Objective weather typing method based on numerical statistics
A technology of numerical statistics and classification methods, applied in weather forecasting, calculation, meteorology, etc., can solve the problem of lack of timeliness, high objective weather classification methods, subjective classification methods, weak universality of classification results, and poor weather types. Analyse problems such as impossible
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Embodiment 1
[0025] like figure 1 Shown, the objective weather typing method based on numerical statistics of the present invention, comprises the following steps:
[0026] (1) Download the long-term global meteorological reanalysis data, select the meteorological elements specific to the 850hPa altitude layer at specific times of the day as the judgment factor, and select the appropriate spatial range according to the classification area;
[0027] (2) Before using the computer to classify the weather, it is necessary to standardize the meteorological grid point data. The standardization process can effectively eliminate the difference in the horizontal pressure gradient in different seasons. The standardized calculation formula is where Z i is the normalized value of the ith grid point, X i is the original value of the ith grid point, is the mean value of the study area, and S is the standard deviation of the study area.
[0028] (3) Integrated monitoring of large-load airships, un...
Embodiment 2
[0033]Taking the meteorological grid data of the Beijing-Tianjin-Hebei region as an example, it focuses on the classification of the dominant weather types in the Beijing-Tianjin-Hebei region over the past three decades. Classified into five dominant circulation situations, combined with the new-generation mesoscale weather forecast model WRF to simulate the meteorological field in the desired area in the next week, and classified and analyzed the weather situation in the next 7 days to the dominant type through the calculation of deviation index and similarity index.
[0034] (1) Download the NCEP / NCAR global meteorological reanalysis data from 1980 to 2016. Because the near-surface meteorological field is significantly affected by the physical characteristics of the surface, it is easy to cause a small-scale circulation disturbance system, and the high-level meteorological field is weakly related to the surface meteorological factors. And the algorithm has poor discrimination...
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