Articles | Volume 15, issue 21
https://doi.org/10.5194/gmd-15-8135-2022
© 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-15-8135-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
11 Nov 2022
Model evaluation paper |
| 11 Nov 2022
| 11 Nov 2022
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
Xingying Huang
CORRESPONDING AUTHOR
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Andrew Gettelman
National Center for Atmospheric Research, Boulder, CO 80305,
USA
William C. Skamarock
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Peter Hjort Lauritzen
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Miles Curry
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Adam Herrington
National Center for Atmospheric Research, Boulder, CO 80305,
USA
John T. Truesdale
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Michael Duda
National Center for Atmospheric Research, Boulder, CO 80305,
USA
Related authors
No articles found.
Ci Song, Daniel T. McCoy, Isabel L. McCoy, Hunter Brown, Andrew Gettelman, Trude Eidhammer, and Donifan Barahona
EGUsphere, https://doi.org/10.5194/egusphere-2025-2009, https://doi.org/10.5194/egusphere-2025-2009, 2025
Short summary
Short summary
This study examines how aerosols from human activities alter cloud microphysical properties. Airborne observations from a field campaign are used to constrain an ensemble of global model configurations and their associated cloud property changes. Results show that airborne in-situ measurements of aerosol and cloud properties do provide insight into global changes in cloud microphysics but are sensitive to uncertainties in both airborne measurements and Earth system model emulators.
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.
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
Atmos. Chem. Phys., 25, 4547–4570, https://doi.org/10.5194/acp-25-4547-2025, https://doi.org/10.5194/acp-25-4547-2025, 2025
Short summary
Short summary
Whether increased aerosol increases or decreases liquid cloud mass has been a longstanding question. Observed correlations suggest that aerosols thin liquid cloud, but we are able to show that observations were consistent with an increase in liquid cloud in response to aerosols by leveraging a model where causality could be traced.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
Short summary
Short summary
The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
René R. Wijngaard, Willem Jan van de Berg, Christaan T. van Dalum, Adam R. Herrington, and Xavier J. Levine
EGUsphere, https://doi.org/10.5194/egusphere-2025-1070, https://doi.org/10.5194/egusphere-2025-1070, 2025
Short summary
Short summary
We used the variable-resolution CESM to simulate present-day and future temperature and precipitation extremes in the Arctic by applying global grids (~111 km) with and without regional refinement (~28 km) and following a storyline approach. We found that global grids with (without) regional refinement generally perform better in simulating present-day precipitation (temperature) extremes, and that future high (low) temperature and wet precipitation extremes are projected to increase (decrease).
Weiyu Zhang, Kwinten Van Weverberg, Cyril J. Morcrette, Wuhu Feng, Kalli Furtado, Paul R. Field, Chih-Chieh Chen, Andrew Gettelman, Piers M. Forster, Daniel R. Marsh, and Alexandru Rap
Atmos. Chem. Phys., 25, 473–489, https://doi.org/10.5194/acp-25-473-2025, https://doi.org/10.5194/acp-25-473-2025, 2025
Short summary
Short summary
Contrail cirrus is the largest, but also most uncertain, contribution of aviation to global warming. We evaluate, for the first time, the impact of the host climate model on contrail cirrus properties. Substantial differences exist between contrail cirrus formation, persistence, and radiative effects in the host climate models. Reliable contrail cirrus simulations require advanced representation of cloud optical properties and microphysics, which should be better constrained by observations.
Johannes Mülmenstädt, Andrew S. Ackerman, Ann M. Fridlind, Meng Huang, Po-Lun Ma, Naser Mahfouz, Susanne E. Bauer, Susannah M. Burrows, Matthew W. Christensen, Sudhakar Dipu, Andrew Gettelman, L. Ruby Leung, Florian Tornow, Johannes Quaas, Adam C. Varble, Hailong Wang, Kai Zhang, and Youtong Zheng
Atmos. Chem. Phys., 24, 13633–13652, https://doi.org/10.5194/acp-24-13633-2024, https://doi.org/10.5194/acp-24-13633-2024, 2024
Short summary
Short summary
Stratocumulus clouds play a large role in Earth's climate by reflecting incoming solar energy back to space. Turbulence at stratocumulus cloud top mixes in dry, warm air, which can lead to cloud dissipation. This process is challenging for coarse-resolution global models to represent. We show that global models nevertheless agree well with our process understanding. Global models also think the process is less important for the climate than other lines of evidence have led us to conclude.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
Short summary
Short summary
We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Annelise Waling, Adam Herrington, Katharine Duderstadt, Jack Dibb, and Elizabeth Burakowski
Weather Clim. Dynam., 5, 1117–1135, https://doi.org/10.5194/wcd-5-1117-2024, https://doi.org/10.5194/wcd-5-1117-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are channel-shaped features within the atmosphere that carry moisture from the mid-latitudes to the poles, bringing warm temperatures and moisture that can cause melt in the Arctic. We used variable-resolution grids to model ARs around the Greenland ice sheet and compared this output to uniform-resolution grids and reanalysis products. We found that the variable-resolution grids produced ARs and precipitation that were more similar to observation-based products.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
Short summary
Short summary
Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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.
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
Short summary
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.
Rajashree Tri Datta, Adam Herrington, Jan T. M. Lenaerts, David P. Schneider, Luke Trusel, Ziqi Yin, and Devon Dunmire
The Cryosphere, 17, 3847–3866, https://doi.org/10.5194/tc-17-3847-2023, https://doi.org/10.5194/tc-17-3847-2023, 2023
Short summary
Short summary
Precipitation over Antarctica is one of the greatest sources of uncertainty in sea level rise estimates. Earth system models (ESMs) are a valuable tool for these estimates but typically run at coarse spatial resolutions. Here, we present an evaluation of the variable-resolution CESM2 (VR-CESM2) for the first time with a grid designed for enhanced spatial resolution over Antarctica to achieve the high resolution of regional climate models while preserving the two-way interactions of ESMs.
René R. Wijngaard, Adam R. Herrington, William H. Lipscomb, Gunter R. Leguy, and Soon-Il An
The Cryosphere, 17, 3803–3828, https://doi.org/10.5194/tc-17-3803-2023, https://doi.org/10.5194/tc-17-3803-2023, 2023
Short summary
Short summary
We evaluate the ability of the Community Earth System Model (CESM2) to simulate cryospheric–hydrological variables, such as glacier surface mass balance (SMB), over High Mountain Asia (HMA) by using a global grid (~111 km) with regional refinement (~7 km) over HMA. Evaluations of two different simulations show that climatological biases are reduced, and glacier SMB is improved (but still too negative) by modifying the snow and glacier model and using an updated glacier cover dataset.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
Short summary
Short summary
A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
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
Short summary
Short summary
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.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
Short summary
Short summary
Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
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.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
Short summary
Short summary
Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Andrew Gettelman, Chieh-Chieh Chen, and Charles G. Bardeen
Atmos. Chem. Phys., 21, 9405–9416, https://doi.org/10.5194/acp-21-9405-2021, https://doi.org/10.5194/acp-21-9405-2021, 2021
Short summary
Short summary
The COVID-19 pandemic caused significant economic disruption in 2020 and severely impacted air traffic. We use a climate model to evaluate the effect of the reductions in aviation on climate in 2020. Contrails, in general, warm the planet, and COVID-19-related reductions in contrails cooled the land surface in 2020. The timing of reductions in aviation was important, and this may change how we think about the future effects of contrails.
Cited articles
Bacmeister, J. T., Reed, K. A., Hannay, C., Lawrence, P., Bates, S.,
Truesdale, J. E., Rosenbloom, N., and Levy, M.: Projected changes in tropical
cyclone activity under future warming scenarios using a high-resolution
climate model, Clim. Change, 146, 547–560, 2018.
Bellprat, O., Guemas, V., Doblas-Reyes, F., and Donat, M. G.: Towards reliable
extreme weather and climate event attribution, Nat. Commun., 10,
1–7, 2019.
Broxton, P., Zeng, X., and Dawson, N.: Daily 4 km Gridded SWE and Snow Depth
from Assimilated In-Situ and Modeled Data over the Conterminous US, Version
1. Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed
Active Archive Center, https://doi.org/10.5067/0GGPB220EX6A.
2019.
Caldwell, P. M., Terai, C. R., Hillman, B., Keen, N. D., Bogenschutz, P., Lin,
W., Beydoun, H., Taylor, M., Bertagna, L., Bradley, A. M., and Clevenger,
T. C.: Convection-Permitting Simulations With the E3SM Global Atmosphere
Model, J. Adv. Model. Earth Sy., 13,
e2021MS002544, https://doi.org/10.1029/2021MS002544, 2021.
Daly, C., Slater, M. E., Roberti, J. A., Laseter, S. H., and Swift Jr., L. W.: High‐resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset, Int. J. Climatol., 37, 124–137, 2017.
Danabasoglu, G., Lamarque, J. F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., and Hannay, C.: The community earth system model version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Dettinger, M. D., Ralph, F. M., Das, T., Neiman, P. J., and Cayan, D. R.:
Atmospheric rivers, floods and the water resources of California, Water,
3, 445–478, 2011.
DeWalle, D. R. and Rango, A.: Principles of snow hydrology, Cambridge
University Press, 410 pp., ISBN-10 0511535678, 2008.
Dueben, P. D., Wedi, N., Saarinen, S., and Zeman, C.: Global simulations of
the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting
System, J. Meteorol. Soc. Japan Ser. II, 98, 551–572, 2020.
Fan, Y. and Van den Dool, H.: A global monthly land surface air temperature
analysis for 1948–present, J. Geophys. Res.-Atmos., 113, D01103, 2008.
Feng, Z., Song, F., Sakaguchi, K., and Leung, L. R.: Evaluation of mesoscale
convective systems in climate simulations: Methodological development and
results from MPAS-CAM over the United States, J. Climate, 34,
2611–2633, 2021.
Gettelman, A., Morrison, H., Santos, S., Bogenschutz, P., and Caldwell, P. M.:
Advanced two-moment bulk microphysics for global models. Part II: Global
model solutions and aerosol–cloud interactions, J. Climate,, 28, 1288–1307, 2015.
Gettelman, A., Callaghan, P., Larson, V. E., Zarzycki, C. M., Bacmeister,
J. T., Lauritzen, P. H., Bogenschutz, P. A., and Neale, R. B.: Regional climate
simulations with the community earth system model, J. Adv.
Model. Earth Sy., 10, 1245–1265, 2018.
Gettelman, A., Morrison, H., Thayer-Calder, K., and Zarzycki, C. M.: The
impact of rimed ice hydrometeors on global and regional climate, J.
Adv. Model. Earth Sy., 11, 1543–1562, 2019.
Golaz, J. C., Larson, V. E., and Cotton, W. R.: A PDF-based model for boundary
layer clouds. Part I: Method and model description, J. Atmos. Sci., 59, 3540–3551,
2002.
Hamlet, A. F. and Lettenmaier, D. P.: Effects of 20th century warming and
climate variability on flood risk in the western US, Water Resour.
Res., 43, W06427, https://doi.org/10.1029/2006WR005099, 2007.
Hart, D.: Cheyenne supercomputer, NCAR CISL, https://doi.org/10.5065/D6RX99HX, 2021.
Huang, X. and Ullrich, P. A.: The changing character of twenty-first-century
precipitation over the western United States in the variable-resolution
CESM, J. Climate, 30, 7555–7575, 2017.
Huang, X., Rhoades, A. M., Ullrich, P. A., and Zarzycki, C. M.: An evaluation of
the variable-resolution CESM for modeling California's climate, J.
Adv. Model. Earth Sy., 8, 345–369, 2016.
Huang, X., Stevenson, S., and Hall, A. D.: Future warming and intensification
of precipitation extremes: A “double whammy” leading to increasing flood
risk in California, Geophys. Res. Lett., 47, e2020GL088679, https://doi.org/10.1029/2020GL088679,
2020a.
Huang, X., Swain, D. L., and Hall, A. D.: Future precipitation increase from
very high resolution ensemble downscaling of extreme atmospheric river
storms in California, Sci. Adv., 6, eaba1323, https://doi.org/10.1126/sciadv.aba1323, 2020b.
Huang, X., et al.: WUS-Precip-SIMA-MPAS, Zenodo [code and data set], https://doi.org/10.5281/zenodo.6558578, 2022.
Kapnick, S. B., Yang, X., Vecchi, G. A., Delworth, T. L., Gudgel, R., Malyshev,
S., Milly, P. C., Shevliakova, E., Underwood, S., and Margulis, S. A.:
Potential for western US seasonal snowpack prediction, P.
Natl. Acad. Sci., 115, 1180–1185, 2018.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. E., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S.-H.: Surface irradiances
of Edition 4.0 Clouds and the Earth's Radiant Energy System (CERES) Energy
Balanced and Filled (EBAF) data product, J. Climate, 31, 4501–4527, https://doi.org/10.1175/JCLI-D-17-0523.1, 2018.
Klemp, J. B.: A terrain-following coordinate with smoothed coordinate
surfaces, Mon. Weather Rev. 139, 2163–2169, 2011.
Lauritzen, P. H. and Williamson, D. L.: A total energy error analysis of
dynamical cores and physics-dynamics coupling in the Community Atmosphere
Model (CAM), J. Adv. Model. Earth Sy., 11, 1309–1328, https://doi.org/10.1029/2018MS001549, 2019.
Lauritzen, P. H., Kevlahan, N. R., Toniazzo, T., Eldred, C., Dubos, T.,
Gassmann, A., Larson, V. E., Jablonowski, C., Guba, O., Shipway, B., and
Harrop, B. E.: Reconciling and improving formulations for thermodynamics and
conservation principles in Earth System Models (ESMs), J. Adv. Model. Earth Sys., 14, e2022MS003117, https://doi.org/10.1029/2022MS003117, 2022.
Leung, L. R. and Qian, Y.: Atmospheric rivers induced heavy precipitation and
flooding in the western US simulated by the WRF regional climate model,
Geophys. Res. Lett., 36, L03820, https://doi.org/10.1029/2008GL036445, 2009.
Lin, G., Jones, C. R., Leung, L. R., Feng, Z., and Ovchinnikov, M.: Mesoscale
convective systems in a superparameterized E3SM simulation at high
resolution, J. Adv. Model. Earth Sy., 14,
e2021MS002660, https://doi.org/10.1029/2021MS002660, 2022.
Liu, C., Ikeda, K., Rasmussen, R., Barlage, M., Newman, A. J., Prein, A. F.,
Chen, F., Chen, L., Clark, M., Dai, A., and Dudhia, J.: Continental-scale
convection-permitting modeling of the current and future climate of North
America, Clim. Dynam., 49, 71–95, 2017.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's
Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)
Top-of-Atmosphere (TOA) Edition-4.0 Data Product, J. Climate, 31, 895–918,
https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Meehl, G. A., Zwiers, F., Evans, J., Knutson, T., Mearns, L., and Whetton, P.:
Trends in extreme weather and climate events: issues related to modeling
extremes in projections of future climate change, B. Am.
Meteorol. Soc., 81, 427–436, 2000.
Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An overview of the global historical climatology network-daily database, J. Atmos. Ocean. Tech., 29, 897–910, 2012.
NCAR: SIMA-MPAS (V1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7218023, 2022.
Neiman, P. J., Schick, L. J., Ralph, F. M., Hughes, M., and Wick, G. A.: Flooding
in western Washington: The connection to atmospheric rivers, J.
Hydrometeorol., 12, 1337–1358, 2011.
Pierce, D. W., Su, L., Cayan, D. R., Risser, M. D., Livneh, B., and Lettenmaier,
D. P.: An Extreme-Preserving Long-Term Gridded Daily Precipitation Dataset
for the Conterminous United States, J. Hydrometeorol., 22,
1883–1895, 2021.
Ralph, F. M., Rutz, J. J., Cordeira, J. M., Dettinger, M., Anderson, M.,
Reynolds, D., Schick, L. J., and Smallcomb, C.: A scale to characterize the
strength and impacts of atmospheric rivers, B. Am.
Meteorol. Soc., 100, 269–289, 2019.
Rasmussen, R., Dai, A., Liu, C., and Ikeda, K.: CONUS (Continental
U.S.) II High Resolution Present and Future Climate Simulation. Research
Data Archive at the National Center for Atmospheric Research, Computational
and Information Systems Laboratory, https://rda.ucar.edu/datasets/ds612.5/, last access: 4 December 2021.
Rauscher, S. A. and Ringler, T. D.: Impact of variable-resolution meshes on
midlatitude baroclinic eddies using CAM-MPAS-A, Mon. Weather Rev., 142, 4256–4268, 2014.
Rauscher, S. A., Ringler, T. D., Skamarock, W. C., and Mirin, A. A.: Exploring a
global multiresolution modeling approach using aquaplanet simulations,
J. Climate, 26, 2432–2452, 2013.
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.
Rhoades, A. M., Huang, X., Ullrich, P. A., and Zarzycki, C. M.: Characterizing
Sierra Nevada snowpack using variable-resolution CESM, J. Appl. Meteorol. Climatol., 55, 173–196,
2016.
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological characteristics
of atmospheric rivers and their inland penetration over the western United
States, Mon. Weather Rev., 142, 905–921, 2014.
Sakaguchi, K., Lu, J., Leung, L. R., Zhao, C., Li, Y., and Hagos, S.: Sources
and pathways of the upscale effects on the Southern Hemisphere jet in
MPAS-CAM4 variable-resolution simulations, J. Adv. Model. Earth Sy., 8, 1786–1805, 2016.
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S. J., Putman, W. M.,
and Düben, P.: Global cloud-resolving models, Curr. Clim. Change
Rep., 5, 172–184, 2019.
Sillmann, J., Thorarinsdottir, T., Keenlyside, N., Schaller, N., Alexander,
L. V., Hegerl, G., Seneviratne, S. I., Vautard, R., Zhang, X., and Zwiers,
F. W.: Understanding, modeling and predicting weather and climate extremes:
Challenges and opportunities, Weather Climate Extremes, 18, 65–74,
2017.
Skamarock, W. C., Klemp, J. B., Duda, M. G., Fowler, L. D., Park, S. H., and
Ringler, T. D.: A multiscale nonhydrostatic atmospheric model using
centroidal Voronoi tesselations and C-grid staggering, Mon. Weather
Rev., 140, 3090–3105, 2012.
Skamarock, W. C., Park, S. H., Klemp, J. B., and Snyder, C.: Atmospheric kinetic
energy spectra from global high-resolution nonhydrostatic simulations,
J. Atmos. Sci., 71, 4369–4381, 2014.
Small, R. J., Bacmeister, J., Bailey, D., Baker, A., Bishop, S., Bryan, F.,
Caron, J., Dennis, J., Gent, P., Hsu, H. M., and Jochum, M.: A new synoptic
scale resolving global climate simulation using the Community Earth System
Model, J. Adv. Model. Earth Sy., 6, 1065–1094, 2014.
Stevens, B., Satoh, M., Auger, L., Biercamp, J., Bretherton, C. S., Chen, X.,
Düben, P., Judt, F., Khairoutdinov, M., Klocke, D., and Kodama, C.:
DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On
Non-hydrostatic Domains, Prog. Earth Planet. Sc., 6,
1–17, 2019.
Stevens, B., Acquistapace, C., Hansen, A., Heinze, R., Klinger, C., Klocke,
D., Rybka, H., Schubotz, W., Windmiller, J., Adamidis, P., and Arka, I.: The
added value of large-eddy and storm-resolving models for simulating clouds
and precipitation, J. Meteorol. Soc. Japan Ser. II, 98, 395–435,
2020.
van Kampenhout, L., Rhoades, A. M., Herrington, A. R., Zarzycki, C. M., Lenaerts, J. T. M., Sacks, W. J., and van den Broeke, M. R.: Regional grid refinement in an Earth system model: impacts on the simulated Greenland surface mass balance, The Cryosphere, 13, 1547–1564, https://doi.org/10.5194/tc-13-1547-2019, 2019.
Zarzycki, C. M. and Jablonowski, C.: A multidecadal simulation of Atlantic
tropical cyclones using a variable-resolution global atmospheric general
circulation model, J. Adv. Model. Earth Sy., 6, 805–828, 2014.
Zarzycki, C. M., Jablonowski, C., Thatcher, D. R., and Taylor, M. A.: Effects of
localized grid refinement on the general circulation and climatology in the
Community Atmosphere Model, J. Climate, 28, 2777–2803, 2015.
Zeman, C., Wedi, N. P., Dueben, P. D., Ban, N., and Schär, C.: Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing, Geosci. Model Dev., 14, 4617–4639, https://doi.org/10.5194/gmd-14-4617-2021, 2021.
Zeng, X., Broxton, P., and Dawson, N.: Snowpack Change From 1982 to 2016 Over
Conterminous United States, Geophys. Res. Lett., 45, 12940–12947,
https://doi.org/10.1029/2018GL079621, 2018.
Zhao, C., Leung, L. R., Park, S. H., Hagos, S., Lu, J., Sakaguchi, K., Yoon,
J., Harrop, B. E., Skamarock, W., and Duda, M. G.: Exploring the impacts of
physics and resolution on aqua-planet simulations from a nonhydrostatic
global variable-resolution modeling framework, J. Adv.
Model. Earth Sy., 8, 1751–1768, 2016.
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.
We focus on the recent development of a state-of-the-art storm-resolving global climate model...
