Articles | Volume 15, issue 11
https://doi.org/10.5194/gmd-15-4355-2022
https://doi.org/10.5194/gmd-15-4355-2022
Development and technical paper
 | 
07 Jun 2022
Development and technical paper |  | 07 Jun 2022

Multiple same-level and telescoping nesting in GFDL's dynamical core

Joseph Mouallem, Lucas Harris, and Rusty Benson

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Cited articles

Black, T. L., Abeles, J. A., Blake, B. T., Jovic, D., Rogers, E., Zhang, X., Aligo, E. A., Dawson, L. C., Lin, Y., Strobach, E., Shafran, P. C., and Carley, J. R.: A Limited Area Modeling Capability for the Finite-Volume Cubed-Sphere (FV3) Dynamical Core and Comparison With a Global Two-Way Nest, J. Adv. Model. Earth Sy., 13, e2021MS002483, https://doi.org/10.1029/2021MS002483, 2021. a
Clark, A. J., Jirak, I. L., Gallo, B. T., Knopfmeier, K. H., Roberts, B., Krocak, M., Vancil, J., Hoogewind, K. A., Dahl, N. A., Loken, E. D., Jahn, D., Harrison, D., Imy, D., Burke, P., Wicker, L. J., Skinner, P. S., Heinselman, P. L., Marsh, P., Wilson, K. A., Dean, A. R., Creager, G. J., Jones, T. A., Gao, J., Wang, Y., Flora, M., Potvin, C. K., Kerr, C. A., Yussouf, N., Martin, J., Guerra, J., Matilla, B. C., and Galarneau, T. J.: The Second Real-Time, Virtual Spring Forecasting Experiment to Advance Severe Weather Prediction, B. Am. Meteorol. Soc., 103, E1114–E1116, https://doi.org/10.1175/BAMS-D-21-0239.1, 2022. a
Dong, J., Liu, B., Zhang, Z., Wang, W., Mehra, A., Hazelton, A. T., Winterbottom, H. R., Zhu, L., Wu, K., Zhang, C., Tallapragada, V., Zhang, X., Gopalakrishnan, S., and Marks, F.: The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season, Atmosphere, 11, 617, https://doi.org/10.3390/atmos11060617, 2020. a
Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J. D.: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res.-Atmos., 108, 8851, https://doi.org/10.1029/2002JD003296, 2003. a
Gao, K., Chen, J.-H., Harris, L., Sun, Y., and Lin, S.-J.: Skillful Prediction of Monthly Major Hurricane Activity in the North Atlantic with Two-way Nesting, Geophys. Res. Lett., 46, 9222–9230, https://doi.org/10.1029/2019GL083526, 2019a. a
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Short summary
The single-nest capability in GFDL's dynamical core, FV3, is upgraded to support multiple same-level and telescoping nests. Grid nesting adds a refined grid over an area of interest to better resolve small-scale flow features necessary to accurately predict special weather events such as severe storms and hurricanes. This work allows concurrent execution of multiple same-level and telescoping multi-level nested grids in both global and regional setups.
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