Articles | Volume 17, issue 15
https://doi.org/10.5194/gmd-17-5883-2024
© Author(s) 2024. 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-17-5883-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Aug 2024
Development and technical paper |
| 07 Aug 2024
| 07 Aug 2024
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province, Center for Weather Forecasting and Climate Prediction of Lanzhou University, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020, China
Yi Yang
CORRESPONDING AUTHOR
Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province, Center for Weather Forecasting and Climate Prediction of Lanzhou University, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Jian Sun
China Meteorological Administration Earth System Modeling and Prediction Centre, Beijing 100081, China
Yuan Jiang
China Meteorological Administration Earth System Modeling and Prediction Centre, Beijing 100081, China
Ruhui Gan
Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province, Center for Weather Forecasting and Climate Prediction of Lanzhou University, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Qian Xie
Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province, Center for Weather Forecasting and Climate Prediction of Lanzhou University, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
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The China New-type Power Systems Meteorological (CNPS-Met) dataset covers mainland China from 1980 to 2016 with a daily resolution and a 25 km grid. It includes eight meteorological variables and eleven high-impact weather events related to power generation, grid transmission, and electricity demand. CNPS-Met outperforms other existing datasets in accuracy for most meteorological variables. We also quantified the frequency hotspots and intensity extremes of high-impact weather events.
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Short summary
Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by...
