Complex terrain processing method and system suitable for three-dimensional non-hydrostatic atmospheric model

CN122242364APending Publication Date: 2026-06-19EARTH SYST NUMERICAL PREDICTION CENT OF CHINA METEOROLOGICAL ADMINISTRATION
View PDF 0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
EARTH SYST NUMERICAL PREDICTION CENT OF CHINA METEOROLOGICAL ADMINISTRATION
Filing Date
2026-03-20
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing three-dimensional non-hydrostatic atmospheric models suffer from problems such as uneven grid division, low computational efficiency, large deviations in physical quantity calculations, and unreasonable boundary conditions when dealing with complex terrain, which affect forecast accuracy and computational stability.

Method used

By employing critical grid identification and adaptive densification techniques, combined with high-order numerical discretization and Moning-Obukhov similarity theory, we optimize grid distribution and load balancing. We also handle complex terrain through local coordinate transformation and immersion boundary algorithms, ensuring the conservation of physical quantities and the accuracy of near-ground velocity simulation.

Benefits of technology

It improves the computational efficiency and forecast accuracy of the three-dimensional non-hydrostatic atmospheric model under complex terrain, reduces numerical oscillations, optimizes the application of boundary conditions, and enhances the reliability of the model.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122242364A_ABST
    Figure CN122242364A_ABST
Patent Text Reader

Abstract

This invention discloses a method and system for processing complex terrain in a three-dimensional non-hydrostatic atmospheric model. The method includes: using terrain data and atmospheric background field from a preset region; performing atmospheric model preprocessing on the terrain data; identifying key grids in the preset region to obtain a grid distribution; marking grid points near the terrain according to the grid distribution and recording distance and slope information to obtain a marked grid distribution; dividing the marked grid distribution into sub-regions based on the number of processes and calculating sub-regions; adaptively refining the grids in the sub-regions; updating the atmospheric equations of the sub-regions through high-order numerical discretization to obtain the predicted variable values ​​for the next time step; generating a logarithmic velocity profile based on the Moning-Obukhov similarity theory; processing the boundary layer atmospheric velocity according to the logarithmic velocity profile to obtain an ideal velocity distribution curve; and outputting atmospheric motion characteristics under complex terrain by correcting the predicted variables at grid points near the underlying surface boundary.
Need to check novelty before this filing date? Find Prior Art