Articles | Volume 15, issue 21
https://doi.org/10.5194/gmd-15-8135-2022
https://doi.org/10.5194/gmd-15-8135-2022
Model evaluation paper
 | 
11 Nov 2022
Model evaluation paper |  | 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, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda

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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. 
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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. 
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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.
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