Detection method and device for melting layer in cloud, electronic equipment and storage medium

Abstract

The invention provides a method and device for detecting a melting layer in cloud, electronic equipment and a storage medium, and belongs to the technical field of remote sensing image processing, and the method comprises the steps: obtaining a melting layer probability value, judged in each distance library, between each radar observation profile of a to-be-observed region and a profile template; and calculating the melting layer probability values corresponding to all the distance libraries in each radar observation profile, determining whether the melting layer in the cloud exists in the to-be-observed area, and outputting the height of the melting layer in the cloud. According to the method and the device for detecting the melting layer in the cloud, the electronic equipment and the storage medium provided by the invention, the non-dimensionalized radar observation profile including the reflectivity factor template and the Doppler velocity template is used for matching the observed radar observation profile, so that the probability that the melting layer appears in each distance library is calculated; and empirical parameters are not needed, and a temperature profile or a 0 DEG C layer height is not needed, so that the independence of radar identification of a melting layer and the reliability of actual operation are enhanced. The calculation mode is simple and the result is visual.

Description

Technical Field

[0001] The present invention relates to the technical field of remote sensing image processing, and in particular to a method, device, electronic equipment and storage medium for detecting a melting layer in a cloud. Background Art

[0002] The cloud melt layer is a horizontal distribution zone formed by the melting of ice particles such as ice crystals, snow, and graupel in the layered clouds after falling below the 0°C layer. The melting of hydrometeors in the clouds will lead to changes in their own physical properties such as dielectric properties and falling speed. For example, the increase in dielectric constant after the melting of ice particles will lead to an increase in radar reflectivity factor; the increase in density of ice particles after melting will lead to an increase in falling speed, resulting in a decrease in the number of particles per unit volume. Accurately identifying the melt layer can effectively distinguish between layered clouds and convective clouds, and can distinguish the phase state of precipitation particles in the clouds, and can also reduce the error of quantitative estimation of rainfall.

[0003] At present, various radar methods for identifying the melting layer require the input of the vertical temperature profile and a variety of radar observation parameters. Based on the image features of the melting layer reflected in the radar observation parameter profile, the thresholds of the temperature and various radar observation parameters and their vertical change rates are set to realize the identification of the melting layer.

[0004] All existing radar algorithms for identifying the melt layer need to first input the vertical temperature profile or the height of the 0°C layer from the outside through data other than the radar, and need to set the thresholds of various variables based on experience. However, relying on the input of external data such as the temperature profile not only greatly reduces the independence of radar observations, but also increases the construction cost and operational uncertainty of the observation system. In addition, the use of fixed thresholds to identify the melt layer will inevitably lead to great uncertainty when dealing with extreme weather in the context of climate change. Summary of the invention

[0005] The present invention provides a method, device, electronic device and storage medium for detecting a melting layer in a cloud, so as to solve the defects of the prior art in the construction cost and operation uncertainty when identifying a melting layer in a cloud, especially the great uncertainty that is bound to exist when dealing with extreme weather.

[0006] The present invention provides a method for detecting a melting layer in a cloud, comprising: Obtain multiple radar observation profiles of the area to be observed; For any target radar observation profile, interpolation processing is performed on a predetermined profile template of a melting layer in the cloud, so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile; Calculating the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; Traversing all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each of the radar observation profiles to determine whether there is a melting layer in the cloud in the area to be observed; When it is determined that the cloud melting layer exists, the height of the cloud melting layer is output.

[0007] According to a method for detecting a melting layer in a cloud provided by the present invention, the calculation of the melting layer probability value determined in each distance library between the target radar observation profile and the target profile template includes: Setting any distance library of the target radar observation profile as the target distance library; Determining a reflectivity factor matching score and a Doppler velocity matching score according to a matching result between the target radar observation profile and the target profile template in the target distance library; Calculating a melting layer probability value of the target distance library according to the reflectivity factor matching score and the Doppler velocity matching score; Resetting the next distance library as a new target distance library, and calculating the melting layer probability value associated with the new target distance library; The steps of setting the target distance library to calculating the melting layer probability value are iterated until all distance libraries on the target radar observation profile are traversed to obtain the melting layer probability value associated with each distance library.

[0008] According to a method for detecting a melting layer in a cloud provided by the present invention, determining the reflectivity factor matching score according to a matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all reflectivity factor observations collected in the target distance library; Normalizing each of the reflectivity factor observation values ​​to obtain a normalized reflectivity factor observation value; Performing matching calculation on each normalized reflectivity factor observation value and the reflectivity factor template value at the same distance on the target profile template to obtain a matching value corresponding to each normalized reflectivity factor observation value; The matching values ​​corresponding to all the normalized reflectivity factor observation values ​​are accumulated to obtain a reflectivity factor matching score corresponding to the target distance library.

[0009] According to a method for detecting a melting layer in a cloud provided by the present invention, determining the Doppler velocity matching score according to a matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all Doppler velocity observations collected in the target range library; Normalizing each of the Doppler velocity observation values ​​to obtain a normalized Doppler velocity observation value; Performing matching calculation on each of the normalized Doppler velocity observation values ​​and the Doppler velocity template value at the same distance on the target profile template to obtain a matching value corresponding to each of the normalized Doppler velocity observation values; The matching values ​​corresponding to all the normalized Doppler velocity observation values ​​are accumulated to obtain a Doppler velocity matching score corresponding to the target distance library.

[0010] According to a method for detecting a melting layer in a cloud provided by the present invention, the melting layer probability value of the target distance library is calculated according to the reflectivity factor matching score and the Doppler velocity matching score, including: The melting layer probability value is determined according to the product of the reflectivity factor matching score and the Doppler velocity matching score.

[0011] According to a method for detecting a melting layer in a cloud provided by the present invention, the profile template is determined based on the following steps: Acquire multiple historical radar observation data, and screen out typical profiles containing characteristics of a melting layer in a cloud, wherein the typical profiles include a reflectivity factor profile and a Doppler velocity profile, wherein the reflectivity factor profile includes a first typical characteristic of a reflectivity factor, and the Doppler velocity profile includes a second typical characteristic of a Doppler velocity, wherein the first typical characteristic includes at least a peak characteristic, and the second typical characteristic includes at least a mutation characteristic from small to large; Normalizing and averaging the parts of all the screened reflectivity factor profiles containing the melting layer to obtain an average reflectivity factor profile; Normalizing and averaging the parts of all the selected Doppler velocity profiles containing the melting layer to obtain an average Doppler velocity profile; The reflectivity factor average profile and the Doppler velocity average profile are respectively normalized again to obtain the profile template.

[0012] According to a method for detecting a melting layer in a cloud provided by the present invention, the profile template includes a reflectivity factor profile template and a Doppler velocity profile template in the same height sequence; the profile template of the predetermined melting layer in the cloud is interpolated so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile, including: Obtaining the distance starting point of the height sequence; Evenly distributing interpolation points in the height sequence according to the range resolution, and respectively calculating a reflectivity factor template value corresponding to each of the interpolation points on the reflectivity factor profile template, and calculating a Doppler velocity template value corresponding to each of the interpolation points on the Doppler velocity profile template; The reflectivity factor template value of each feature point in the new height sequence inserted into all interpolation points is combined to obtain a target reflectivity factor profile template; and the Doppler velocity template value of each feature point is combined to obtain a Doppler velocity profile template; The target reflectivity factor profile template and the Doppler velocity profile template associated with the new height sequence constitute the target profile template.

[0013] The present invention also provides a device for detecting a melting layer in a cloud, comprising: A radar monitoring unit, used to obtain multiple radar observation profiles of the area to be observed; A profile preprocessing unit is used to interpolate a profile template of a predetermined melting layer in a cloud for any target radar observation profile, so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile; A probability analysis unit, used to calculate the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; A melting layer judgment unit is used to traverse all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile to determine whether there is a melting layer in the cloud in the area to be observed; The judgment result output unit is used to output the height of the melting layer in the cloud when it is determined that the melting layer in the cloud exists.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for detecting a melting layer in a cloud as described above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described methods for detecting a melting layer in a cloud.

[0016] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned methods for detecting a melting layer in a cloud.

[0017] The method, device, electronic device and storage medium for detecting the melting layer in the cloud provided by the present invention use dimensionless radar observation profiles including reflectivity factor templates and Doppler velocity templates to match the observed radar observation profiles, thereby calculating the probability of the melting layer appearing in each distance library, without using empirical parameters, temperature profiles or 0°C layer heights, thereby enhancing the independence of radar identification of the melting layer and the reliability of actual operation. The calculation method is simple and the results are intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is one of the flow diagrams of the method for detecting the melting layer in the cloud provided by the present invention.

[0020] Figure 2 This is the second flow chart of the method for detecting the melting layer in the cloud provided by the present invention.

[0021] Figure 3 It is a schematic diagram of the reflectivity factor profile in the profile template provided by the present invention.

[0022] Figure 4 It is a schematic diagram of the Doppler velocity profile in the profile template provided by the present invention.

[0023] Figure 5 It is a schematic diagram of a reflectivity factor profile in a target radar observation profile provided by the present invention.

[0024] Figure 6 It is a schematic diagram of a Doppler velocity profile in a target radar observation profile provided by the present invention.

[0025] Figure 7 It is a schematic diagram of the probability distribution of a melting layer corresponding to a target radar observation profile provided by the present invention.

[0026] Figure 8 This is one of the schematic diagrams of a radar reflectivity factor profile sequence provided by the present invention.

[0027] Fig. 9 This is one of the Doppler velocity profile sequence schematic diagrams provided by the present invention.

[0028] Fig.10 This is one of the distribution diagrams of the reflectivity factor matching scores calculated using the method of the present invention.

[0029] Fig.11 This is one of the distribution diagrams of the Doppler velocity matching scores calculated using the method of the present invention.

[0030] Fig.12 This is one of the distribution diagrams of the melting layer probability calculated by the method of the present invention.

[0031] Fig.13 This is the second schematic diagram of a radar reflectivity factor profile sequence provided by the present invention.

[0032] Fig.14 This is the second schematic diagram of a Doppler velocity profile sequence provided by the present invention.

[0033] Fig.15 This is the second distribution diagram of the melting layer probability calculated by the method of the present invention.

[0034] Fig.16 This is the third schematic diagram of a radar reflectivity factor profile sequence provided by the present invention.

[0035] Fig.17 This is the third schematic diagram of a Doppler velocity profile sequence provided by the present invention.

[0036] Fig.18 This is the third distribution diagram of the melting layer probability calculated by the method of the present invention.

[0037] Fig.19 It is a schematic structural diagram of a device for detecting a melting layer in a cloud provided by the present invention.

[0038] Fig. 20 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] It should be noted that, in the description of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0041] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0042] Using precipitation radar / cloud radar to identify the melt layer in clouds has many application values, such as: (1) Differentiate between stratiform clouds and convective clouds. Stratiform clouds are usually formed by the slow horizontal uplift of the atmosphere caused by the encounter between cold and warm air masses, while convective clouds are formed by vertical convective movement triggered by unstable atmospheric conditions.

[0043] Because the positional uncertainty of the falling and melting of hydrometeor particles in convective clouds is large, it is difficult for a melting layer to have a uniform horizontal distribution characteristic like that of stratiform clouds. Therefore, the identification of the melting layer in clouds can help distinguish between stratiform clouds and convective clouds.

[0044] Strongly developed convective clouds can produce severe weather such as hail, thunderstorms, and short-term heavy precipitation, and are objects that require close attention in weather monitoring. However, some stratiform clouds have precipitation fluctuations or discontinuities in the time-height diagrams observed by vertically pointing precipitation radars / cloud radars, which can easily be misidentified as convective clouds by inexperienced forecasters or observers, resulting in false alarms. Therefore, an automatic and reliable method for detecting the melt layer in clouds can avoid such false alarms.

[0045] (2) Distinguishing the phases of precipitation particles in clouds. The melt layer in clouds generally separates the upper cold layer, which is mainly composed of ice particles, from the lower warm layer, which is mainly composed of raindrops.

[0046] By identifying the melt layer in the clouds, the dynamics of precipitation type changes can be monitored and predicted. For example, when the melt layer is monitored to descend and touch the ground, it can be judged that the ground precipitation type will change from rain to sleet or even snow.

[0047] (3) Reduce the error in quantitative estimation of rainfall. The radar reflectivity factor of precipitation radar / cloud radar is often used to quantitatively estimate rainfall. However, the "bright band" feature of the radar reflectivity factor in the melt layer in the cloud will lead to an overestimation of the rainfall rate there, thereby affecting the judgment of the subsequent rainfall intensity. By automatically identifying the melt layer in the cloud, it can help forecasters or observers eliminate or reduce the rainfall estimation error caused by the "bright band" feature in the melt layer.

[0048] Various radar methods for identifying melt layers used in the prior art generally require the input of a temperature vertical profile and a radar observation parameter profile formed by a variety of radar observation parameters. By determining the image features of the melt layer in the cloud reflected in the radar observation parameter profile, setting the thresholds of temperature and various radar observation parameters and their vertical change rates, the melt layer in the cloud can be identified.

[0049] For precipitation radars that scan at variable elevation and azimuth angles, the melting layer in the cloud is identified mainly near the 0°C layer height, for different regions and seasons, by setting empirical thresholds for the radar reflectivity factor and its vertical gradient. For dual-polarization precipitation radars, empirical thresholds can also be set for radar observation parameters such as differential reflectivity, co-polarization correlation coefficient, linear depolarization ratio, differential phase shift rate, and their gradients for comprehensive discrimination.

[0050] For vertically pointing Doppler precipitation radars or cloud radars, mainly near the 0°C layer height, for different regions and seasons, the melting layer in the cloud is identified by setting thresholds for the radar reflectivity factor (or signal-to-noise ratio) and the gradient of the Doppler velocity. For vertically pointing Doppler precipitation radars or cloud radars with dual polarization and the ability to observe the linear depolarization ratio, an empirical threshold can also be set for the linear depolarization ratio to comprehensively identify the melting layer in the cloud.

[0051] However, this approach of obtaining temperature data externally has significant limitations.

[0052] First, the real temperature vertical profile data can only be obtained by operational meteorological sounding, which only conducts observations twice a day, and the observation sites are extremely sparse, with imprecise temporal and spatial representativeness, making it difficult to fully respond to local weather or weather that changes significantly within half a day.

[0053] Secondly, although microwave radiometers can invert local vertical temperature profiles in real time, they are prone to unreliability in precipitation weather due to more interference.

[0054] Furthermore, the 0°C layer height used by some algorithms is derived from climate statistical data, which has great uncertainty in the context of climate change and is not easy to cope with the increasing number of extreme weather conditions.

[0055] Finally, in general, relying on the input of external data such as temperature profiles not only greatly reduces the independence of radar observations, but also increases the construction cost and operation uncertainty of the observation system.

[0056] In addition, in the current different radar algorithms for identifying the melt layer in clouds, the threshold settings for various variables are different, which is reasonable for certain regions and seasons. However, the characteristics targeted by these thresholds have their own inherent variability in nature. For example, the shape, size, number concentration of falling ice particles and background vertical airflow will affect the strength and vertical gradient characteristics of radar signals in the melt layer. Therefore, using a fixed threshold to identify the melt layer is bound to have great uncertainty when dealing with extreme weather in the context of climate change.

[0057] In view of the many defects of the existing technology in identifying the melting layer in the cloud, it is urgent to provide a detection method that is easier to operate and has higher accuracy.

[0058] Combine the following Figure 1-Figure 20 The method, device, electronic device and storage medium for detecting the melting layer in the cloud provided by the present invention only need to input the radar observation profile (including the profile of the radar reflectivity factor and Doppler velocity observation value at different altitudes), so as to quickly calculate and output the melting layer probability (with a value range of 0~100%), so as to achieve the purpose of more conveniently distinguishing the melting layer in the cloud.

[0059] Figure 1 FIG. 1 is one of the flow charts of the method for detecting the melting layer in the cloud provided by the present invention, such as Figure 1 As shown, including but not limited to the following steps: Step 101, obtaining a plurality of radar observation profiles of the area to be observed.

[0060] Considering that the Doppler velocity detected by the low-elevation scanning radar cannot reflect the falling conditions of the particles, although the vertical pointing radar cannot obtain the precipitation cloud monitoring results in a large horizontal range through azimuth scanning, it only needs to detect the altitude of up to 10~20km above, so it does not require high power and gain. The antenna size used can be smaller, and the servo system (the system responsible for controlling the rotation of the antenna) can be omitted. There is no need to consider the obstruction of surrounding houses and mountains, and it does not rely on special building infrastructure. Therefore, the construction cost is much lower than that of the low-elevation radar with azimuth scanning.

[0061] Therefore, the radar used by the present invention to detect the melting layer in the cloud can adopt a Doppler precipitation radar or cloud radar for vertical pointing observation, such as a Ka-band cloud radar, a K-band light rain radar, and a K-band micro precipitation profile radar.

[0062] Optionally, the present invention uses a Doppler precipitation radar or cloud radar (such as a Ka-band cloud radar, a K-band light rain radar, etc.) for vertical observation to continuously and systematically observe the designated area to be observed. These radar devices will output a set of data every fixed time period (such as 10 seconds or 60 seconds), including the radar reflectivity factor Z, the Doppler velocity V and the corresponding height sequence H at different heights (also referred to as distances in the present invention). By integrating these data according to the height sequence, a radar observation profile consisting of multiple profiles can be formed, and each radar observation profile covers complete information from the ground to the maximum detection height of the radar (usually greater than 1.05km).

[0063] Of course, in actual operation, the radar's observation parameters will be adjusted according to observation needs and weather conditions to ensure that the collected data has sufficient resolution and accuracy. At the same time, the radar equipment will be regularly maintained and calibrated to reduce errors and interference and improve data reliability.

[0064] Step 102: for any target radar observation profile, interpolation processing is performed on a profile template of a predetermined melting layer in the cloud, so that the interpolated target profile template has the same distance resolution as the target radar observation profile.

[0065] Among all the radar observation profiles obtained in step 101, the radar observation profiles collected at each moment are designated as the target radar observation profiles. The present invention will prepare a set of profile templates of the melting layer in the cloud in advance, including the radar reflectivity factor template Z of the melting layer. model , Melting layer Doppler velocity template V model And the corresponding height sequence h. These profile templates are obtained by screening a part of the typical profile containing the melting layer from a large number of radar observations, and then normalizing and averaging them.

[0066] It should be noted that before performing the matching calculation, the profile template needs to be interpolated. The purpose of interpolation is to make the profile template consistent with the target radar observation profile in terms of resolution and height range.

[0067] Specifically, the profile template can be interpolated according to the distance resolution ΔH and the maximum detection height of the target radar observation profile to generate an interpolation template that completely matches the target radar observation profile, which is called the target profile template.

[0068] The specific interpolation method used can be flexibly selected according to the actual situation, such as linear interpolation, polynomial interpolation or spline interpolation, etc. When selecting the interpolation method, it is necessary to comprehensively consider factors such as calculation efficiency, accuracy and stability to ensure that the interpolation result can meet the needs of subsequent matching calculations.

[0069] Step 103, calculating the melting layer probability value judged between the target radar observation profile and the target profile template in each distance library.

[0070] After completing the interpolation processing of the initial profile template to obtain the target profile template, we can take all the observed reflectivity factors Z and Doppler velocities V in the range of iw to i+w from the w+1th distance library along the target radar observation profile from low to high, and match them with the reflectivity factors and Doppler velocities at the corresponding heights on the target profile template.

[0071] The matching algorithm used may be a correlation coefficient method to calculate the reflectivity factor matching score Z related to the reflectivity factor and the Doppler velocity. score and Doppler velocity matching score V score , these two scores reflect the consistency between the radar observation characteristics and the typical characteristics of the melt layer.

[0072] Finally, the calculated reflectivity factor matching score Z can be used to score and Doppler velocity matching score V score The melting layer probability value S corresponding to each distance library is calculated comprehensively.

[0073] Where w is the half width of the sliding window. The specific calculation formula (1) can be expressed as: (1) in, is the number of interpolation points of the target profile template, This is the rounding operation.

[0074] For example, assuming that the distance resolution of the target radar observation profile is 200 m, the number of interpolation points when interpolating the original 1.05 km long profile template into the target profile template with a distance resolution of 200 m is 5. The half width of the sliding window calculated according to formula (1) is fix(5-1) / 2=2.

[0075] For another example, assuming that the distance resolution of the target radar observation profile is 200 m, the number of interpolation points when interpolating the original 1.05 km long profile template into the target profile template with a distance resolution of 100 m is 10. The half width of the sliding window calculated according to formula (1) is fix((10-1) / 2)=4.

[0076] Step 104, traverse all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile to determine whether there is a melting layer in the cloud in the area to be observed.

[0077] Repeat the above step 103 until the melting layer probability value corresponding to each distance bin on the target radar observation profile is calculated, then it is considered that the processing of one radar observation profile is completed, and then, in this way, each radar observation profile on the time axis is traversed once, and the melting layer probability value judged between each radar observation profile and the target profile template in each distance bin is calculated in turn. If all radar observation profiles have continuous and high melting layer probability values ​​(for example, more than 90%) within a certain height range, it can be considered that there is a melting layer in the cloud within the height range.

[0078] Step 105: When it is determined that the cloud melting layer exists, the height of the cloud melting layer is output.

[0079] Finally, when it is determined that there is a melting layer in the cloud, the height range in which there are continuous and high probability values ​​of the melting layer in a certain height range can be used as the height range where the melting layer in the cloud is located. Of course, this height range can be obtained by averaging or taking the median of the distance library with a high probability of melting layer.

[0080] The method for detecting the melting layer in the cloud provided by the present invention uses a dimensionless radar observation profile including a reflectivity factor template and a Doppler velocity template to match the observed radar observation profile, thereby calculating the probability of the melting layer appearing in each distance library, without using empirical parameters or temperature profiles or 0°C layer heights, thereby enhancing the independence of radar identification of the melting layer and the reliability of actual operation, and the calculation method is simple and the results are intuitive.

[0081] Figure 2 FIG. 2 is a flow chart of the method for detecting the melting layer in the cloud provided by the present invention. As an optional embodiment, Figure 2 As shown, the calculation of the melting layer probability value judged between the target radar observation profile and the target profile template in each distance library specifically includes: Setting any distance library of the target radar observation profile as the target distance library; Determining a reflectivity factor matching score and a Doppler velocity matching score according to a matching result between the target radar observation profile and the target profile template in the target distance library; Calculating a melting layer probability value of the target distance library according to the reflectivity factor matching score and the Doppler velocity matching score; Resetting the next distance library as a new target distance library, and calculating the melting layer probability value associated with the new target distance library; The steps of setting the target distance library to calculating the melting layer probability value are iterated until all distance libraries on the target radar observation profile are traversed to obtain the melting layer probability value associated with each distance library.

[0082] The present invention adopts a distance library iterative matching method to perform feature comparison between a target radar observation profile and the target profile template.

[0083] First, input the target radar observation profile to be analyzed. In this embodiment, the data of Ka-band cloud radar or K-band light rain radar is used as an example. The radar outputs a set of data every certain period of time (such as 10s or 60s), which characterizes the reflectivity factor Z and Doppler velocity V at different heights during the period. The number of libraries of the three variable profiles contained in the target radar observation profile is n, the distance resolution ΔH must be uniform, and the maximum detection height represented is greater than 1.05km.

[0084] In the present invention, a profile template is constructed in advance based on historically collected radar data. The profile template also includes a height sequence h, a radar reflection factor profile Z of the melting layer, and a height sequence h of the melting layer. model and the Doppler velocity profile V of the melt layer model .

[0085] It should be noted that before actual detection, the profile template needs to be interpolated in the manner described in the previous embodiment so that the target profile template obtained by the interpolation processing has the same distance resolution as the currently observed target radar observation profile, and the size of the sliding window for subsequent matching is determined.

[0086] Further, starting from the first distance library of the radar observation profile, it is set as the target distance library and prepared for matching calculation.

[0087] All reflectivity factors Z in the array from iw to i+w are processed into normalized variables Z*. Here, the normalization of a variable is calculated by processing it into a variable with a mean of 0 and a square sum of 1. For example, the normalized value Z of the reflectivity factor Z is * The calculation formula (2) can be expressed as: (2) in, is the reflectivity factor before processing, is the average value of the reflectivity factor within the range.

[0088] The normalized Z* is compared with the interpolated and normalized target profile template Z model Perform matching calculations.

[0089] As an optional embodiment, determining the reflectivity factor matching score according to the matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all reflectivity factor observations collected in the target distance library; Normalizing each of the reflectivity factor observation values ​​to obtain a normalized reflectivity factor observation value; Performing matching calculation on each normalized reflectivity factor observation value and the reflectivity factor template value at the same distance on the target profile template to obtain a matching value corresponding to each normalized reflectivity factor observation value; The matching values ​​corresponding to all the normalized reflectivity factor observation values ​​are accumulated to obtain a reflectivity factor matching score corresponding to the target distance library.

[0090] According to the records of the above embodiment, assuming that there are 5 groups of data on the target profile template after interpolation processing, then when matching the target radar observation profile with the target profile template, the 1st to 5th groups of data, 2nd to 6th groups of data, 3rd to 7th groups of data, 4th to 8th groups of data and 5th to 9th groups of data on the target radar observation profile are matched and calculated in turn with the 5 groups of values ​​of the corresponding heights on the interpolated and renormalized target profile template.

[0091] Specifically, when performing reflectivity factor matching, the formula (3) used in the calculation can be expressed as: (3) in, is the reflectivity factor matching score of the i-th distance library; w is the half width of the sliding window; is the jth normalized reflectivity factor observation value; is the reflectivity factor template value at the same distance on the target profile template.

[0092] It should be noted that if If the calculated result is less than 0, it is directly assigned to 0.

[0093] As another optional embodiment, determining the Doppler velocity matching score according to the matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all Doppler velocity observations collected in the target range library; Normalizing each of the Doppler velocity observation values ​​to obtain a normalized Doppler velocity observation value; Performing matching calculation on each of the normalized Doppler velocity observation values ​​and the Doppler velocity template value at the same distance on the target profile template to obtain a matching value corresponding to each of the normalized Doppler velocity observation values; The matching values ​​corresponding to all the normalized Doppler velocity observation values ​​are accumulated to obtain a Doppler velocity matching score corresponding to the target distance library.

[0094] The calculation logic is similar to that of the reflectivity factor matching score. The difference is that when performing the Doppler velocity matching score, it is necessary to first determine its directionality in the observation system. If the movement toward the radar is defined as a negative velocity, no processing is done; if it is defined as a positive velocity, V is multiplied by a negative sign to unify the direction.

[0095] Next, the Doppler velocities in the target range bin and the w range bins before and after it can be normalized to obtain a normalized variable V*.

[0096] Then, the normalized V* is compared with the interpolated and normalized target profile template V model Perform matching calculations.

[0097] The matching calculation method also uses the correlation coefficient method. The specific calculation method can be calculated using the following formula (4): (4) in, is the Doppler velocity matching score of the i-th range bin; w is the half width of the sliding window; is the jth normalized Doppler velocity observation; is the Doppler velocity template value at the same distance on the target profile template.

[0098] If it needs to be explained If the calculated result is less than 0, it is directly assigned to 0.

[0099] By calculation, we can obtain the matching result between the Doppler velocity on the target distance library and the target profile template of the typical model of the melting layer, that is, the Doppler velocity matching score V score .

[0100] For i distance libraries, the calculation of the melting layer probability value of the target distance library according to the reflectivity factor matching score and the Doppler velocity matching score includes: The melting layer probability value is determined according to the product of the reflectivity factor matching score and the Doppler velocity matching score.

[0101] Specifically, the reflectivity factor matching score is calculated according to the above steps. Doppler velocity matching score After that, the melting layer probability S(i) on the i-th distance bin can be directly calculated. For details, please refer to the following formula (5): (5) After calculating the melting layer probability of the i-th distance bin, when it is determined that i+w is still less than the total number of distance bins n of the observation profile, set i=i+1 and return to the previous step to recalculate the melting layer probability value corresponding to the next distance bin until all distance bins in the entire radar observation profile are traversed to obtain the melting layer probability distribution.

[0102] As an optional embodiment, the present invention also provides a method for pre-building a profile template, and the specific steps are as follows: Acquire multiple historical radar observation data, and screen out typical profiles containing characteristics of a melting layer in a cloud, wherein the typical profiles include a reflectivity factor profile and a Doppler velocity profile, wherein the reflectivity factor profile includes a first typical characteristic of a reflectivity factor, and the Doppler velocity profile includes a second typical characteristic of a Doppler velocity, wherein the first typical characteristic includes at least a peak characteristic, and the second typical characteristic includes at least a mutation characteristic from small to large; Normalizing and averaging the parts of all the screened reflectivity factor profiles containing the melting layer to obtain an average reflectivity factor profile; Normalizing and averaging the parts of all the selected Doppler velocity profiles containing the melting layer to obtain an average Doppler velocity profile; The reflectivity factor average profile and the Doppler velocity average profile are respectively normalized again to obtain the profile template.

[0103] Specifically, typical profiles including reflectivity factor profile and Doppler velocity profile are extracted and processed from a large amount of historical radar observation data collected, and these typical profiles contain the characteristics of the melt layer in the cloud. Among them, the processing of these typical profiles mainly includes averaging and normalization, and the specific implementation method will not be repeated here.

[0104] Table 1 Parameters of radar reflectivity factor and Doppler velocity of melt layer in original profile template

[0105] Figure 3 is a schematic diagram of the reflectivity factor profile in the profile template provided by the present invention, such as Figure 3 As shown, it reflects a typical dimensionless reflectivity factor in the melting layer with a peak value (i.e., "bright band" feature), corresponding to an altitude of about 0.5 km.

[0106] Figure 4 is a schematic diagram of the Doppler velocity profile in the profile template provided by the present invention, such as Figure 4 As shown in the figure, it reflects a typical dimensionless characteristic of the Doppler velocity in the melting layer, where the velocity changes toward a large negative gradient, corresponding to a curve with a large rate of change with distance between 0.5 and 0.75 km.

[0107] Combine the following Figures 5 to 7 An example of using the method for detecting a melting layer in a cloud provided by the present invention to process any target radar observation profile is introduced.

[0108] Figure 5 is a schematic diagram of a reflectivity factor profile in a target radar observation profile provided by the present invention, from Figure 5 It can be seen from the visual that there is a peak of the reflectivity factor between 2 and 3 km altitude.

[0109] Figure 6 is a schematic diagram of a Doppler velocity profile in a target radar observation profile provided by the present invention, from Figure 6 Visual observation shows that there is a characteristic of a large negative velocity gradient between 2 and 3 km altitude.

[0110] Figure 7 is a schematic diagram of the probability distribution of the melting layer corresponding to a target radar observation profile provided by the present invention, specifically Figure 5 The reflectivity factor profiles and Figure 6 The Doppler velocity profile shown is calculated to obtain the probability distribution of the melting layer. Figure 7 The height at which the probability of a visible melting layer exceeds 90% is Figure 3 as well as Figure 4The characteristic height of the melting layer in the cloud given in the provided profile template is completely consistent, which fully proves the feasibility of the detection method of the melting layer in the cloud provided by the present invention.

[0111] The following is a detailed description of the method of correlation coefficient used in the present invention when matching the target profile template with the target radar observation profile. That is, the formula (3) and formula (4) used in the above embodiment are actually to calculate the correlation coefficient between the target profile template with a total length of 1.05 km and the radar observation profile.

[0112] For the correlation coefficient of two variables A and B, its original definition is as described in formula (6): (6) Among them, cov stands for covariance and std stands for standard deviation.

[0113] Compared with formula (6), formula (3) and formula (4) firstly omit the calculation of dividing both the numerator and denominator by the variable length. Secondly, the reflectivity factor template Z input in each calculation is model Or Doppler velocity template V model It is constant, so there is no need to calculate its standard deviation every time. Instead, by normalizing it in advance, we can save the calculation of dividing it by the standard deviation of one of the variables when calculating the correlation coefficient.

[0114] In general, the above formula (3) and formula (4) adopted by the present invention are an optimization of the calculation efficiency of calculating the correlation coefficient.

[0115] It should also be noted that the reflectivity factor matching score Z obtained by formula (3) and formula (4) is score and Doppler velocity matching score V score The value range is 0~1, which represents the difference between the reflectivity factor Z (or Doppler velocity V) of each 1.05km data segment sliding on the radar observation profile and the reflectivity factor Z on the target profile template. model (or Doppler velocity V model ) can reflect whether the radar observation profile conforms to the reflectivity factor peak and Doppler velocity large gradient change characteristics of the melting layer.

[0116] The calculation is based on the normalized dimensionless variables, avoiding the judgment of the absolute value of the reflectivity factor Z (or Doppler velocity V) and its changing trend, thereby avoiding the setting of various empirical thresholds in existing methods.

[0117] The final melting layer probability is defined as the product of the two scores × 100%, that is, the melting layer probability is greater when both the reflectivity factor peak and the Doppler velocity large gradient change characteristics are met, and the result is intuitive.

[0118] The method for detecting the melt layer in the cloud provided by the present invention uses a dimensionless melt layer radar reflectivity factor profile model and a Doppler velocity profile model to match the observation data, thereby realizing the discrimination of the radar reflectivity factor peak value and the Doppler velocity large gradient change characteristics, does not involve multiple empirical parameters used in traditional methods, and reduces the empiricism of the identification method.

[0119] In addition, by using the product of the scores calculated by the radar reflectivity factor and the Doppler velocity respectively as the final melting layer probability, the calculation is simple and the result is intuitive.

[0120] Finally, the present invention does not involve the need to input the temperature profile or the height of the 0°C layer in the existing methods, which enhances the independence of radar identification of the melting layer and the reliability of actual operation.

[0121] As an optional embodiment, the present invention also provides a specific implementation method for interpolating a predetermined profile template of a melting layer in a cloud.

[0122] The profile template includes a reflectivity factor profile template and a Doppler velocity profile template in the same height sequence; the interpolation processing is performed on the profile template of the predetermined melting layer in the cloud so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile, including: Obtaining the distance starting point of the height sequence; Evenly distributing interpolation points in the height sequence according to the range resolution, and respectively calculating a reflectivity factor template value corresponding to each of the interpolation points on the reflectivity factor profile template, and calculating a Doppler velocity template value corresponding to each of the interpolation points on the Doppler velocity profile template; The reflectivity factor template value of each feature point in the new height sequence inserted into all interpolation points is combined to obtain a target reflectivity factor profile template; and the Doppler velocity template value of each feature point is combined to obtain a Doppler velocity profile template; The target reflectivity factor profile template and the Doppler velocity profile template associated with the new height sequence constitute the target profile template.

[0123] The present invention proposes an automatic detection method for a melt layer in a cloud, which uses vertically pointed radar observation data to identify the melt layer in the cloud through matching processing. The following is a detailed description of a specific embodiment of the present invention, especially the specific steps of interpolating a predetermined contour template of a melt layer in a cloud.

[0124] The profile template used in the present invention includes the reflectivity factor profile template Z on the same height sequence modeland Doppler velocity profile template V model These profile templates are typical profiles selected from a large number of radar observation cases, and the part containing the melt layer is obtained by normalizing and averaging. For example, in the historical data, the center of the melt layer on a radar observation profile is at an altitude of 3km, so the reflectivity factor and Doppler velocity in the altitude range of 2.5~3.55km are taken out for normalization as a historical sample. After accumulating a large number of such historical samples, they are averaged and normalized again. The final obtained profile template can be referred to Figure 3 The normalized reflectivity factor profile diagram and Figure 4 Schematic diagram of the normalized Doppler velocity profile shown.

[0125] In specific implementation, the data related to these profile templates can be obtained from a pre-stored database, such as the data shown in Table 1 and its corresponding graphical representation (such as Figure 3 and Figure 4 ) as shown.

[0126] Furthermore, the range resolution of the target radar observation profile is determined. The target radar observation profile is output by a vertically pointing radar (such as a Ka-band cloud radar, a K-band light rain radar, etc.), and contains relevant data such as a height sequence H, a radar reflectivity factor Z, and a Doppler velocity V. When implementing the present invention, it is first necessary to determine the range resolution ΔH of the target radar observation profile, which is the basis for subsequent interpolation processing.

[0127] Then, the profile template is interpolated, which mainly includes: Step 3.1: Obtain the distance starting point of the height sequence. According to the height sequence h of the original profile template (the "Distance" column in Table 1), determine the distance starting point. In this embodiment, the distance starting point can be set to 0 km.

[0128] Step 3.2: Evenly distribute interpolation points in the height sequence. According to the range resolution ΔH of the target radar observation profile, evenly distribute interpolation points in the height sequence h of the original profile template. The number of interpolation points n model It is determined by the length of the original template (such as 35 points) and the target distance resolution. For example, if the target distance resolution is 0.2km, the interpolated template will contain 5+1=6 points (because 1.05km / 0.2km=5.25, rounded up to 6, but considering the symmetry of the template, an additional point may need to be added during the actual interpolation to ensure the integrity of the template). However, in this embodiment, in order to simplify the description, it is assumed that the target distance resolution is similar to or the same as the distance resolution of the original template, so there is no need to perform too much interpolation processing.

[0129] Step 3.3: Calculate the template value corresponding to the interpolation point. model and Doppler velocity profile template V model The corresponding template value is calculated according to the position of the interpolation point. This is usually achieved by simple linear interpolation or other suitable interpolation methods. In this embodiment, since it is assumed that the target distance resolution is similar to the original template, the value of the original template can be directly used as the value of the interpolation point, or slightly adjusted to match the target distance resolution.

[0130] Step 3.4: Combine into a target profile template. Combine the reflectivity factor template values ​​of each feature point in the new height sequence after inserting all interpolation points to obtain the target reflectivity factor profile template. Similarly, combine the Doppler velocity template values ​​of each feature point to obtain the Doppler velocity profile template. These two profile templates together constitute the target profile template for subsequent matching processing.

[0131] After obtaining the target profile template, it can be matched with the target radar observation profile. This usually involves sliding the target profile template along the height direction of the observation profile and calculating the score of the matching degree (such as correlation coefficient) at each position, which will not be described in detail here.

[0132] The score Z obtained based on the matching process score and V score , the melting layer probability S(i) at each location is calculated using the above formula 5. This melting layer probability value reflects the possibility of the existence of a melting layer at that location.

[0133] Finally, the calculated melting layer probability is output as a visualization result and applied to fields such as weather monitoring, forecasting, and precipitation type judgment as needed.

[0134] In order to further illustrate the feasibility and technical effect of the method for detecting the melting layer in the cloud provided by the present invention, the actual effect of the present invention is specifically demonstrated through three embodiments below.

[0135] Example 1 is a typical example of stratiform cloud observation. The melting layer can be easily identified by visual inspection, which is used to illustrate the concept of the intermediate variable of the melting layer probability calculated by the present invention and the reliability of the final result. Example 2 and Example 3 are observation examples of different seasons and different precipitation types, which are used to further demonstrate the effect of the present invention.

[0136] (1) Example 1, typical layered cloud example: Example 1 uses Ka-band cloud radar data with a negative velocity toward the radar, observed in a certain observation area in October.

[0137] Figure 8is one of the schematic diagrams of a radar reflectivity factor profile sequence provided by the present invention, such as Figure 8 As shown, from the observed reflectivity factor profile sequence, it can be seen that there is a faint horizontally distributed bright band feature between 2 and 3 km altitude.

[0138] Fig. 9 This is one of the schematic diagrams of a Doppler velocity profile sequence provided by the present invention. Fig. 9 It can be seen that there is a sudden change in V between the 2 and 3 km altitudes. Forecasters or observers can easily identify the presence of a melting layer between the 2 and 3 km altitudes.

[0139] Fig.10 is one of the distribution diagrams of the reflectivity factor matching score calculated by the method of the present invention, Fig.11 is one of the distribution diagrams of the Doppler velocity matching scores calculated by the method of the present invention, combined with Fig.10 and Fig.11 As shown, from the reflectivity factor matching score Z of the present invention score and Doppler velocity matching score V score It can be seen that, except for the altitude of 2~3km, there are also some identifiable reflectivity factor peak characteristics and Doppler velocity gradient change characteristics at other altitudes. If the 0°C layer altitude of about 3km on that day is not taken into account, the gradient thresholds of the reflectivity factor Z and Doppler velocity V required by the current traditional method may lead to the erroneous identification of the melting layer at other altitudes.

[0140] Fig.12 is one of the distribution diagrams of the melting layer probability calculated by the method of the present invention, such as Fig.12 As shown, from the melting layer probability finally obtained by the present invention, there is only a horizontal continuity between the 2~3 km altitude and the value exceeds 90% of the discrimination result, which can intuitively display the cloud melting layer between 2~3 km, and does not require additional input of temperature profile or 0°C layer altitude.

[0141] (2) Example 2, layered cloud example with intermittent precipitation: Example 2 uses K-band light rain radar data, with a positive velocity toward the radar, and is observed in a certain observation area in July.

[0142] Fig.13 This is the second schematic diagram of a radar reflectivity factor profile sequence provided by the present invention, such as Fig.13 As shown, in this example of intermittent stratiform cloud precipitation, the bright band of the melting layer shown by the reflectivity factor is discontinuous in time, and the bright band feature is close to the value of the rainfall echo below, and the bright band feature is not obvious enough.

[0143] Fig.14This is the second schematic diagram of a Doppler velocity profile sequence provided by the present invention, such as Fig.14 As shown in the figure, although the Doppler velocity has a sudden change in value at 5 km, the echo of the reflectivity factor above it is weak, which can be easily mistaken as being close to the cloud top, thereby ignoring the sudden change in the Doppler velocity. In the above case, the cloud shown in Example 2 can be easily misjudged as a convective cloud by an inexperienced forecaster / observer, thereby misjudging the precipitation development trend.

[0144] Fig.15 This is the second schematic diagram of the distribution of the melting layer probability calculated by the method of the present invention, such as Fig.15 As shown, the melting layer probability calculated by the present invention shows that a relatively clear melting layer probability high value band is given at an altitude of 5 km. Compared with the current traditional direct observation, it can more intuitively reflect the melting layer in the cloud, and accordingly the monitored cloud system is characterized as a layered cloud.

[0145] (3) Example 3, Example of light rain turning into sleet: Example 3 uses K-band light rain radar data, the velocity toward the radar is positive, and it is observed in a certain observation area in November. The ground measurement on that day is a light rain turning into sleet weather process.

[0146] Fig.16 This is the third schematic diagram of a radar reflectivity factor profile sequence provided by the present invention. Fig.17 This is a third schematic diagram of a Doppler velocity profile sequence provided by the present invention, such as Fig.16 and Fig.17 As shown, the measured reflectivity factor and Doppler velocity show features that are suspected to be the sinking of the melt layer. However, since there is no operational meteorological sounding in the observation area between 8:00 and 20:00, it is impossible to obtain the local reliable temperature profile and 0°C layer height in real time, making the traditional melt layer identification algorithm that relies on the 0°C layer height unfeasible.

[0147] Fig.18 This is the third schematic diagram of the distribution of the melting layer probability calculated by the method of the present invention, as shown in FIG. Fig.18 As shown, the melting layer probability calculated by the present invention can clearly show the process of the melting layer gradually sinking from high altitude to near the ground, which can predict the change of rain into sleet, which is very consistent with the weather phenomenon measured later on the same day. This shows that the present invention can help forecasters or observers make reliable forecasts of the evolution of precipitation types.

[0148] In summary, the method for detecting the melt layer in the cloud provided by the present invention uses the dimensionless melt layer radar reflectivity factor profile model and Doppler velocity profile model to match the observation data, thereby realizing the discrimination of the peak value of the radar reflectivity factor and the large gradient change characteristics of the Doppler velocity, without involving multiple empirical parameters used in the traditional method, thus reducing the empirical nature of the identification method. And because it does not involve the need for the temperature profile or 0°C layer height that must be input in the current traditional method, it enhances the independence of radar identification of the melt layer and the reliability of actual operation.

[0149] Fig.19 Schematic diagram of the structure of the device for detecting the melting layer in the cloud provided by the present invention. Fig.19 As shown, it mainly includes: The radar monitoring unit 91 is mainly used to obtain multiple radar observation profiles of the area to be observed; The profile preprocessing unit 92 is mainly used to perform interpolation processing on the profile template of the predetermined melting layer in the cloud for any target radar observation profile, so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile; The probability analysis unit 93 is mainly used to calculate the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; The melting layer judgment unit 94 is mainly used to traverse all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile to determine whether there is a melting layer in the cloud in the area to be observed; The judgment result output unit 95 is used to output the height of the cloud melting layer when it is determined that the cloud melting layer exists.

[0150] It should be noted that the device for detecting the melting layer in the cloud provided by the present invention can execute the method for detecting the melting layer in the cloud described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0151] The device for detecting the melting layer in the cloud provided by the present invention uses a dimensionless radar observation profile including a reflectivity factor template and a Doppler velocity template to match the observed radar observation profile, thereby calculating the probability of the melting layer appearing in each distance library, without using empirical parameters, temperature profiles or 0°C layer height, thereby enhancing the independence of radar identification of the melting layer and the reliability of actual operation. The calculation method is simple and the result is intuitive.

[0152] Fig. 20 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Fig. 20As shown, the electronic device may include: a processor 210, a communication interface 220, a memory 230 and a communication bus 240, wherein the processor 210, the communication interface 220 and the memory 230 communicate with each other through the communication bus 240. The processor 210 may call the logic instructions in the memory 230 to execute the method for detecting the melting layer in the cloud, which method includes: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, interpolating the profile template of the predetermined melting layer in the cloud so that the target profile template after interpolation has the same distance resolution as the target radar observation profile; calculating the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile, and determining whether there is a melting layer in the cloud in the area to be observed; when it is determined that there is a melting layer in the cloud, outputting the height of the melting layer in the cloud.

[0153] In addition, the logic instructions in the above-mentioned memory 230 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0154] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the detection method of the melting layer in the cloud provided by the above-mentioned embodiments, the method including: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, interpolating a profile template of a predetermined melting layer in the cloud so that the distance resolution of the target profile template after interpolation is the same as that of the target radar observation profile; calculating the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile, and determining whether there is a melting layer in the cloud in the area to be observed; when it is determined that there is a melting layer in the cloud, outputting the height of the melting layer in the cloud.

[0155] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the method for detecting a melting layer in the cloud provided by the above-mentioned embodiments, the method comprising: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, interpolating a profile template of a predetermined melting layer in the cloud so that the distance resolution of the target profile template after the interpolation is the same as that of the target radar observation profile; calculating a melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile, and determining whether there is a melting layer in the cloud in the area to be observed; when it is determined that there is a melting layer in the cloud, outputting the height of the melting layer in the cloud.

[0156] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0157] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting a melting layer in a cloud, characterized in that: include: Acquire multiple radar observation profiles of the area to be observed; For any target radar observation profile, interpolation processing is performed on a predetermined profile template of a melting layer in the cloud, so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile; Calculating the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; Traversing all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each of the radar observation profiles to determine whether there is a melting layer in the cloud in the area to be observed; When it is determined that the cloud melting layer exists, the height of the cloud melting layer is output.

2. The method for detecting the melting layer in clouds according to claim 1, characterized in that: The calculating of the melting layer probability value determined in each distance library between the target radar observation profile and the target profile template comprises: Setting any distance library of the target radar observation profile as the target distance library; Determining a reflectivity factor matching score and a Doppler velocity matching score according to a matching result between the target radar observation profile and the target profile template in the target distance library; Calculating a melting layer probability value of the target distance library according to the reflectivity factor matching score and the Doppler velocity matching score; Resetting the next distance library as a new target distance library, and calculating the melting layer probability value associated with the new target distance library; The steps of setting the target distance library to calculating the melting layer probability value are iterated until all the distance libraries on the target radar observation profile are traversed to obtain the melting layer probability value related to each of the distance libraries.

3. The method for detecting the melting layer in clouds according to claim 2, characterized in that: The step of determining the reflectivity factor matching score according to the matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all reflectivity factor observations collected in the target distance library; Normalizing each of the reflectivity factor observation values ​​to obtain a normalized reflectivity factor observation value; Performing matching calculation on each normalized reflectivity factor observation value and the reflectivity factor template value at the same distance on the target profile template to obtain a matching value corresponding to each normalized reflectivity factor observation value; The matching values ​​corresponding to all the normalized reflectivity factor observation values ​​are accumulated to obtain a reflectivity factor matching score corresponding to the target distance library.

4. The method for detecting a melting layer in a cloud according to claim 2, characterized in that: Determining the Doppler velocity matching score according to the matching result between the target radar observation profile and the target profile template in the target distance library specifically includes: Obtaining all Doppler velocity observations collected in the target range library; Normalizing each of the Doppler velocity observation values ​​to obtain a normalized Doppler velocity observation value; Performing matching calculation on each of the normalized Doppler velocity observation values ​​and the Doppler velocity template value at the same distance on the target profile template to obtain a matching value corresponding to each of the normalized Doppler velocity observation values; The matching values ​​corresponding to all the normalized Doppler velocity observation values ​​are accumulated to obtain a Doppler velocity matching score corresponding to the target distance library.

5. The method for detecting the melting layer in clouds according to claim 2, characterized in that: The calculating the melting layer probability value of the target distance library according to the reflectivity factor matching score and the Doppler velocity matching score includes: The melting layer probability value is determined according to the product of the reflectivity factor matching score and the Doppler velocity matching score.

6. The method for detecting the melting layer in clouds according to any one of claims 1 to 5, characterized in that: The profile template is determined based on the following steps: Acquire multiple historical radar observation data, and screen out typical profiles containing characteristics of a melting layer in a cloud, wherein the typical profiles include a reflectivity factor profile and a Doppler velocity profile, wherein the reflectivity factor profile includes a first typical characteristic of a reflectivity factor, and the Doppler velocity profile includes a second typical characteristic of a Doppler velocity, wherein the first typical characteristic includes at least a peak characteristic, and the second typical characteristic includes at least a mutation characteristic from small to large; Normalizing and averaging the parts of all the screened reflectivity factor profiles containing the melting layer to obtain an average reflectivity factor profile; Normalizing and averaging the parts of all the selected Doppler velocity profiles containing the melting layer to obtain an average Doppler velocity profile; The reflectivity factor average profile and the Doppler velocity average profile are respectively normalized again to obtain the profile template.

7. The method for detecting the melting layer in clouds according to claim 6, characterized in that: The profile template includes a reflectivity factor profile template and a Doppler velocity profile template in the same height sequence; the interpolation processing is performed on the profile template of the predetermined melting layer in the cloud so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile, including: Obtaining the distance starting point of the height sequence; Evenly distributing interpolation points in the height sequence according to the range resolution, and respectively calculating a reflectivity factor template value corresponding to each of the interpolation points on the reflectivity factor profile template, and calculating a Doppler velocity template value corresponding to each of the interpolation points on the Doppler velocity profile template; The reflectivity factor template value of each feature point in the new height sequence inserted into all interpolation points is combined to obtain a target reflectivity factor profile template; and the Doppler velocity template value of each feature point is combined to obtain a Doppler velocity profile template; The target reflectivity factor profile template and the Doppler velocity profile template associated with the new height sequence constitute the target profile template.

8. A device for detecting a melting layer in a cloud, characterized in that: include: A radar monitoring unit, used to obtain multiple radar observation profiles of the area to be observed; A profile preprocessing unit is used to interpolate a profile template of a predetermined melting layer in a cloud for any target radar observation profile, so that the target profile template after the interpolation processing has the same distance resolution as the target radar observation profile; A probability analysis unit, used to calculate the melting layer probability value judged in each distance library between the target radar observation profile and the target profile template; A melting layer judgment unit is used to traverse all the radar observation profiles to comprehensively calculate the melting layer probability values ​​corresponding to all distance libraries in each radar observation profile to determine whether there is a melting layer in the cloud in the area to be observed; The judgment result output unit is used to output the height of the melting layer in the cloud when it is determined that the melting layer in the cloud exists.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for detecting a melting layer in a cloud as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for detecting a melting layer in a cloud as described in any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting a melting layer in a cloud as described in any one of claims 1 to 7 is implemented.

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