CN113406644B - Weather radar data quality control method, device and equipment - Google Patents
Weather radar data quality control method, device and equipment Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a weather radar data processing method, a device and equipment, wherein the method comprises the following steps: acquiring dual-polarization radar data; processing the dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result; determining a first initial radar data processing model, taking double-polarization radar data at a first moment as input, taking a double-polarization radar marking result at the first moment as output, and training the first initial weather data processing model to obtain a double-polarization radar data processing model; and acquiring real-time Doppler radar data, and processing the real-time Doppler radar data according to the dual-polarization radar data processing model to acquire a Doppler radar real-time identification result. According to the technical scheme, the recognition effect on the clutter can be improved, the precipitation echo and the clutter can be accurately distinguished, and the misjudgment rate of the precipitation echo is reduced.
Description
Technical Field
The disclosure relates to the field of atmosphere detection and atmosphere remote sensing, in particular to a weather radar data quality control method, device and equipment.
Background
Since the birth of radar, people have begun to use it for precipitation detection and measurement, and weather radars with wider applications include doppler radars and double polarization radars. Compared with a Doppler radar, the double-polarization radar data acquired by the double-polarization radar has more measurement information (characteristic parameters such as differential reflectivity, differential phase, correlation coefficient and the like), can provide a plurality of polarization amounts containing raindrop spectrum information, and the polarization amounts can better express the microphysical characteristics of precipitation, so that the double-polarization radar can accurately distinguish precipitation echoes from clutter, and the accuracy of weather detection and prediction is improved. Due to the influence of the above factors, dual-polarization radar is currently the mainstream of weather radar. However, although the number of doppler radars is small compared to the number of double polarization radars, doppler radars are currently an integral part of weather prediction systems. Because the Doppler radar has low recognition rate to clutter such as ground objects, super refraction, electromagnetic interference, clear sky and the like, precipitation echoes and clutter are difficult to distinguish, and the false judgment rate of the Doppler radar to the precipitation echoes is high, so that the Doppler radar has important research significance on how to accurately recognize the clutter.
Disclosure of Invention
The embodiment of the disclosure provides a weather radar data quality control method, device and equipment.
In a first aspect, an embodiment of the present disclosure provides a weather radar data quality control method, including:
acquiring dual-polarization radar data acquired by a dual-polarization radar;
processing the dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result;
determining a first initial radar data processing model, taking double-polarization radar data at a first moment as input, taking a double-polarization radar marking result at the first moment as output, and training the first initial weather data processing model to obtain a double-polarization radar data processing model;
the method comprises the steps of acquiring real-time Doppler radar data acquired by a Doppler radar in real time, and processing the real-time Doppler radar data according to a dual-polarization radar data processing model to acquire a Doppler radar real-time identification result, wherein the distance between the Doppler radar and the dual-polarization radar is smaller than or equal to a radar distance threshold.
Further, determining a first initial radar data processing model, taking double-polarization radar data at a first moment as input, taking a double-polarization radar labeling result at the first moment as output, and training the first initial weather data processing model to obtain the double-polarization radar data processing model, wherein before the method further comprises the steps of:
Obtaining the accuracy of the labeling result of the double-polarization radar according to a double-polarization quality control inspection algorithm;
performing error investigation on the double-polarization radar labeling result with the accuracy rate smaller than or equal to the accuracy rate threshold according to an error investigation algorithm to obtain a double-polarization radar labeling result after error investigation;
determining the double-polarization radar marking result at the first moment from the double-polarization radar marking result after error processing and the double-polarization radar marking result with the accuracy greater than the accuracy threshold.
Further, before acquiring the real-time doppler radar data acquired by the doppler radar in real time and processing the real-time doppler radar data according to the dual-polarization radar data processing model to acquire the real-time doppler radar recognition result, the method further comprises:
processing the double-polarization radar data at the second moment according to the double-polarization radar data processing model to obtain a double-polarization radar identification result;
obtaining the similarity of the identification result of the double-polarization radar and the identification result of the double-polarization radar marking result at the second moment;
acquiring real-time Doppler radar data acquired by the Doppler radar in real time, and processing the real-time Doppler radar data according to a dual-polarization radar data processing model to acquire a Doppler radar real-time identification result, wherein the method comprises the following steps:
And when the similarity of the recognition results is greater than or equal to the similarity threshold of the recognition results, acquiring real-time Doppler radar data, and processing the real-time Doppler radar data according to the dual-polarization radar data processing model so as to acquire the real-time Doppler radar recognition results.
Further, the method further comprises:
acquiring Doppler radar data acquired by a Doppler radar;
determining a second initial radar data processing model, taking Doppler radar data at a third moment as input, training the second initial weather data processing model by taking a double-polarization radar labeling result at the third moment, and obtaining a Doppler radar data processing model;
and processing the real-time Doppler radar data according to the Doppler radar data processing model so as to obtain a target Doppler real-time weather identification result.
Further, processing the dual-polarization radar data according to the dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result, including:
acquiring cross correlation coefficient rho between horizontal polarization radar returns and vertical polarization radar returns according to dual-polarization radar data HV ；
According to ρ cor ＝ρ hv ×(1+1/10 0.1SNR ) Obtaining noise reduction cross correlation coefficient rho cor Wherein SNR is a dual-polarization radar measurement signal ratio parameter;
And obtaining a double-polarization radar labeling result according to the noise reduction cross correlation coefficient.
Further, the method further comprises:
obtaining differential reflectivity factor Z of precipitation system according to dual-polarization radar data DR ；
When the cross correlation coefficient ρ cor Above 0.9, according to
obtaining a dual-polarization radar labeling result according to the noise reduction cross correlation coefficient comprises the following steps:
and obtaining a double-polarization radar labeling result according to the differential reflectivity factor horizontal texture and the correlation coefficient horizontal texture.
Further, the method further comprises:
obtaining a horizontal polarization reflectivity factor of the precipitation system according to the dual-polarization radar data;
and filling the precipitation echo cavity according to the horizontal polarization reflectivity factor for the double-polarization radar labeling result.
Further, the method further comprises:
obtaining a horizontal polarization reflectivity factor Z of a precipitation system according to the number of the double-polarization radars, and 18dBz echo top-up ETOP of the precipitation system 18dBz 0dBz echo top-up ETOP of precipitation system 0dBz Storm monomer core-to-double polarization radar arrival slant distance r in precipitation system storm_core And a range of single to dual-polarization radar arrival observed in the precipitation system;
when the cross correlation coefficient ρ cor Less thanOr equal to 0.9 and a cross-correlation coefficient ρ cor 18dBz echo top-up ETOP of precipitation system 18dBz The horizontal polarization reflectivity factor Z of the precipitation system meets ρ cor ＜0.95∩(ETOP 18dBz > 8.0km n Z > 45 dBz), the precipitation system is determined to be hail;
when the cross correlation coefficient ρ cor Less than or equal to 0.9, and a cross-correlation coefficient ρ cor 0dBz echo top-up ETOP of precipitation system 0dBz Storm monomer core-to-double polarization radar arrival slant distance r in precipitation system storm_core And the range of the single-to-double polarization radar arrival station observed in the precipitation system satisfies ρ cor ＜0.95∩(ETOP 0dBz ＞9.0km∩range＞r storm_core ) And when the precipitation system is determined to be in nonuniform beam filling.
In a second aspect, an embodiment of the present invention provides a weather radar data quality control processing apparatus, including:
a dual-polarization radar data acquisition module configured to acquire dual-polarization radar data acquired by a dual-polarization radar;
the dual-polarization radar data processing module is configured to process dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result;
the dual-polarization model training module is configured to determine a first initial radar data processing model, takes dual-polarization radar data at a first moment as input, takes a dual-polarization radar labeling result as output, and trains the first initial weather data processing model to obtain a dual-polarization radar data processing model;
The Doppler radar data processing module is configured to acquire real-time Doppler radar data acquired by the Doppler radar in real time, and process the real-time Doppler radar data according to the dual-polarization radar data processing model so as to acquire a Doppler radar real-time identification result, wherein the distance between the Doppler radar and the dual-polarization radar is smaller than or equal to a radar distance threshold.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory, where the processor executes the computer program to implement any one of the methods of the first aspect.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
according to the method, the first initial radar data processing model is utilized to learn the dual-polarization radar data acquired by the dual-polarization radar and process the dual-polarization radar marking result acquired by the dual-polarization radar data according to the dual-polarization radar data quality control algorithm, so that the dual-polarization radar data processing model obtained after training can learn the dual-polarization radar data quality control algorithm, then the dual-polarization radar data processing model is applied to Doppler radar data acquired by the processing Doppler radar, the recognition effect of clutter such as ground objects/super-refraction clutter, electromagnetic interference clutter, noise/isolated points and clear sky echo according to the Doppler radar data can be improved, precipitation echoes and clutter can be accurately distinguished according to the Doppler radar real-time recognition result, and the misjudgment rate of the precipitation echoes according to the Doppler radar real-time recognition result is reduced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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Other features, objects and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 4 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 5 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 6 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 7 illustrates a flow chart of a weather radar data processing method according to an embodiment of the present disclosure;
FIG. 8 shows a schematic block diagram of a gas radar data processing device according to an embodiment of the present disclosure;
FIG. 9 shows a schematic block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 10 shows a schematic structural diagram of an electronic device used to implement a weather radar data method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, portions irrelevant to description of the exemplary embodiments are omitted in the drawings.
In this disclosure, it should be understood that terms such as "comprises" or "comprising," etc., are intended to indicate the presence of features, numbers, steps, acts, components, portions, or combinations thereof disclosed in this specification, and do not preclude the presence or addition of one or more other features, numbers, steps, acts, components, portions, or combinations thereof.
In addition, it should be noted that, without conflict, the embodiments of the present disclosure and features of the embodiments may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Since the birth of radar, people have begun to use it for precipitation detection and measurement, and weather radars with wider applications include doppler radars and double polarization radars. Compared with Doppler radar, the dual-polarization radar data acquired by the dual-polarization radar has more measurement information (characteristic parameters such as differential reflectivity, differential phase, correlation coefficient and the like), can provide a plurality of polarization amounts containing raindrop spectrum information, and the plurality of polarization amounts can better express the micro-physical characteristics of precipitation, so that the dual-polarization radar can accurately distinguish the phase state of a precipitation echo, namely a cloud and rain target, so as to determine the precipitation echo and non-precipitation echo. The precipitation echoes mainly comprise convection precipitation echoes, lamellar cloud precipitation echoes, typhoon precipitation echoes and the like, and the non-precipitation echoes mainly comprise ground features/super-refraction clutter, noise/isolated point clutter, electromagnetic interference clutter, sea wave echoes, clear sky echoes and the like. By 2021, 6 months, the weather radar 216 is built in China, 68 parts are arranged at the double-polarization radar upgrading sites, a weather radar service network for monitoring large, medium and small scale disastrous weather is formed, and the monitoring capability for the structural evolution of a large-scale weather system and a medium-scale weather system is improved.
Doppler radar is currently an integral part of weather prediction systems. Because the Doppler radar has low recognition rate to clutter such as ground objects, super refraction, electromagnetic interference, clear sky and the like, precipitation echoes and clutter are difficult to distinguish, and the false judgment rate of the Doppler radar to the precipitation echoes is high, so that the Doppler radar has important research significance on how to accurately recognize the clutter.
In order to solve the above problems, the present disclosure learns dual-polarization radar data acquired by dual-polarization radar by using a first initial radar data processing model and processes dual-polarization radar labeling results acquired by the dual-polarization radar data according to a dual-polarization radar data quality control algorithm, so that the dual-polarization radar data processing model obtained after training can learn the dual-polarization radar data quality control algorithm, and then applies the dual-polarization radar data processing model to Doppler radar data acquired by processing Doppler radar, thereby improving the recognition effect of clutter such as ground object/super-refraction clutter, electromagnetic interference clutter, noise/isolated point, clear sky echo and the like according to Doppler radar data, ensuring that precipitation echoes and clutter can be accurately distinguished according to Doppler radar real-time recognition results, and reducing the misjudgment rate of precipitation echoes according to Doppler radar real-time recognition results.
Details of embodiments of the present disclosure are described in detail below with reference to specific embodiments.
Fig. 1 shows a flowchart of a weather radar data processing method according to an embodiment of the present disclosure, and as shown in fig. 1, the fog visibility inversion method includes the following steps S101 to S104:
in step S101, dual-polarization radar data acquired by the dual-polarization radar is acquired.
In step S102, dual-polarization radar data is processed according to a dual-polarization radar data quality control algorithm, and a dual-polarization radar labeling result is obtained.
And determining the precipitation echo and the non-precipitation echo in the radar echo according to the double-polarization radar labeling result.
In step S103, a first initial radar data processing model is determined, dual-polarization radar data at a first moment is used as input, dual-polarization radar labeling results at the first moment are used as output, and the first initial weather data processing model is trained to obtain a dual-polarization radar data processing model.
The first initial radar data processing model may be a Linknet image semantic segmentation network model, which may include a first convolution layer of size 7*7, a pooling layer of size 3*3, 4 encoders, 4 decoders, a first lamination of size 3*3, a second convolution layer of size 3*3, and a second deconvolution layer of size 2 x 2.
In step S104, real-time doppler radar data acquired by the doppler radar in real time is acquired, and the real-time doppler radar data is processed according to the dual-polarization radar data processing model, so as to acquire a real-time doppler radar recognition result.
The method comprises the steps of determining precipitation echo and non-precipitation echo in radar echo according to Doppler radar real-time identification results.
The range of the doppler radar from the dual-polarization radar is less than or equal to the radar range threshold. Specifically, considering that weather conditions faced by weather radars with too far distance may be greatly different due to the influence of geographical factors, the weather conditions faced by the Doppler radars and the double-polarization radars can be ensured to be similar by limiting the distance between the Doppler radars and the double-polarization radars. For example, the radar distance threshold may be 200km.
According to the method, the first initial radar data processing model is utilized to learn the dual-polarization radar data acquired by the dual-polarization radar and process the dual-polarization radar marking result acquired by the dual-polarization radar data according to the dual-polarization radar data quality control algorithm, so that the dual-polarization radar data processing model obtained after training can learn the dual-polarization radar data quality control algorithm, then the dual-polarization radar data processing model is applied to Doppler radar data acquired by the processing Doppler radar, the recognition effect of clutter such as ground objects/super-refraction clutter, electromagnetic interference clutter, noise/isolated points and clear sky echo according to the Doppler radar data can be improved, precipitation echoes and clutter can be accurately distinguished according to the Doppler radar real-time recognition result, and the misjudgment rate of the precipitation echoes according to the Doppler radar real-time recognition result is reduced.
In an optional implementation manner of this embodiment, fig. 2 shows a flowchart of a weather radar data processing method according to an implementation manner of the present disclosure, as shown in fig. 2, before step S103, the weather radar data processing method may further include the following steps:
in step S105, the accuracy of the labeling result of the dual-polarization radar is obtained according to the dual-polarization quality control inspection algorithm.
In step S106, the dual-polarization radar labeling result with the accuracy rate less than or equal to the accuracy rate threshold is processed by error investigation according to the error investigation algorithm, so as to obtain the dual-polarization radar labeling result after error investigation.
In step S107, a dual-polarization radar labeling result at the first moment is determined from the dual-polarization radar labeling result after the error processing and the dual-polarization radar labeling result with the accuracy greater than the accuracy threshold.
In the alternative implementation mode, although the overall physical control effect of the dual-polarization radar labeling result is better, some poor-effect examples still exist, the examples often appear at night of 9 months in a concentrated mode, the dual-polarization radar data quality control algorithm cannot effectively identify due to the fact that the ground reverse temperature effect is close to autumn, the area of clear sky echo is large, and the poor-effect examples account for about 10% of all the dual-polarization radar labeling results. Through the steps, the double-polarization radar labeling results of which the accuracy is smaller than or equal to the accuracy threshold can be determined, and the examples are subjected to error exploration, so that the accuracy is over-closed, the loss of data which can be used for training is avoided, and the training speed is accelerated on the premise of not reducing the training reliability.
In an optional implementation manner of this embodiment, fig. 3 shows a flowchart of a weather radar data processing method according to an implementation manner of the present disclosure, as shown in fig. 3, before step S104, the weather radar data processing method may further include the following steps:
in step S108, the dual-polarized radar data at the second moment is processed according to the dual-polarized radar data processing model, so as to obtain a dual-polarized radar identification result.
Wherein the dual polarized radar data at the second time may account for 20% of the total dual polarized radar data. Correspondingly, the double-polarization radar labeling result at the second moment can also account for 20% of all the double-polarization radar labeling results.
In step S109, the similarity between the identification result of the dual-polarization radar and the identification result of the dual-polarization radar labeling result at the second moment is obtained.
In step S104, the real-time doppler radar data acquired by the doppler radar in real time is acquired, and the real-time doppler radar data is processed according to the dual-polarization radar data processing model to acquire the real-time doppler radar recognition result, which can be implemented in step S1041:
in step S1041, when the similarity of the recognition result is greater than or equal to the similarity threshold of the recognition result, real-time doppler radar data is acquired, and the real-time doppler radar data is processed according to the dual-polarization radar data processing model, so as to acquire the real-time recognition result of the doppler radar.
In the alternative implementation manner, the dual-polarization radar data at the second moment is processed by utilizing the dual-polarization radar data processing model to obtain a dual-polarization radar identification result, and the identification result similarity of the dual-polarization radar identification result and the dual-polarization radar labeling result at the second moment is obtained, wherein the identification result similarity can reflect the accuracy of the trained dual-polarization radar data processing model for identifying the precipitation echo and the non-precipitation clutter, and when the identification result similarity is greater than or equal to the identification result similarity threshold, the accuracy of the trained dual-polarization radar data processing model for identifying the precipitation echo and the non-precipitation clutter is higher, at the moment, real-time Doppler data is obtained, and the real-time Doppler radar data is processed according to the dual-polarization radar data processing model to obtain the Doppler radar real-time identification result, so that the accuracy of the Doppler radar real-time identification result for identifying the precipitation echo and the non-precipitation clutter can be ensured to be higher.
In an optional implementation manner of this embodiment, fig. 4 shows a flowchart of a weather radar data processing method according to an implementation manner of the present disclosure, and as shown in fig. 4, the weather radar data processing method may further include the following steps:
In step S110, doppler radar data acquired by the doppler radar is acquired.
In step S111, a second initial radar data processing model is determined, doppler radar data at a third moment is taken as input, a dual-polarization radar labeling result at the third moment is taken as output, and the second initial weather data processing model is trained to obtain a doppler radar data processing model.
The second initial radar data processing model can also be a Linknet image semantic segmentation network model.
In step S112, the real-time doppler radar data is processed according to the doppler radar data processing model, so as to obtain a target doppler real-time weather identification result.
In the alternative implementation manner, through utilizing the Doppler radar data acquired by the Doppler radar by the second initial radar data processing model and processing the double-polarization radar labeling result acquired by the double-polarization radar data according to the double-polarization radar data quality control algorithm, the double-polarization radar data processing model obtained after training can learn how to acquire the double-polarization radar labeling result according to the Doppler radar data, and then the Doppler radar data processing model is applied to the Doppler radar data acquired by the processing Doppler radar, so that the recognition effect of the Doppler radar real-time recognition result on ground feature/super-refraction clutter, electromagnetic interference clutter and noise/isolated point clutter is improved, and the misjudgment rate of precipitation echo according to the target Doppler radar real-time recognition result is reduced.
In an optional implementation manner of this embodiment, fig. 5 shows a flowchart of a weather radar data processing method according to an embodiment of the present disclosure, and as shown in fig. 5, step S102 in the weather radar data processing method may be implemented as the following steps:
in step S1021, a cross correlation coefficient ρ between the horizontal polarized radar returns and the vertical polarized radar returns is obtained from the dual polarized radar data HV 。
In step S1022, according to ρ cor ＝ρ hv ×(1+1/10 0.1SNR ) Obtaining noise reduction cross correlation coefficient rho cor Wherein SNR is a dual-polarization radar measurement signal ratio parameter;
in step S1023, a dual-polarization radar labeling result is obtained according to the noise reduction cross correlation coefficient.
In this alternative implementation, since the signal-to-noise ratio of the dual-polarization radar tends to be unstable, the acquired cross-correlation coefficient is susceptible to the signal-to-noise ratio and is small relative to the normal value, with a certain error. By acquiring the noise reduction cross correlation coefficient and acquiring the double-polarization radar labeling result according to the noise reduction cross correlation coefficient, misjudgment on partial precipitation echo caused by error of the cross correlation coefficient can be reduced.
In an optional implementation manner of this embodiment, fig. 6 shows a flowchart of a weather radar data processing method according to an implementation manner of the present disclosure, as shown in fig. 6, before step S1023, the weather radar data processing method may further include:
In step S113, a precipitation system is acquired from the dual-polarization radar dataDifferential reflectance factor Z of a system DR ；
In step S114, when the cross correlation coefficient ρ cor Above 0.9, according to
Wherein N is A To be an index value for identifying window azimuth, N R Is an index value of the windowed distance.
In step S1023, the dual-polarization radar labeling result is obtained according to the noise reduction cross correlation coefficient, which may be implemented by the following steps:
in step S1123, a dual-polarization radar labeling result is obtained according to the differential reflectivity factor horizontal texture and the correlation coefficient horizontal texture.
Wherein the texture ρ is horizontal according to the correlation coefficient HV Texture can distinguish between a rainfall echo and a non-rainfall echo, and specifically, the rainfall echo has uniform Texture structure and a correlation coefficient horizontal Texture rho HV Texture is small, but the Texture of non-rainfall echo is rough, and its correlation coefficient is horizontal Texture ρ HV The value of_texture is large. Thereafter, the texture Z may be horizontally textured according to the differential reflectivity factor DR Texture filters residual clutter.
In this alternative implementation, the texture ρ is horizontally textured by a number of relationships HV Texture and differential reflectance factor horizontal Texture Z DR And (3) identifying the precipitation echo and the non-precipitation echo by the Texture, so that a double-polarization radar marking result is obtained, and the effective identification rate of the precipitation echo and the non-precipitation echo can be improved.
In an optional implementation manner of this embodiment, fig. 7 shows a flowchart of a weather radar data processing method according to an implementation manner of the present disclosure, as shown in fig. 7, before step S103, the weather radar data processing method may further include the following steps:
in step S115, a horizontally polarized reflectivity factor of the precipitation system is acquired from the dual polarized radar data.
In step S116, the precipitation echo cavity is filled up according to the horizontal polarization reflectivity factor for the dual-polarization radar labeling result.
And when the precipitation echo cavity is filled according to the horizontal polarization reflectivity factor to the double-polarization radar labeling result, a median method can be adopted. For example, in a window having an echo cavity point as the center 9×9, if the number of effective echoes is 70% or more of the total number of windows, the average value of the horizontal polarization reflectance factors of the effective echoes in the 9×9 window may be used instead of the value of the horizontal polarization reflectance factor of the echo cavity point, and the unit of the horizontal polarization reflectance factor is (mm 6/m 3). Specifically, the value of the reflectivity factor dBz in the 9×9 window is converted into (mm 6/m 3) and then averaged, and finally the averaged (mm 6/m 3) value is converted into the value of the reflectivity factor dBz.
Since the correlation coefficient of most precipitation echoes is larger than 0.95, and the correlation coefficient of few precipitation echoes is smaller than 0.7, some precipitation echo points may be misjudged as non-precipitation echoes to form precipitation echo cavities.
In the alternative implementation mode, the horizontal polarization reflectivity factor of the precipitation system is obtained according to the dual-polarization radar data, and the precipitation echo cavity is filled according to the horizontal polarization reflectivity factor to the dual-polarization radar labeling result, so that the probability of forming the precipitation echo cavity caused by misjudgment of a precipitation echo point as a non-precipitation echo can be reduced, and the effective recognition rate of the precipitation echo and the non-precipitation echo is improved.
In an optional implementation manner of this embodiment, the weather radar data processing method may further include the following steps:
obtaining horizontal polarization reflectivity factor Z of precipitation system according to dual-polarization radar data and 18dBz echo top-up ETOP of precipitation system 18dBz 0dBz echo top-up ETOP of precipitation system 0dBz Storm monomer core-to-double polarization radar arrival slant distance r in precipitation system storm_core And a range of single to dual polarization radar arrival observed in the precipitation system.
When the cross correlation coefficient ρ cor Less than or equal to 0.9 and a cross-correlation coefficient ρ cor 18dBz echo top-up ETOP of precipitation system 18dBz The horizontal polarization reflectivity factor Z of the precipitation system meets ρ cor ＜0.95∩(ETOP 18dBz > 8.0km ≡z > 45 dBz), the precipitation system is determined to be hail.
When the cross correlation coefficient ρ cor Less than or equal to 0.9, and a cross-correlation coefficient ρ cor 0dBz echo top-up ETOP of precipitation system 0dBz Storm monomer core-to-double polarization radar arrival slant distance r in precipitation system storm_core And the range of the single-to-double polarization radar arrival station observed in the precipitation system satisfies ρ cor ＜0.95∩(ETOP 0dBz ＞9.0km∩range＞r storm_core ) And when the precipitation system is determined to be in nonuniform beam filling.
Among the radar echoes, the correlation coefficient value of the water echo is large, more than 0.95, and the correlation coefficient of the non-precipitation echo is small, less than 0.7. When the correlation coefficient of precipitation echoes is less than 0.95 or even lower, the possibility of non-uniform beam filling in the observation process of hail, convection monomers and ice-water mixtures is considered to be high. In a pulse period, when the decrease of the correlation coefficient value is accompanied by a larger gradient, or the cross-correlation coefficient ρ is caused by gradient change HV This phenomenon is called non-uniform beam filling. When the resolution of the horizontal and vertical beams of the dual-polarization radar is 1 DEG, in the process of convective precipitation observation, if hail or a convective monomer exists in the beam irradiation body and the convective monomer is not filled with the 1 DEG beam, nonuniform beam filling easily occurs, and the farther the distance is, the more obvious the nonuniform beam filling phenomenon is along with the widening action of the radar beam, the cross correlation coefficient rho is HV 。
In this alternative implementation, hail, convective monomer and non-uniform beam filling typically occur during strong convective precipitation with higher echo intensities and echo peaks. When the correlation coefficient in one distance library is smaller than 0.95, the reflectivity factor value and echo top ETOP (18 dBz) and ETOP (0 dBz) values corresponding to the distance library are checked. When the correlation coefficient in the distance library is smaller than 0.95, the reflectivity factor value is higher than 45dBz, and the 18dBz echo top value is higher than 8km, the precipitation system is identified as hail. When high reflectivity factor values (Z >45 dBz) continuously appear in the radial direction and the length exceeds 1km, the precipitation system is considered to be a storm monomer core, and when the echo top of 0dBz is higher than 9km at a position far away from the storm monomer core, the precipitation system is identified as nonuniform beam filling. Thereby improving the identification accuracy of hail and non-uniform beam filling.
The following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure.
Fig. 8 shows a schematic block diagram of a weather radar data processing device according to an embodiment of the present disclosure. The air radar data processing device may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 8, the air radar data processing device includes:
The dual polarization radar data acquisition module 201 is configured to acquire dual polarization radar data acquired by the dual polarization radar.
The dual-polarization radar data processing module 202 is configured to process dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result;
the dual-polarization model training module 203 is configured to determine a first initial radar data processing model, take dual-polarization radar data at a first moment as input, take a dual-polarization radar labeling result at the first moment as output, and train the first initial weather data processing model to obtain a dual-polarization radar data processing model.
The doppler radar data processing module 204 is configured to acquire real-time doppler radar data acquired by the doppler radar in real time, and process the real-time doppler radar data according to the dual-polarization radar data processing model, so as to acquire a real-time doppler radar recognition result, wherein the distance between the doppler radar and the dual-polarization radar is less than or equal to a radar distance threshold.
According to the technical scheme provided by the embodiment of the disclosure, the first initial radar data processing model is utilized to learn dual-polarization radar data acquired by the dual-polarization radar and the dual-polarization radar labeling result acquired by processing the dual-polarization radar data according to the dual-polarization radar data quality control algorithm, so that the dual-polarization radar data processing model obtained after training can learn the dual-polarization radar data quality control algorithm, and then the dual-polarization radar data processing model is applied to Doppler radar data acquired by processing Doppler radar, the recognition effect of clutter such as ground objects/super-refraction clutter, electromagnetic interference clutter, noise/isolated points and clear sky echoes according to the Doppler radar data can be improved, the precipitation echoes and the clutter can be accurately distinguished according to the Doppler radar real-time recognition result, and the misjudgment rate of the precipitation echoes according to the Doppler radar real-time recognition result is reduced.
The present disclosure also discloses an electronic device, fig. 9 shows a schematic block diagram of the electronic device according to an embodiment of the present disclosure, and as shown in fig. 9, the electronic device 300 includes a memory 301 and a processor 302; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory 301 is used to store one or more computer instructions that are executed by the processor 302 to implement any of the methods of the disclosed embodiments.
Fig. 10 shows a schematic structural diagram of an electronic device used to implement a weather radar data method according to an embodiment of the present disclosure.
As shown in fig. 10, the electronic device 400 includes a processing unit 401, which may be implemented as a processing unit CPU, GPU, FPGA, NPU or the like. The processing unit 401 may execute various processes in the embodiments of any of the above methods of the present disclosure according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for the operation of the electronic device 400 are also stored. The processing unit 401, ROM402, and RAM403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output portion 407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage section 408 including a hard disk or the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. The drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.
In particular, according to embodiments of the present disclosure, any of the methods described above with reference to embodiments of the present disclosure may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing any of the methods of embodiments of the present disclosure. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 409 and/or installed from the removable medium 411.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software, or may be implemented by hardware. The units or modules described may also be provided in a processor, the names of which in some cases do not constitute a limitation of the unit or module itself.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus described in the above embodiment; or may be a computer-readable storage medium, alone, that is not assembled into a device. The computer-readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention referred to in this disclosure is not limited to the specific combination of features described above, but encompasses other embodiments in which any combination of features described above or their equivalents is contemplated without departing from the inventive concepts described. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Claims (10)
1. A method for processing weather radar data, comprising:
Acquiring dual-polarization radar data acquired by a dual-polarization radar;
processing the dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result, wherein precipitation echo and non-precipitation echo in a radar echo can be determined according to the dual-polarization radar labeling result;
determining a first initial radar data processing model, taking dual-polarization radar data at a first moment as input, taking a dual-polarization radar labeling result at the first moment as output, and training the first initial radar data processing model to obtain a dual-polarization radar data processing model, wherein the first initial radar data processing model is a Linknet image semantic segmentation network model, and the Linknet image semantic segmentation network model comprises a first convolution layer with a size of 7*7, a pooling layer with a size of 3*3, 4 encoders, 4 decoders, a first deconvolution layer with a size of 3*3, a second convolution layer with a size of 3*3 and a second deconvolution layer with a size of 2 x 2;
the method comprises the steps of acquiring real-time Doppler radar data acquired by a Doppler radar in real time, and processing the real-time Doppler radar data according to a dual-polarization radar data processing model to acquire a Doppler radar real-time identification result, wherein the distance between the Doppler radar and the dual-polarization radar is smaller than or equal to a radar distance threshold value, and precipitation echo and non-precipitation echo in a radar echo can be determined according to the Doppler radar real-time identification result.
2. The weather radar data processing method according to claim 1, wherein the determining a first initial radar data processing model, taking dual-polarized radar data at a first moment as input, taking dual-polarized radar labeling results at the first moment as output, training the first initial radar data processing model, and before obtaining the dual-polarized radar data processing model, the method further comprises:
acquiring the accuracy of the labeling result of the dual-polarization radar according to a dual-polarization data quality control algorithm;
performing error investigation on the double-polarization radar labeling result with the accuracy rate smaller than or equal to the accuracy rate threshold according to an error investigation algorithm to obtain a double-polarization radar labeling result after error investigation;
and determining the double-polarization radar marking result at the first moment from the double-polarization radar marking result after the error processing and the double-polarization radar marking result with the accuracy greater than the accuracy threshold.
3. The weather radar data processing method according to claim 1, wherein before the acquiring the real-time doppler radar data acquired by the doppler radar in real time and processing the real-time doppler radar data according to the dual-polarization radar data processing model to acquire the real-time recognition result of the doppler radar, the method further comprises:
Processing the double-polarization radar data at the second moment according to the double-polarization radar data processing model so as to obtain a double-polarization radar identification result;
obtaining the similarity of the identification result of the double-polarization radar and the identification result of the double-polarization radar marking result at the second moment;
the acquiring the real-time Doppler radar data acquired by the Doppler radar in real time, and processing the real-time Doppler radar data according to the dual-polarization radar data processing model to acquire the Doppler radar real-time identification result comprises the following steps:
and when the similarity of the recognition results is greater than or equal to a similarity threshold of the recognition results, acquiring the real-time Doppler radar data, and processing the real-time Doppler radar data according to the dual-polarization radar data processing model so as to acquire the real-time Doppler radar recognition results.
4. A weather radar data processing method according to any one of claims 1-3, wherein the method further comprises:
acquiring doppler radar data acquired by the doppler radar;
determining a second initial radar data processing model, taking Doppler radar data at a third moment as input, taking a double-polarization radar labeling result at the third moment as output, and training the second initial radar data processing model to obtain a Doppler radar data processing model;
And processing the real-time Doppler radar data according to the Doppler radar data processing model so as to obtain a target Doppler real-time weather identification result.
5. A weather radar data processing method according to any one of claims 1-3, wherein the processing the dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result comprises:
acquiring a cross correlation coefficient rho between a horizontal polarization radar return and a vertical polarization radar return according to the dual-polarization radar data HV ；
According to ρ cor ＝ρ HV ×(1+1/10 0.1SNR ) Obtaining noise reduction cross correlation coefficient rho cor Wherein SNR is a dual-polarization radar measurement signal ratio parameter;
and obtaining the dual-polarization radar labeling result according to the noise reduction cross correlation coefficient.
6. The weather radar data processing method of claim 5, wherein the method further comprises:
obtaining differential reflectivity factor Z of the precipitation system according to the dual-polarization radar data DR ；
When the noise reduction cross correlation coefficient ρ cor Above 0.9, according to
the obtaining the dual-polarization radar labeling result according to the noise reduction cross correlation coefficient comprises the following steps:
and obtaining the dual-polarization radar labeling result according to the differential reflectivity factor horizontal texture and the correlation coefficient horizontal texture.
7. The weather radar data processing method of claim 6, wherein the method further comprises:
acquiring a horizontal polarization reflectivity factor of a precipitation system according to the dual-polarization radar data;
and filling the precipitation echo cavity according to the horizontal polarization reflectivity factor and the double-polarization radar labeling result.
8. The weather radar data processing method of claim 6, wherein the method further comprises:
acquiring a horizontal polarization reflectivity factor Z of the precipitation system according to the dual-polarization radar data, and raising an ETOP of 18dBz echo of the precipitation system 18dBz 0dBz echo top-up ETOP of precipitation system 0dBz The slope distance r from storm monomer core to double-polarization radar station in precipitation system storm_core And a range of monomer observed in the precipitation system to the dual-polarization radar station;
When the noise reduction cross correlation coefficient ρ cor Less than or equal to 0.9, and the noise reduction cross correlation coefficient ρ cor 18dBz echo top-up ETOP of the precipitation system 18dBz The horizontal polarization reflectivity factor Z of the precipitation system satisfies ρ cor ＜0.95∩(ETOP 18dBz > 8.0km n Z > 45 dBz), determining that the precipitation system is hail;
when the noise reduction cross correlation coefficient ρ cor Less than or equal to 0.9, and the noise reduction cross correlation coefficient ρ cor 0dBz echo top-up ETOP of precipitation system 0dBz The slope distance r from storm monomer core to double-polarization radar station in precipitation system storm_core And the range of the monomer observed in the precipitation system to the dual-polarization radar station satisfies the following conditionsρ cor ＜0.95∩(ETOP 0dBz ＞9.0km∩range＞r storm_core ) And determining that the precipitation system is a non-uniform beam filling.
9. A weather radar data processing apparatus, comprising:
a dual-polarization radar data acquisition module configured to acquire dual-polarization radar data acquired by a dual-polarization radar;
the dual-polarization radar data processing module is configured to process the dual-polarization radar data according to a dual-polarization radar data quality control algorithm to obtain a dual-polarization radar labeling result, wherein precipitation echo and non-precipitation echo in a radar echo can be determined according to the dual-polarization radar labeling result;
The dual-polarization model training module is configured to determine a first initial radar data processing model, takes dual-polarization radar data at a first moment as input, takes a dual-polarization radar labeling result at the first moment as output, trains the first initial radar data processing model to obtain the dual-polarization radar data processing model, wherein the first initial radar data processing model is a Linknet image semantic segmentation network model, and the Linknet image semantic segmentation network model comprises a first convolution layer with the size of 7*7, a pooling layer with the size of 3*3, 4 encoders, 4 decoders, a first deconvolution layer with the size of 3*3, a second convolution layer with the size of 3*3 and a second deconvolution layer with the size of 2 x 2;
the Doppler radar data processing module is configured to acquire real-time Doppler radar data acquired by the Doppler radar in real time, and process the real-time Doppler radar data according to the dual-polarization radar data processing model so as to acquire a Doppler radar real-time identification result, wherein the distance between the Doppler radar and the dual-polarization radar is smaller than or equal to a radar distance threshold value, and precipitation echo and non-precipitation echo in a radar echo can be determined according to the Doppler radar real-time identification result.
10. An electronic device comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the method of any of claims 1-8.
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