Nowcasting and short-term forecasting fusion system for wind field
A technology of nowcasting and short-term forecasting, applied in the intersection of meteorology and engineering disaster prevention, can solve problems such as the difficulty of wind speed forecasting accuracy, and achieve the effect of improving the accuracy.
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specific Embodiment approach 1
[0040] Specific implementation mode 1. Combination figure 1 Describe this embodiment, a fusion system of nowcasting and short-term forecasting for wind fields, build a model through artificial neural network, use nowcasting and short-term numerical forecasting as input source data, and obtain wind speed with higher accuracy. Including quality control module, error feature analysis module, model building module, inspection module and comprehensive effect evaluation module;
[0041] Quality control module: Preliminary screening of observation data by controlling the threshold range (0≤V≤50m / s) of live observation wind speed; according to the quality control code of the monitoring instrument, the data of poor quality of observation data and abnormal period of observation instrument are eliminated; The quality of data with high wind speed (V ≥ 24m / s) is reconfirmed. By comparing the sliding average value of the time series before and after the same station or the spatial average win...
specific Embodiment approach 2
[0053] Specific embodiment two, combine Figure 2 to Figure 15 Describe this implementation mode, this implementation mode is an embodiment of a wind field-oriented nowcasting and short-term forecasting system described in the first specific implementation mode:
[0054] A wind field-oriented nowcasting and short-term forecasting system described in this implementation is applied to the Beijing area. Four characteristic months of October 2019, January 2020, April, and July were selected as sample data for model establishment. The live data uses the data of national and regional automatic stations as the live observation data, including 20 national stations and 567 regional stations, a total of 587 stations. After preliminary quality control, a total of 363 sites were eligible. Two schemes of multiple linear regression and BP neural network were used to model respectively, and the actual data of related samples and independent samples were tested and compared.
[0055] Such ...
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