Multispectral rainfall detection system and method based on random forest algorithm

Abstract

The invention discloses a multispectral rainfall detection method based on a random forest algorithm. The method comprises the steps: carrying out observation of the same cloud region at the same timethrough a visible and infrared spin scanning radiometer carried on a stationary satellite and a microwave temperature detector carried on a polar orbit satellite, and obtaining observation data; after visible and infrared spin scanning radiometer high-resolution cloud products are matched into microwave temperature detector phase elements, acquiring information on a surface of a cloud body in AMSU-A image elements of a microwave temperature detector and information inside the cloud body; and then simulating a nonlinear relationship between cloud top optical information and microwave rainfallinformation in the cloud body by using the random forest algorithm, and establishing a relationship between the optical information and the microwave rainfall information. The invention further provides a multispectral rainfall detection system based on the random forest algorithm. The system comprises a data acquisition module, a matching module, a modeling module, a model verification module anda rainfall detection module. Compared with a traditional detection method, the detection system and method have higher accuracy, higher detection rate and lower error rate.

Description

technical field [0001] The invention belongs to the technical field of satellite remote sensing, and in particular relates to a method for detecting precipitation by combining the random forest algorithm in the field of machine learning and utilizing cross-spectral information of visible light and microwaves. Background technique [0002] Satellite microwave data is an important source of observational data for numerical weather prediction (NWP). Studies have shown that introducing microwave observational data into data assimilation can bring positive effects to numerical weather prediction. Compared with satellite infrared and visible light instruments, microwave sounders can Through the non-precipitating clouds to obtain atmospheric temperature and humidity profile information. However, microwaves are easily affected by the scattering of large-diameter water particles, and it is difficult to penetrate precipitation clouds. Microwave observation data in precipitation areas ...

AI Technical Summary

Problems solved by technology

However, the traditional precipitation detection method is limited by the load of polar-orbiting satellites, and has the problems of low time and space resolution and insufficient space coverage.

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