Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-205-2021
https://doi.org/10.5194/gmd-14-205-2021
Development and technical paper
 | 
12 Jan 2021
Development and technical paper |  | 12 Jan 2021

Spin-up characteristics with three types of initial fields and the restart effects on forecast accuracy in the GRAPES global forecast system

Zhanshan Ma, Chuanfeng Zhao, Jiandong Gong, Jin Zhang, Zhe Li, Jian Sun, Yongzhu Liu, Jiong Chen, and Qingu Jiang

Related authors

Stripe Patterns in Wind Forecasts Induced by Physics-Dynamics Coupling on a Staggered Grid in CMA-GFS 3.0
Jiong Chen, Yong Su, Zhe Li, Zhanshan Ma, and Xueshun Shen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2704,https://doi.org/10.5194/egusphere-2025-2704, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Simulation study of a Squall line hailstorm using High-Resolution GRAPES-Meso with a modified Double-Moment Microphysics scheme
Zhe Li, Qijun Liu, Xiaomin Chen, Zhanshan Ma, Jiong Chen, and Yuan Jiang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-439,https://doi.org/10.5194/gmd-2020-439, 2021
Preprint withdrawn
Short summary

Related subject area

Climate and Earth system modeling
Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev., 18, 4009–4021, https://doi.org/10.5194/gmd-18-4009-2025,https://doi.org/10.5194/gmd-18-4009-2025, 2025
Short summary
ICON-HAM-lite 1.0: simulating the Earth system with interactive aerosols at kilometer scales
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025,https://doi.org/10.5194/gmd-18-3877-2025, 2025
Short summary
Process-based modeling framework for sustainable irrigation management at the regional scale: integrating rice production, water use, and greenhouse gas emissions
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev., 18, 3799–3817, https://doi.org/10.5194/gmd-18-3799-2025,https://doi.org/10.5194/gmd-18-3799-2025, 2025
Short summary
Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration
Carolina A. Bieri, Francina Dominguez, Gonzalo Miguez-Macho, and Ying Fan
Geosci. Model Dev., 18, 3755–3779, https://doi.org/10.5194/gmd-18-3755-2025,https://doi.org/10.5194/gmd-18-3755-2025, 2025
Short summary
Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev., 18, 3661–3679, https://doi.org/10.5194/gmd-18-3661-2025,https://doi.org/10.5194/gmd-18-3661-2025, 2025
Short summary

Cited articles

Anthes, R. A., Kuo, Y., Hsie, E., Low-Nam, S., and Bettge, T. W.: Estimation of skill and uncertainty in regional numerical models, Q. J. Roy. Meteor. Soc., 115, 763–806, https://doi.org/10.1002/qj.49711548803, 1989. 
Arakawa, A. and Schubert, W. H.: Interaction of a cumulus cloud ensemble with the large-scale environment, Part I, J. Atmos. Sci., 31, 674–701, https://doi.org/10.1175/1520-0469(1974)031<0674:IOACCE>2.0.CO;2, 1974. 
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. 
Bjerknes, V.: Das Problem der Wettervorhersage, betrachtet vom Standpunkte der Mechanick und der Physik [The problem of weather prediction as seen from the standpoint of mechanics and physics], Meteorol. Z., 21, 1–7, 1904. 
Bryan, K.: Accelerating the convergence to equilibrium of ocean–climate models, J. Phys. Oceanogr., 14, 666–673, https://doi.org/10.1175/1520-0485(1984)014<0666:ATCTEO>2.0.CO;2, 1984. 
Download
Short summary
The spin-up in GRAPES_GFS, under different initial fields, goes through a dramatic adjustment in the first half-hour of integration and slow dynamic and thermal adjustments afterwards. It lasts for at least 6 h, with model adjustment gradually completed from lower to upper layers in the model. Thus, the forecast results, at least in the first 6 h, should be avoided when used. In addition, the spin-up process should repeat when the model simulation is interrupted.
Share