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| Forecasting Methods of Regional Historical Atmospheric Pressure |
| Received:September 03, 2024 Revised:December 18, 2024 |
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| DOI：10.7643/issn.1672-9242.2025.02.019 |
| KeyWord:historical environmental factors spline function time series model spatiotemporal distribution model boundary conditions prediction |
| Author | Institution |
| LIU Jianhong |
Southwest Institute of Technology and Engineering, Chongqing , China |
| LUO Laizheng |
Southwest Institute of Technology and Engineering, Chongqing , China |
| WANG Jiankun |
Southwest Institute of Technology and Engineering, Chongqing , China |
| LI Qian |
Southwest Institute of Technology and Engineering, Chongqing , China |
| WU Xinrui |
Southwest Institute of Technology and Engineering, Chongqing , China |
| SUN Youmei |
Southwest Institute of Technology and Engineering, Chongqing , China |
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| Abstract: |
| The work aims to research the accurate prediction method of historical data of regional typical environmental factors, such as pressure, temperature and humidity. Specifically, by analyzing the spatial and temporal variation of atmospheric pressure, spline function was used to fit the temporal variation, and Gaussian distribution was used to depict the spatial correlation between different stations. Then, a spatial and temporal distribution model of regional historical environmental factors was constructed. Results showed that the maximum absolute error and the average absolute error between the fitted and measured atmospheric pressure data of a station in Hainan Island were less than 0.8 hPa and 0.2 hPa respectively.In addition, the average absolute error of the model for a station in Hainan Island was less than 6 hPa (95.3%), which was about 29.5 hPa for a station in the plateau area. Meanwhile, the average relative error was about 4.6%, indicating high prediction accuracy of the model. Therefore, the constructed spatiotemporal distribution model provides more basic data for the calculation of the extremesdata of regional historical environmental factors, and it also provides new ideas for predicting boundary conditions of environmental factors such as absolute humidity and temperature. |
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