Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-3029-2023
https://doi.org/10.5194/gmd-16-3029-2023
Model evaluation paper
 | 
01 Jun 2023
Model evaluation paper |  | 01 Jun 2023

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

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

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Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferrado, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D. T., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979 – Present), J. Hydrometeorol., 4, 1147–1167, 2003. a
Allen, T., Daley, C. S., Doerfler, D., Austin, B., and Wright, N. J.: Performance and energy usage of workloads on KNL and haswell architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10724 LNCS, 236–249, https://doi.org/10.1007/978-3-319-72971-8_12, 2018. a
Atmospheric Model Working Group: Atmospheric Model Working Group (AMWG) diagnostics package, Subversion Repository [code], https://www2.cesm.ucar.edu/working_groups/Atmosphere/amwg-diagnostics-package/index.html (last access: 18 May 2023), 2014. a, b
Atmosphere Model Working Group: CAM5.4: Final configuration AMWG diagnostic package, https://webext.cgd.ucar.edu/FAMIP/f.e13.FAMIPC5.f09_f09_beta17_cam5.4_alpha03.002/atm/f.e13.FAMIPC5.f09_f09_beta17_cam5.4_alpha03.002-obs/ (last access: 13 May 2023), 2015. a, b, c
Bacmeister, J. T., Wehner, M. F., Neale, R. B., Gettelman, A., Hannay, C., Lauritzen, P. H., Caron, J. M., and Truesdale, J. E.: Exploratory high-resolution climate simulations using the Community Atmosphere Model (CAM), J. Climate, 27, 3073–3099, https://doi.org/10.1175/JCLI-D-13-00387.1, 2014. a, b, c
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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.