An urban rainfall retrieval algorithm based on microwave attenuation feature response fingerprint identification

Abstract

The invention discloses an urban rainfall inversion algorithm based on microwave attenuation characteristic response fingerprint identification, includes the acquisition and preliminary processing ofmicrowave signals, the separation and classification of clutter signals, the establishment of clutter characteristic response fingerprint database, the identification and removal of clutter, rainfallinversion, scale matching of multi-source rainfall data, the optimization of model parameters and the real-time correction of inversion results. The invention can quickly judge and remove the influence of different types of clutter in the microwave attenuation signal under the urban environment, and provides urban multi-resolution rainfall big data with a spatial resolution of 100 meters-200 meters and a time resolution of 5 minutes-10 minutes.

Description

technical field [0001] The invention relates to the technical field of meteorological factor monitoring, in particular to an urban rainfall inversion algorithm based on microwave attenuation characteristic response fingerprint recognition. Background technique [0002] Real-time and high-precision rainfall monitoring data is the premise of realizing flood and drought disaster prevention, water resources development and utilization, and comprehensive management. At present, the more common real-time rainfall data monitoring methods mainly include rainfall stations and radar. Difficult to maintain, low station network density, poor data reliability and other outstanding problems, compared with the demand for fine urban management, there is a big gap; radar observation is also an important monitoring method, which can provide a maximum time resolution of 5 minutes, spatial resolution The rainfall distribution is 100m×100m, but the radar has defects such as being easily affecte...

AI Technical Summary

Problems solved by technology

[0005] However, the environment in urban areas is complex, and different types of noise and clutter greatly affect the ability of microwave signals to capture rainfall. Therefore, how to quickly identify and extract the characteristic response of microwave decay to sensitive atmospheric variables such as water vapor content and atmospheric visibility , and then removing the influence of environmental noise and clutter is one of the key issues that must be considered in the application of this technology to the construction of urban high-resolution real-time rainfall data, and it is also the main shortcoming of the current research

On the other hand, due to the inevitable influence of various clutter, super refraction, plant growth and other factors in the microwave signal transmission process, the error cannot be completely eliminated

At the same time, in different regions or in different rainfall processes, there are also large differences in the parameter values ​​of the inversion model, resulting in a large deviation between the estimated rainfall value and the actual rainfall value. For cities with limited rainfall ground stations, the data fusion technology and correction algorithm are An Important Guarantee for Improving the Accuracy and Stability of Rainfall Observation Data

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