Research on liquid precipitation phenomenon and scale comprehensive identification based on multi-source detection data
This paper analyzes the phenomenon of liquid precipitation,using observation data from automatic weather stations,dual polarization weather radars,and other equipment,using XGBoost GBDT and other machine learning algorithms to carry out the correlation analysis of detection data and precipitation magnitude,establishes a precipitation type and magnitude recognition model based on multi-source data,realizes the recognition of five types of precipitation,namely,no rain,light rain,moderate rain,heavy rain,rainstorm and above,and finally generates recognition grid products,so as to improve the spatial resolution of precipitation type recognition to a certain extent.
万方数据
维普
