Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-205-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-205-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
12 Jan 2021
Development and technical paper |
| 12 Jan 2021
| 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
State Key Laboratory of Earth Surface Processes and Resource Ecology, and College of Global Change and Earth System Science, and Joint Center for Global Change Studies, Beijing Normal University, Beijing, 100875, China
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
State Key Laboratory of Earth Surface Processes and Resource Ecology, and College of Global Change and Earth System Science, and Joint Center for Global Change Studies, Beijing Normal University, Beijing, 100875, China
Jiandong Gong
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
Jin Zhang
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
Jian Sun
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
Yongzhu Liu
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
Jiong Chen
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
Qingu Jiang
National Meteorological Center, Beijing, 100081, China
Numerical Weather Prediction Center of China Meteorological Administration, Beijing, 100081, China
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Cited
12 citations as recorded by crossref.
- Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors W. Jia et al. 10.5194/gmd-16-6833-2023
- Impact of land surface processes on convection over West Africa in convection‐permitting ensemble forecasts: A case study using the MOGREPS ensemble V. Semeena et al. 10.1002/asl.1167
- Improving the Forecasts of Surface Latent Heat Fluxes and Surface Air Temperature in the GRAPES Global Forecast System M. Liang et al. 10.3390/atmos14081241
- Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective W. Jia et al. 10.5194/gmd-16-6635-2023
- A case study of evaluating the GRAPES_Meso V5.0 forecasting performance utilizing observations from South China Sea Experiment 2020 of the “Petrel Project” Z. Ma et al. 10.1016/j.atmosres.2022.106437
- Effect of 2-m Temperature Data Assimilation in the CMA-MESO 3DVAR System Z. Xu et al. 10.1007/s13351-023-2115-9
- A forecast model of short-term wind speed based on the attention mechanism and long short-term memory W. Xing et al. 10.1007/s11042-023-17307-4
- Coupling a New Version of the Common Land Model (CoLM) to the Global/Regional Assimilation and Prediction System (GRAPES): Implementation, Experiment, and Preliminary Evaluation Z. Yuan & N. Wei 10.3390/land11060770
- Assimilating FY3D‐MWRI 23.8 GHz observations in the CMA‐GFS 4DVAR system based on a pseudo All‐Sky data assimilation method H. Xie et al. 10.1002/qj.4544
- Sensitivity of snowfall forecast over North China to ice crystal deposition/sublimation parameterizations in the WSM6 cloud microphysics scheme Z. Ma et al. 10.1002/qj.4132
- Development and validation of a parametric tropical cyclone wave height prediction model G. Grossmann-Matheson et al. 10.1016/j.oceaneng.2023.115353
- Impacts of Transition Approach of Water Vapor-Related Microphysical Processes on Quantitative Precipitation Forecasting Z. Ma et al. 10.3390/atmos13071133
12 citations as recorded by crossref.
- Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors W. Jia et al. 10.5194/gmd-16-6833-2023
- Impact of land surface processes on convection over West Africa in convection‐permitting ensemble forecasts: A case study using the MOGREPS ensemble V. Semeena et al. 10.1002/asl.1167
- Improving the Forecasts of Surface Latent Heat Fluxes and Surface Air Temperature in the GRAPES Global Forecast System M. Liang et al. 10.3390/atmos14081241
- Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective W. Jia et al. 10.5194/gmd-16-6635-2023
- A case study of evaluating the GRAPES_Meso V5.0 forecasting performance utilizing observations from South China Sea Experiment 2020 of the “Petrel Project” Z. Ma et al. 10.1016/j.atmosres.2022.106437
- Effect of 2-m Temperature Data Assimilation in the CMA-MESO 3DVAR System Z. Xu et al. 10.1007/s13351-023-2115-9
- A forecast model of short-term wind speed based on the attention mechanism and long short-term memory W. Xing et al. 10.1007/s11042-023-17307-4
- Coupling a New Version of the Common Land Model (CoLM) to the Global/Regional Assimilation and Prediction System (GRAPES): Implementation, Experiment, and Preliminary Evaluation Z. Yuan & N. Wei 10.3390/land11060770
- Assimilating FY3D‐MWRI 23.8 GHz observations in the CMA‐GFS 4DVAR system based on a pseudo All‐Sky data assimilation method H. Xie et al. 10.1002/qj.4544
- Sensitivity of snowfall forecast over North China to ice crystal deposition/sublimation parameterizations in the WSM6 cloud microphysics scheme Z. Ma et al. 10.1002/qj.4132
- Development and validation of a parametric tropical cyclone wave height prediction model G. Grossmann-Matheson et al. 10.1016/j.oceaneng.2023.115353
- Impacts of Transition Approach of Water Vapor-Related Microphysical Processes on Quantitative Precipitation Forecasting Z. Ma et al. 10.3390/atmos13071133
Latest update: 17 Apr 2024
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.
The spin-up in GRAPES_GFS, under different initial fields, goes through a dramatic adjustment in...
