X-band rain measuring radar rainfall estimation method based on T matrix and multi-raindrop spectrum model

Abstract

The invention belongs to the technical field of rainfall estimation of rain-measuring radars, and particularly relates to an X-waveband rain-measuring radar rainfall estimation method based on a T matrix and a multi-raindrop spectrum model. The problem of rainfall estimation errors caused by a single raindrop spectrum model in the prior art is solved, and the precision of rainfall estimation is improved by combining the X-band dual-polarization radar measurement data with multiple raindrop spectrum models. The method comprises the following steps: S1, carrying out data acquisition on a target area by using an X-waveband dual-polarization rain measurement radar; s2, carrying out raindrop spectrum model selection according to the rainfall intensity of the target area; s3, calculating polarization parameters based on a T matrix theory; s4, rainfall estimation is carried out in combination with the polarization parameters and the raindrop spectrum model; and S5, correcting and optimizing the raindrop model based on actually measured raindrop spectrum data. In combination with the multi-raindrop spectrum model and the T matrix theory, the rainfall capacity can be estimated more accurately under different rainfall intensities, and particularly, errors caused by raindrop spectrum selection can be remarkably reduced under the condition of heavy rainfall.

Description

Technical Field

[0001] The present invention belongs to the technical field of rainfall estimation using a rain measuring radar, and in particular relates to a rainfall estimation method using an X-band rain measuring radar based on a T matrix and a multi-raindrop spectrum model. Background Art

[0002] In meteorological observation, radar is an important tool for rainfall monitoring, especially dual-polarization radar, which helps estimate rainfall intensity by providing more microphysical information (such as raindrop morphology and distribution). X-band dual-polarization radar has been widely used in meteorological research and rainfall monitoring due to its high resolution and convenience.

[0003] Rainfall estimation methods include single variable and multivariate QPE (Quantitative Precipitation Estimation) techniques. Among them, single variable QPE methods include ZR relationship and K DP -R relationship, etc., and estimate rainfall through a single radar parameter. However, in quantitative estimation of rainfall, these common rainfall estimation parameters have their own limitations, mainly due to the significant influence of raindrop spectrum, the attenuation of X-band radar, K DP limitations such as computational limitations.

[0004] Drop size distribution (DSD) significantly influences the scattering characteristics of radar echoes and rainfall inversion. Commonly used drop size distribution models in existing technologies include the Marshall-Palmer distribution, the Gamma distribution, the Weibull distribution, and the Joss distribution. These models are effective under certain conditions, but in extreme weather conditions, improperly selected drop size distribution models can lead to large estimation errors, thus affecting the accuracy of radar rainfall measurements.

[0005] Therefore, the X-band rain radar rainfall estimation method based on the T matrix and multi-raindrop spectrum model can provide more accurate rainfall intensity estimation under different rainfall conditions, and has become an important research direction in rain radar detection inversion technology. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention provides an X-band rainfall estimation method based on a T matrix and multiple raindrop spectrum models. This method addresses the rainfall estimation errors caused by a single raindrop spectrum model in existing technologies. By combining X-band dual-polarization radar measurement data with multiple raindrop spectrum models, the present invention improves the accuracy of rainfall estimation.

[0007] To solve the above technical problems, the present invention adopts a technical solution: a method for estimating rainfall using an X-band rain radar based on a T matrix and a multi-raindrop spectrum model, comprising the following steps:

[0008] S1, using X-band dual-polarization rainfall radar to collect data on the target area: using X-band dual-polarization rainfall radar to collect rainfall data in the target area and obtain polarization parameters;

[0009] S2, select a raindrop spectrum model based on the rainfall intensity of the target area: Based on the rainfall intensity, a raindrop spectrum model is selected. The model describes the distribution of rainfall particles under different rainfall intensities by analyzing the characteristics of raindrop size distribution;

[0010] S3, calculate polarization parameters based on T-matrix theory: use the T-matrix method to calculate the scattering and attenuation characteristics of raindrops on radar signals, and obtain the backscattering matrix and forward scattering amplitude matrix;

[0011] S4, combining polarization parameters and raindrop spectrum model for rainfall estimation: rainfall estimation includes single variable QPE and multivariate QPE methods;

[0012] S5, calibrate and optimize the raindrop model based on measured raindrop spectrum data: improve the accuracy of radar-derived rainfall intensity and microphysical properties.

[0013] Furthermore, the S1 step includes:

[0014] S10, when observing rainfall, uses X-band dual-polarization rainfall radar to scan the target area and obtain the polarization parameters of the target area, including horizontal and vertical reflectivity factors Z H and Z V , differential reflectivity Z DR , differential propagation phase Φ DP , differential phase K DP , horizontal and vertical attenuation rates A H and A V and the differential attenuation rate A DP .

[0015] Furthermore, the S2 step includes:

[0016] S20, raindrop spectrum models include Marshall-Palmer distribution, Gamma distribution, Weibull distribution, JossDrizzle distribution, and JossThunderStorm distribution models;

[0017] The Marshall-Palmer distribution is:

[0018] N(D)=N0exp(-ΛD) Formula 1;

[0019] Where N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter;

[0020] The Gamma distribution is:

[0021] N(D)=N0D μ exp(-ΛD) Formula 2;

[0022] Where μ is the shape parameter, ranging from 0 to 3 from light rainfall to heavy rainfall, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter;

[0023] The Weibull distribution is:

[0024]

[0025] Where μ is the shape parameter, which ranges from 1.5 to 2.0 for heavy rainfall, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, D is the raindrop diameter, η is the density parameter, and σ is the particle size parameter;

[0026] The Joss Drizzle distribution and the Joss ThunderStorm distribution are the same as the Gamma distribution;

[0027] S21, the selection method of the quantitative raindrop spectrum model, defines the level of rainfall intensity R:

[0028] Rainfall intensity R (unit: mm / h) is divided into:

[0029] Light rainfall: R<2.5mm / h;

[0030] Moderate rainfall: 2.5≤R<10mm / h;

[0031] Heavy rainfall: 10≤R<50mm / h;

[0032] Heavy rain: R ≥ 50 mm / h;

[0033] S22, based on the rainfall intensity R, select the raindrop spectrum model:

[0034] If R<2.5, the Joss-Drizzle distribution model is preferred, followed by the Marshall-Palmer distribution model;

[0035] If 2.5≤R<10, the Marshall-Palmer distribution model is preferred, followed by the Gamma distribution model;

[0036] If 10≤R<50, the Marshall-Palmer distribution model is preferred, followed by the Weibull distribution model;

[0037] If R≥50, the Joss ThunderStorm distribution model is preferred, followed by the Weibull distribution model.

[0038] Furthermore, the S3 step includes:

[0039] S30, using the T-matrix method to numerically calculate the scattering characteristics of electromagnetic waves in raindrops, substituting the obtained raindrop spectrum model parameters into the T-matrix, calculating the backscattering matrix and forward scattering amplitude matrix under horizontal and vertical polarization conditions, and calculating the scattering characteristics and signal attenuation of the radar signal in the target area;

[0040] S31, based on T matrix theory, construct the backscattering matrix Z and forward scattering amplitude matrix S:

[0041]

[0042] S32, the polarization parameters obtained by solving the polarized electromagnetic wave are divided into two categories: one is the radar reflectivity factor Z based on backscattering H , Z V , differential reflectivity Z DR , correlation coefficient ρ and backscatter differential phase δ; the other is based on the forward scattering differential propagation phase shift Φ DP , differential propagation phase shift rate K DP , attenuation rate A H 、A V and differential attenuation rate A DP ;

[0043]

[0044] Where n0 represents the total number of particles per cubic meter of air, C = 10 18 λ 4 / (π 5 |K| 2 ), K = (ε-1) / (ε+2), ε is the complex dielectric constant of rainfall particles;

[0045] S33, rainfall parameters are calculated using the moment method, that is, expressed as the integral of the raindrop spectrum. The rainfall intensity R can be expressed using the raindrop spectrum as:

[0046]

[0047] S34, dual polarization observations can also be expressed as raindrop spectra, where the radar reflectivity is:

[0048]

[0049] λ is the wavelength of electromagnetic wave, D is the equivalent diameter of raindrop, K is the dielectric constant, which is defined as K = (ε-1) / (ε+2), ε is the relative dielectric constant of raindrop, D max and D min Represent the maximum and minimum raindrop equivalent diameters, s hh,vv (π, D) represents the backscatter coefficient in the horizontal and vertical directions. Similarly, the following reasoning can be obtained:

[0050] Z H,V =10log 10 (Z h,v ), (dBz) Formula 9;

[0051]

[0052] Among them, Re represents the real part of the complex number, s hh (0, D) represents the forward scattering coefficient of horizontal incident horizontal scattering, s vv (0, D) represents the forward scattering coefficient at normal incidence and vertical scattering;

[0053]

[0054] S35, combined with T-matrix theory, the polarization parameters of the raindrop spectrum inversion rainfall radar can be combined to construct the corresponding mathematical relationship.

[0055] Furthermore, the S4 step includes:

[0056] S40, univariate QPE methods including ZR relationship and K DP -R relationship, estimating rainfall using a single radar parameter;

[0057] The multivariate QPE method combines multiple radar parameters and performs joint fitting of different parameters to improve the accuracy of rainfall estimation;

[0058] Among them, rainfall R and reflectivity Z, differential phase K DP , differential reflectivity Z DR There is an exponential function relationship, which is expressed as:

[0059]

[0060] Among them, a, b, and c are parameters in the empirical formula. The parameters are calibrated and adjusted according to the climate characteristics of different regions to adapt to local rainfall conditions. The difference in parameters determines that the applicability and accuracy of the same relationship in different regions vary;

[0061] S41, combines the polarization parameters obtained in S1 with the selected raindrop spectrum model to estimate rainfall, and introduces a new parameter R(K DP ,ZDR ), its empirical formula is expressed as:

[0062]

[0063] The new parameters are used to estimate rainfall intensity more stably under moderate to heavy rainfall conditions.

[0064] Furthermore, in the Marshall-Palmer distribution, the intercept parameter N0 defaults to 8000m. -3 mm -1 , the slope parameter Λ is taken as 4.1R -0.21 ;

[0065] In the Gamma distribution: N0=64500R -0.5 , μ=1.5,Λ=7.09R -0.27 ;

[0066] In the Weibull distribution: N0 = 1000, η ​​= 0.95R 0.14 ,σ=0.26R 0.42 ;

[0067] In the Joss Drizzle distribution: N0 = 30000, Λ = 5.7R -0.21 ;

[0068] In the Joss ThunderStorm distribution: N0 = 1400, Λ = 3.0R -0.21 .

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention combines the multi-raindrop spectrum model and T-matrix theory to more accurately estimate rainfall under different rainfall intensities, and can significantly reduce the error caused by raindrop spectrum selection in heavy rainfall. In addition, the combination of multiple polarization parameters, such as Z DR and K DP Rainfall estimation can improve the stability and accuracy of measurements and is suitable for applications in radar rainfall inversion and rain attenuation correction.

[0071] The present invention uses an X-band dual-polarization rainfall radar to collect rainfall data and extract polarization parameters such as horizontal reflectivity factor, vertical reflectivity factor, and differential reflectivity; selects appropriate raindrop spectrum models based on different rainfall intensities, including Marshall-Palmer distribution, Gamma distribution, Weibull distribution, and Joss distribution; combines T-matrix theory to calculate the scattering and attenuation characteristics of raindrops on radar signals, and optimizes estimation accuracy by integrating radar parameters and raindrop spectrum models through single-variable or multi-variable rainfall inversion methods. The introduction of new parameters significantly improves stability and accuracy under moderate to heavy rainfall conditions; in addition, the model is calibrated and optimized through measured raindrop spectrum data, making the estimation results more consistent with actual rainfall characteristics. The present invention can effectively improve the accuracy of rainfall intensity estimation, especially showing significant advantages under heavy rainfall conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0073] Figure 1 Schematic diagram of a flow chart of a method for estimating rainfall using an X-band rainfall radar based on a T matrix and a multi-raindrop spectrum model according to the present invention;

[0074] Figure 2 Schematic diagram of rainfall intensity estimation based on the influence of multi-parameter simultaneous operators on raindrop spectrum according to an embodiment of the present invention. DETAILED DESCRIPTION

[0075] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0076] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention but is merely representative of selected embodiments of the present invention.

[0077] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field under the description before making any creative work shall fall within the scope of protection of the present invention.

[0078] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0079] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0080] like Figure 1 As shown:

[0081] A method for estimating rainfall using an X-band rain radar based on a T matrix and a multi-raindrop spectrum model comprises the following steps:

[0082] S1, using X-band dual-polarization rainfall radar to collect data on the target area: using X-band dual-polarization rainfall radar to collect rainfall data in the target area and obtain polarization parameters;

[0083] S10, when observing rainfall, uses X-band dual-polarization rainfall radar to scan the target area and obtain the polarization parameters of the target area, including horizontal and vertical reflectivity factors Z H and Z V , differential reflectivity Z DR , differential propagation phase Φ DP , differential phase K DP , horizontal and vertical attenuation rates A H and A V and the differential attenuation rate A DP The sampling frequency of the observation data is dynamically adjusted according to the rainfall intensity and the size of the target area.

[0084] S2, select a raindrop spectrum model based on the rainfall intensity of the target area: Based on the rainfall intensity, a raindrop spectrum model is selected. The model describes the distribution of rainfall particles under different rainfall intensities by analyzing the characteristics of raindrop size distribution;

[0085] S20, raindrop spectrum models include Marshall-Palmer distribution, Gamma distribution, Weibull distribution, JossDrizzle distribution, and JossThunderStorm distribution models;

[0086] The Marshall-Palmer distribution is:

[0087] N(D)=N0exp(-ΛD) Formula 1;

[0088] Where N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter;

[0089] In the Marshall-Palmer distribution, the intercept parameter N0 defaults to 8000m. -3 mm -1 , the slope parameter Λ is taken as 4.1R -0.21 ;

[0090] The Gamma distribution is:

[0091] N(D)=N0D μ exp(-ΛD) Formula 2;

[0092] Where μ is a shape parameter, and its value is related to the rain intensity, ranging from 0 to 3 from light rain to heavy rain, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter;

[0093] In the Gamma distribution: N0=64500R -0.5 , μ=1.5,Λ=7.09R -0.27 ;

[0094] The Weibull distribution is:

[0095]

[0096] Where μ is the shape parameter, which ranges from 1.5 to 2.0 for heavy rainfall, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, D is the raindrop diameter, η is the density parameter, and σ is the particle size parameter;

[0097] In the Weibull distribution: N0 = 1000, η ​​= 0.95R 0.14 ,σ=0.26R 0.42 ;

[0098] The Joss Drizzle distribution and the Joss ThunderStorm distribution are the same as the Gamma distribution;

[0099] In the Joss Drizzle distribution: N0 = 30000, Λ = 5.7R -0.21 ;

[0100] In the Joss ThunderStorm distribution: N0 = 1400, Λ = 3.0R -0.21 ;

[0101] S21, the selection method of the quantitative raindrop spectrum model, defines the level of rainfall intensity R:

[0102] Rainfall intensity R (unit: mm / h) is divided into:

[0103] Light rainfall: R<2.5mm / h;

[0104] Moderate rainfall: 2.5≤R<10mm / h;

[0105] Heavy rainfall: 10≤R<50mm / h;

[0106] Heavy rain: R ≥ 50 mm / h;

[0107] S22, based on the rainfall intensity R, select the raindrop spectrum model:

[0108] If R<2.5, the Joss-Drizzle distribution model is preferred, followed by the Marshall-Palmer distribution model;

[0109] If 2.5≤R<10, the Marshall-Palmer distribution model is preferred, followed by the Gamma distribution model;

[0110] If 10≤R<50, the Marshall-Palmer distribution model is preferred, followed by the Weibull distribution model;

[0111] If R≥50, the Joss ThunderStorm distribution model is preferred, followed by the Weibull distribution model.

[0112] S3, calculate polarization parameters based on T-matrix theory: use the T-matrix method to calculate the scattering and attenuation characteristics of raindrops on radar signals, and obtain the backscattering matrix and forward scattering amplitude matrix;

[0113] S30, using the T-matrix method to numerically calculate the scattering characteristics of electromagnetic waves in raindrops, substituting the obtained raindrop spectrum model parameters into the T-matrix, calculating the backscattering matrix and forward scattering amplitude matrix under horizontal and vertical polarization conditions, and calculating the scattering characteristics and signal attenuation of the radar signal in the target area;

[0114] S31, based on T matrix theory, construct the backscattering matrix Z and forward scattering amplitude matrix S:

[0115]

[0116] S32, the polarization parameters obtained by solving the polarized electromagnetic wave are divided into two categories: one is the radar reflectivity factor Z based on backscattering H , Z V , differential reflectivity Z DR , correlation coefficient ρ and backscatter differential phase δ; the other is based on the forward scattering differential propagation phase shift Φ DP , differential propagation phase shift rate K DP , attenuation rate A H 、A V and differential attenuation rate A DP ;

[0117]

[0118] Where n0 represents the total number of particles per cubic meter of air, C = 10 18 λ 4 / (π 5 |K| 2 ), K = (ε-1) / (ε+2), ε is the complex dielectric constant of rainfall particles;

[0119] S33, rainfall parameters are calculated using the moment method, that is, expressed as the integral of the raindrop spectrum. The rainfall intensity R can be expressed using the raindrop spectrum as:

[0120]

[0121] S34, dual polarization observations can also be expressed as raindrop spectra, where the radar reflectivity is:

[0122]

[0123] λ is the wavelength of electromagnetic wave, D is the equivalent diameter of raindrop, K is the dielectric constant, which is defined as K = (ε-1) / (ε+2), ε is the relative dielectric constant of raindrop, D max and D min Represent the maximum and minimum raindrop equivalent diameters, s hh,vv (π, D) represents the backscatter coefficient in the horizontal and vertical directions. Similarly, the following reasoning can be obtained:

[0124] Z H,V =10log 10 (Z h,v ), (dBz) Formula 9;

[0125]

[0126] Among them, Re represents the real part of the complex number, s hh (0, D) represents the forward scattering coefficient of horizontal incident horizontal scattering, s vv (0, D) represents the forward scattering coefficient at normal incidence and vertical scattering;

[0127]

[0128] S35, combined with T-matrix theory, the polarization parameters of the raindrop spectrum inversion rainfall radar can be combined to construct the corresponding mathematical relationship.

[0129] S4, combining polarization parameters and raindrop spectrum model for rainfall estimation: rainfall estimation includes single variable QPE and multivariate QPE methods;

[0130] S40, univariate QPE methods including ZR relationship and K DP -R relationship, estimating rainfall using a single radar parameter;

[0131] The multivariate QPE method combines multiple radar parameters and performs joint fitting of different parameters to improve the accuracy of rainfall estimation;

[0132] Among them, rainfall R and reflectivity Z, differential phase K DP , differential reflectivity Z DR There is an exponential function relationship, which is expressed as:

[0133]

[0134] Among them, a, b, and c are parameters in the empirical formula. The parameters are calibrated and adjusted according to the climate characteristics of different regions to adapt to local rainfall conditions. The difference in parameters determines that the applicability and accuracy of the same relationship in different regions vary;

[0135] S41, combines the polarization parameters obtained in S1 with the selected raindrop spectrum model to estimate rainfall, and introduces a new parameter R(K DP ,Z DR ), its empirical formula is expressed as:

[0136]

[0137] The new parameters are used to estimate rainfall intensity more stably under moderate to heavy rainfall conditions. Through multiple observation experiments, it was found that R(K DP ,Z DR ) significantly reduces its dependence on the choice of raindrop spectrum model, which can effectively reduce measurement errors, especially when the rainfall intensity is high.

[0138] S5, calibrate and optimize the raindrop model based on measured raindrop spectrum data: improve the accuracy of radar-derived rainfall intensity and microphysical properties.

[0139] In this example, the X-band radar frequency was set to 9.3 GHz, and the measured raindrop distribution in Qingdao, Shandong Province, was used as a reference. By comparing the rainfall estimation results of different models with actual observation data, the model's shape and scale parameters were adjusted to better align with the actual raindrop distribution. For example, the shape parameter μ in the Gamma distribution was adjusted based on the measured data to reduce the underestimation of the large raindrop fraction.

[0140] The method of the present invention was verified under rainfall conditions of different intensities. The experimental results show that the method of the present invention has significant advantages under heavy rainfall conditions, can better reflect the changing characteristics of raindrop spectrum, and improve the rainfall estimation accuracy of X-band dual-polarization radar. Figure 2 Under thunderstorm conditions, this method can reduce the error by about 15% compared with the traditional single raindrop spectrum model.

[0141] This invention aims to improve the accuracy and stability of X-band dual-polarization rainfall radar in rainfall intensity estimation. This estimation method uses X-band dual-polarization radar to obtain the polarization parameters of the target area. Based on the rainfall intensity, the appropriate raindrop spectrum model is selected from various raindrop spectrum models such as Marshall-Palmer distribution, Gamma distribution, Weibull distribution, and Joss distribution to estimate rainfall amount. The scattering characteristics of raindrops are calculated using T matrix theory, and the new parameter R(K DP ,Z DR ) for rainfall inversion, significantly reducing the dependence of different raindrop spectrum model selection on the estimation results. In addition, the present invention proposes a multi-parameter joint analysis method, by using Z DR and K DP This method effectively improves measurement robustness, particularly under moderate to heavy rainfall conditions, by performing rainfall estimation. Through model correction and optimization, this method improves the accuracy of large-size raindrop content estimation and addresses the systematic error caused by attenuation in X-band radar. Experimental verification demonstrates that this method exhibits significant advantages across various rainfall conditions, particularly under heavy rainfall conditions such as thunderstorms. It effectively reflects the changing characteristics of raindrop spectra, reduces rainfall estimation errors, and enhances the accuracy and reliability of meteorological observations.

[0142] The present invention has been described above by way of example with reference to the accompanying drawings. It is apparent that the specific implementation of the present invention is not limited to the above-described embodiments. Those skilled in the art may make various modifications or variations to the present invention without departing from the technical concept of the present invention, and such modifications or variations shall naturally fall within the scope of protection of the present invention.

Claims

1. A method for estimating rainfall using an X-band rain radar based on a T matrix and a multi-raindroplet spectrum model, characterized by: The following steps are involved: S1, using X-band dual-polarization rainfall radar to collect data on the target area: using X-band dual-polarization rainfall radar to collect rainfall data in the target area and obtain polarization parameters; S2, select a raindrop spectrum model based on the rainfall intensity of the target area: Based on the rainfall intensity, a raindrop spectrum model is selected. The model describes the distribution of rainfall particles under different rainfall intensities by analyzing the characteristics of raindrop size distribution; S3, calculate polarization parameters based on T-matrix theory: use the T-matrix method to calculate the scattering and attenuation characteristics of raindrops on radar signals, and obtain the backscattering matrix and forward scattering amplitude matrix; S4, combining polarization parameters and raindrop spectrum model for rainfall estimation: rainfall estimation includes single variable QPE and multivariate QPE methods; S5, calibrate and optimize the raindrop model based on measured raindrop spectrum data: improve the accuracy of radar-derived rainfall intensity and microphysical properties.

2. The X-band rainfall estimation method based on T matrix and multiple raindrop spectrum model according to claim 1 is characterized by: The S1 step includes: S10, when observing rainfall, uses X-band dual-polarization rainfall radar to scan the target area and obtain the polarization parameters of the target area, including horizontal and vertical reflectivity factors Z H and Z V , differential reflectivity Z DR , differential propagation phase Φ DP , differential phase K DP , horizontal and vertical attenuation rates A H and A V and the differential attenuation rate A DP .

3. The X-band rainfall estimation method based on T matrix and multiple raindrop spectrum model according to claim 2, characterized in that: The S2 step includes: S20, raindrop spectrum models include Marshall-Palmer distribution, Gamma distribution, Weibull distribution, Joss Drizzle distribution, and Joss ThunderStorm distribution models; The Marshall-Palmer distribution is: N(D)=N0exp(-ΛD) Formula 1; Where N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter; The Gamma distribution is: N(D)=N0D μ exp(-ΛD) Formula 2; Where μ is the shape parameter, ranging from 0 to 3 from light rainfall to heavy rainfall, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, Λ is the slope parameter, and D is the raindrop diameter; The Weibull distribution is: Where μ is the shape parameter, which ranges from 1.5 to 2.0 for heavy rainfall, N(D) is the number density of raindrops with diameter D, N0 is the intercept parameter, D is the raindrop diameter, η is the density parameter, and σ is the particle size parameter; The Joss Drizzle distribution and the Joss ThunderStorm distribution are the same as the Gamma distribution; S21, the selection method of the quantitative raindrop spectrum model, defines the level of rainfall intensity R: Rainfall intensity R (unit: mm / h) is divided into: Light rainfall: R<2.5mm / h; Moderate rainfall: 2.5≤R<10mm / h; Heavy rainfall: 10≤R<50mm / h; Heavy rain: R ≥ 50 mm / h; S22, based on the rainfall intensity R, select the raindrop spectrum model: If R<2.5, the Joss-Drizzle distribution model is preferred, followed by the Marshall-Palmer distribution model; If 2.5≤R<10, the Marshall-Palmer distribution model is preferred, followed by the Gamma distribution model; If 10≤R<50, the Marshall-Palmer distribution model is preferred, followed by the Weibull distribution model; If R≥50, the Joss ThunderStorm distribution model is preferred, followed by the Weibull distribution model.

4. The method for estimating rainfall using an X-band rain radar based on a T matrix and a multi-raindrop spectrum model according to claim 3, wherein: The S3 step includes: S30, using the T-matrix method to numerically calculate the scattering characteristics of electromagnetic waves in raindrops, substituting the obtained raindrop spectrum model parameters into the T-matrix, calculating the backscattering matrix and forward scattering amplitude matrix under horizontal and vertical polarization conditions, and calculating the scattering characteristics and signal attenuation of the radar signal in the target area; S31, based on T matrix theory, construct the backscattering matrix Z and forward scattering amplitude matrix S: S32, the polarization parameters obtained by solving the polarized electromagnetic wave are divided into two categories: one is the radar reflectivity factor Z based on backscattering H , Z V , differential reflectivity Z DR , correlation coefficient ρ and backscatter differential phase δ; the other is based on the forward scattering differential propagation phase shift Φ DP , differential propagation phase shift rate K DP , attenuation rate A H 、A V and differential attenuation rate A DP ; Where n0 represents the total number of particles per cubic meter of air, C = 10 18 λ 4 / (π 5 |K| 2 ), K = (ε-1) / (ε+2), ε is the complex dielectric constant of rainfall particles; S33, rainfall parameters are calculated using the moment method, that is, expressed as the integral of the raindrop spectrum. The rainfall intensity R can be expressed using the raindrop spectrum as: S34, dual polarization observations can also be expressed as raindrop spectra, where the radar reflectivity is: λ is the wavelength of electromagnetic wave, D is the equivalent diameter of raindrop, K is the dielectric constant, which is defined as K = (ε-1) / (ε+2), ε is the relative dielectric constant of raindrop, D max and D min Represent the maximum and minimum raindrop equivalent diameters, s hh,vv (π, D) represents the backscatter coefficient in the horizontal and vertical directions. Similarly, the following reasoning can be obtained: Z H,V =10log 10 (Z h,v ), (dBz) Formula 9; Among them, Re represents the real part of the complex number, s hh (0, D) represents the forward scattering coefficient of horizontal incident horizontal scattering, s vv (0, D) represents the forward scattering coefficient at normal incidence and vertical scattering; S35, combined with T-matrix theory, the polarization parameters of the raindrop spectrum inversion rainfall radar can be combined to construct the corresponding mathematical relationship.

5. The X-band rainfall estimation method based on T matrix and multiple raindrop spectrum model according to claim 4 is characterized in that: The S4 step includes: S40, univariate QPE methods including ZR relationship and K DP -R relationship, estimating rainfall using a single radar parameter; The multivariate QPE method combines multiple radar parameters and performs joint fitting of different parameters to improve the accuracy of rainfall estimation; Among them, rainfall R and reflectivity Z, differential phase K DP , differential reflectivity Z DR There is an exponential function relationship, which is expressed as: Among them, a, b, and c are parameters in the empirical formula. The parameters are calibrated and adjusted according to the climate characteristics of different regions to adapt to local rainfall conditions. The difference in parameters determines that the applicability and accuracy of the same relationship in different regions vary; S41, combines the polarization parameters obtained in S1 with the selected raindrop spectrum model to estimate rainfall, and introduces a new parameter R(K DP ,Z DR ), its empirical formula is expressed as: The new parameters are used to estimate rainfall intensity more stably under moderate to heavy rainfall conditions.

6. The X-band rainfall estimation method based on T matrix and multiple raindrop spectrum model according to claim 3, characterized in that: In the Marshall-Palmer distribution, the intercept parameter N0 defaults to 8000m. -3 mm -1 , the slope parameter Λ is taken as 4.1R -0.21 ; In the Gamma distribution: N0=64500R -0.5 , μ=1.5,Λ=7.09R -0.27 ; In the Weibull distribution: N0 = 1000, η ​​= 0.95R 0.14 ,σ=0.26R 0.42 ; In the Joss Drizzle distribution: N0 = 30000, Λ = 5.7R -0.21 ; In the Joss ThunderStorm distribution: N0 = 1400, Λ = 3.0R -0.21 .

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