Sea surface parameter synchronous inversion optimization method

Abstract

The invention provides a sea surface parameter synchronous inversion optimization method which includes the steps: 1) acquiring multi-incident-angle radiation brightness temperature observation valuesand multi-incident-angle backscattering coefficient observation values; 2) performing median filtering, adaptive median filtering and Wiener filtering on the multi-incident-angle radiation brightnesstemperature observation values to obtain three-type radiation brightness temperature observation values after noise reduction; 3) acquiring multi-incident-angle radiation brightness temperature simulation values by a forward radiation brightness temperature theoretical model, and acquiring multi-incident-angle backscattering coefficient simulation values by a backscattering coefficient theoretical model; 4) substituting the three-type radiation brightness temperature observation values, the radiation brightness temperature simulation values, the backscattering coefficient observation values and the backscattering coefficient simulation values into an L / C / K waveband multi-priced function to synchronously obtain three-type sea surface parameters; 5) comparing the three-type sea surface parameters with float measurement sea surface parameters, calculating inversion root-mean-square errors and selecting sea surface parameter values corresponding to the minimum root-mean-square error as final sea surface parameter values.

Description

technical field [0001] The invention relates to the field of microwave remote sensing, in particular to a method for synchronous inversion optimization of sea surface parameters. Background technique [0002] Seawater salinity refers to the ratio of all dissolved solids in seawater to the weight of seawater, which is an important characteristic of seawater. Its annual, seasonal and interannual variations play a key role in the marine climate system, and are an important basis for studying global climate change and weather and climate forecast models. Therefore, the study of the distribution and variation of sea surface salinity helps to further understand the ocean, has an important impact on the mechanism of ocean remote sensing, and occupies an important position in ocean remote sensing science. [0003] To study the distribution and changes of sea surface salinity, it is first necessary to study how to invert sea surface salinity through satellite measurements; currently...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings of the lack of synchronous auxiliary data in the prior art, the sea surface temperature and sea surface wind speed cannot be synchronously inverted, and the inversion sea surface parameters have low precision, and a synchronous inversion optimization of sea surface parameters is provided. method, this method obtains the observed values ​​of the radiation brightness temperature in the L / C / K band and the observed value of the backscatter coefficient in the L band through the spaceborne microwave radiometer and the scatterometer respectively, and marks the observed brightness temperature within 200km from the coastline value, using median filtering, adaptive median filtering and Wiener filtering methods to process the radiation brightness temperature of multi-incident angles; The model obtains the simulated values ​​of the radiation brightness temperature and backscatter coefficient of the top layer of the atmosphere at multiple incident angles respectively; finally, the obtained three types of optimized brightness temperature observations and simulated values ​​and the backscatter coefficient observed and simulated values ​​are substituted into the cost function to perform Sea surface multi-parameter inversion calculation compared with

Images