CN114417264A - Raindrop spectrum inversion method and device - Google Patents
Raindrop spectrum inversion method and device Download PDFInfo
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- CN114417264A CN114417264A CN202210308972.1A CN202210308972A CN114417264A CN 114417264 A CN114417264 A CN 114417264A CN 202210308972 A CN202210308972 A CN 202210308972A CN 114417264 A CN114417264 A CN 114417264A
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Abstract
The invention provides a raindrop spectrum inversion method and a raindrop spectrum inversion device, wherein the method comprises the following steps: acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontal polarization reflectivity factor and the first differential reflectivity factor are obtained by observing a dual-polarization radar of the target area; determining a first raindrop spectrum sixth order moment, a raindrop spectrum seventh order moment and a target shape factor pair based on the first horizontal polarization reflectivity factor and the first differential reflectivity factor; and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair. According to the method, the six-order moment, the seven-order moment and the shape factor pair of the raindrop spectrum are obtained by utilizing the horizontal polarization reflectivity factor and the differential reflectivity factor, the initial raindrop spectrum of the target area is further obtained by utilizing the pre-established raindrop spectrum model, the influence of the error of the differential propagation phase shift rate on the raindrop spectrum inversion is avoided, and the raindrop spectrum inversion precision is improved.
Description
Technical Field
The invention relates to the technical field of atmospheric science, in particular to a raindrop spectrum inversion method and device.
Background
The raindrop spectrum of the precipitation process can be inverted through polarization radar parameters obtained by observation in the dual-polarization radar, and the raindrop spectrum is the distribution of the quantity of raindrops in unit volume along with the size of the raindrops. When the dual-polarization radar is used for inverting the raindrop spectrum, the inversion method is often based on a certain raindrop spectrum model, for example: a constrained Gamma model, a normalized Gamma model, etc.
In the method of the constraint Gamma model, the constraint is that the shape factor (mu) and the slope factor (Lambda) in the standard Gamma model are not independent and have a certain deterministic relationship, and a relational expression between the droplet spectrum parameter and the polarization radar parameter is derived based on the relationship. However, the assumption that μ and Λ are not independent has been questioned by some scholars: mu and Λ do not behave independently due to excessive quality control of the data, especially the mu- Λ relationship in convective cloud precipitation is less reliable.
In the prior art (Estimation of random size distribution parameters from polar radial measurements, Journal of the atomic Sciences, 59, 2373-DPInversion of raindrop spectra, but due to pair KDPThe error of (2) is sensitive, and the inversion result is not ideal. In the prior art (regenerative of the raindrop size distribution from polar data using double-molecular-statistical normal analysis. Atmosonic Measurement Techniques, 10 (7); 2573) and when inverting raindrop spectrum by using X-band dual-polarization radar observation parameters, K is also neededDPThus when K is presentDPIn the presence of significant errors, the results obtained tend to be unreliable.
Disclosure of Invention
The invention provides a raindrop spectrum inversion method and device, which are used for overcoming the defects in the prior art.
In a first aspect, the present invention provides a raindrop spectrum inversion method, including: acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area; determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor; and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
According to the raindrop spectrum inversion method provided by the invention, the determining a first raindrop spectrum sixth order moment, a raindrop spectrum seventh order moment and a target shape factor pair based on the first horizontal polarization reflectivity factor and the first differential reflectivity factor comprises the following steps: acquiring the target form factor pair from a pre-established form factor lookup table according to the numerical values of the first horizontal polarization reflectivity factor and the first differential reflectivity factor; acquiring the sixth moment of the first raindrop spectrum by utilizing a pre-established first fitting function according to the first horizontal polarization reflectivity factor; and determining the seventh moment of the raindrop spectrum by utilizing a pre-established second fitting function according to the sixth moment of the first raindrop spectrum and the first differential reflectivity factor.
According to the raindrop spectrum inversion method provided by the invention, after the initial raindrop spectrum of the target region is obtained by using a pre-established raindrop spectrum model according to the first raindrop spectrum sixth order moment, the raindrop spectrum seventh order moment and the target shape factor pair, the method further comprises the following steps: acquiring a second horizontal polarization reflectivity factor by utilizing a polarization radar parameter calculation formula according to the initial raindrop spectrum; according to the second horizontal polarization reflectivity factor, acquiring a second raindrop spectrum sixth moment corresponding to the initial raindrop spectrum by using the first fitting function; determining a number density correction factor according to the ratio of the sixth moment of the first raindrop spectrum to the sixth moment of the second raindrop spectrum; and correcting the initial raindrop spectrum by using the number density correction factor to obtain a target raindrop spectrum.
According to the raindrop spectrum inversion method provided by the present invention, before the target shape factor pair is obtained from a pre-established shape factor lookup table according to the numerical values of the first horizontal polarization reflectivity factor and the first differential reflectivity factor, the method further includes: acquiring a raindrop spectrum observation data set of the target area; acquiring a group of inversion parameters corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set; each set of inversion parameters includes: a first shape factor pair, a third horizontally polarized reflectance factor, and a third differential reflectance factor; constructing an inversion parameter data set according to each group of inversion parameters; dividing the inversion parameter data set into different inversion parameter subsets according to the numerical values of a third horizontal polarization reflectivity factor and a third differential reflectivity factor in each set of inversion parameters; and acquiring a second shape factor pair corresponding to any inversion parameter subset to establish the shape factor lookup table.
According to the raindrop spectrum inversion method provided by the invention, the obtaining of the second shape factor pair corresponding to any inversion parameter subset to establish the shape factor lookup table includes: acquiring the number of sets of inversion parameters in any inversion parameter subset; and under the condition that the group number is greater than or equal to a preset threshold value, acquiring a second shape factor pair corresponding to any inversion parameter subset according to the probability distribution of the first shape factor pair in any inversion parameter subset so as to establish the shape factor lookup table.
According to the raindrop spectrum inversion method provided by the invention, under the condition that the group number is smaller than the preset threshold value, the method further comprises the following steps: and acquiring a shape factor pair default value corresponding to the inversion parameter data set according to the probability distribution of the first shape factor pair in the inversion parameter data set so as to establish the shape factor lookup table.
According to the raindrop spectrum inversion method provided by the invention, a group of inversion parameters corresponding to any raindrop spectrum observation data are obtained according to the raindrop spectrum observation data set, and the method comprises the following steps: calculating a third horizontal polarized reflectivity factor and a third differential reflectivity factor corresponding to each raindrop spectrum observation data by using a polarized radar parameter calculation formula according to the raindrop spectrum observation data set; and acquiring a first shape factor pair corresponding to each raindrop spectrum observation data by using the raindrop spectrum model according to the raindrop spectrum observation data set.
According to the raindrop spectrum inversion method provided by the invention, before the first raindrop spectrum sixth moment is obtained by using a pre-established fitting function according to the first horizontal polarization reflectivity factor, the method further comprises the following steps: determining a third raindrop spectrum sixth order moment and a third raindrop spectrum seventh order moment corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set; determining the first fitting function according to a fitting relation between a third raindrop spectrum sixth moment corresponding to each raindrop spectrum observation data and a third horizontal polarization reflectivity factor; and determining the second fitting function according to the fitting relation between the sixth moment of the third raindrop spectrum and the seventh moment of the third raindrop spectrum.
In a second aspect, the present invention further provides a raindrop spectrum inversion apparatus, including:
the radar parameter acquisition module is used for acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area;
a raindrop spectrum parameter obtaining module, configured to determine a first raindrop spectrum sixth order moment, a raindrop spectrum seventh order moment, and a target shape factor pair based on the first horizontal polarization reflectivity factor and the first differential reflectivity factor;
and the initial raindrop spectrum acquisition module is used for acquiring an initial raindrop spectrum of the target area by utilizing a pre-established raindrop spectrum model according to the first raindrop spectrum sixth moment, the raindrop spectrum seventh moment and the target shape factor pair.
In a third aspect, the present invention provides an electronic device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the raindrop spectrum inversion method as described in any one of the above.
In a fourth aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the raindrop spectrum inversion method as described in any one of the above.
According to the raindrop spectrum inversion method and device, the six-order moment, the seven-order moment and the shape factor pair of the raindrop spectrum are obtained by utilizing the horizontal polarization reflectivity factor and the differential reflectivity factor, the initial raindrop spectrum of the target area is further obtained by utilizing the pre-established raindrop spectrum model, the influence of the error of the differential propagation phase shift rate on the raindrop spectrum inversion is avoided, and the raindrop spectrum inversion precision is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is one of the flow diagrams of the raindrop spectrum inversion method provided in the present invention;
fig. 2 is a second schematic flow chart of the raindrop spectrum inversion method provided in the present invention;
FIG. 3 is a probability density distribution graph provided by the present invention;
FIG. 4 is a schematic diagram of the results of a simulation provided by the present invention;
FIG. 5 is a second schematic diagram of the simulation results provided by the present invention;
FIG. 6 is a third schematic diagram of the simulation results provided by the present invention;
FIG. 7 is a fourth schematic diagram of the simulation results provided by the present invention;
FIG. 8 is a fifth schematic diagram of simulation results provided by the present invention;
fig. 9 is a schematic structural diagram of a raindrop spectrum inversion apparatus provided in the present invention;
fig. 10 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that in the description of the embodiments of the present invention, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element. The terms "upper", "lower", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred devices or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The terms "first," "second," and the like in this application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. Further, "and/or" indicates at least one of the connected objects, the character "/", generally indicating that the former and latter related objects are in an "or" relationship.
The method and apparatus for inversion of raindrop spectra provided by the embodiments of the present invention are described below with reference to fig. 1 to 10.
Fig. 1 is a schematic flow chart of a raindrop spectrum inversion method provided in the present invention, as shown in fig. 1, including but not limited to the following steps:
step 101: a first horizontally polarized reflectivity factor and a first differential reflectivity factor are obtained.
The dual-polarization radar can utilize the observation parameters thereof to realize the inversion of the raindrop spectrum of the target area. S-band dual-polarization radar widely existed KDPPoor quality, especially in light rain, is more severe using KDPInverting the raindrop spectrum may have a large impact on the result. Based on this, the observation parameters adopted by the invention are: a horizontally polarized reflectivity factor and a differential reflectivity factor.
Taking the guangdong region as an example, in order to invert the raindrop spectrum of the guangdong region, an S-band dual-polarization radar of the guangdong region may be used for observation to obtain a corresponding first horizontally polarized reflectance factor and a corresponding first differential reflectance factor.
Step 102: determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor.
Step 103: and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
When the dual-polarization radar is used for inverting the raindrop spectrum, the method is usually based on a pre-established raindrop spectrum model, and a generalized Gamma model is converted by using a dual-moment normalization method to obtain the following form:
whereinNDenotes the particle number density of the raindrop, D denotes the raindrop diameter,N(D) denotes the particle number density of a raindrop of diameter D,M i indicating raindrop spectrumiThe order of the moment is set to be,M j indicating raindrop spectrumjThe order of the moment is set to be,μandctwo form factors in the model, i.e. form factor pair, Γ i And Γ j Is an intermediate variable. Γ denotes the gamma function. In the embodiment of the present inventioniThe value of the number is 6,jthe value is 7.
Compared with a constraint Gamma model, the raindrop spectrum model has no influence on raindrop spectrum inversion caused by uncertainty of mu-Lambda relation, and has a better inversion effect.
According to the method, the historical raindrop spectrum data of the target area can be utilized to establish a relevant fitting model, so that the observation parameters of the dual-polarization radar are utilized to obtain corresponding pairs of the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor, and then the formulas (1) to (5) are utilized to carry out the inversion of the raindrop spectrum.
According to the raindrop spectrum inversion method, the six-order moment, the seven-order moment and the shape factor pair of the raindrop spectrum are obtained by utilizing the horizontal polarization reflectivity factor and the differential reflectivity factor, the initial raindrop spectrum of the target area is further obtained by utilizing the pre-established raindrop spectrum model, the influence of the error of the differential propagation phase shift rate on the raindrop spectrum inversion is avoided, and the raindrop spectrum inversion precision is improved.
Fig. 2 is a second schematic flow chart of the raindrop spectrum inversion method provided by the present invention, and as shown in fig. 2, the present invention is divided into two stages, a parameter acquisition stage and a raindrop spectrum inversion stage. And in the parameter acquisition stage, a shape factor lookup table and a fitting function need to be established, so that parameters needed in the raindrop spectrum inversion stage are acquired by using the shape factor lookup table and the fitting function, and then raindrop spectrum inversion is carried out.
Because the raindrop spectrums in different regions have different characteristics, corresponding shape factor lookup tables and fitting functions are required to be established for different regions. The present invention is illustrated by taking the Guangzhou Longmen area as an example.
Optionally, the step of building the form factor lookup table includes, but is not limited to: acquiring a raindrop spectrum observation data set of the target area; acquiring a group of inversion parameters corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set; constructing an inversion parameter data set according to each group of inversion parameters; dividing the inversion parameter data set into different inversion parameter subsets according to the numerical values of a third horizontal polarization reflectivity factor and a third differential reflectivity factor in each set of inversion parameters; and acquiring a second shape factor pair corresponding to any inversion parameter subset to establish the shape factor lookup table.
The method obtains the raindrop spectrum observation data of the Guangzhou gantry region through the observation of the ground raindrop spectrum analyzer, and constructs the raindrop spectrum observation data set through the long-time raindrop spectrum observation data, wherein one raindrop spectrum observation data set comprises a plurality of raindrop spectrum observation data.
And calculating a third horizontal polarized reflectivity factor and a third differential reflectivity factor corresponding to each raindrop spectrum observation data by using a polarized radar parameter calculation formula according to the raindrop spectrum observation data.
The calculation formula of the polarization radar parameters is as follows:
wherein the content of the first and second substances,
which represents the horizontally polarized reflectivity factor, is,
which represents the vertically polarized reflectivity factor, is,
showing the backscatter cross section of a horizontally polarized wave-emitting raindrop,
showing the backscatter cross section of a vertically polarized wave-emitting raindrop,
m is the refractive index of water for the radar wavelength.
The third horizontally polarized reflectivity factor and the third differential reflectivity factor can be calculated by the above formula.
Further, the formula (1) to the formula (5) may be combined, and a raindrop spectrum model is used to obtain a first shape factor pair corresponding to each raindrop spectrum observation data. It should be noted that a form factor pair includes two form factors: shape factor μ and shape factor c.
It can be known that a set of inversion parameters can be obtained from each raindrop spectrum observation data, and an inversion parameter data set can be constructed from each set of inversion parameters. Each set of inversion parameters includes: a first shape factor pair, a third horizontally polarized reflectivity factor, and a third differential reflectivity factor.
According to the numerical values of the third horizontal polarization reflectivity factor and the third differential reflectivity factor, the inversion parameter data set can be divided into different inversion parameter subsets.
Optionally, the present invention looks up the table in the form factor by obtaining a second form factor pair corresponding to any one of the subsets of inversion parameters.
Specifically, the present invention may set a predetermined threshold, such as 100. When the number of sets of inversion parameters in the inversion parameter subsets is greater than or equal to 100, the probability distribution of the first shape factor pair in each inversion parameter subset can be counted to obtain a corresponding probability density distribution map, and the value μ, c at the maximum probability position is found as a second shape factor pair corresponding to the inversion parameter subset.
When the number of sets of inversion parameters in the inversion parameter subset is less than 100, a shape factor pair default value corresponding to the inversion parameter dataset may be obtained according to the probability distribution of the first shape factor pair in the inversion parameter dataset.
Fig. 3 is a probability density distribution diagram provided by the present invention, and as shown in fig. 3, the μ, c value at the maximum probability in the probability density distribution diagram can be found as the shape factor pair default value of the inversion parameter data set, and the shape factor pair default value is used as the corresponding μ, c value of the inversion parameter subset.
Table 1 is a form factor lookup table provided by the present invention, and as shown in table 1, the contents in the table are sequentially (μ, log10 c), and the number of sets of inversion parameters in the corresponding inversion parameter subset is less than 100, which may be replaced by the form factor pair default values. The default values for the shape factor pairs obtained using the inversion parameter dataset in the present invention are (1.33, 0.25).
Table 1 form factor lookup table
In the parameter obtaining stage, the invention also needs to obtain a fitting function, wherein the fitting function includes: a first fitting function and a second fitting function. The step of obtaining the fitting function includes, but is not limited to: determining a third raindrop spectrum sixth order moment and a third raindrop spectrum seventh order moment corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set; determining the first fitting function according to a fitting relation between a third raindrop spectrum sixth moment corresponding to each raindrop spectrum observation data and a third horizontal polarization reflectivity factor; and determining the second fitting function according to the fitting relation between the sixth moment of the third raindrop spectrum and the seventh moment of the third raindrop spectrum.
Specifically, the sixth moment and the seventh moment of the third raindrop spectrum of any raindrop spectrum observation data can be calculated by using the following formulas:
further, M can be fitted using the raindrop spectrum observation dataset6And ZHTo obtain a first fitting function:
further, according to the following formula:
it can be found that the second fitting function:
where r is the slope of the axial ratio of precipitation particles, where the slope of the axial ratio r is related to the particle diameter, ZDRAlso related to particle diameter, r can therefore be expressed as ZDRFitting to obtain the relationship:
thus, the present invention may obtain a first fitting function and a second fitting function as well as a form factor look-up table. The process of inversion of the raindrop spectrum is explained below.
Based on the content of the foregoing embodiment, as an optional embodiment, in the method for inverting a raindrop spectrum provided by the present invention, after obtaining the first horizontal polarization reflectivity factor and the first differential reflectivity factor observed by the dual-polarization radar, the corresponding target shape factor pair may be found through the shape factor lookup table.
Then, according to the first horizontal polarization reflectivity factor, a corresponding first raindrop spectrum sixth moment can be obtained by using a first fitting function, namely formula (12); further, the seventh moment of the raindrop spectrum can be obtained according to a second fitting function, that is, formula (15).
Alternatively, using equations (1) to (5), an initial raindrop spectrum of the target region may be obtained according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum, and the target shape factor pair.
After the initial raindrop spectrum is obtained, calculating a second horizontal polarization reflectivity factor corresponding to the initial raindrop spectrum by referring to a formula (6); further, according to the second horizontally polarized reflectivity factor, the corresponding sixth moment of the second raindrop spectrum can be obtained by using the first fitting function, i.e. formula (12).
Under the condition that the number density proportion of different particle diameters is accurate, a number density correction factor can be determined according to the ratio of the sixth moment of the first raindrop spectrum to the sixth moment of the second raindrop spectrum; and finally, taking the product of the number density correction factor and the initial raindrop spectrum as a final target raindrop spectrum.
According to the raindrop spectrum inversion method provided by the invention, the raindrop spectrum inversion is carried out through two stages of parameter acquisition and raindrop spectrum inversion, after the initial raindrop spectrum is obtained, the initial raindrop spectrum is corrected according to the number density correction factor to obtain the target raindrop spectrum, and the accuracy of the raindrop spectrum inversion is further improved.
Optionally, the method provided by the invention further verifies the advantages of the method provided by the invention by calculating the drop spectrum parameters by using the target raindrop spectrum acquired by the raindrop spectrum inversion.
Specifically, the correlated polarization radar parameter Z may be calculated by combining the raindrop spectrum data with the polarization radar parameter calculation formulas, i.e., formulas (6) to (9)H、ZDRAnd then, the raindrop spectrum can be inverted by using the method, and the target raindrop spectrum obtained by inversion is used for calculating the raindrop spectrum parameters: mass weighted mean diameter DmAnd normalizing order moment parameter NwAnd a polarization radar parameter ZH、ZDRAnd KDPAnd comparing the parameters with corresponding parameters calculated by the observed raindrop spectrum data. The significance of the test is that the feasibility of the method provided by the invention is verified on the basis of eliminating the observation error of the polarization radar parameter.
Fig. 4 is a schematic diagram of a simulation experiment result provided by the present invention, fig. 5 is a schematic diagram of a simulation experiment result provided by the present invention, fig. 6 is a schematic diagram of a simulation experiment result provided by the present invention, fig. 7 is a schematic diagram of a simulation experiment result provided by the present invention, and fig. 8 is a schematic diagram of a simulation experiment result provided by the present invention. As shown in fig. 4 to 8, the horizontal axis in the drawings represents a calculated value using observed raindrop spectrum data, with a DSD suffix as a label, and the vertical axis represents a calculated value using inverted raindrop spectrum data, with a PR suffix as a label. Wherein, the calculation formula of the related parameters is as follows:
wherein the content of the first and second substances,
representing the real part of the forward scattering function,
indicating the liquid water density and W the liquid water content. Taking a parameter calculated according to an observed raindrop spectrum as a true value, normalizing a relative error (NB) by using a Correlation Coefficient (CC), and normalizing an absolute error (NE) to evaluate a result, wherein the expression of each evaluation parameter is as follows:
wherein E isiRepresenting a parameter calculated from the inverted raindrop spectrum, OiRepresenting the parameters calculated from the observed raindrop spectrum, and the upper line "-" indicates taking the average.
According to the simulation experiment result, the parameters calculated according to the inversion raindrop spectrum data are closer to the result calculated by utilizing the observation raindrop spectrum, the CC is over 0.9, the correlation is very high, the NB is (-3%, 3%), the average deviation is very small, the NE is less than 9%, and the absolute deviation is very small, so that the inversion result is close to the observation condition, and the method is reasonable and feasible.
Fig. 9 is a schematic structural diagram of a raindrop spectrum inversion apparatus provided in the present invention, and as shown in fig. 9, the raindrop spectrum inversion apparatus includes: a radar parameter obtaining module 901, a raindrop spectrum parameter obtaining module 902, and an initial raindrop spectrum obtaining module 903.
A radar parameter obtaining module 901, configured to obtain a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area;
a raindrop spectrum parameter obtaining module 902, configured to determine a first raindrop spectrum sixth order moment, a raindrop spectrum seventh order moment, and a target shape factor pair based on the first horizontal polarization reflectivity factor and the first differential reflectivity factor;
an initial raindrop spectrum obtaining module 903, configured to obtain an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the first raindrop spectrum sixth-order moment, the raindrop spectrum seventh-order moment, and the target shape factor pair.
According to the raindrop spectrum inversion device, the six-order moment, the seven-order moment and the shape factor pair of the raindrop spectrum are obtained by utilizing the horizontal polarization reflectivity factor and the differential reflectivity factor, the initial raindrop spectrum of the target area is further obtained by utilizing the pre-established raindrop spectrum model, the influence of the error of the differential propagation phase shift rate on the raindrop spectrum inversion is avoided, and the raindrop spectrum inversion accuracy is improved.
It should be noted that, when the raindrop spectrum inversion apparatus provided in the embodiment of the present invention is specifically operated, the raindrop spectrum inversion method described in any of the above embodiments may be executed, and details of this embodiment are not described herein.
Fig. 10 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 10, the electronic device may include: a processor (processor) 1010, a communication Interface (Communications Interface) 1020, a memory (memory) 1030, and a communication bus 1040, wherein the processor 1010, the communication Interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. The processor 1010 may invoke logic instructions in the memory 1030 to perform a method of rain drop spectrum inversion, the method comprising: acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area; determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor; and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
Furthermore, the logic instructions in the memory 1030 can be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform a method for inversion of a raindrop spectrum provided by the above methods, the method comprising: acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area; determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor; and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the method for inverting a raindrop spectrum provided in the above embodiments, the method including: acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area; determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor; and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A raindrop spectrum inversion method, comprising:
acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area;
determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor;
and acquiring an initial raindrop spectrum of the target area by using a pre-established raindrop spectrum model according to the sixth moment of the first raindrop spectrum, the seventh moment of the raindrop spectrum and the target shape factor pair.
2. The raindrop spectrum inversion method of claim 1, wherein determining a first raindrop spectrum sixth order moment, raindrop spectrum seventh order moment, and target shape factor pair based on the first horizontally polarized reflectance factor and the first differential reflectance factor comprises:
acquiring the target form factor pair from a pre-established form factor lookup table according to the numerical values of the first horizontal polarization reflectivity factor and the first differential reflectivity factor;
acquiring the sixth moment of the first raindrop spectrum by utilizing a pre-established first fitting function according to the first horizontal polarization reflectivity factor;
and determining the seventh moment of the raindrop spectrum by utilizing a pre-established second fitting function according to the sixth moment of the first raindrop spectrum and the first differential reflectivity factor.
3. The raindrop spectrum inversion method according to claim 2, further comprising, after obtaining an initial raindrop spectrum of the target region using a pre-established raindrop spectrum model according to the first raindrop spectrum sixth order moment, the raindrop spectrum seventh order moment and the target shape factor pair, the method further comprising:
acquiring a second horizontal polarization reflectivity factor by utilizing a polarization radar parameter calculation formula according to the initial raindrop spectrum;
according to the second horizontal polarization reflectivity factor, acquiring a second raindrop spectrum sixth moment corresponding to the initial raindrop spectrum by using the first fitting function;
determining a number density correction factor according to the ratio of the sixth moment of the first raindrop spectrum to the sixth moment of the second raindrop spectrum;
and correcting the initial raindrop spectrum by using the number density correction factor to obtain a target raindrop spectrum.
4. The raindrop spectrum inversion method according to claim 2, further comprising, before obtaining the target shape factor pair from a pre-established shape factor lookup table according to the values of the first horizontally polarized reflectance factor and the first differential reflectance factor:
acquiring a raindrop spectrum observation data set of the target area;
acquiring a group of inversion parameters corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set; each set of inversion parameters includes: a first shape factor pair, a third horizontally polarized reflectance factor, and a third differential reflectance factor;
constructing an inversion parameter data set according to each group of inversion parameters;
dividing the inversion parameter data set into different inversion parameter subsets according to the numerical values of a third horizontal polarization reflectivity factor and a third differential reflectivity factor in each set of inversion parameters;
and acquiring a second shape factor pair corresponding to any inversion parameter subset to establish the shape factor lookup table.
5. The raindrop spectrum inversion method according to claim 4, wherein the obtaining a second shape factor pair corresponding to any one of the inversion parameter subsets to establish the shape factor lookup table comprises:
acquiring the number of sets of inversion parameters in any inversion parameter subset;
and under the condition that the group number is greater than or equal to a preset threshold value, acquiring a second shape factor pair corresponding to any inversion parameter subset according to the probability distribution of the first shape factor pair in any inversion parameter subset so as to establish the shape factor lookup table.
6. The raindrop spectrum inversion method according to claim 5, wherein in a case where the number of sets is less than a preset threshold, the method further comprises:
and acquiring a shape factor pair default value corresponding to the inversion parameter data set according to the probability distribution of the first shape factor pair in the inversion parameter data set so as to establish the shape factor lookup table.
7. The raindrop spectrum inversion method according to claim 4, wherein the obtaining a set of inversion parameters corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set includes:
calculating a third horizontal polarized reflectivity factor and a third differential reflectivity factor corresponding to each raindrop spectrum observation data by using a polarized radar parameter calculation formula according to the raindrop spectrum observation data set;
and acquiring a first shape factor pair corresponding to each raindrop spectrum observation data by using the raindrop spectrum model according to the raindrop spectrum observation data set.
8. The raindrop spectrum inversion method according to claim 4, before obtaining the first raindrop spectrum sixth moment by using a pre-established fitting function according to the first horizontally polarized reflectivity factor, further comprising:
determining a third raindrop spectrum sixth order moment and a third raindrop spectrum seventh order moment corresponding to any raindrop spectrum observation data according to the raindrop spectrum observation data set;
determining the first fitting function according to a fitting relation between a third raindrop spectrum sixth moment corresponding to each raindrop spectrum observation data and a third horizontal polarization reflectivity factor;
and determining the second fitting function according to the fitting relation between the sixth moment of the third raindrop spectrum and the seventh moment of the third raindrop spectrum.
9. A raindrop spectrum inversion apparatus, comprising:
the radar parameter acquisition module is used for acquiring a first horizontal polarization reflectivity factor and a first differential reflectivity factor; the first horizontally polarized reflectivity factor and the first differential reflectivity factor are obtained from dual polarization radar observations of a target area;
a raindrop spectrum parameter obtaining module, configured to determine a first raindrop spectrum sixth order moment, a raindrop spectrum seventh order moment, and a target shape factor pair based on the first horizontal polarization reflectivity factor and the first differential reflectivity factor;
and the initial raindrop spectrum acquisition module is used for acquiring an initial raindrop spectrum of the target area by utilizing a pre-established raindrop spectrum model according to the first raindrop spectrum sixth moment, the raindrop spectrum seventh moment and the target shape factor pair.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the raindrop spectrum inversion method according to any one of claims 1 to 7 when executing the computer program.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104316930A (en) * | 2014-10-29 | 2015-01-28 | 安徽四创电子股份有限公司 | Raininess estimation method based on dual polarization Doppler weather radar detection |
| CN106644104A (en) * | 2016-10-13 | 2017-05-10 | 哈尔滨工业大学 | Phase screen modeling method for discrete raindrop media based on spectral inversion method |
| CN108415019A (en) * | 2017-12-29 | 2018-08-17 | 南京信息工程大学 | A kind of production method that experiment measures precipitation particles group model |
| CN109444893A (en) * | 2018-11-14 | 2019-03-08 | 中国气象科学研究院 | Phase identification product pattern splicing method and device based on dual polarization radar net |
| CN109597038A (en) * | 2018-12-12 | 2019-04-09 | 北京无线电测量研究所 | A kind of the radar reflectivity factor correction method and system of dual polarization radar |
| CN109633783A (en) * | 2018-11-14 | 2019-04-16 | 中国气象科学研究院 | Parameter pattern splicing method and device based on dual polarization radar net |
| CN110082842A (en) * | 2019-05-24 | 2019-08-02 | 北京敏视达雷达有限公司 | A kind of precipitation estimation method and device |
| CN110488393A (en) * | 2019-09-24 | 2019-11-22 | 中国科学院大气物理研究所 | X-band dual-polarization radar measurement method and system |
| CN113960606A (en) * | 2021-10-19 | 2022-01-21 | 中国气象科学研究院 | Application method of comprehensive quality index in combined radar and automatic station rainfall estimation |
-
2022
- 2022-03-28 CN CN202210308972.1A patent/CN114417264B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104316930A (en) * | 2014-10-29 | 2015-01-28 | 安徽四创电子股份有限公司 | Raininess estimation method based on dual polarization Doppler weather radar detection |
| CN106644104A (en) * | 2016-10-13 | 2017-05-10 | 哈尔滨工业大学 | Phase screen modeling method for discrete raindrop media based on spectral inversion method |
| CN108415019A (en) * | 2017-12-29 | 2018-08-17 | 南京信息工程大学 | A kind of production method that experiment measures precipitation particles group model |
| CN109444893A (en) * | 2018-11-14 | 2019-03-08 | 中国气象科学研究院 | Phase identification product pattern splicing method and device based on dual polarization radar net |
| CN109633783A (en) * | 2018-11-14 | 2019-04-16 | 中国气象科学研究院 | Parameter pattern splicing method and device based on dual polarization radar net |
| CN109597038A (en) * | 2018-12-12 | 2019-04-09 | 北京无线电测量研究所 | A kind of the radar reflectivity factor correction method and system of dual polarization radar |
| CN110082842A (en) * | 2019-05-24 | 2019-08-02 | 北京敏视达雷达有限公司 | A kind of precipitation estimation method and device |
| CN110488393A (en) * | 2019-09-24 | 2019-11-22 | 中国科学院大气物理研究所 | X-band dual-polarization radar measurement method and system |
| CN113960606A (en) * | 2021-10-19 | 2022-01-21 | 中国气象科学研究院 | Application method of comprehensive quality index in combined radar and automatic station rainfall estimation |
Non-Patent Citations (10)
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|---|---|
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