3results about How to "Improve the forecast effect" patented technology

This invention relates to the field of AI weather forecasting technology and discloses a weather forecasting method based on an AI weather forecasting model and a WRF model. The method includes: inputting ERA5 global atmospheric reanalysis gridded data into the AI ​​weather forecasting model to obtain an assimilated background field; constructing an effective multi-source observation vector based on observation data from ground automatic weather stations, radiosonde observation data, geostationary meteorological satellite radiance data, and Doppler radar VAD wind profile data; solving for the optimal atmospheric analysis field; extracting atmospheric state variables from the optimal atmospheric analysis field and writing them into the WRF model's side boundary driving file, driving the WRF model to complete the integration operation, and obtaining a gridded forecast field of meteorological elements. This method enables the WRF boundary condition update frequency to be higher than the traditional 6-hour static scheme, effectively characterizing the rapid evolution of the atmospheric state in the boundary region at the sub-hourly scale, thereby improving the WRF model's forecasting capability for high-impact weather events such as severe convection.

The invention belongs to the crossing field of new energy and meteorology, and discloses a meteorological inversion assimilation method based on new energy power generation data and a related device. The meteorological inversion assimilation method based on the new energy power generation data comprises the following steps: acquiring original power generation data of a new energy station; performing state discrimination and data cleaning on the original power generation data to obtain inversion basic data; carrying out meteorological inversion by adopting a physical-data hybrid driving model, and carrying out uncertainty quantification and screening on meteorological inversion initial data to obtain meteorological inversion screening data; and based on meteorological inversion screening data and a selected assimilation algorithm, state correction is carried out on the numerical weather forecast NWP model, and an NWP model after initial field optimization is obtained. According to the technical scheme disclosed by the invention, the problem of insufficient precision in the process of simulating and forecasting the meteorological conditions of the new energy station region by the NWP model at the present stage can be solved.

The invention discloses a solar flare forecasting method and system based on fusion of physical parameters and geometric features of an active area. The method comprises the following steps: acquiring magnetic field observation data and optical image data of a target solar active area; extracting magnetic field physical parameters from the magnetic field observation data, and extracting geometric features of an active area from the optical image data; acquiring magnetic field observation data and optical image data of the target solar active area in a historical time window, and constructing a time sequence of magnetic field physical parameters and geometric features; extracting dynamic evolution characteristics of physical parameters and geometric characteristics of the magnetic field from the time sequence; fusing the physical parameters and the geometric features of the current magnetic field with the dynamic evolution features, and constructing an enhanced fusion feature vector; inputting the enhanced fusion feature vector into a pre-trained neural network model, and obtaining a prediction probability of generating a specific-level flare in the target solar activity area in the future; and generating and issuing flare forecast information according to a comparison result of the forecast probability and a preset threshold value.