Mechanism Study of Two-Dimensional Precipitation Diagnostic Models Within a Dynamic Framework

This study investigates the formation and triggering mechanisms of precipitation processes. Given the substantial effort required to construct a 3D model, we developed an idealized 2D precipitation scenario, using a simplified dynamical framework with vortex wind fields as the background atmospheric flow field. By modeling the transport, uplift, and subsidence of water vapor and liquid water, a condensation model was developed to simulate air parcel uplift and high-altitude water vapor condensation. Further, a cloud microphysics precipitation scheme was incorporated to simulate precipitation triggering and falling processes following water vapor condensation. Model results demonstrate that the approach accurately reproduces key processes of water vapor transport, condensation, and precipitation formation. With a time step of 15 s and a total of 120 steps, the simulation of a 30-min scenario was completed in just 158.5 s, indicating the high computational efficiency of the model. This paper introduces an innovative research scheme for a diagnostic model. Upon technological maturity, the model will utilize radar wind field data as its input to evaluate and enhance the performance of precipitation diagnostic models in real weather processes. This research lays a solid foundation for the further refinement and optimization of precipitation forecasting models, thereby advancing the accuracy of weather prediction.

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Publication Details

Journal
Atmosphere
Published
2025-03-27
DOI
https://doi.org/10.3390/atmos16040380
Citations
1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.30

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article

Mechanism Study of Two-Dimensional Precipitation Diagnostic Models Within a Dynamic Framework

Xiangqian Wei, Xinyu Chang, Yi Liu, Jun Guo et al.
1 citations
Atmosphere
Meteorological Phenomena and Simulations
1.30
article

Mechanism Study of Two-Dimensional Precipitation Diagnostic Models Within a Dynamic Framework

Xiangqian Wei, Xinyu Chang, Yi Liu, Jun Guo, Haochuan Li
article en
1 citations

Abstract

This study investigates the formation and triggering mechanisms of precipitation processes. Given the substantial effort required to construct a 3D model, we developed an idealized 2D precipitation scenario, using a simplified dynamical framework with vortex wind fields as the background atmospheric flow field. By modeling the transport, uplift, and subsidence of water vapor and liquid water, a condensation model was developed to simulate air parcel uplift and high-altitude water vapor condensation. Further, a cloud microphysics precipitation scheme was incorporated to simulate precipitation triggering and falling processes following water vapor condensation. Model results demonstrate that the approach accurately reproduces key processes of water vapor transport, condensation, and precipitation formation. With a time step of 15 s and a total of 120 steps, the simulation of a 30-min scenario was completed in just 158.5 s, indicating the high computational efficiency of the model. This paper introduces an innovative research scheme for a diagnostic model. Upon technological maturity, the model will utilize radar wind field data as its input to evaluate and enhance the performance of precipitation diagnostic models in real weather processes. This research lays a solid foundation for the further refinement and optimization of precipitation forecasting models, thereby advancing the accuracy of weather prediction.

AtmosphereVol. 16(4)
Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, Chinese Academy of Engineering, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 25%
Meteorological Phenomena and Simulations
1.30
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Mechanism Study of Two-Dimensional Precipitation Diagnostic Models Within a Dynamic Framework — Xiangqian Wei, Xinyu Chang, et al. · Atmosphere (2025) | TGRS Research Map | TGRS