Detection Method, Device, Electronic Device and Storage Medium for Melting Layer in Cloud

Abstract

The detection method, device, electronic device and storage medium for the melting layer in clouds provided by the present invention belong to the technical field of remote sensing image processing, and include: obtaining the melting layer probability values judged at each range bin between each radar observation profile of the area to be observed and the profile template; calculating the melting layer probability values corresponding to all range bins in each radar observation profile, determining whether there is a melting layer in the area to be observed, and outputting the height where the melting layer in the cloud is located. The detection method, device, electronic device and storage medium for the melting layer in clouds provided by the present invention use dimensionless radar observation profiles containing 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 range bin, without the need to use empirical parameters or temperature profiles or the height of the 0°C layer, enhancing the independence of radar in identifying the melting layer and the reliability of actual operation. The calculation method is simple, and the result is intuitive.

Description

Technical Field

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

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

[0003] Currently, various methods for radar to identify the melting layer require the input of temperature vertical profiles and various radar observation parameters, and based on the image features of the melting layer reflected in the radar observation parameter profiles, thresholds of temperature and various radar observation parameters and their vertical change rates are set to achieve the discrimination of the melting layer.

[0004] All existing algorithms for radar to identify the melting layer need to first input the temperature vertical profile or the 0°C layer height from external data other than the radar, and need to set the thresholds of various variables based on experience. However, relying on the input of this external data of the temperature profile not only greatly reduces the independence of radar observations, but also increases the construction cost and operation uncertainty of the observation system. In addition, using fixed thresholds to discriminate the melting layer will inevitably have great uncertainty when dealing with extreme weather under the background 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 clouds, so as to solve the defects of the construction cost and operation uncertainty existing in the prior art when identifying the melting layer in clouds, 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 clouds, including:

[0007] Obtaining multiple radar observation profiles of the area to be observed;

[0008] For any target radar observation profile, performing interpolation processing on the pre-determined profile template of the melting layer in clouds so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile;

[0009] Calculate the probability value of the melting layer judged at each range bin between the target radar observation profile and the target profile template;

[0010] Traverse all the radar observation profiles to comprehensively calculate the probability values of the melting layer corresponding to all range bins in each of the radar observation profiles, and determine whether there is a melting layer in the cloud in the area to be observed;

[0011] When it is determined that there is a melting layer in the cloud, output the height where the melting layer in the cloud is located.

[0012] According to a method for detecting a melting layer in a cloud provided by the present invention, the calculating the probability value of the melting layer judged at each range bin between the target radar observation profile and the target profile template includes:

[0013] Set any range bin of the target radar observation profile as the target range bin;

[0014] According to the matching result between the target radar observation profile and the target profile template in the target range bin, determine the reflectivity factor matching degree score and the Doppler velocity matching degree score;

[0015] Calculate the probability value of the melting layer of the target range bin according to the reflectivity factor matching degree score and the Doppler velocity matching degree score;

[0016] Set the next range bin as the new target range bin, and calculate the probability value of the melting layer related to the new target range bin;

[0017] Iteratively execute the steps of setting the target range bin to calculating the probability value of the melting layer until all range bins on the target radar observation profile are traversed, and obtain the probability values of the melting layer related to each range bin.

[0018] According to a method for detecting a melting layer in a cloud provided by the present invention, the determining the reflectivity factor matching degree score according to the matching result between the target radar observation profile and the target profile template in the target range bin specifically includes:

[0019] Obtain all the reflectivity factor observation values collected in the target range bin;

[0020] Perform normalization processing on each reflectivity factor observation value to obtain the normalized reflectivity factor observation value;

[0021] Match and calculate each normalized reflectivity factor observation value with the reflectivity factor template value at the same distance on the target profile template to obtain the matching value corresponding to each normalized reflectivity factor observation value;

[0022] Accumulate the matching values corresponding to all the normalized reflectivity factor observations to obtain the reflectivity factor matching degree score corresponding to the target range bin.

[0023] According to a method for detecting a melting layer in clouds provided by the present invention, determining the Doppler velocity matching degree score according to the matching result between the target radar observation profile and the target profile template within the target range bin specifically includes:

[0024] Obtain all the Doppler velocity observations collected within the target range bin;

[0025] Perform normalization processing on each of the Doppler velocity observations to obtain normalized Doppler velocity observations;

[0026] Perform matching calculations between each of the normalized Doppler velocity observations and the Doppler velocity template values at the same distances on the target profile template to obtain the matching values corresponding to each of the normalized Doppler velocity observations;

[0027] Accumulate the matching values corresponding to all the normalized Doppler velocity observations to obtain the Doppler velocity matching degree score corresponding to the target range bin.

[0028] According to a method for detecting a melting layer in clouds provided by the present invention, calculating the melting layer probability value of the target range bin according to the reflectivity factor matching degree score and the Doppler velocity matching degree score includes:

[0029] Determine the melting layer probability value according to the product between the reflectivity factor matching degree score and the Doppler velocity matching degree score.

[0030] According to a method for detecting a melting layer in clouds provided by the present invention, the profile template is determined based on the following steps:

[0031] Obtain multiple historical radar observation data, and screen out typical profiles including characteristics of the melting layer in clouds from them. The typical profiles include a reflectivity factor profile and a Doppler velocity profile. The reflectivity factor profile includes the first typical characteristics of the reflectivity factor, and the Doppler velocity profile includes the second typical characteristics of the Doppler velocity. The first typical characteristics at least include peak characteristics, and the second typical characteristics at least include mutation characteristics from small to large;

[0032] Perform normalization processing and averaging processing on the parts containing the melting layer in all the screened reflectivity factor profiles to obtain a reflectivity factor average profile;

[0033] Perform normalization processing and averaging processing on the parts containing the melting layer in all the screened Doppler velocity profiles to obtain a Doppler velocity average profile;

[0034] Normalize the average profile of the reflectivity factor and the average profile of the Doppler velocity again to obtain the profile template.

[0035] 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 on the same height sequence; the interpolation process for the profile template of the melting layer in the cloud determined in advance so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile includes:

[0036] Obtain the starting point of the distance of the height sequence;

[0037] Distribute interpolation points evenly in the height sequence according to the distance resolution, and calculate the reflectivity factor template value corresponding to each interpolation point on the reflectivity factor profile template and calculate the Doppler velocity template value corresponding to each interpolation point on the Doppler velocity profile template respectively;

[0038] Combine the reflectivity factor template values of each feature point in the new height sequence with all interpolation points inserted to obtain a target reflectivity factor profile template; and combine the Doppler velocity template values of each feature point to obtain a Doppler velocity profile template;

[0039] The target reflectivity factor profile template and the Doppler velocity profile template related to the new height sequence constitute the target profile template.

[0040] The present invention also provides a device for detecting a melting layer in a cloud, including:

[0041] A radar monitoring unit for obtaining multiple radar observation profiles of the area to be observed;

[0042] A profile preprocessing unit for, for any target radar observation profile, performing an interpolation process on the profile template of the melting layer in the cloud determined in advance so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile;

[0043] A probability analysis unit for calculating the melting layer probability value judged at each distance bin between the target radar observation profile and the target profile template;

[0044] A melting layer judgment unit for traversing all the radar observation profiles to comprehensively calculate the melting layer probability values corresponding to all distance bins in each of the radar observation profiles, and determine whether there is a melting layer in the area to be observed;

[0045] A determination result output unit, configured to output the height where the melting layer in the cloud is located when it is determined that there is a melting layer in the cloud.

[0046] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the detection method of the melting layer in the cloud as described in any one of the above is implemented.

[0047] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the detection method of the melting layer in the cloud as described in any one of the above is implemented.

[0048] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, the detection method of the melting layer in the cloud as described in any one of the above is implemented.

[0049] The detection method, device, electronic device, and storage medium of 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 range bin. It does not require the use of empirical parameters, temperature profiles, or the height of the 0°C layer, enhancing the independence of radar in identifying the melting layer and the reliability of actual operation. The calculation method is simple, and the result is intuitive. Description of the Drawings

[0050] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0051] Figure 1 is one of the flow diagrams of the detection method of the melting layer in the cloud provided by the present invention.

[0052] Figure 2 is another flow diagram of the detection method of the melting layer in the cloud provided by the present invention.

[0053] Figure 3 is a schematic diagram of the reflectivity factor profile in the profile template provided by the present invention.

[0054] Figure 4 is a schematic diagram of the Doppler velocity profile in the profile template provided by the present invention.

[0055] Figure 5 is a schematic diagram of the reflectivity factor profile in a target radar observation profile provided by the present invention.

[0056] Figure 6 It is a schematic diagram of the Doppler velocity profile in a target radar observation profile provided by the present invention.

[0057] Figure 7 It is a schematic diagram of the probability distribution of the melting layer corresponding to a target radar observation profile provided by the present invention.

[0058] Figure 8 It is one of the schematic diagrams of a radar reflectivity factor profile sequence provided by the present invention.

[0059] Figure 9 It is one of the schematic diagrams of a Doppler velocity profile sequence provided by the present invention.

[0060] Figure 10 It is one of the schematic diagrams of the distribution of the reflectivity factor matching degree scores calculated by the method of the present invention.

[0061] Figure 11 It is one of the schematic diagrams of the distribution of the Doppler velocity matching degree scores calculated by the method of the present invention.

[0062] Figure 12 It is one of the schematic diagrams of the distribution of the melting layer probability calculated by the method of the present invention.

[0063] Figure 13 It is the second of the schematic diagrams of a radar reflectivity factor profile sequence provided by the present invention.

[0064] Figure 14 It is the second of the schematic diagrams of a Doppler velocity profile sequence provided by the present invention.

[0065] Figure 15 It is the second of the schematic diagrams of the distribution of the melting layer probability calculated by the method of the present invention.

[0066] Figure 16 It is the third of the schematic diagrams of a radar reflectivity factor profile sequence provided by the present invention.

[0067] Figure 17 It is the third of the schematic diagrams of a Doppler velocity profile sequence provided by the present invention.

[0068] Figure 18 It is the third of the schematic diagrams of the distribution of the melting layer probability calculated by the method of the present invention.

[0069] Figure 19 It is a schematic diagram of the structure of a detection device for the melting layer in clouds provided by the present invention.

[0070] Figure 20 It is a schematic diagram of the structure of an electronic device provided by the present invention. Detailed implementation manners

[0071] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0072] It should be noted that in the description of the present invention, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element. The orientation or positional relationship indicated by terms such as "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 thus cannot be construed as a limitation on the present invention.

[0073] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data 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. generally belong to the same category, and do not limit the number of objects. For example, the first object can be one or multiple. In addition, "and / or" indicates at least one of the connected objects, and the character " / ", generally represents an "or" relationship between the associated objects before and after.

[0074] Identifying the melting layer in clouds using precipitation radar / cloud radar has many application values, for example:

[0075] (1) Distinguish between stratiform clouds and convective clouds. Stratiform clouds are usually formed by the slow uplift movement of a large horizontal area of the atmosphere caused by the encounter of a cold air mass and a warm air mass, while convective clouds are formed by convective movement in the vertical direction triggered under unstable atmospheric conditions.

[0076] Because the position of the melting of hydrometeor particles falling in convective clouds has a large uncertainty, it is difficult to have a melting layer with a uniform horizontal distribution characteristic like stratiform clouds. Therefore, the identification of the melting layer in clouds can help distinguish between stratiform clouds and convective clouds.

[0077] The development of strong convective clouds can produce severe weather such as hail, thunderstorm gales, and short-term heavy precipitation, which are objects that need to be closely monitored in weather monitoring. However, some stratiform clouds have precipitation fluctuations or discontinuities in the time-height diagram observed by vertically pointing precipitation radars / cloud radars, and are easily misidentified as convective clouds by inexperienced forecasters or observers, resulting in false alarms. Therefore, an automatic and reliable method for detecting the melting layer in clouds can avoid such false alarms.

[0078] (2) Distinguish the phase states of precipitation particles in clouds. Generally, the melting layer in clouds separates the upper cold layer dominated by ice-phase particles from the lower warm layer dominated by raindrops.

[0079] By identifying the melting layer in clouds, the dynamics of changes in precipitation types can be monitored and predicted. For example, when it is monitored that the melting layer is descending and has a tendency to touch the ground, it can be judged that the ground precipitation type will change from rain to sleet or even snow.

[0080] (3) Reduce the error in quantitative rainfall estimation. The radar reflectivity factor of precipitation radars / cloud radars is often used for quantitative rainfall estimation. However, the "bright band" feature of the radar reflectivity factor in the melting layer of clouds will lead to an overestimation of the rainfall rate at that place, thus affecting the judgment of subsequent rainfall intensity. By automatically identifying the melting layer in clouds, it can help forecasters or observers exclude or reduce the rainfall estimation error caused by the "bright band" feature in the melting layer.

[0081] In various methods for radar to identify the melting layer in the prior art, generally, the vertical temperature profile and the radar observation parameter profile formed by various radar observation parameters need to be input. By determining the image features of the melting layer in clouds reflected in the radar observation parameter profile and setting the thresholds of temperature and various radar observation parameters and their vertical change rates, the discrimination of the melting layer in clouds is realized.

[0082] For precipitation radars with variable elevation and azimuth scans, mainly near the height of the 0°C layer, for different regions and seasons, the melting layer in clouds is identified by setting empirical thresholds for the radar reflectivity factor and its vertical change 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, and differential phase shift rate and their change gradients for comprehensive discrimination.

[0083] For vertically pointing Doppler precipitation radars or cloud radars, mainly near the height of the 0°C layer, for different regions and seasons, the melting layer in clouds is identified by setting thresholds for the change gradients of the radar reflectivity factor (or signal-to-noise ratio) and Doppler velocity. For vertically pointing Doppler precipitation radars or cloud radars with dual polarization and capable of observing the linear depolarization ratio, an empirical threshold can also be set for the linear depolarization ratio to comprehensively discriminate the melting layer in clouds.

[0084] However, this method of obtaining temperature data from the outside has great limitations.

[0085] First of all, the relevant data of the true vertical temperature profile can only be obtained from operational meteorological soundings. It is observed only twice a day, and the observation sites are extremely sparse. The spatio-temporal representativeness is not fine, and it is not easy to fully cope with local weather or weather with large changes within half a day.

[0086] Secondly, although a microwave radiometer can invert the local vertical temperature profile in real time, it is prone to unreliable situations due to more interference in precipitation weather.

[0087] Furthermore, the height of the 0°C layer used in some algorithms comes from climate statistical data, which has great uncertainties in the context of climate change and is not easy to cope with the increasing number of extreme weather events.

[0088] Finally, generally speaking, relying on the input of this external data of the temperature profile not only greatly reduces the independence of radar observations, but also increases the construction cost of the observation system and the uncertainty of operation.

[0089] In addition, among the current algorithms for identifying the melting layer in clouds by different radars, the threshold settings for various variables are different, which is reasonable for a specific region and season. However, the characteristics targeted by these thresholds have their inherent variations in nature. For example, the shape, size, number concentration of falling ice-phase particles, and the background vertical air flow will all affect the strength and vertical gradient characteristics of the radar signal in the melting layer. Therefore, using fixed thresholds to distinguish the melting layer will inevitably have great uncertainties when dealing with extreme weather in the context of climate change.

[0090] In view of the many defects existing in the prior art in the identification of the melting layer in clouds, there is an urgent need to provide a detection method that is easier to operate and has higher accuracy.

[0091] The following combines Figures 1 - 20 Describe the detection method, device, electronic device and storage medium of the melting layer in clouds provided by the present invention. Only by inputting the radar observation profile (including the profile of radar reflectivity factor and Doppler velocity observations at different heights), it is possible to quickly calculate and output the melting layer probability (value range 0-100%) to achieve the purpose of more conveniently distinguishing the melting layer in clouds.

[0092] Figure 1 is one of the schematic flowcharts of the detection method of the melting layer in clouds provided by the present invention, as Figure 1 shown, including but not limited to the following steps:

[0093] Step 101, obtain multiple radar observation profiles of the area to be observed.

[0094] Considering that the Doppler velocity detected by a radar with low elevation angle scanning cannot reflect the falling situation of particles, although a vertically directed radar cannot obtain the monitoring results of precipitation clouds over a large horizontal range through azimuth scanning, since it only needs to detect up to a height of 10 - 20 km above, 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 occlusion of surrounding houses and mountains, and it does not rely on special building infrastructure. Therefore, the construction cost is much lower than that of a low elevation angle radar with azimuth scanning.

[0095] Therefore, the radar used in the present invention for detecting the melting layer in clouds can adopt a Doppler precipitation radar or cloud radar with vertical pointing observation, such as a Ka - band cloud radar, a K - band micro - rain radar, a K - band micro - precipitation profile radar.

[0096] Optionally, the present invention uses a Doppler precipitation radar or cloud radar with vertical pointing observation (such as a Ka - band cloud radar, a K - band micro - rain radar, etc.) to continuously and systematically observe a specified area to be observed. These radar devices output a set of data at fixed time intervals (such as 10 seconds or 60 seconds), including the radar reflectivity factor Z, Doppler velocity V at different heights (also called distances in the present invention), and the corresponding height sequence H. By integrating these data according to the height sequence, a radar observation profile composed of multiple profiles can be formed, and each radar observation profile covers the complete information from the ground to the maximum detection height of the radar (usually greater than 1.05 km).

[0097] Of course, in actual operation, the observation parameters of the radar will be adjusted according to the observation requirements and weather conditions to ensure that the collected data has sufficient resolution and accuracy. At the same time, the radar device will also be regularly maintained and calibrated to reduce errors and interference and improve the reliability of the data.

[0098] Step 102, for any target radar observation profile, perform interpolation processing on the pre - determined profile template of the cloud melting layer so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile.

[0099] Among all the radar observation profiles obtained in step 101, each radar observation profile collected at each moment is designated as the target radar observation profile. The present invention will pre - prepare a set of profile templates of the cloud melting layer, including the melting layer radar reflectivity factor template Z model , the melting layer Doppler velocity template V model and the corresponding height sequence h. These profile templates are obtained by screening out a part of the typical profiles containing the melting layer from a large number of radar observation cases and undergoing normalization processing and averaging processing.

[0100] It should be noted that before performing the matching calculation, interpolation processing needs to be performed on this set of contour templates. The purpose of interpolation is to make the contour templates consistent with the target radar observation contour in terms of resolution and altitude range.

[0101] Specifically, according to the range resolution ΔH and the maximum detection altitude of the target radar observation contour, corresponding interpolation operations can be performed on the contour templates to generate an interpolation template that exactly matches the target radar observation contour, which is called the target contour template.

[0102] Among them, the specific method of interpolation processing adopted can be flexibly selected according to the actual situation, such as linear interpolation, polynomial interpolation, or spline interpolation, etc. When selecting the interpolation method, factors such as calculation efficiency, accuracy, and stability need to be comprehensively considered to ensure that the interpolation results can meet the requirements of subsequent matching calculations.

[0103] Step 103, calculate the melting layer probability values judged at each range bin between the target radar observation contour and the target contour template.

[0104] After completing the interpolation processing of the initial contour template to obtain the target contour template, starting from the (w + 1)-th range bin in the direction from low to high along the target radar observation contour, all observed reflectivity factors Z and Doppler velocities V within the range of i - w to i + w can be taken, and the reflectivity factors and Doppler velocities at the corresponding heights on the target contour template are respectively subjected to matching calculations.

[0105] Among them, the matching algorithm adopted can be the method using the correlation coefficient, and the reflectivity factor matching degree score Z score and the Doppler velocity matching degree score V score are respectively calculated. These two scores reflect the degree of consistency between the radar observation characteristics and the typical characteristics of the melting layer.

[0106] Finally, based on the calculated reflectivity factor matching degree score Z score and the Doppler velocity matching degree score V score the melting layer probability value S corresponding to each range bin can be comprehensively calculated.

[0107] Among them, the specific calculation formula (1) for w, the half-width of the sliding window, can be expressed as:

[0108] (1)

[0109] Among them, is the number of interpolation points of the target contour template, is the rounding operation.

[0110] For example, assume that the range resolution of the target radar observation profile is 200 m. When interpolating the original 1.05 km long profile template into a target profile template with a 200 m range resolution, the number of interpolation points is 5. Then, according to formula (1), the half-width of the sliding window calculated is fix(5 - 1) / 2 = 2.

[0111] For another example, assume that the range resolution of the target radar observation profile is 200 m. When interpolating the original 1.05 km long profile template into a target profile template with a 100 m range resolution, the number of interpolation points is 10. Then, according to formula (1), the half-width of the sliding window calculated is fix((10 - 1) / 2) = 4.

[0112] Step 104: Traverse all the radar observation profiles to comprehensively calculate the melting layer probability values corresponding to all range bins in each of the radar observation profiles, and determine whether there is a melting layer in the cloud in the area to be observed.

[0113] Repeat the above step 103 until the melting layer probability values corresponding to each range bin on the target radar observation profile are calculated. Then, it is considered that the processing of one radar observation profile is completed. Then, in this way, each radar observation profile on the time axis is traversed once, and the melting layer probability values judged at each range bin between each radar observation profile and the target profile template are calculated in turn. If there are continuous and relatively high melting layer probability values (e.g., exceeding 90%) in a certain height range for all radar observation profiles, it can be considered that there is a melting layer in the cloud in this height range.

[0114] Step 105: When it is determined that there is the melting layer in the cloud, output the height where the melting layer in the cloud is located.

[0115] Finally, when it is determined that there is a melting layer in the cloud, the height range where there are continuous and relatively high melting layer probability values 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 range bins with high probability melting layers.

[0116] The method for detecting a melting layer in a cloud provided by the present invention uses dimensionless radar observation profiles including a reflectivity factor template and a Doppler velocity template to match the observed radar observation profiles, thereby calculating the probability of the occurrence of a melting layer at each range bin, without the need to use empirical parameters or the temperature profile or the 0°C layer height, enhancing the independence of radar in identifying the melting layer and the reliability of actual operation, with a simple calculation method and an intuitive result.

[0117] Figure 2 It is the second flow schematic diagram of the method for detecting a melting layer in a cloud provided by the present invention. As an alternative embodiment, asFigure 2 As shown, calculating the probability value of the melting layer judged at each range bin between the target radar observation profile and the target profile template specifically includes:

[0118] Set any range bin of the target radar observation profile as the target range bin;

[0119] According to the matching result between the target radar observation profile and the target profile template within the target range bin, determine the reflectivity factor matching degree score and the Doppler velocity matching degree score;

[0120] According to the reflectivity factor matching degree score and the Doppler velocity matching degree score, calculate the probability value of the melting layer for the target range bin;

[0121] Set the next range bin as the new target range bin and calculate the probability value of the melting layer related to the new target range bin;

[0122] Iteratively execute the steps from setting the target range bin to calculating the probability value of the melting layer until all range bins on the target radar observation profile are traversed to obtain the probability value of the melting layer related to each range bin.

[0123] The present invention adopts an iterative matching method for each range bin to perform feature comparison between the target radar observation profile and the target profile template.

[0124] First, input the target radar observation profile to be analyzed. In this embodiment, the data of a Ka - band cloud radar or a K - band micro - rain radar is taken as an example for illustration. The radar outputs a set of data at regular intervals (such as 10 s or 60 s), and this data characterizes the reflectivity factor Z and the Doppler velocity V at different heights within this time period. The number of range bins of the three variable profiles included in the target radar observation profile is n, the range resolution ΔH must be uniform, and the maximum detection height characterized is greater than 1.05 km.

[0125] In the present invention, a profile template will be pre - constructed according to the historically collected radar data. This profile template also includes the height sequence h, the radar reflectivity factor profile Z of the melting layer model and the Doppler velocity profile V of the melting layer model .

[0126] 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 interpolation has the same range resolution as the currently observed target radar observation profile, and determine the size of the sliding window for subsequent matching.

[0127] Further, starting from the first range bin of the radar observation profile, it is set as the target range bin to prepare for the matching calculation.

[0128] Process all the reflectivity factors Z in the array within the range of i - w to i + w into the normalized variable Z*. Here, when calculating the normalization of a variable, it is processed into a variable with a mean of 0 and a sum of squares of 1. For example, the normalized quantity Z of the reflectivity factor Z * The calculation formula (2) can be expressed as:

[0129] (2)

[0130] Where, is the reflectivity factor before processing, is the average value of the reflectivity factors within the range.

[0131] Perform a matching calculation on the normalized Z* and the interpolated and normalized target profile template Z model for matching calculation.

[0132] As an alternative embodiment, determining the matching degree score of the reflectivity factor according to the matching result between the target radar observation profile and the target profile template within the target range bin specifically includes:

[0133] Obtain all the reflectivity factor observation values collected within the target range bin;

[0134] Perform normalization processing on each of the reflectivity factor observation values to obtain the normalized reflectivity factor observation values;

[0135] Perform a matching calculation on each of the normalized reflectivity factor observation values and the reflectivity factor template values at the same distance on the target profile template to obtain the matching values corresponding to each of the normalized reflectivity factor observation values;

[0136] Accumulate the matching values corresponding to all the normalized reflectivity factor observation values to obtain the matching degree score of the reflectivity factor corresponding to the target range bin.

[0137] According to the description of the above embodiment, assuming that there are a total of 5 groups of data on the target profile template after interpolation processing, then when performing the matching between the target radar observation profile and the target profile template, it is to match the 1st - 5th groups of data, 2nd - 6th groups of data, 3rd - 7th groups of data, 4th - 8th groups of data, and 5th - 9th groups of data on the target radar observation profile with the 5 groups of values at the corresponding heights on the interpolated and re - normalized target profile template in sequence for matching calculation.

[0138] Specifically, when performing the reflectivity factor matching, the calculation formula (3) used can be expressed as:

[0139] (3)

[0140] Wherein, is the reflectivity factor matching degree score of the i-th distance bin; w is the half-width of the sliding window; is the j-th normalized reflectivity factor observation value; is the reflectivity factor template value at the same distance on the target profile template.

[0141] It should be noted that if the calculation result of is less than 0, it is directly assigned 0.

[0142] As another alternative embodiment, determining the Doppler velocity matching degree score according to the matching result between the target radar observation profile and the target profile template in the target distance bin specifically includes:

[0143] Obtain all Doppler velocity observation values collected in the target distance bin;

[0144] Normalize each of the Doppler velocity observation values to obtain normalized Doppler velocity observation values;

[0145] Match and calculate each of the normalized Doppler velocity observation values with the Doppler velocity template value at the same distance on the target profile template to obtain the matching value corresponding to each of the normalized Doppler velocity observation values;

[0146] Accumulate the matching values corresponding to all the normalized Doppler velocity observation values to obtain the Doppler velocity matching degree score corresponding to the target distance bin.

[0147] The calculation logic for the reflectivity factor matching degree score is basically similar. The difference is that when calculating the Doppler velocity matching degree score, it is necessary to first judge its directionality in the observation system. If the movement towards the radar is defined as negative velocity, no processing is done; if it is defined as positive velocity, then V is multiplied by a negative sign to unify the direction.

[0148] Next, the Doppler velocities in the target distance bin and the w distance bins before and after it can be normalized to obtain the normalized variable V*.

[0149] Then, match and calculate the normalized V* with the interpolated and normalized target profile template V model .

[0150] The matching calculation method also uses the method of correlation coefficient. The specific calculation method can adopt the following formula (4):

[0151] (4)

[0152] Among them, is the Doppler velocity matching degree score of the i-th range bin; w is the half-width of the sliding window; is the j-th normalized Doppler velocity observation value; is the Doppler velocity template value at the same range on the target profile template.

[0153] It should be noted that if the calculation result of is less than 0, it is directly assigned a value of 0.

[0154] By calculation, the result of matching the Doppler velocity on the target range bin with the target profile template of the typical model of the melting layer can be obtained, that is, the Doppler velocity matching degree score V score .

[0155] For the i-th range bin, calculating the melting layer probability value of the target range bin according to the reflectivity factor matching degree score and the Doppler velocity matching degree score includes:

[0156] Determining the melting layer probability value according to the product between the reflectivity factor matching degree score and the Doppler velocity matching degree score.

[0157] Specifically, after calculating the reflectivity factor matching degree score and the Doppler velocity matching degree score according to the foregoing steps, the melting layer probability S(i) of the i-th range bin can be directly calculated. Specifically, reference can be made to the following formula (5):

[0158] (5)

[0159] After calculating the melting layer probability of the i-th range bin, when it is determined that i + w is still less than the total number of range bins n of the observed profile, let i = i + 1, and return to the previous step to recalculate the melting layer probability value corresponding to the next range bin until all range bins in the entire radar observed profile are traversed to obtain the melting layer probability distribution.

[0160] As an optional embodiment, the present invention also provides a method for pre-constructing a profile template, and the specific steps are as follows:

[0161] Obtain multiple historical radar observation data, and screen out typical profiles including the characteristics of the melting layer in the cloud from them. The typical profiles include a reflectivity factor profile and a Doppler velocity profile. The reflectivity factor profile includes the first typical characteristics of the reflectivity factor, and the Doppler velocity profile includes the second typical characteristics of the Doppler velocity. The first typical characteristics at least include peak characteristics, and the second typical characteristics at least include mutation characteristics from small to large;

[0162] Normalize and average the parts containing the melting layer in all the selected reflectivity factor profiles to obtain the average reflectivity factor profile;

[0163] Normalize and average the parts containing the melting layer in all the selected Doppler velocity profiles to obtain the average Doppler velocity profile;

[0164] Normalize the average reflectivity factor profile and the average Doppler velocity profile again to obtain the profile template.

[0165] Specifically, the typical profiles, including the reflectivity factor profile and the Doppler velocity profile, are extracted and processed from a large number of historical radar observation data collected. These typical profiles contain the characteristics of the cloud melting layer. Among them, the processing of these typical profiles mainly includes averaging and normalization, and the specific implementation methods will not be elaborated here.

[0166] Table 1 Parameter list of radar reflectivity factor and melting layer Doppler velocity in the original profile template

[0167]

[0168] Figure 3 is a schematic diagram of the reflectivity factor profile in the profile template provided by the present invention. As Figure 3 shown, it reflects a dimensionless typical situation where the reflectivity factor peaks (i.e., the "bright band" feature) in the melting layer, corresponding to a height of about 0.5 km.

[0169] Figure 4 is a schematic diagram of the Doppler velocity profile in the profile template provided by the present invention. As Figure 4 shown, it reflects a dimensionless typical feature where the Doppler velocity shows a large negative gradient change in the melting layer, corresponding to a section of the curve with a large rate of change with distance between 0.5 and 0.75 km.

[0170] Next, in combination with Figures 5 - 7 an example of processing any target radar observation profile using the detection method of the cloud melting layer provided by the present invention will be introduced.

[0171] Figure 5 is a schematic diagram of the reflectivity factor profile in a target radar observation profile provided by the present invention. It can be visually seen from Figure 5 that there is a peak in the reflectivity factor between 2 and 3 km in height.

[0172] Figure 6 is a schematic diagram of the Doppler velocity profile in a target radar observation profile provided by the present invention. It can be visually seen from Figure 6It can be visually observed that there is a characteristic of a large negative gradient change in velocity between the altitudes of 2 and 3 km.

[0173] Figure 7 It 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, it is for Figure 5 the reflectivity factor profile shown in Figure 6 and Figure 7 the Doppler velocity profile shown in Figure 3 to calculate, and the obtained schematic diagram of the probability distribution of the melting layer. It can be visually observed from Figure 4 that the altitude where the probability of the melting layer exceeds 90% is completely consistent with

[0174] the altitude where the characteristics of the melting layer in the cloud given in the profile template provided by

[0175] fully proves the feasibility of the method for detecting the melting layer in the cloud provided by the present invention.

[0176] (6)

[0177] where cov represents calculating the covariance and std represents calculating the standard deviation.

[0178] Compared with formula (6), formulas (3) and (4) first omit the calculation of dividing both the numerator and denominator by the variable length. Secondly, the reflectivity factor template Z model or the Doppler velocity template V model input each time during the calculation is unchanged. Therefore, it is not necessary to calculate its standard deviation each time, but by normalizing it in advance, the calculation of dividing by the standard deviation of one of the variables when calculating the correlation coefficient is omitted.

[0179] Generally speaking, the above formulas (3) and (4) adopted by the present invention are an optimization of the calculation efficiency for calculating the correlation coefficient.

[0180] In addition, it should be noted that the reflectivity factor matching degree score Z score and the Doppler velocity matching degree score V score obtained by formulas (3) and (4) have a numerical range of 0 to 1, which represents the reflectivity factor Z (or Doppler velocity V) data segment of each 1.05 km sliding on the radar observation profile and the reflectivity factor Z on the target profile template model(or Doppler velocity V model ) The consistency of the change trend can reflect the degree to which the radar observation profile conforms to the peak of the reflectivity factor and the large gradient change characteristics of the Doppler velocity in the melting layer characteristics.

[0181] The calculation is based on the normalized dimensionless variables, avoiding the judgment of the absolute values of the reflectivity factor Z (or Doppler velocity V) and its change trend, thus avoiding the setting of various empirical thresholds in the existing methods.

[0182] 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 peak of the reflectivity factor and the large gradient change characteristics of the Doppler velocity are met, and the result is intuitive.

[0183] The method for detecting the melting layer in clouds provided by the present invention uses the dimensionless melting layer radar reflectivity factor profile model and Doppler velocity profile model to match the observation data, thereby realizing the discrimination of the peak of the radar reflectivity factor and the large gradient change characteristics of the Doppler velocity, without involving multiple empirical parameters used in the traditional methods, and reducing the empiricism of the identification method.

[0184] 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.

[0185] Finally, the present invention does not involve the requirement of the temperature profile or the 0°C layer height that must be input in the existing methods, enhancing the independence of the radar in identifying the melting layer and the reliability of the actual operation.

[0186] As an alternative embodiment, the present invention also provides a specific implementation manner for interpolating the profile template of the pre-determined melting layer in clouds.

[0187] The profile template includes a reflectivity factor profile template and a Doppler velocity profile template on the same height sequence; the interpolation processing of the pre-determined profile template of the melting layer in clouds to make the distance resolution of the interpolated target profile template the same as that of the target radar observation profile includes:

[0188] Obtain the distance starting point of the height sequence;

[0189] Distribute interpolation points evenly in the height sequence according to the distance resolution, and calculate the corresponding reflectivity factor template values for each interpolation point on the reflectivity factor profile template and the corresponding Doppler velocity template values for each interpolation point on the Doppler velocity profile template respectively;

[0190] Combine the template values of the reflectivity factor for each feature point in the new height sequence into which all interpolation points are inserted to obtain a target reflectivity factor profile template; and combine the template values of the Doppler velocity for each feature point to obtain a Doppler velocity profile template;

[0191] The target reflectivity factor profile template and the Doppler velocity profile template related to the new height sequence constitute the target profile template.

[0192] The present invention proposes an automatic detection method for the melting layer in clouds. This method uses vertically pointing radar observation data to identify the melting layer in clouds through matching processing. Below, specific embodiments of the present invention will be elaborated in detail, especially the specific steps for interpolating the profile template of the pre-determined melting layer in clouds.

[0193] The profile templates used in the present invention include a reflectivity factor profile template Z model and a Doppler velocity profile template V model . These profile templates are typical profiles selected from a large number of radar observation cases, and are obtained by normalizing and averaging the part containing the melting layer. For example, if the center of the melting layer on a radar observation profile in historical data is at a height of 3 km, then the reflectivity factor and Doppler velocity in the height range of 2.5 - 3.55 km are taken out for normalization as a historical sample. After accumulating a large number of such historical samples, averaging processing is performed, and finally normalization is performed again. The finally obtained profile template can refer to Figure 3 the schematic diagram of the reflectivity factor profile after normalization shown in Figure 4 and the schematic diagram of the Doppler velocity profile after normalization shown in

[0194] 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 (as shown in Figure 3 and Figure 4 ).

[0195] Furthermore, determine the range resolution of the target radar observation profile. The target radar observation profile is output by a vertically pointing radar (such as a Ka-band cloud radar, a K-band micro 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, first, it is necessary to determine the range resolution ΔH of the target radar observation profile, which is the basis for subsequent interpolation processing.

[0196] Then, perform interpolation processing on the profile template, mainly including:

[0197] Step 3.1: Obtain the distance starting point of the height sequence. Determine the distance starting point according to the height sequence h (the "distance" column in Table 1) of the original profile template. In this embodiment, the distance starting point can be set to 0 km.

[0198] Step 3.2: Uniformly distribute interpolation points in the height sequence. According to the distance resolution ΔH of the target radar observation profile, uniformly distribute interpolation points in the height sequence h of the original profile template. The number of interpolation points n model is jointly 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 0.2 km, the interpolated template will contain 5 + 1 = 6 points (because 1.05 km / 0.2 km = 5.25, rounded up to 6, but considering the symmetry of the template, an additional point may be needed during actual interpolation to ensure the integrity of the template). However, in this embodiment, for simplicity of explanation, it is assumed that the target distance resolution is similar to or the same as the distance resolution of the original template, so no excessive interpolation processing is required.

[0199] Step 3.3: Calculate the template values corresponding to the interpolation points. On the reflectivity factor profile template Z model and the Doppler velocity profile template V model respectively, calculate the corresponding template values according to the positions of the interpolation points. 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 values of the original template can be directly used as the values of the interpolation points, or slightly adjusted to match the target distance resolution.

[0200] Step 3.4: Combine into the 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 jointly form the target profile template for subsequent matching processing.

[0201] 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 scores of the matching degree (such as the correlation coefficient) at each position, which will not be elaborated here one by one.

[0202] According to the scores Z score and V score obtained from the matching process, calculate the melting layer probability S(i) at each position using the above formula 5. This melting layer probability value reflects the likelihood of the presence of a melting layer at that position.

[0203] Finally, the calculated melting layer probability is output as a visualization result and applied to fields such as weather monitoring, forecasting, and precipitation type determination as needed.

[0204] To further illustrate the feasibility and technical effects of the method for detecting the melting layer in clouds provided by the present invention, the actual effects of the present invention are specifically demonstrated below through three embodiments.

[0205] Embodiment 1 is a typical case of observing stratiform clouds. 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. Embodiments 2 and 3 are observation cases of different seasons and different precipitation types, which are used to further demonstrate the effects of the present invention.

[0206] (1) Embodiment 1, typical stratiform cloud embodiment:

[0207] The Ka-band cloud radar data used in Embodiment 1 has a negative velocity towards the radar and is observed in a certain observation area in October.

[0208] Figure 8 is one of the schematic diagrams of the radar reflectivity factor profile sequence provided by the present invention. As Figure 8 shown, from the observed reflectivity factor profile sequence, there are faintly visible horizontally distributed bright band features between the heights of 2 - 3 km.

[0209] Figure 9 is one of the schematic diagrams of the Doppler velocity profile sequence provided by the present invention. From the observed Figure 9 it can be seen that there is a sudden change in V between the heights of 2 - 3 km. Forecasters or observers can relatively easily identify the existence of a melting layer between the heights of 2 - 3 km.

[0210] Figure 10 is one of the schematic diagrams of the distribution of the reflectivity factor matching degree score calculated by the method of the present invention. Figure 11 is one of the schematic diagrams of the distribution of the Doppler velocity matching degree score calculated by the method of the present invention. Combining Figure 10 and Figure 11 shown, from the reflectivity factor matching degree score Z score and the Doppler velocity matching degree score V score of the present invention, except for the height between 2 - 3 km, there are also some identifiable reflectivity factor peak features and Doppler velocity gradient change features at other heights. If the 0°C layer height around 3 km on that day is not considered, the gradient thresholds of the reflectivity factor Z and Doppler velocity V required to be given according to the current traditional method may lead to misjudging the melting layer at other heights.

[0211] Figure 12One of the schematic diagrams of the distribution of the melting layer probability calculated by the method of the present invention is shown as Figure 12 shown. From the perspective of the melting layer probability finally obtained by the present invention, there is only a discriminant result with horizontal continuity and a value exceeding 90% between the heights of 2 to 3 km, which can intuitively show the melting layer in the cloud between 2 and 3 km, and there is no need to additionally input the temperature profile or the height of the 0°C layer.

[0212] (2) Example 2, an example of stratiform clouds with intermittent precipitation:

[0213] The K-band micro rain radar data is used in Example 2, the velocity towards the radar is positive, and observations are made in a certain observation area in July.

[0214] Figure 13 One of the schematic diagrams of a sequence of radar reflectivity factor profiles provided by the present invention is shown as Figure 13 shown. In this example of stratiform cloud precipitation with intermittency, the bright band of the melting layer shown by the reflectivity factor is discontinuous in time, and the characteristics of the bright band are close to the values of the underlying rainfall echoes, and the characteristics of the bright band are not obvious enough.

[0215] Figure 14 One of the schematic diagrams of a sequence of Doppler velocity profiles provided by the present invention is shown as Figure 14 shown. Although there is a numerical mutation in the Doppler velocity at 5 km, the echo of the reflectivity factor above it is weak itself, and it is easy to be misjudged that it is close to the cloud top, thus ignoring the mutation of the Doppler velocity. In the above situation, the cloud shown in Example 2 will be easily misjudged as a convective cloud by inexperienced forecasters / observers, thus misestimating the precipitation development trend.

[0216] Figure 15 One of the schematic diagrams of the distribution of the melting layer probability calculated by the method of the present invention is shown as Figure 15 shown. From the melting layer probability calculated by the present invention, a relatively clear large value band of the melting layer probability is given at a height of 5 km, which can more intuitively reflect the melting layer in the cloud compared with the current traditional direct observables, and accordingly, the monitored cloud system is qualitatively determined as stratiform cloud.

[0217] (3) Example 3, an example of light rain turning to sleet:

[0218] The K-band micro rain radar data is used in Example 3, the velocity towards the radar is positive, and observations are made in a certain observation area in November. The actual ground measurement on that day was a weather process of light rain turning to sleet.

[0219] Figure 16 One of the schematic diagrams of a sequence of radar reflectivity factor profiles provided by the present invention Figure 17 One of the schematic diagrams of a sequence of Doppler velocity profiles provided by the present invention is shown as Figure 16and Figure 17 As shown, the measured reflectivity factor and Doppler velocity show characteristics suspected of the sinking of the melting layer. However, since there is no operational meteorological sounding in the observation area from 8:00 to 20:00, it is impossible to obtain the local reliable temperature profile and the height of the 0°C layer in real time, resulting in the infeasibility of the traditional melting layer identification algorithm that relies on the height of the 0°C layer.

[0220] Figure 18 It is the third schematic diagram of the distribution of the melting layer probability calculated by the method of the present invention. As Figure 18 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 from rain to sleet and is in good agreement with the subsequent measured weather phenomena on the same day. This shows that the present invention can help forecasters or observers make reliable forecasts of the evolution of precipitation types.

[0221] In summary, the detection method of the melting layer in clouds provided by the present invention uses a dimensionless melting layer radar reflectivity factor profile model and a Doppler velocity profile model to match the observation data, so as to realize the discrimination of the peak of the radar reflectivity factor and the characteristics of large gradient changes in the Doppler velocity. It does not involve multiple empirical parameters used in traditional methods, reducing the empiricism of the identification method. And because it does not involve the requirement of the temperature profile or the height of the 0°C layer that must be input in the current traditional methods, it enhances the independence of the radar in identifying the melting layer and the reliability of actual operation.

[0222] Figure 19 It is the structural schematic diagram of the detection device of the melting layer in clouds provided by the present invention. As Figure 19 shown, it mainly includes:

[0223] A radar monitoring unit 91, mainly used to obtain multiple radar observation profiles of the area to be observed;

[0224] A profile preprocessing unit 92, mainly used to perform interpolation processing on a pre-determined profile template of the melting layer in clouds for any target radar observation profile, so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile;

[0225] A probability analysis unit 93, mainly used to calculate the melting layer probability values judged at each range bin between the target radar observation profile and the target profile template;

[0226] A melting layer judgment unit 94, mainly used to traverse all the radar observation profiles to comprehensively calculate the melting layer probability values corresponding to all range bins in each of the radar observation profiles, and determine whether there is a melting layer in clouds in the area to be observed;

[0227] A determination result output unit 95 is configured to output the height where the melting layer in the cloud is located when it is determined that there is a melting layer in the cloud.

[0228] It should be noted that the detection device for the melting layer in the cloud provided by the present invention can execute the detection method for the melting layer in the cloud described in any of the above embodiments during specific operation, and details thereof will not be elaborated in this embodiment.

[0229] The detection device for the melting layer in the cloud provided by the present invention uses 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 range bin. It does not require the use of empirical parameters, temperature profiles, or the height of the 0°C layer, enhancing the independence of radar in identifying the melting layer and the reliability of actual operation. The calculation method is simple and the results are intuitive.

[0230] Figure 20 is a schematic structural diagram of an electronic device provided by the present invention. As Figure 20 shown, the electronic device may include: a processor 210, a communication interface 220, a memory 230, and a communication bus 240. Among them, the processor 210, the communication interface 220, and the memory 230 communicate with each other through the communication bus 240. The processor 210 can call logical instructions in the memory 230 to execute the detection method for the melting layer in the cloud, and the method includes: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, performing interpolation processing on a pre-determined profile template of the melting layer in the cloud so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile; calculating the probability value of the melting layer judged at each range bin between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the probability values of the melting layer corresponding to all range bins in each of the calculated radar observation profiles, and determining whether there is a melting layer in the area to be observed; when it is determined that there is a melting layer in the cloud, outputting the height where the melting layer in the cloud is located.

[0231] In addition, when the logical instructions in the above-mentioned memory 230 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0232] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the detection method of the cloud melting layer provided in the above-mentioned various embodiments. The method includes: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, performing interpolation processing on a pre-determined profile template of the cloud melting layer so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile; calculating the probability value of the melting layer judged at each distance bin between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the probability values of the melting layer corresponding to all distance bins in each of the radar observation profiles, and determining whether there is a cloud melting layer in the area to be observed; when it is determined that there is a cloud melting layer, outputting the height where the cloud melting layer is located.

[0233] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method for detecting the melting layer in the cloud provided in the above various embodiments. The method includes: obtaining multiple radar observation profiles of the area to be observed; for any target radar observation profile, performing interpolation processing on the pre-determined profile template of the melting layer in the cloud, so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile; calculating the probability value of the melting layer judged at each range bin between the target radar observation profile and the target profile template; traversing all the radar observation profiles to comprehensively calculate the probability values of the melting layer corresponding to all range bins in each of the radar observation profiles, 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 where the melting layer is located.

[0234] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0235] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing 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.

[0236] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for detecting a melting layer in a cloud, characterized in that, Including: Obtaining multiple radar observation profiles of the area to be observed; the radar observation profiles are obtained by a vertically directed radar; For any target radar observation profile, interpolating a pre-determined profile template of the melting layer in the cloud to make the distance resolution of the interpolated target profile template the same as that of the target radar observation profile; the profile template is determined based on the following steps: obtaining multiple historical radar observation data, and screening out typical profiles containing the characteristics of the melting layer in the cloud from them; obtaining the profile template based on the typical profiles; Calculating the melting layer probability value judged at each range bin between the target radar observation profile and the target profile template; Traversing all the radar observation profiles, if there are continuous melting layer probability values greater than a preset threshold within a certain height range in all the radar observation profiles, it is determined that there is a melting layer in the cloud within the certain height range; When it is determined that there is the melting layer in the cloud, outputting the height where the melting layer in the cloud is located.

2. The detection method of the melting layer in the cloud according to claim 1, characterized in that, The calculating the melting layer probability value judged at each range bin between the target radar observation profile and the target profile template includes: Setting any range bin of the target radar observation profile as the target range bin; Determining the reflectivity factor matching degree score and the Doppler velocity matching degree score according to the matching result between the target radar observation profile and the target profile template in the target range bin; Calculating the melting layer probability value of the target range bin according to the reflectivity factor matching degree score and the Doppler velocity matching degree score; Resetting the next range bin as the new target range bin, and calculating the melting layer probability value related to the new target range bin; Iteratively executing the steps from setting the target range bin to calculating the melting layer probability value until all range bins on the target radar observation profile are traversed, and obtaining the melting layer probability values related to each range bin.

3. The detection method of the melting layer in the cloud according to claim 2, wherein, The specifically determining the reflectivity factor matching degree score according to the matching result between the target radar observation profile and the target profile template in the target range bin includes: Obtaining all the reflectivity factor observation values collected in the target range bin; Normalizing each reflectivity factor observation value to obtain the normalized reflectivity factor observation value; Performing a matching calculation on each normalized reflectivity factor observation value with the reflectivity factor template value at the same distance on the target profile template to obtain the matching value corresponding to each normalized reflectivity factor observation value; Accumulating the matching values corresponding to all the normalized reflectivity factor observation values to obtain the reflectivity factor matching degree score corresponding to the target range bin.

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

5. The detection method of the melting layer in the cloud 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 degree score and the Doppler velocity matching degree score includes: Determine the melting layer probability value according to the product between the reflectivity factor matching degree score and the Doppler velocity matching degree score.

6. The detection method of the melting layer in the cloud according to any one of claims 1-5, characterized in that, The typical profile includes a reflectivity factor profile and a Doppler velocity profile. The reflectivity factor profile includes the first typical feature of the reflectivity factor, and the Doppler velocity profile includes the second typical feature of the Doppler velocity. The first typical feature at least includes a peak feature, and the second typical feature at least includes a mutation feature from small to large; Perform normalization processing and averaging processing on the part containing the melting layer in all the selected reflectivity factor profiles to obtain the average reflectivity factor profile; Perform normalization processing and averaging processing on the part containing the melting layer in all the selected Doppler velocity profiles to obtain the average Doppler velocity profile; Perform normalization processing on the average reflectivity factor profile and the average Doppler velocity profile again to obtain the profile template.

7. The detection method of the melting layer in the cloud according to claim 6, characterized in that, The profile template includes a reflectivity factor profile template and a Doppler velocity profile template on the same height sequence; the interpolating the profile template of the melting layer in the cloud determined in advance so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile includes: Obtain the distance starting point of the height sequence; Uniformly distribute interpolation points in the height sequence according to the distance resolution, and calculate the reflectivity factor template value corresponding to each interpolation point on the reflectivity factor profile template and calculate the Doppler velocity template value corresponding to each interpolation point on the Doppler velocity profile template respectively; Combine the reflectivity factor template values of each feature point in the new height sequence with all interpolation points inserted to obtain the target reflectivity factor profile template; and combine the Doppler velocity template values of each feature point to obtain the Doppler velocity profile template; The target reflectivity factor profile template and the Doppler velocity profile template related to the new height sequence form the target profile template.

8. A detection device for a melting layer in a cloud, characterized in that, including: A radar monitoring unit for obtaining multiple radar observation profiles of the area to be observed; The radar observation profile is obtained by a vertically directed radar; A profile preprocessing unit, configured to perform interpolation processing on a pre-determined profile template of the cloud melting layer for any target radar observation profile, so that the distance resolution of the interpolated target profile template is the same as that of the target radar observation profile; the profile template is determined based on the following steps: obtaining a plurality of historical radar observation data, and screening out typical profiles containing cloud melting layer characteristics from them; obtaining the profile template based on the typical profiles; A probability analysis unit, configured to calculate the melting layer probability value judged at each range bin between the target radar observation profile and the target profile template; A melting layer determination unit, configured to traverse all the radar observation profiles. If there are continuous melting layer probability values greater than a preset threshold within a certain height range for all the radar observation profiles, it is determined that there is a cloud melting layer within the certain height range; A judgment result output unit, configured to output the height where the cloud melting layer is located when it is determined that there is a cloud melting layer; 9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for detecting the cloud melting layer according to any one of claims 1 to 7.

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

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

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