A Method of Assimilating Ground-to-Ground Lightning Conversion to Proxy Radar Echoes for Severe Convective Weather Forecast

Abstract

The invention relates to a method for converting the assimilated cloud-to-ground lightning of severe convection weather forecasting into proxy radar echoes. The method comprises: S1) obtaining the cloud-to-ground lightning data; S2) processing the cloud-to-ground lightning data and administering quality control thereto; S3) converting the cloud-to-ground lightning data into three-dimensional proxy echoes; and S4) substituting the proxy echoes to an assimilated three-dimensional variation system to realize the assimilation of the cloud-to-ground lightning data. The step 1 of obtaining the cloud-to-ground lightning data further comprises S11) selecting the time when the convection system starts to set the assimilation time; and S12) extracting the cloud-to-ground lightning data in the assimilation time period. According to the method for converting the assimilated cloud-to-ground lightning of severe convection weather forecasting into proxy radar echoes, the cloud-to-ground lightning data can be assimilated into a three-dimensional variation system, which increases the approaching forecasting for a severe convection system and makes the method applied to the currently available three-dimensional variation service system.

Description

technical field [0001] The invention belongs to the communication field, and in particular relates to a method for assimilating ground-to-ground flashes and converting proxy radar echoes for strong convective weather forecasting. Background technique [0002] In small and medium-scale numerical forecasting, meteorologists use data assimilation to fuse analysis data and observation data to provide the initial field for the model. Due to the limitation of calculation methods, the observation data assimilated in the early stage are generally conventional observations, such as wind, temperature, pressure, humidity, etc. However, a large number of studies have shown that due to the singleness of observation data, the mesoscale and small-scale information contained in the initial field simulated by reanalysis data and conventional observations is often very limited. As the means of atmospheric detection become more and more abundant, many unconventional observation data have appe...

AI Technical Summary

Problems solved by technology

Although the currently applied four-dimensional variational data assimilation solves the time window and mode constraints in three-dimensional variation to a certain extent, the calculation of the gradient of the objective function requires a huge amount of calculation, which makes the four-dimensional variational data assimilation in Business applications are very limited

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