A method, equipment, and storage medium for inverting rainfall data using a spaceborne synthetic aperture radar.

Abstract

This invention relates to a method, device, and storage medium for precipitation retrieval using spaceborne synthetic aperture radar (SAR). Addressing the supercooled water effect, the precipitation particle phases within the range of 2km to 6km above the freezing point include liquid raindrops and frozen particles. A three-layer vertical precipitation structure is proposed, considering a precipitation layer below the freezing point, a mixed layer above the freezing point, and a snow layer at the top of the precipitation layer. The corresponding precipitation particle phases are pure liquid, ice-water mixed state, and pure solid state, respectively. The scattering attenuation characteristics of the ice-water mixed state are calculated using the Debye algorithm. Based on this precipitation vertical structure, the normalized radar cross section (RCS) model and echo path are re-derived and analyzed, resulting in a new method for calculating the RCS. Finally, using a priori precipitation distribution model, the two-dimensional precipitation distribution is inverted. Compared with existing technologies, this invention improves precipitation retrieval accuracy and provides a more diverse model, adapting to more precipitation scenarios.

Description

Technical Field

[0001] This invention relates to the field of meteorological radar technology, and in particular to a method for rainfall inversion using spaceborne synthetic aperture radar based on a rainfall distribution model. Background Technology

[0002] Currently, the only meteorological satellites capable of providing three-dimensional rainfall distribution data are the Rainfall Measurement Satellite (TRMM), jointly developed by the US and Japan and launched in 1997, which carries a Rainfall Measurement Radar (PR), and the Dual-Frequency Rainfall Measurement Radar (DPR) carried by the Global Rainfall Measurement Mission (GPM), which was further developed by the US and Japan based on the successful application of TRMM. Synthetic Aperture Radar (SAR) offers advantages over traditional weather radar in terms of high precision and high resolution. The successful application of the TerraSAR-X satellite, launched by the German Aerospace Center in 2007, in rainfall observation has initially confirmed the value of SAR in rainfall measurement.

[0003] Existing SAR rainfall measurement algorithms are all semi-empirical and semi-statistical, relying on the accuracy and selection of rainfall models. Therefore, improving the accuracy of rainfall models and enriching the types of rainfall models are of great significance to improving the accuracy of SAR rainfall measurement algorithms. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method for rainfall inversion based on a rainfall distribution model for spaceborne synthetic aperture radar.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] As a first aspect of the present invention, a method for inverting rainfall using a spaceborne synthetic aperture radar is provided, wherein a mixed layer containing a mixture of liquid rainfall particles and frozen particles is defined in the vertical structure of rainfall. The rainfall inversion method includes the following steps:

[0007] Using measured vertical rainfall distribution data and related parameter information, the normalized radar cross section (NRCS) data was calculated.

[0008] Based on the scattering and attenuation characteristics of mixed-layer rainfall particles, the NRCS data were reanalyzed and calculated.

[0009] The NRCS data was preprocessed using the statistical-based directional model MOS algorithm to obtain the position information of the precipitation body relative to the spaceborne synthetic aperture radar SAR.

[0010] By analyzing the relationship between a large amount of NRCS data and surface rainfall, a surface rainfall inversion formula was statistically fitted, and the surface rainfall was obtained by inversion using this formula.

[0011] Statistical analysis was performed on a large amount of NRCS data and vertical distribution curves of rainfall. A formula for inverting surface rainfall was statistically fitted, and the parameters to be inverted were obtained through this formula.

[0012] Based on the prior directional rainfall distribution model, the relevant parameters obtained from the inversion are used to obtain the final vertical rainfall distribution.

[0013] Furthermore, the vertical structure of the rainfall is divided into three levels, including a rainfall layer below the freezing height from the ground to the top of the rainfall layer, a mixed layer ranging from 2 to 6 km above the freezing height, and a snow layer at the top of the rainfall layer.

[0014] The precipitation layer contains only liquid precipitation particles; the mixing layer is a mixture of liquid precipitation particles and frozen particles; and the snowfall layer contains only frozen particles.

[0015] Furthermore, the NRCS data received during the spaceborne SAR rain measurement is divided into two parts: backscattered echoes generated from the ground and backscattered echoes from the rain bodies. The NRCS data σ SAR Including surface scattering σ srf Volume scattering σ vol The calculation formulas are as follows:

[0016]

[0017]

[0018] Where σ 0 The NRCS data represents the ground surface, with the integral term indicating the bidirectional attenuation of radar echoes caused by precipitation particles; zr1 and zr2 represent the scattering ranges of the volume scattered echo components; zs1 and zs2 represent the attenuation ranges of the surface scattered echo components; and zr3 and zr4 represent the attenuation ranges of the volume scattered echo components. η is the radar reflectivity, calculated from the complex refractive index of the precipitation particles and the radar reflectivity factor Z, as shown in the following formula:

[0019]

[0020] In the formula, the radar reflectivity factor Z is obtained from the relationship between the radar reflectivity factor Z and the rainfall R, λ is the radar wavelength, and m0 is the complex refractive index of the rainfall particles.

[0021] The rainfall distribution can be simplified into a two-dimensional distribution consisting of mutually independent vertical and horizontal distributions, represented as:

[0022] R(x,z)=H(x)V(z)

[0023] In the formula, x represents the direction perpendicular to the spaceborne SAR track, H(x) represents the horizontal distribution of rainfall, and V(z) represents the rainfall at altitude z.

[0024] NRCS data were calculated by analyzing the echo path.

[0025] Furthermore, based on the scattering attenuation characteristics of mixed-layer rainfall particles, the NRCS data is re-analyzed and calculated. The specific steps for calculating the scattering characteristics of mixed-layer rainfall particles are as follows:

[0026] Reconsider the relationship between the radar reflectivity factor Z of mixed-phase rainfall particles and the rainfall R, as well as the relationship between the attenuation coefficient k and the rainfall R;

[0027] Based on the Debye algorithm, the complex refractive index of precipitation particles in the pure liquid and pure ice phases is used to calculate the complex refractive index of precipitation particles in the mixed phase. The specific calculation formula of the Debye algorithm is as follows:

[0028]

[0029]

[0030] In the formula, f represents the proportion of liquid rain particles, m 0i and m 0w These represent the complex refractive indices of frozen particles and liquid particles, respectively;

[0031] The NRCS data were reanalyzed and calculated based on the new scattering and attenuation characteristics of rainfall particles.

[0032] Furthermore, the aforementioned

[0033] The prior, directional rainfall distribution model is as follows:

[0034]

[0035] In the formula, z represents the height, z0 represents the freezing height, and z m Indicates the height of the top of the hybrid layer, z t V(z) represents the rain top height, V(0) represents the ground rainfall, V(z0) represents the rainfall at the freezing point, and V(z) represents the rainfall at the freezing point. m ) represents the rainfall at the top of the mixed layer, p r and p m p represents the rainfall distribution coefficient of the precipitation layer and the mixed layer. s This represents the precipitation distribution coefficient of the snow layer;

[0036] In the formula, the parameters to be inverted include surface rainfall V(0) and the rainfall distribution coefficient p of the snow layer. s and the height of the rain roof z t ; parameters z0, z mp r p m These are prior values; different rainfall types and regions have different typical values, which are obtained by looking up tables.

[0037] Furthermore, the positional information of the precipitation body relative to the spaceborne SAR obtained using the statistical-based directional model MOS algorithm includes: the precipitation width w, the left starting point x of the precipitation body. L The right end point of the rainfall body x R .

[0038] Furthermore, the ground rainfall V(0) is represented as the average weighted sum of the attenuation of the ground backscattered echo by the rainfall body, the volume scattering at the top of the rainfall body, and the rainfall width w;

[0039]

[0040] Where σ 0 For, σ SAR (x) represents the backscattered echo generated by the ground, and a, b, c, and d are the weighting coefficients.

[0041] Furthermore, the precipitation distribution coefficient p of the snow layer to be inverted... s and the height of the rain roof z t The inversion process is as follows:

[0042] Statistical analysis was performed on a large amount of NRCS data and rainfall vertical distribution curves using the rainfall vertical distribution inversion formula. This yielded the centroid of the rainfall vertical distribution model above the freezing point and the NRCS data σ to the left of the rainfall initiation point. SAR The linear relationship between the centroids of the distribution curve is expressed as:

[0043] <(z-z0)>=a<(xx L )>

[0044] In the formula, the left side of the equation represents the centroid of the rainfall R(z) curve above the freezing point, and the right side of the equation represents the NRCS curve at x. L The formulas for the centroid of the curves on the left are shown below:

[0045]

[0046]

[0047] Where σ 0 The NRCS data represents the ground level. Additionally, the average rainfall above the freezing point is represented as follows:

[0048]

[0049] In the formula, the horizontal rainfall distribution H(x) = 1 represents a rectangular distribution. The quantitative statistical relationship between the average rainfall above the freezing point and the NRCS data is expressed as follows:

[0050]

[0051] In the formula, parameters l, m, and n are empirical coefficients obtained through statistics;

[0052] By combining the centroid formula for the curve above the freezing point with the formula for the average rainfall above the freezing point, the parameter p to be inverted can be calculated. s and z t .

[0053] As a second aspect of the present invention, a rainfall inversion device is provided, comprising:

[0054] One or more processors;

[0055] Memory, used to store one or more programs;

[0056] When the one or more programs are executed by the one or more processors, the one or more processors implement the rainfall inversion method as described in any of the preceding claims.

[0057] As a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the rainfall inversion method as described in any of the preceding claims.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1) The calculation of the scattering characteristics of mixed-phase rainfall particles, namely the Debye algorithm, was introduced, and the relationship between the radar reflectivity factor of mixed rainfall particles and the scattering attenuation of rainfall was reconsidered, which improved the estimation accuracy of the scattering attenuation of rainfall particles to radar echoes in the range of 2 to 6 km above the freezing height.

[0060] 2) A new vertical rainfall distribution model was adopted, which better reflects the actual vertical structure of rainfall compared to the original model. Furthermore, the model is more detailed, and different combinations of prior values ​​make it more diverse and adaptable to a wider range of rainfall scenarios.

[0061] 3) Numerous experiments were conducted using rainfall vertical distribution data measured by conventional meteorological radar. The results show that the average inversion accuracy of ground rainfall in this invention is improved by 1.35%, and the root mean square error of rainfall distribution inversion is reduced by more than 0.2. This invention is highly competitive compared with existing spaceborne SAR rainfall measurement methods. Attached Figure Description

[0062] Figure 1 This is a schematic diagram illustrating the principle of NRCS analysis and calculation in this invention;

[0063] Figure 2 This is a flowchart of a spaceborne synthetic aperture radar rainfall inversion algorithm based on a rainfall distribution model, according to the present invention. Detailed Implementation

[0064] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0065] Example 1

[0066] To improve the capabilities of SAR rainfall measurement, this invention proposes a rainfall inversion algorithm based on a three-layer vertical rainfall distribution model. This algorithm addresses the supercooled water effect, which results in rainfall particles in the range of 2 km to 6 km above the freezing point containing both liquid raindrops and frozen particles. Since the scattering attenuation of liquid raindrops is approximately five times that of frozen particles, this contributes to the calculation error of the radar echo data, i.e., the Normalized Radar Cross Section (NRCS) model, thus affecting the accuracy of the rainfall inversion algorithm. Therefore, the inversion algorithm of this invention divides the vertical structure into three layers: a rainfall layer below the freezing point (containing only liquid raindrops), a mixed layer (a mixture of liquid and frozen particles) in the range of 2–6 km above the freezing point, and a snow layer at the top of the rainfall layer (containing only frozen particles).

[0067] To improve the estimation of radar echo scattering attenuation by mixed-layer rainfall particles, the following scheme is adopted:

[0068] 1) Unlike the scattering attenuation relationship of the precipitation layer and the snow layer, the ZR relationship and kR relationship of the mixed phase precipitation particles are reconsidered, where Z represents the radar reflectivity factor, k represents the attenuation coefficient, and R represents the precipitation amount;

[0069] 2) Based on the Debye algorithm, the complex refractive index of the rain particles in the pure liquid phase and the pure ice phase is used to calculate the complex refractive index of the mixed phase rain particles;

[0070] The specific calculation formula for the Debye algorithm is as follows:

[0071]

[0072]

[0073] In the formula, f represents the proportion of liquid rain particles, m 0i and m 0wThese represent the complex refractive indices of frozen particles and liquid particles, respectively. Based on the new scattering attenuation characteristics of precipitation particles, the NRCS data were reanalyzed and recalculated.

[0074] After optimizing the analysis and calculation of NRCS, a statistically based directional model (MOS) algorithm is adopted to invert the vertical distribution of rainfall. The formula for inverting the vertical distribution of rainfall using the prior directional three-layer rainfall vertical distribution model is as follows:

[0075]

[0076] In the formula, z represents the height, z0 represents the freezing height, and z m Indicates the height of the top of the hybrid layer, z t V(z) represents the rain top height, V(0) represents the ground rainfall, V(z0) represents the rainfall at the freezing point, and V(z) represents the rainfall at the freezing point. m ) represents the rainfall at the top of the mixed layer, p r and p m p represents the rainfall distribution coefficient of the precipitation layer and the mixed layer. s This represents the precipitation distribution coefficient of the snow layer. In the formula, the parameters to be inverted are the surface precipitation V(0) and the precipitation distribution coefficient p of the snow layer. s and the height of the rain roof z t Parameters z0, z m p r p m These are prior values; different rainfall types and regions have different typical values, which can be obtained by looking up tables. Thus, a wide variety of rainfall models can be derived from these four-dimensional parameter data.

[0077] Appendix Figure 1 This is a schematic diagram illustrating the principle of analyzing and calculating NRCS model data. The NRCS data received during spaceborne SAR rain measurement can be divided into two parts: backscattered echoes generated from the ground and backscattered echoes from the rain volume. That is, NRCS can be divided into surface scattering and volume scattering, and the calculation formulas are shown in Formulas 5 and 6 respectively:

[0078] σ SAR =σ srf +σ vol (4)

[0079]

[0080]

[0081] Where σ 0 Let represent the NRCS of the ground, the integral term represent the bidirectional attenuation of radar echoes caused by rainfall particles, and η be the radar reflectivity, calculated from the complex refractive index of the rainfall particles and the radar reflectivity factor Z, as shown in the following formula:

[0082]

[0083] In the formula, Z is obtained from the ZR relationship, λ is the radar wavelength, and m0 is the complex refractive index of the rain particles. (From the attached...) Figure 1 It can be seen that rainfall distribution can be simplified into a two-dimensional distribution consisting of mutually independent vertical and horizontal rainfall distributions. This can be represented as:

[0084] R(x,z)=H(x)V(z) (8)

[0085] In the formula, x represents the direction perpendicular to the spaceborne SAR track, H(x) represents the horizontal distribution of rainfall, and H(x) = 1 represents a rectangular distribution. The different geometric positions of the radar echo and the rainfall particles cause corresponding changes in the scattering intervals zr1 and zr2 and the attenuation intervals zr3 and zr4 (zs1 and zs2) of the rainfall particles in Formulas 5 and 6. The attenuation relationship of different rainfall layers is specified by k(z). Therefore, NRCS data can be calculated through detailed echo path analysis.

[0086] Appendix Figure 2 This is a flowchart illustrating the specific process of the spaceborne SAR rainfall inversion algorithm of this invention.

[0087] 1) First, utilize measured vertical rainfall distribution data and related parameter information, such as ZR relationship, kR relationship, complex refractive index, and ground NRCSσ. 0 NRCS data are calculated using radar downward angle θ, etc.

[0088] 2) The MOS algorithm is used to preprocess the NRCS data to obtain the position information of the rain body relative to the spaceborne SAR, such as the rain width w and the left starting point x of the rain body. L The right end point of the rainfall body x R .

[0089] 3) The formula for retrieving surface rainfall is shown in Formula 8. Through analysis of the relationship between a large amount of NRCS data and surface rainfall, V(0) is expressed as the average weighted sum of the attenuation of the backscattered echo from the ground by the rainfall body, the volume scattering from the top of the rainfall body, and the width of the rainfall. Coefficients a, b, c, and d are the weighting coefficients. Empirical values ​​obtained statistically under different rainfall distribution types and different radar viewing angles will vary.

[0090]

[0091] 4) The rainfall vertical distribution inversion formula, through statistical analysis of a large amount of NRCS data and rainfall vertical distribution curves, reveals a certain linear relationship between the centroid of the rainfall vertical distribution model curve above the freezing point and the centroid of the NRCS data distribution curve to the left of the rainfall initiation point, expressed as:

[0092] <(z-z0)>=a<(xx L (10)

[0093] In the equation, the left side represents the centroid of the curve R(z) above the freezing point, and the right side represents the NRCS at x L The formulas for the centroid of the curves on the left are shown below:

[0094]

[0095]

[0096] Furthermore, the average rainfall above the freezing point can be expressed as:

[0097]

[0098] As attached Figure 1 As shown in the formula, H(x) = 1 represents a rectangular distribution. Its quantitative statistical relationship with NRCS data can be expressed as:

[0099]

[0100] The parameters l, m, and n are empirical coefficients obtained through statistics. Finally, by simultaneously solving formulas 11 and 13, the parameter p to be inverted can be calculated. s and z t .

[0101] 5) Finally, based on the prior directional rainfall distribution model, the relevant parameters obtained from the inversion are substituted to obtain the final vertical rainfall distribution.

[0102] This invention presents a spaceborne synthetic aperture radar (SAR) rainfall inversion algorithm based on a rainfall distribution model. Addressing the supercooled water effect, the rainfall particle phases within the range of 2km to 6km above the freezing point include both liquid raindrops and frozen particles. Since the scattering attenuation characteristics of liquid raindrops are approximately five times that of frozen particles, this leads to an underestimation of radar echo attenuation, thus affecting the accuracy of the rainfall inversion algorithm. A three-layer vertical rainfall structure is proposed, considering a rainfall layer below the freezing point, a mixed layer above the freezing point, and a snow layer at the top of the rainfall layer. The corresponding rainfall particle phases are pure liquid, a mixture of ice and water, and a pure solid, respectively. The scattering attenuation characteristics of the mixture of ice and water are calculated using the Debye algorithm. Based on this vertical rainfall structure, the normalized radar cross section (RCS) model and echo path are re-derived and analyzed, resulting in a new method for calculating the RCS. Finally, using a priori rainfall distribution model, the two-dimensional rainfall distribution is inverted. Experimental results show that the improved rainfall inversion algorithm improves the average inversion accuracy of ground rainfall by 1.35%, and reduces the root mean square error of rainfall distribution inversion by more than 0.2.

[0103] Example 2

[0104] As a second aspect of the present invention, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the rainfall inversion method described above. In addition to the processors, memory, and interface described above, any data processing device in the embodiments may also include other hardware depending on the actual function of the data processing device, which will not be elaborated further.

[0105] Example 3

[0106] As a third aspect of the present invention, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the rainfall inversion method described above. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.

[0107] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for precipitation inversion using spaceborne synthetic aperture radar, characterized in that, The rainfall inversion method involves defining a mixed layer containing both liquid and frozen particles within the vertical structure of rainfall. The steps include: Using measured vertical rainfall distribution data and related parameter information, the normalized radar cross section (NRCS) data was calculated. Based on the scattering and attenuation characteristics of mixed-layer rainfall particles, the NRCS data were reanalyzed and calculated. The NRCS data was preprocessed using the statistical-based directional model MOS algorithm to obtain the position information of the precipitation body relative to the spaceborne synthetic aperture radar SAR. By analyzing the relationship between a large amount of NRCS data and surface rainfall, a surface rainfall inversion formula was statistically fitted, and the surface rainfall was obtained by inversion using this formula. Statistical analysis was performed on a large amount of NRCS data and vertical distribution curves of rainfall. A formula for inverting surface rainfall was statistically fitted, and the parameters to be inverted were obtained through this formula. Based on the prior directional rainfall distribution model, the relevant parameters obtained from the inversion are used to obtain the final vertical rainfall distribution.

2. The method for inverting rainfall using spaceborne synthetic aperture radar according to claim 1, characterized in that, The vertical structure of the rainfall is divided into three levels, including a rainfall layer below the freezing height from the ground to the top of the rainfall layer, a mixed layer ranging from 2 to 6 km above the freezing height, and a snow layer at the top of the rainfall layer. The precipitation layer contains only liquid precipitation particles; the mixing layer is a mixture of liquid precipitation particles and frozen particles; and the snowfall layer contains only frozen particles.

3. The spaceborne synthetic aperture radar rainfall inversion method according to claim 2, characterized in that, The NRCS data received by the spaceborne synthetic aperture radar (SAR) during rain measurement is divided into two parts: backscattered echoes generated from the ground and backscattered echoes from the rain particles. Including surface scattering Volume scattering The calculation formulas are as follows: In the formula, σ 0 The integral term represents the two-way attenuation of radar echo caused by the rain body; zr1 and zr2 represent the scattering range of the volume scattering echo component; zs1 and zs2 represent the attenuation range of the surface scattering echo component; and zr3 and zr4 represent the attenuation range of the volume scattering echo component. η Radar reflectivity is calculated from the complex refractive index of the rain particles and the radar reflectivity factor Z, as shown in the following formula: In the formula, the radar reflectivity factor Z is obtained from the relationship between the radar reflectivity factor Z and the rainfall R, and λ is the radar wavelength. It is the complex refractive index of the rain particles; The rainfall distribution can be simplified into a two-dimensional distribution consisting of mutually independent vertical and horizontal distributions, represented as: In the formula, x Indicates the direction of the vertical spaceborne SAR track. H(x) Indicates the horizontal distribution of rainfall; V (z) represents the rainfall at height z. NRCS data were calculated by analyzing the echo path.

4. The spaceborne synthetic aperture radar rainfall inversion method according to claim 3, characterized in that, The NRCS data was re-analyzed and calculated based on the scattering attenuation characteristics of mixed-layer rainfall particles. The specific steps for calculating the scattering characteristics of mixed-layer rainfall particles are as follows: Reconsider the relationship between the radar reflectivity factor Z of mixed-phase rainfall particles and the rainfall R, as well as the relationship between the attenuation coefficient k and the rainfall R; Based on the Debye algorithm, the complex refractive index of precipitation particles in the pure liquid and pure ice phases is used to calculate the complex refractive index of precipitation particles in the mixed phase. The specific calculation formula of the Debye algorithm is as follows: In the formula, f This indicates the proportion of liquid rain particles. and These represent the complex refractive indices of frozen particles and liquid particles, respectively; The NRCS data were reanalyzed and calculated based on the new scattering and attenuation characteristics of rainfall particles.

5. The spaceborne synthetic aperture radar rainfall inversion method according to claim 2, characterized in that, The The prior, directional rainfall distribution model is as follows: In the formula, z represents the height, z0 represents the freezing height, and z m Indicates the height of the top of the hybrid layer, z t Indicates the height of the rain roof. V (0) represents the ground rainfall. V (z0) represents the rainfall at the freezing point. V (z m () indicates the rainfall at the top of the mixed layer. p r and p m This represents the rainfall distribution coefficient of the precipitation layer and the mixed layer. p s This represents the precipitation distribution coefficient of the snow layer; In the formula, the parameters to be inverted include surface rainfall. V (0) Rainfall distribution coefficient of snow layer p s and the height of the rain roof z t ; parameters z0, z m , p r , p m These are prior values; different rainfall types and regions have different typical values, which are obtained by looking up tables.

6. The spaceborne synthetic aperture radar rainfall inversion method according to claim 5, characterized in that, The positional information of the precipitation body relative to spaceborne SAR obtained using the statistical-based directional model MOS algorithm includes: precipitation width. The starting point on the left side of the rainfall body The right end point of the rainfall body .

7. The spaceborne synthetic aperture radar rainfall inversion method according to claim 6, characterized in that, The ground rainfall V (0) represents the attenuation of the backscattered echo from the ground by the rainfall body, the volume scattering from the top of the rainfall body, and the rainfall width. w The average weighted average; In the formula, σ 0 For ground-based NRCS data, The backscattered echo generated by the ground, a , b , c , d These are the weighting coefficients.

8. The spaceborne synthetic aperture radar rainfall inversion method according to claim 5, characterized in that, The parameter to be inverted is the precipitation distribution coefficient of the snow layer. p s and the height of the rain roof z t The inversion process is as follows: Statistical analysis was performed on a large amount of NRCS data and rainfall vertical distribution curves using the rainfall vertical distribution inversion formula. This yielded the NRCS data to the left of the rainfall initiation point for the rainfall vertical distribution model's curve centroid above the freezing point. The linear relationship between the centroids of the distribution curve is expressed as: In the formula, the left side of the equation represents the centroid of the rainfall R(z) curve above the freezing height, and the right side of the equation represents the starting point of the NRCS on the left side of the rainfall volume. x L The formulas for the centroid of the curves on the left are shown below: In the formula, σ 0 Represents NRCS data on the ground. σ SAR ( x The number ) represents the backscattered echo generated by the ground; in addition, the average rainfall above the freezing point is expressed as: In the formula, the horizontal distribution of rainfall H (x) = 1 represents a rectangular distribution. Therefore, the quantitative statistical relationship between the average rainfall above the freezing point and the NRCS data is expressed as follows: In the formula, the parameter l , m , n These are empirical coefficients obtained through statistics; w Indicates the width of the rainfall; By combining the centroid formula for the curve above the freezing point with the formula for the average rainfall above the freezing point, the parameters to be inverted can be calculated. p s and z t .

9. A rainfall inversion device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the rainfall inversion method as described in any one of claims 1-8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the rainfall inversion method as described in any one of claims 1-8.

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