Atmospheric environment data assimilation method based on set optimal interpolation algorithm

Abstract

The invention relates to an atmospheric environment data assimilation method based on a set optimal interpolation algorithm; the method comprises the following steps: simulating the pollution process of a selected region through an air quality model, and obtaining the concentration of atmospheric pollutants; extracting simulated pollution data according to the space grid points; collecting and monitoring the atmospheric pollutant data monitored by a ground station and generating the grid data, consistent with air quality model simulation data in spatial resolution and matched with the air quality model simulation data in longitude and latitude, through the station monitoring data by means of a spatial interpolation algorithm; and setting a background error covariance of set optimal interpolation according to the station data, and performing set optimal interpolation data assimilation on the analog data and the station data. The simulation result of the air quality model can be effectively improved, and the precision and spatial resolution of air pollution monitoring are remarkably improved, so that the method is an effective method for developing air quality data assimilation technology research and is a data assimilation algorithm widely applicable to a nonlinear power system, and has the advantages of high universality and high assimilation precision.

Description

[0001] (1) Technical field [0002] The invention relates to an atmospheric environment data assimilation method based on an ensemble optimal interpolation algorithm, belongs to the field of atmospheric environment science, and has great significance in air pollution data monitoring and simulation prediction technology research and air pollution control. [0003] (2) Background technology [0004] Air quality is closely related to human health. For this reason, the World Health Organization has promulgated a series of guidelines for the prevention and control of air pollution, and some countries and regions have also promulgated corresponding laws and regulations. Although in the past few decades, people have made great progress in the traceability of pollutant emissions and the reduction of air pollutant concentration levels in urban areas, but according to relevant statistics, millions of people still die every year worldwide. to air pollution. In order to protect the genera...

AI Technical Summary

Problems solved by technology

The prediction results of high-precision air quality models are of great significance for the precise implementation of air pollution prevention and control measures. Although the output of the air quality model provides the spatial distribution characteristics and time evolution characteristics of pollutants, the simulation results are often difficult to show regional sporadic Sexual and sudden pollution

On the other hand, the interpolation processing of station monitoring data fails to fully consider the complex physical and chemical mechanisms in the process of air pollution formation

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