Abstract: Taking Shaoguan City, Guangdong Province as an example, the modeling analysis method of the impact of severe convective weather on agricultural production based on the least square method was studied, so as to provide a reliable basis for effectively preventing and reducing agricultural production problems caused by severe convective weather. The data related to severe convective weather prediction were collected by Doppler radar, and the radar reflectivity image generated by the reflectivity factor was used to identify severe convective weather and extract the characteristics of storm monomer. Combined with TITAN and SCIT algorithms, taking into account the internal structure and overall information of the storm, the storm monomer was tracked, and the least square straight line fitting method was used to fit the trajectory of the monomer. By calculating the monomer velocity and performing the single extrapolation operation, the severe convective weather prediction results were obtained. Combined with the general situation of the study area, the impact of severe convective weather on agricultural production was analyzed. The experimental results showed that this method could effectively predict severe convective weather. The application of the prediction results to the analysis of the impact of severe convective weather on agricultural production could provide a reliable basis for effectively preventing and reducing the harm of severe convective weather to agricultural production.

Key words: least square method, severe convective weather, agricultural production, modeling analysis, reflectivity factor, storm cell characteristics