CN-121656290-B - Three-dimensional water vapor chromatographic inversion method and system integrating Beidou and wind cloud data

CN121656290BCN 121656290 BCN121656290 BCN 121656290BCN-121656290-B

Abstract

The application relates to a three-dimensional water vapor tomographic inversion method and system for fusing Beidou and wind cloud data, comprising the steps of constructing a multi-source data combined observation system integrating Beidou observation signals, wind cloud remote sensing observation signals and wind cloud occultation observation signals, wherein the Beidou observation signals are provided by Beidou satellites, and the wind cloud remote sensing observation signals and the wind cloud occultation observation signals are provided by wind cloud satellites; and establishing and solving a joint observation equation set to obtain the three-dimensional water vapor field. The method comprises the steps of firstly constructing a multisource data combined observation system, ensuring a basic geometric framework and a high-precision reference required by chromatography by a Beidou observation signal, providing fine structure information in the horizontal direction of the atmosphere by a wind cloud remote sensing observation signal, and providing a water vapor profile with high vertical resolution by the wind cloud occultation observation signal as a strong constraint of chromatography in the vertical direction. And then, a three-dimensional water vapor field is obtained by establishing and solving a joint observation equation set, so that the geometric configuration of an observation signal is fundamentally optimized, and the inversion precision is effectively improved.

Inventors

ZHANG QI
YAO YIBIN
Xu Chaohan
ZHANG BAO
MA XIONGWEI
Chu Ruitao

Assignees

湖北珞珈实验室

Dates

Publication Date: 20260512
Application Date: 20260206

Claims (9)

1. A three-dimensional water vapor chromatographic inversion method integrating Beidou and wind cloud data is characterized by comprising the following steps of: Constructing a multi-source data combined observation system integrating Beidou observation signals, wind cloud remote sensing observation signals and wind cloud occultation observation signals, wherein the Beidou observation signals are provided by Beidou satellites, and the wind cloud remote sensing observation signals and the wind cloud occultation observation signals are provided by wind cloud satellites; establishing and resolving a joint observation equation set to obtain a three-dimensional water vapor field; the set of joint observation equations is expressed as: ; SWV BDS and SWV RS respectively represent the inclined path delay amount of the Beidou observation signal and the virtual inclined path delay amount of the wind cloud remote sensing observation signal, PWV OM represents the water vapor observation value formed by the wind cloud occultation observation signal, A BDS 、A RS 、A OM respectively represents intercept data of the corresponding Beidou observation signal, wind cloud remote sensing observation signal and wind cloud occultation observation signal in a chromatographic voxel block, A H and A V respectively represent coefficient matrixes corresponding to horizontal constraint and vertical constraint, and X represents a three-dimensional water vapor field; The calculation process of the virtual inclined path delay SWV RS of the wind cloud remote sensing observation signal comprises the following steps: Regarding each pixel in the wind cloud remote sensing observation signal as a virtual observation station, wherein the virtual inclined path delay SWV RS of the wind cloud remote sensing observation signal is the inclined path water vapor content corresponding to each virtual observation station, and the water vapor content corresponding to the virtual observation station is taken as the water vapor observation value of the pixel to form combined observation with the Beidou observation signal; Calculating a virtual inclined path delay SWV RS of the wind cloud remote sensing observation signal; The calculation formula is as follows: ; wherein PWV represents a water vapor observation value formed by a wind cloud remote sensing observation signal, And Representing the wet mapping function and the gradient mapping function respectively, Represents the horizontal gradient delay term(s), And Respectively the azimuth and elevation angles, Representing the conversion factor.
2. The method for three-dimensional water vapor tomographic inversion fusing Beidou and wind cloud data as recited in claim 1, wherein said horizontal gradient delay term And calculating by a troposphere parameter differential estimation method.
3. The three-dimensional water vapor tomographic inversion method integrating Beidou and wind cloud data as claimed in claim 1, wherein the calculation process of the water vapor observation value PWV OM formed by the wind cloud occultation observation signals comprises the following steps: calculating the water vapor content value of the occultation observation point according to the wind cloud occultation observation signal; The calculation formula is as follows: ; Wherein, the Indicating the density of the liquid water, Represents the specific humidity of the i-th layer, g represents the gravitational acceleration, The pressure difference between the i-th layer and the i+1-th layer is represented, and n represents the number of air pressure layers.
4. The three-dimensional water vapor tomographic inversion method integrating Beidou and wind cloud data as claimed in claim 1, wherein the calculation process of the water vapor observation value PWV OM formed by the wind cloud occultation observation signals comprises the following steps: based on the voxel block discretization water vapor chromatography principle, taking a vertical integral value of water vapor density of atmospheric water vapor above a occultation observation point as a water vapor observation value; discretization is expressed as: ; Wherein, the And The moisture density value and the thickness value of the k-th analytical voxel block are respectively shown.
5. The method of three-dimensional water vapor tomographic inversion fusing Beidou and wind cloud data as recited in claim 1, wherein prior to solving said set of joint observation equations, adaptively adjusting the grid resolution based on the observed signal density, comprising: Constructing a three-dimensional signal density field of a chromatographic region based on a radial basis function for all voxels in the chromatographic voxel block; identifying sensitivity of the vertical layer based on density change in the horizontal direction, and defining a sensitive layer; and carrying out self-adaptive adjustment on the grid resolution of the sensitive layer.
6. The method of three-dimensional water vapor tomographic inversion fusing Beidou and wind cloud data as recited in claim 5 wherein said constructing a three-dimensional signal density field of a tomographic region based on radial basis functions for all voxels in said block of tomographic voxels comprises: Discretizing by adopting self-adaptive non-uniform index layering in the vertical direction, and uniformly discretizing by adopting fixed resolution in the horizontal direction so as to establish an initial grid; based on a nuclear density estimation method, counting the signal density in a unit voxel in the chromatographic voxel block; constructing a three-dimensional signal density field based on the radial basis function; The expression is as follows: ; Wherein, the The signal density values representing the voxels (x, y, h), x, y, h representing the horizontal coordinates and elevation of the voxel center respectively, Representing the normalized distance of the kth ray from the current voxel center, Representing the radial basis function.
7. The method of three-dimensional water vapor tomography inversion with the combination of Beidou and wind cloud data as claimed in claim 6, wherein the identifying vertical layer sensitivity based on density variation in the horizontal direction, defining the sensitive layer includes: calculating relative density change index in horizontal direction ; The calculation formula is as follows: ; Wherein, the Representing the average value of the densities of all voxels of the horizontal layer; Calculating local dispersion To determine the anisotropy of the observed signal density distribution; The calculation formula is as follows: ; Setting an empirical threshold When the local dispersion of a horizontal layer When this layer is defined as a sensitive layer.
8. The method of three-dimensional water vapor tomographic inversion fusing Beidou and wind cloud data as recited in claim 7 wherein said adaptively adjusting the grid resolution of said sensitive layer comprises: Calculating a density gradient for each voxel of the sensitive layer to represent observed signal density variations; The calculation formula is as follows: ; Setting a density threshold And gradient threshold Judging whether the voxels meet the following conditions; ; And for voxels meeting the conditions, encrypting by adopting a four-splitting method.
9. A three-dimensional water vapor tomographic inversion system which fuses the beidou and the wind cloud data, wherein the three-dimensional water vapor tomographic inversion method which fuses the beidou and the wind cloud data according to any one of claims 1 to 8 is applied, and the system comprises: the observation system construction module is configured to construct a multi-source data combined observation system integrating Beidou observation signals, wind cloud remote sensing observation signals and wind cloud occultation observation signals, wherein the Beidou observation signals are provided by Beidou satellites, and the wind cloud remote sensing observation signals and the wind cloud occultation observation signals are provided by wind cloud satellites; and the equation set calculation module is configured to establish and calculate a joint observation equation set so as to obtain a three-dimensional water vapor field.

Description

Three-dimensional water vapor chromatographic inversion method and system integrating Beidou and wind cloud data Technical Field The invention relates to the technical field of three-dimensional water vapor tomography inversion, in particular to a three-dimensional water vapor tomography inversion method and system integrating Beidou and wind cloud data. Background Three-dimensional water vapor chromatography has become an important research branch of GNSS meteorology since the first implementation. The basic principle is that a ground GNSS observation network is utilized to obtain an inclined path wet delay observation value, a chromatographic equation set is constructed through three-dimensional space discretization, and then an atmospheric wet refractive index field is inverted. Compared with single GPS observation, the related technology improves the water vapor chromatographic inversion precision by fusing multi-source data, such as fusing multi-constellation GNSS observation data, or fusing other star source data such as radio occultation of a weather ionosphere weather constellation observation system, but due to the natural difference of the observation geometric forms of heterogeneous data in the multi-source data, the existing method has limited fusion effect and influences the chromatographic precision. Disclosure of Invention The application provides a three-dimensional water vapor chromatography inversion method and system for fusing Beidou and wind cloud data, and aims to solve the technical problem that the chromatographic precision is affected due to limited fusion effect during multi-source data fusion in the related art. The embodiment of the application provides a three-dimensional water vapor chromatographic inversion method integrating Beidou and wind cloud data, which comprises the following steps of: Constructing a multi-source data combined observation system integrating Beidou observation signals, wind cloud remote sensing observation signals and wind cloud occultation observation signals, wherein the Beidou observation signals are provided by Beidou satellites, and the wind cloud remote sensing observation signals and the wind cloud occultation observation signals are provided by wind cloud satellites; establishing and resolving a joint observation equation set to obtain a three-dimensional water vapor field; the set of joint observation equations is expressed as: ; SWV BDS and SWV RS respectively represent the inclined path delay amount of the Beidou observation signal and the virtual inclined path delay amount of the wind cloud remote sensing observation signal, PWV OM represents the water vapor observation value formed by the wind cloud occultation observation signal, A BDS、ARS、AOM respectively represents intercept data of the corresponding Beidou observation signal, wind cloud remote sensing observation signal and wind cloud occultation observation signal in a chromatographic voxel block, A H and A V respectively represent coefficient matrixes corresponding to horizontal constraint and vertical constraint, and X represents a three-dimensional water vapor field. In one embodiment, the calculation process of the virtual diagonal path delay SWV RS of the wind cloud remote sensing observation signal includes: Regarding each pixel in the wind cloud remote sensing observation signal as a virtual measuring station, taking the water vapor content corresponding to the virtual measuring station as the water vapor observation value of the pixel, and forming combined observation with the Beidou observation signal; Calculating a virtual inclined path delay SWV RS of the wind cloud remote sensing observation signal; The calculation formula is as follows: ; wherein PWV represents a water vapor observation value formed by a wind cloud remote sensing observation signal, AndRepresenting the wet mapping function and the gradient mapping function respectively,Represents the horizontal gradient delay term(s),AndRespectively the azimuth and elevation angles,Representing the conversion factor. In one embodiment, the horizontal gradient delay termAnd calculating by a troposphere parameter differential estimation method. In one embodiment, the calculation process of the water vapor observation value PWV OM formed by the wind cloud occultation observation signal includes: calculating the water vapor content value of the occultation observation point according to the wind cloud occultation observation signal; The calculation formula is as follows: ; Wherein, the Indicating the density of the liquid water,Represents the specific humidity of the i-th layer, g represents the gravitational acceleration,The pressure difference between the i-th layer and the i+1-th layer is represented, and n represents the number of air pressure layers. In one embodiment, the calculation process of the water vapor observation value PWV OM formed by the wind cloud occultation observation signal includes: based on the voxel bl