aerosols. As models become more detailed, traditional methods are too slow. TChem-atm runs on both standard processors and graphics processors, making these simulations faster and more efficient. The tool provides a foundation for next-generation models that improve predictions of air quality and climate.
Oksana Guba, Arjun Sharma, Mark A. Taylor, Peter A. Bosler, and Erika L. Roesler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3966, https://doi.org/10.5194/egusphere-2025-3966, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
It is important for computational Earth system models to capture interactions between the ocean and the atmosphere accurately. Because of incredible complexity of these interactions, computational models contain simplifications, which may hinder the models' capabilities. Here we focus on detailed analysis of thermodynamic interactions between the ocean and the atmosphere in computational Earth system models. We also provide a framework to show how modeling these interactions can be improved.
Jishi Zhang, Peter Bogenschutz, Mark Taylor, and Philip Cameron-Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-2223, https://doi.org/10.5194/egusphere-2025-2223, 2025
Short summary
Short summary
We pushed a global cloud-resolving model to a novel 100 m resolution setup over the San Francisco Bay Area using a regionally refined mesh. The model captured fine-scale air motions over complex terrain and coastal regions at large-eddy scales with fully comprehensive global modeling configuration, enabled by scale-aware turbulence parameterization. Performance tests demonstrated that GPU acceleration can make such high-resolution simulations feasible within practical timeframes.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-1868, https://doi.org/10.5194/egusphere-2025-1868, 2025
Short summary
Short summary
Our study assesses the aerosol effective radiative forcing in a global cloud-resolving atmosphere model at ultra-high resolution. We demonstrate that global ERFaer 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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
Short summary
Short summary
Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
Short summary
Short summary
An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Oksana Guba, Mark A. Taylor, Andrew M. Bradley, Peter A. Bosler, and Andrew Steyer
Geosci. Model Dev., 13, 6467–6480, https://doi.org/10.5194/gmd-13-6467-2020, https://doi.org/10.5194/gmd-13-6467-2020, 2020
Cited articles
Bendall, T. M., Gibson, T. H., Shipton, J., Cotter, C. J., and Shipway, B.: A compatible finite-element discretisation for the moist compressible Euler equations, Q. J. Roy. Meteor. Soc., 146, 3187–3205, https://doi.org/10.1002/qj.3841, 2020. a
Bogenschutz, P. A., Eldred, C., and Caldwell, P. M.: Horizontal Resolution Sensitivity of the Simple Convection-Permitting E3SM Atmosphere Model in a Doubly-Periodic Configuration, J. Adv. Model. Earth Sy., 15, e2022MS003466, https://doi.org/10.1029/2022MS003466, 2023. a
Bryan, G. H. and Fritsch, J. M.: A Benchmark Simulation for Moist Nonhydrostatic Numerical Models, Mon. Weather Rev., 130, 2917–2928, https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2, 2002. a
Eldred, C., Taylor, M., and Guba, O.: Thermodynamically consistent versions of approximations used in modelling moist air, Q. J. Roy. Meteor. Soc., 148, 3184–3210, https://doi.org/10.1002/qj.4353, 2022. a
Emanuel, K.: Atmospheric Convection, Oxford University Press, ISBN 9780195066302, https://doi.org/10.1002/qj.49712152516, 1994. a
Foucar, J., Edwards, J., Petersen, M., Bertagna, L., Hoffman, M., Jacobsen, D., Wolfe, J., Mametjanov, A., Duda, M., Jacob, R., singhbalwinder, AaronDonahue, Taylor, M., Hillman, B. R., Sacks, B., onguba, for E3SM related projects, A., Asay-Davis, X., Hannah, W., Turner, A. K., noel, Bradley, A. M., jayeshkrishna, Roekel, L. V., fischer ncar, Paul, K., Ringler, T., Deakin, M., Turner, M., and ldfowler58: oksanaguba/E3SM: support-materials5, Zenodo [code], https://doi.org/10.5281/zenodo.8336379, 2023. a
Golaz, J.-C., Caldwell, P. M., Roekel, L. P. V., Petersen, M. R., Tang, Q., Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay-Davis, X. S., Bader, D. C., Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M. A., Brus, S. R., Burrows, S. M., Cameron-Smith, P. J., Donahue, A. S., Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J. G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H.-Y., Lin, W., Lipscomb, W. H., Ma, P.-L., Mahajan, S., Maltrud, M. E., Mametjanov, A., McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch, P. J., Eyre, J. J. R., Riley, W. J., Ringler, T. D., Roberts, A. F., Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J., Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang, Y., Yoon, J.-H., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang, K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution, J. Adv. Model. Earth Sy., 11, 2089–2129, https://doi.org/10.1029/2018ms001603, 2019. a, b, c, d
Golaz, J.-C., Van Roekel, L. P., Zheng, X., Roberts, A. F., Wolfe, J. D., Lin, W., Bradley, A. M., Tang, Q., Maltrud, M. E., Forsyth, R. M., Zhang, C., Zhou, T., Zhang, K., Zender, C. S., Wu, M., Wang, H., Turner, A. K., Singh, B., Richter, J. H., Qin, Y., Petersen, M. R., Mametjanov, A., Ma, P.-L., Larson, V. E., Krishna, J., Keen, N. D., Jeffery, N., Hunke, E. C., Hannah, W. M., Guba, O., Griffin, B. M., Feng, Y., Engwirda, D., Di Vittorio, A. V., Dang, C., Conlon, L. M., Chen, C.-C.-J., Brunke, M. A., Bisht, G., Benedict, J. J., Asay-Davis, X. S., Zhang, Y., Zhang, M., Zeng, X., Xie, S., Wolfram, P. J., Vo, T., Veneziani, M., Tesfa, T. K., Sreepathi, S., Salinger, A. G., Reeves Eyre, J. E. J., Prather, M. J., Mahajan, S., Li, Q., Jones, P. W., Jacob, R. L., Huebler, G. W., Huang, X., Hillman, B. R., Harrop, B. E., Foucar, J. G., Fang, Y., Comeau, D. S., Caldwell, P. M., Bartoletti, T., Balaguru, K., Taylor, M. A., McCoy, R. B., Leung, L. R., and Bader, D. C.: The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation, J. Adv. Model. Earth Sy., 14, e2022MS003156, https://doi.org/10.1029/2022MS003156, 2022. a
Harrop, B. E., Pritchard, M. S., Parishani, H., Gettelman, A., Hagos, S., Lauritzen, P. H., Leung, L. R., Lu, J., Pressel, K. G., and Sakaguchi, K.: Conservation of Dry Air, Water, and Energy in CAM and Its Potential Impact on Tropical Rainfall, J. Climate, 35, 2895–2917, https://doi.org/10.1175/JCLI-D-21-0512.1, 2022. a
Lauritzen, P. H., Kevlahan, N. K.-R., Toniazzo, T., Eldred, C., Dubos, T., Gassmann, A., Larson, V. E., Jablonowski, C., Guba, O., Shipway, B., Harrop, B. E., Lemarié, F., Tailleux, R., Herrington, A. R., Large, W., Rasch, P. J., Donahue, A. S., Wan, H., Conley, A., and Bacmeister, J. T.: Reconciling and Improving Formulations for Thermodynamics and Conservation Principles in Earth System Models (ESMs), J. Adv. Model. Earth Sy., 14, e2022MS003117, https://doi.org/10.1029/2022MS003117, 2022. a, b, c, d
Lin, S.-J.: A Vertically Lagrangian Finite-Volume Dynamical Core for Global Models, Mon. Weather Rev., 132, 2293–2397, 2004. a
Liu, W., Ullrich, P. A., Guba, O., Caldwell, P. M., and Keen, N. D.: An Assessment of Nonhydrostatic and Hydrostatic Dynamical Cores at Seasonal Time Scales in the Energy Exascale Earth System Model (E3SM), J. Adv. Model. Earth Sy., 14, e2021MS002805, https://doi.org/10.1029/2021MS002805, 2022. a, b, c
Lock, S.-J., Wood, N., and Weller, H.: Numerical analyses of Runge-Kutta implicit-explicit schemes for horizontally explicit, vertically implicit solutions of atmospheric models, Q. J. Roy. Meteor. Soc., 140, 1654–1669, https://doi.org/10.1002/qj.2246, 2014. a
Neale, R. B., Chen, C.-C., Gettelman, A., Lauritzen, P. H., Park, S., Williamson, D. L., Conley, A. J., Garcia, R., Kinnison, D., Lamarque, J.-F., Marsh, D., Mills, M., Smith, A. K., Tilmes, S., Vitt, F., Morrison, H., Cameron-Smith, P., Collins, W. D., Iacono, M. J., Easter, R. C., Ghan, S. J., Liu, X., Rasch, P. J., and Taylor, M. A.: Description of the NCAR Community Atmosphere Model (CAM 5.0), https://www.cesm.ucar.edu/models/cesm1.0/cam/docs/description/cam5_desc.pdf (last access: 2 July 2021), 2012. a
Rasch, P. J., Xie, S., Ma, P.-L., Lin, W., Wang, H., Tang, Q., Burrows, S. M., Caldwell, P., Zhang, K., Easter, R. C., Cameron-Smith, P., Singh, B., Wan, H., Golaz, J.-C., Harrop, B. E., Roesler, E., Bacmeister, J., Larson, V. E., Evans, K. J., Qian, Y., Taylor, M., Leung, L. R., Zhang, Y., Brent, L., Branstetter, M., Hannay, C., Mahajan, S., Mametjanov, A., Neale, R., Richter, J. H., Yoon, J.-H., Zender, C. S., Bader, D., Flanner, M., Foucar, J. G., Jacob, R., Keen, N., Klein, S. A., Liu, X., Salinger, A., Shrivastava, M., and Yang, Y.: An Overview of the Atmospheric Component of the Energy Exascale Earth System Model, J. Adv. Model. Earth Sy., 11, 2377–2411, https://doi.org/10.1029/2019MS001629, 2019. a
Reed, K. A. and Jablonowski, C.: Idealized tropical cyclone simulations of intermediate complexity: A test case for AGCMs, J. Adv. Model. Earth Sy., 4, M04001, https://doi.org/10.1029/2011MS000099, 2012. a, b, c
Satoh, M.: Conservative scheme for the compressible nonhydrostatic models with the horizontally explicit and vertically implicit time integration scheme, Mon. Weather Rev., 130, 1227–1245, 2002. a
Séférian, R., Delire, C., Decharme, B., Voldoire, A., Salas y Melia, D., Chevallier, M., Saint-Martin, D., Aumont, O., Calvet, J.-C., Carrer, D., Douville, H., Franchistéguy, L., Joetzjer, E., and Sénési, S.: Development and evaluation of CNRM Earth system model – CNRM-ESM1, Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, 2016. a
Staniforth, A. N.: Global Atmospheric and Oceanic Modelling: Fundamental Equations, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/9781108974431, 2022. a
Taylor, M. A.: Conservation of mass and energy for the moist atmospheric primitive equations on unstructured grids, in: Numerical Techniques for Global Atmospheric Models, Springer Lecture Notes in Computational Science and Engineering, edited by: Lauritzen, P. H., Jablonowski, C., Taylor, M. A., and Nair., R. D., vol. 80 of Lecture Notes in Computational Science and Engineeering, Springer, Berlin, Heidelberg, New York, https://doi.org/10.1007/978-3-642-11640-7, 2011. a, b
Taylor, M. A., Guba, O., Steyer, A., Ullrich, P. A., Hall, D. M., and Eldrid, C.: An Energy Consistent Discretization of the Nonhydrostatic Equations in Primitive Variables, J. Adv. Model. Earth Sy., 12, e2019MS001783, https://doi.org/10.1029/2019MS001783, 2020. a
Termonia, P., Fischer, C., Bazile, E., Bouyssel, F., Brožková, R., Bénard, P., Bochenek, B., Degrauwe, D., Derková, M., El Khatib, R., Hamdi, R., Mašek, J., Pottier, P., Pristov, N., Seity, Y., Smolíková, P., Španiel, O., Tudor, M., Wang, Y., Wittmann, C., and Joly, A.: The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1, Geosci. Model Dev., 11, 257–281, https://doi.org/10.5194/gmd-11-257-2018, 2018. a
Wan, H., Rasch, P. J., Taylor, M. A., and Jablonowski, C.: Short-term time step convergence in a climate model, J. Adv. Model. Earth Sy., 7, 215–225, https://doi.org/10.1002/2014MS000368, 2015. a
Weller, H., Lock, S.-J., and Wood, N.: Runge-Kutta IMEX schemes for the Horizontally Explicit/Vertically Implicit (HEVI) solution of wave equations, J. Comput. Phys., 252, 365–381, https://doi.org/10.1016/j.jcp.2013.06.025, 2013. a
Williamson, D. L., Olson, J. G., Hannay, C., Toniazzo, T., Taylor, M., and Yudin, V.: Energy considerations in the Community Atmosphere Model (CAM), J. Adv. Model. Earth Sy., 7, 1178–1188, 2015. a
Short summary
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.
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a...
