A method and system for estimating rainfall time based on cloud base height variation patterns

Abstract

The present invention relates to a method and system for estimating rainfall timing based on cloud base height variations, belonging to the field of radio. The method comprises: inputting THI data, making a judgment based on a reflectivity threshold, eliminating interference data, and calculating the cloud base height in each radial direction, where THI stands for vertical to top scanning; determining whether rainfall is likely to form based on cloud base height variations and cloud base velocity; and performing data fitting if the conditions are met; estimating the rainfall time based on the fitting results and outputting the results. The present invention solves the problem that prior art techniques fail to fully utilize the strong correlation between dynamic changes in cloud base height and rainfall formation. It can provide meteorological service guarantees for major events, offer technical support for weather modification operations, and provide prerequisite services for business forecasters to issue nowcast information.

Description

Technical Field

[0001] The present invention relates to the field of radio, and in particular to a method and system for estimating rainfall time based on a cloud base height variation rule. Background Art

[0002] During rainfall, clouds typically become thicker, their cloud base gradually decreases, and their reflectivity increases significantly. The ceilometer's vertical overhead scanning method is well suited to monitoring these changes. The ceilometer's rainfall estimation algorithm uses extensive observations to identify patterns in cloud formation before rainfall and predict future rainfall events.

[0003] Current rainfall forecasting relies primarily on weather radar and satellite remote sensing, but their ability to capture weak or nascent precipitation clouds is limited. Traditional methods struggle to accurately predict localized, sudden precipitation events, such as those in the complex terrain of the Chengdu Basin. Cloud radars (such as the Ka-BM) can detect cloud vertical structure at high resolution, but existing technologies fail to fully exploit the strong correlation between dynamic changes in cloud base height and rainfall formation. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method and system for estimating rainfall time based on the cloud base height change law, thereby solving the shortcomings of the prior art.

[0005] The object of the present invention is achieved by the following technical solution: a method for estimating rainfall time based on the cloud base height variation law, the estimation method comprising:

[0006] Step 1: Input THI data, make a judgment based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction. THI stands for vertical top scan.

[0007] Step 2: Determine whether rainfall is likely to form based on the cloud base height change and cloud base velocity. If the conditions are met, perform data fitting.

[0008] Step 3: Estimate the rainfall time based on the fitting results and output the results.

[0009] The input THI data is judged according to the reflectivity threshold, including: inputting the basic data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last N minutes, using -25dBz as the threshold, assigning invalid values ​​to data with Z<-25dBz for elimination to eliminate interference from clear sky echoes.

[0010] Calculating the cloud base height in each radial direction includes:

[0011] Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz;

[0012] Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

[0013] The second step specifically includes the following contents:

[0014] Determine the number of radial cloud base heights within the set range. If the data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is less than -1.5m / s from the library number, the fitting condition is met, otherwise it is not met.

[0015] The cloud base height in each radial direction is calculated by fitting the formula y= a x+b is linearly fitted, where x Indicates different moments, y represents the cloud base height at the corresponding moment, a is the fitting slope, which indicates the speed of cloud base height change before rainfall occurs. b It is the slant distance of the fitted cloud base height at the time of rainfall estimation.

[0016] The step three specifically includes: a <0, calculate y =300m corresponding to the rainfall time x If the predicted rainfall time - current time < 30 minutes, the probability of rainfall is high and the result is output.

[0017] A rainfall time prediction system based on cloud base height variation law, the system comprising: a threshold judgment and calculation module, a rainfall judgment module and a result output module;

[0018] The threshold judgment and calculation module is configured to input THI data, make judgments based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction, where THI stands for vertical to top scanning;

[0019] The rainfall judgment module is configured to judge whether rainfall is likely to form based on the change in cloud base height and cloud base speed, and perform data fitting if the conditions are met;

[0020] The result output module is configured to estimate the rainfall time according to the fitting result and output the result.

[0021] The input THI data is judged according to the reflectivity threshold, including: inputting the basic data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last N minutes, using -25dBz as the threshold, assigning invalid values ​​to data with Z<-25dBz for elimination to eliminate interference from clear sky echoes.

[0022] Calculating the cloud base height in each radial direction includes:

[0023] Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz;

[0024] Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

[0025] The rainfall judgment module specifically performs the following steps:

[0026] Determine the number of radial cloud base heights within the set range. If the data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is less than -1.5m / s from the library number, the fitting condition is met, otherwise it is not met.

[0027] The cloud base height in each radial direction is calculated by fitting the formula y= a x+b is linearly fitted, where x Indicates different rainfall times, y represents the cloud base height at the corresponding moment, a is the fitting slope, which indicates the speed of cloud base height change before rainfall occurs. b It is the slant distance of the fitted cloud base height at the time of rainfall estimation.

[0028] The specific contents of the result output module include: a <0, calculate the corresponding rainfall time when y=300m x If the predicted rainfall time - current time < 30 minutes, the probability of rainfall is high and the result is output.

[0029] The present invention has the following advantages: a method and system for estimating rainfall time based on the law of cloud base height changes, which solves the problem that the existing technology does not fully utilize the strong correlation between the dynamic changes of cloud base height and rainfall formation. It can provide meteorological service guarantees for major events, provide technical support for artificial weather modification operations, and provide prerequisite services for business forecasters to publish short-term forecast information. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the process of the present invention;

[0031] Figure 2 is the reflectivity change corresponding to a certain rainfall moment Figure 1 ;

[0032] Figure 3 is the reflectivity change corresponding to a certain rainfall moment Figure 2 . DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided below in conjunction with the drawings is not intended to limit the scope of protection of the present application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application. The present invention is further described below in conjunction with the drawings.

[0034] like Figure 1 One embodiment of the present invention relates to a method for estimating rainfall time based on the cloud base height variation pattern monitored by cloud radar. The method is based on the fact that the cloud base height variation of most clouds before rainfall forms generally satisfies a linear relationship over time, and is supplemented by cloud thickness and velocity to predict rainfall time. Specifically, the method includes the following:

[0035] Step 1: Input THI data, make a judgment based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction. THI stands for vertical top scan.

[0036] Step 2: Determine whether rainfall is likely to form based on the cloud base height change and cloud base velocity. If the conditions are met, perform data fitting.

[0037] Step 3: Estimate the rainfall time based on the fitting results and output the results.

[0038] Furthermore, the input THI data is judged according to the reflectivity threshold, including: inputting the base data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last 5 minutes, using -25dBz as the threshold, assigning invalid values ​​to the data with Z<-25dBz to eliminate the interference of clear sky echo.

[0039] Furthermore, the calculation of the cloud base height in each radial direction includes:

[0040] Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz;

[0041] Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

[0042] Furthermore, step 2 specifically includes the following:

[0043] Fitting condition judgment: According to statistics, if the cloud base height is >3km, there will be no rainfall in the short term, and if the cloud base height is <0.3km, it is raining. Therefore, the number of radial cloud base heights within the set range is determined. If this data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is <-1.5m / s from the library number, the fitting condition is met, otherwise it is not met.

[0044] Data fitting: The cloud base height in each radial direction is fitted by the formula y= a x+b is linearly fitted, wherex Indicates different rainfall times, y represents the cloud base height at the corresponding moment, a and b It is a coefficient determined by minimizing the sum of squares of errors.

[0045] in, a and b The calculation formula is as follows:

[0046] ,

[0047] .

[0048] If the update frequency of the cloud meter data is 5s / time, then n=60, which is the number of sample points of the fitting time series. Indicates the fitting i A moment in time, Indicates the i The cloud base height value at a certain time point, and are the time average of the fitting and the average cloud base height of n times, a is the fitting slope, which indicates the speed of cloud base height change before rainfall occurs. b It is the slant distance of the fitted cloud base height at the time of rainfall estimation.

[0049] Furthermore, step three specifically includes: a <0, calculate y =300m corresponding to the rainfall time x If the predicted rainfall time - current time < 30 minutes, then the possibility of rainfall is high, and the result is output.

[0050] Another embodiment of the present invention relates to a rainfall time prediction system based on cloud base height variation patterns monitored by cloud radar, the system comprising: a threshold judgment and calculation module, a rainfall judgment module, and a result output module;

[0051] The threshold judgment and calculation module is configured to input THI data, make judgments based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction, where THI stands for vertical to top scanning;

[0052] The rainfall judgment module is configured to judge whether rainfall is likely to form based on the change in cloud base height and cloud base speed, and perform data fitting if the conditions are met;

[0053] The result output module is configured to estimate the rainfall time according to the fitting result and output the result.

[0054] The input THI data is judged according to the reflectivity threshold, including: inputting the base data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last 5 minutes, using -25dBz as the threshold, assigning invalid values ​​to data with Z<-25dBz for elimination to eliminate interference from clear sky echoes.

[0055] Calculating the cloud base height in each radial direction includes:

[0056] Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz;

[0057] Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

[0058] The rainfall judgment module specifically performs the following:

[0059] Determine the number of radial cloud base heights within the set range. If the data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is less than -1.5m / s from the library number, the fitting condition is met, otherwise it is not met.

[0060] The cloud base height in each radial direction is calculated by fitting the formula y= a x+b is linearly fitted, where x Indicates different rainfall times, y Indicates the cloud base height at the corresponding moment.

[0061] The specific contents of the result output module include: a <0, calculate y =300m corresponding to the rainfall time x If the predicted rainfall time - current time < 30 minutes, then the possibility of rainfall is high, and the result is output.

[0062] like Figure 2 and Figure 3The figure shows the reflectivity change image corresponding to a specific rainfall moment. The red curve represents the cloud base height of the first layer of clouds, the black dots represent the time of input data, and the blue dots represent the predicted rainfall moment. The reflectivity image shows that rainfall is occurring. As can be seen from the figure, the predicted rainfall moment is close to the actual rainfall moment, indicating a good prediction effect.

[0063] The foregoing description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein and should not be construed as excluding other embodiments. Rather, the present invention is capable of various other combinations, modifications, and improvements, and is capable of modification within the scope of the concepts described herein, through the above teachings, or through techniques or knowledge in the relevant field. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention are intended to be within the scope of the appended claims.

Claims

1. A method for estimating rainfall time based on the cloud base height variation pattern, characterized by: The estimation method includes: Step 1: Input THI data, make a judgment based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction. THI stands for vertical top scan. Step 2: Determine whether rainfall is likely to form based on the cloud base height change and cloud base velocity. If the conditions are met, perform data fitting. Step 3: Estimate the rainfall time based on the fitting results and output the results; The second step specifically includes the following contents: Determine the number of radial cloud base heights within the set range. If the data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is less than -1.5m / s from the library number, the fitting condition is met, otherwise it is not met. The cloud base height in each radial direction is linearly fitted using the fitting formula y=ax+b, where: x Indicates different rainfall times, y represents the cloud base height at the corresponding moment, a is the fitting slope, which indicates the speed of cloud base height change before rainfall occurs. b It is the slant distance of the fitted cloud base height at the time of rainfall estimation.

2. The method for estimating rainfall time based on the cloud base height variation pattern according to claim 1, characterized in that: The input THI data is judged according to the reflectivity threshold, including: inputting the basic data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last N minutes, using -25dBz as the threshold, assigning invalid values ​​to data with Z<-25dBz for elimination to eliminate interference from clear sky echoes.

3. The method for estimating rainfall time based on the cloud base height variation pattern according to claim 1, characterized in that: Calculating the cloud base height in each radial direction includes: Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz; Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

4. The method for estimating rainfall time based on the cloud base height variation pattern according to claim 1, characterized in that: The step three specifically includes: a <0, calculate y =300m corresponding to the rainfall time x If the predicted rainfall time - current time < 30 minutes, the probability of rainfall is high and the result is output.

5. A rainfall time prediction system based on cloud base height variation patterns, characterized by: The system includes: a threshold judgment and calculation module, a rainfall judgment module and a result output module; The threshold judgment and calculation module is configured to input THI data, make judgments based on the reflectivity threshold, remove interference data, and calculate the cloud base height in each radial direction, where THI stands for vertical to top scanning; The rainfall judgment module is configured to judge whether rainfall is likely to form based on the change in cloud base height and cloud base speed, and perform data fitting if the conditions are met; The result output module is configured to estimate the rainfall time according to the fitting result and output the result; The rainfall judgment module specifically performs the following steps: Determine the number of radial cloud base heights within the set range. If the data exceeds 1 / 3 of the total number of radial data in N minutes, and the radial velocity corresponding to the last radial cloud base height is less than -1.5m / s from the library number, the fitting condition is met, otherwise it is not met. The cloud base height in each radial direction is linearly fitted using the fitting formula y=ax+b, where: x Indicates different rainfall times, y represents the cloud base height at the corresponding moment, a is the fitting slope, which indicates the speed of cloud base height change before rainfall occurs. b It is the slant distance of the fitted cloud base height at the time of rainfall estimation.

6. The rainfall time prediction system based on cloud base height variation pattern according to claim 5, characterized in that: The input THI data is judged according to the reflectivity threshold, including: inputting the basic data in the cloud radar TIH mode, obtaining the basic reflectivity Z in the last N minutes, using -25dBz as the threshold, assigning invalid values ​​to data with Z<-25dBz for elimination to eliminate interference from clear sky echoes.

7. The rainfall time prediction system based on cloud base height variation pattern according to claim 5, characterized in that: Calculating the cloud base height in each radial direction includes: Eliminate void point interference: In the radial direction, the distance library is screened from low to high. If the reflectivity of the current distance library is invalid and the reflectivity of the previous and next distance libraries is valid, the reflectivity of the current distance library is assigned to 1dBz; Filter cloud layers: In the radial direction, the distance libraries are filtered from low to high. If the reflectivity of the current distance library num1 is an invalid value and the reflectivity of the next distance library num1+1 is a valid value, then record the starting distance library k1=num1+1 of the cloud layer; continue filtering upwards, and for the first distance library num2 with an invalid reflectivity, record the ending distance library k2=num2-1 of the cloud layer; if k2-k1>10, k1 to k2 are considered to be a layer of cloud and record the cloud base height distance library number k1 of the current cloud layer; otherwise, clear k1 and k2, and continue filtering upwards until the first cloud layer that meets the conditions is found or the distance library number exceeds the threshold. Find the cloud base height distance library number of the first cloud layer in each radial direction, and obtain the cloud base height = cloud base height distance library number × distance resolution.

8. The rainfall time prediction system based on cloud base height variation pattern according to claim 5, characterized in that: The specific contents of the result output module include: a <0, calculate y =300m corresponding to the rainfall time x If the predicted rainfall time - current time < 30 minutes, the probability of rainfall is high and the result is output.

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