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

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Preprint withdrawn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
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024,https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
CD-type discretization for sea ice dynamics in FESOM version 2
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024,https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024,https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024,https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024,https://doi.org/10.5194/gmd-17-2117-2024, 2024
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.