6 results about "Atmospheric column" patented technology

This invention discloses a method for inverting atmospheric N2O column concentration based on thermal infrared satellite remote sensing, belonging to the field of atmospheric environment remote sensing technology. The method includes: acquiring and preprocessing satellite observation data; selecting a specific spectral range as the inversion characteristic spectral region; introducing a fast radiative transfer model to construct a forward simulation operator to simulate the radiance of the top atmospheric layer; selecting N2O-sensitive characteristic bands with high signal-to-noise ratio and low interference based on a channel optimization strategy using the N2O / CO2 Jacobi intensity ratio; constructing an extended state vector, using surface temperature as an unknown parameter and performing joint optimal estimation iterative inversion with the N2O profile to correct the surface temperature in the reanalysis data, thereby achieving high-precision inversion of N2O atmospheric column concentration. This invention transforms surface temperature from a fixed input parameter into a state variable to be inverted, effectively decoupling surface temperature error from the N2O signal, eliminating systematic bias, and significantly improving the inversion accuracy of N2O column concentration.

The application discloses a satellite atmospheric column average carbon dioxide concentration field super-resolution reconstruction method and relates to the technical field of satellite remote sensing and atmospheric environment monitoring. The method comprises the following steps: obtaining satellite carbon dioxide observation data and satellite auxiliary observation parameters, and performing data preprocessing to form input data; a feature extraction module is used to perform multi-scale spatial feature extraction on the input data to obtain first features; a preliminary reconstruction module is used to perform up-sampling reconstruction on the first features to obtain a preliminary reconstruction result; and a physical perception bias correction module is used to correct the preliminary reconstruction result in combination with the satellite auxiliary observation parameters to obtain a super-resolution carbon dioxide concentration field. Through the construction of a multi-scale residual feature extraction mechanism, the model's ability to capture the spatial structure of low-resolution satellite data is enhanced, and a physical perception bias correction module is designed to dynamically encode observation geometry and quality parameters, generate a bias field, effectively alleviate the problem of systematic bias drift, and improve the numerical accuracy of the CO2 concentration detail recovery.

This application relates to the field of radiometric calibration technology, providing a method and apparatus for quantitative evaluation of satellite radiometric calibration fields based on an airship platform. The method includes: constructing an optimized surface directional reflectance function based on multi-angle surface reflectance data collected by an unmanned aerial vehicle (UAV) and ground-measured reference data; constructing an apparent radiance function of the top of the atmosphere based on atmospheric column data collected by the airship platform, the optimized surface directional reflectance function, and ground-measured reference data; and retrieving an evaluation index of the satellite radiometric calibration field based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value. This application effectively overcomes the shortcomings of existing technologies, such as temporal discontinuity, strong meteorological constraints, and limited spatial representativeness, achieving high-frequency, high-precision, and high-stability quantitative evaluation of the radiometric calibration field.

The invention provides an aerosol micro-physical property profile determination method, device and equipment and a medium, and the method comprises the steps: obtaining atmospheric whole-layer column average aerosol volume scale spectral distribution and multi-wavelength complex refractive indexes of a plurality of ground sites in different time periods, and obtaining monitoring data including a real part and an imaginary part; constructing a coarse and fine modal aerosol six-parameter distribution database according to the monitoring data, and clustering the database to generate a plurality of coarse and fine modal aerosol scale spectrum distribution models; and each model calculates a preset wavelength backscattering coefficient calculation value based on a Mie scattering theory, performs layer-by-layer iterative comparison on the preset wavelength backscattering coefficient calculation value and corresponding wavelength observation values of different altitudes of the spaceborne laser radar by using a preset cost function, and inverts an aerosol micro-physical property profile. By adopting the scheme, high-precision and large-scale aerosol micro-physical property profile inversion can be realized, so that atmospheric aerosol monitoring research is effectively supported.

The application belongs to the technical field of greenhouse gas emission monitoring, and discloses a method and system for monitoring urban CO2 emission plume by integrating observation and simulation. The method comprises the following steps: collecting and preprocessing multi-source data; constructing a prediction model for atmospheric CO2 column concentration (XCO2) based on machine learning and multi-source satellite observation; simulating long-term artificial CO2 concentration by using an atmospheric transmission model; simulating hourly artificial CO2 concentration data; and constructing an artificial CO2 emission estimation model based on optimal estimation and verifying the results. The application has high automation degree, can automatically identify emission plume on the basis of multi-source data fusion and model simulation, reduces the need for manual intervention, improves monitoring efficiency, and is suitable for large-scale urban emission source monitoring and management.