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- Title
GFS 气温预报模型在黄河内蒙古河段应用效果检验与分析.
- Authors
范旻昊; 田文君
- Abstract
The short-to-mid range temperature forecasting model of the ice-run flood season of the Yellow River was established based on GFS model and multiple stepwise regression method. In this study, the GFS model data and the daily mean temperature data of Baotou Hydrological Station from November 1 to March 31, 2019-2020 were selected to access the forecasting results which were analyzed and evaluated to show the prediction accuracy of the model by means of some error analysis methods such as mean absolute error, root mean square error, forecasting accuracy and curve analysis. The results show that the model has a certain forecasting capability and can be used in ice-run flood control and scientific research in up-stream regions along the Yellow River. The mean absolute error of 1-3 days( 24-72 h) forecasting results is within 2 t. The mean absolute error of 4-7 days( 96-168 h) forecasting results is within 2.5 t. The mot mean square error of 1-10 days( 24-240 h) forecasting results is within 2.5 t, while the accuracy rate is more than 60%. The forecasting effect of each foreseeable period within 1-7 days( 24-168 h) in November and March is obviously better than that in other months. Since temperature forecasting is the basis of ice flow forecasting, and November and March is the critical period of ice flow and thawing, the capability of 1-7 days( 24-168 h) forecasting in November and March has great significance in ice-run flood control and disaster reduction.
- Publication
Yellow River, 2022, Vol 44, Issue 8, p52
- ISSN
1000-1379
- Publication type
Article
- DOI
10.3969/j.issn.1000-1379.2022.08.011