JP6929908B2 - Snow cover distribution estimation device and method - Google Patents

Description

An embodiment of the present invention relates to a snow cover distribution estimation device and a method.

Single-polarized weather radar has been used for meteorological observations at airports, but it is not possible to distinguish precipitation particles from the observed radar information in the single-polarized type, and particles over the runway, which are particularly important, are found. I couldn't tell if it was raining or snowing. After that, a dual-polarization type weather radar appeared, and by the technology that discriminates precipitation particles using the polarization parameters obtained by observation, whether the precipitation particles observed by the radar are rain or snow, etc. Information is now available.

In the above-mentioned dual polarization type weather radar, as a method of improving the discrimination accuracy of precipitation particles, it is generally discriminated from the type of precipitation particles obtained by directly observing the inside of a cloud and the polarization parameters obtained by observing with a radar. A method is adopted in which the processing parameters for discriminating the precipitation particles from the radar are adjusted by collating with the type of the precipitation particles to be generated. However, since this method is a verification in a limited number of cases, the optimum processing parameters are always applied to the meteorological phenomenon with rich regional characteristics, especially the snowfall phenomenon, which changes from moment to moment, and the accuracy is improved. It is difficult to obtain a high discrimination result.

On the other hand, focusing on the amount of snowfall or snowfall, in conventional meteorological observation, information at a specific point (for example, AMeDAS point) is provided only as spatially sparse information. In addition, on the runway, the snow quality (dry snow, wet snow, etc.) and the amount of snow just above the installation point can be observed by an optical method, and highly accurate information can be obtained in one dimension (point). A "type runway snow / ice monitoring sensor" is provided.

However, with the above method, even if snowfall / snow cover information at a certain point can be obtained accurately, observation at multiple points can be obtained in order to obtain flat snowfall / snow cover information (hereinafter referred to as area information) in a certain range. And analysis processing is required. For example, in the case of a runway, not only grasping the amount of snowfall at a certain point, but also surface information showing the distribution of the amount of snowfall on a flat surface is very important information for runway maintenance and safe takeoff and landing of aircraft. , It is difficult to obtain the area information by the above point observation method.

It is an advantage of the meteorological radar that such surface information can be acquired, but since the result of precipitation particle discrimination and the rainfall intensity (or snowfall intensity) obtained from the radar information are information in a certain sky above the ground. It is often different from what is observed on the ground. Therefore, it is problematic in terms of accuracy to estimate the snow cover distribution in a specific area on the ground from the surface weather information obtained by the weather radar.

Japanese Unexamined Patent Publication No. 2016-170069

Buried runway snow and ice monitoring sensor: http://www.jwing.net/news/8761

As described above, it is problematic in terms of accuracy to estimate the snow cover distribution in a specific area on the ground from the surface weather information obtained by the weather radar.

An object of this embodiment is to provide a snow cover distribution estimation device and a method capable of estimating the area distribution of the snow cover in a specific area on the ground with high accuracy.

According to the snow cover distribution estimation device according to the embodiment, a meteorological radar that sends a dual polarization radar wave over the target area, receives the reflected wave, and outputs meteorological radar data, and the meteorological radar. Data analysis that inputs meteorological radar data, generates observation data of three-dimensional volume from this meteorological radar data, discriminates precipitation particles in the sky above the target area in mesh units, and analyzes rainfall and snow intensity. The device and the one-dimensional snow observation data obtained by a plurality of snow observation sensors dispersed and buried on the ground in the target area are collated with the precipitation particle discrimination result in the sky obtained by the data analysis device, and the snow observation is performed. A correction unit that corrects the precipitation particle discrimination result, which is the mesh data directly above the sensor, to the actual observation result, and the ground of the target area based on the corrected actual observation result and the analysis result of the rainfall / snow intensity. It is equipped with an estimation unit that estimates the snow cover distribution.

FIG. 1 is a block diagram showing a configuration of a meteorological observation system using the snow cover distribution estimation device according to the embodiment. FIG. 2 is a block diagram showing an example of a weather radar data analysis device used in the meteorological observation system shown in FIG. FIG. 3 is a block diagram showing a configuration of a snow cover amount distribution estimation device according to the embodiment shown in FIG. FIG. 4 is a conceptual diagram showing the usage environment of the meteorological observation system shown in FIG. FIG. 5 is a flowchart showing a processing flow of the snow cover amount distribution estimation device shown in FIG.

Hereinafter, embodiments will be described with reference to the drawings.
FIG. 1 is a block diagram showing the configuration of a meteorological observation system for observing meteorological conditions including snowfall and snow cover on the runway. This system includes a weather radar 11, a data analysis device 12, a snow cover distribution estimation device 13 according to the present embodiment, and a road snow cover observation device 14. The weather radar 11 sends a dually polarized radar wave over the runway, receives the reflected wave, and outputs the weather radar data. The data analysis device 12 inputs the weather radar data from the weather radar 11, analyzes the weather condition over the runway in mesh units from the weather radar data, and outputs the weather analysis data to the snow cover distribution estimation device 13. .. The road snow observation device 14 uses, for example, the buried runway snow and ice monitoring sensors (hereinafter referred to as snow observation sensors) shown in Patent Document 1 and Non-Patent Document 1, and a plurality of snow observation sensors 141 to 14N are mounted on the runway, respectively. It is embedded in multiple points, and snow cover is observed at each installation point to acquire one-dimensional snow cover observation data. The one-dimensional snow cover observation data output from each snow cover observation sensor of the road snow cover observation device 14 is input to the snow cover amount distribution estimation device 13. The snow cover distribution estimation device 13 inputs meteorological analysis data from the data analysis device 12 and one-dimensional snow cover observation data at a plurality of points from the road snow cover observation device 14, and combines the meteorological analysis data and the one-dimensional snow cover observation data. , Estimate the distribution of the amount of snow that spreads on the runway, and provide the estimated data to the user.

FIG. 2 is a flock diagram showing an example of a specific configuration of the weather radar 11 and the data analysis device 12.

In FIG. 2, the weather radar 11 includes a dual polarization antenna unit 111 and a radar signal processing unit 112. The dually polarized wave antenna unit 111 transmits a radar wave with dually polarized waves orthogonal to each other and receives the reflected wave. The radar signal processing unit 112 removes unnecessary wave components (reflected wave components from the structure, etc.) from the received radar reflected waves of the dual polarization antenna unit 111, and acquires weather radar data. This radar data is two-dimensional polar coordinate system observation data. For example, when PPI (plan position indication) observation is performed, radar data is acquired for each elevation angle.

Further, the data analysis device 12 includes a communication interface unit (hereinafter, communication I / F unit) 121, a RAW data processing unit 122, a RAW data storage unit 123, a radar data analysis calculation unit 124, and an analysis data storage unit. It is equipped with 125.

The communication I / F unit 121 is an interface for inputting weather radar data output from the signal processing unit 112 of the weather radar 11. The input weather radar data is sent to the RAW data processing unit 122. The RAW data processing unit 122 performs, for example, rainfall attenuation correction processing on the weather radar data and outputs it as RAW data. This RAW data is sent to the RAW data storage unit 123 and stored in an internal recording medium.

The radar data analysis calculation unit 124 takes in the latest RAW data for one cycle from the RAW data storage unit 123, analyzes precipitation particle discrimination, rainfall intensity, etc. in mesh units, and digitizes them. The analysis data obtained by the radar data analysis calculation unit 124 is sent to the analysis data storage unit 125 and stored in the internal recording medium.

That is, in the above configuration, when the RAW data storage unit 123 stores three-dimensional observation data (a plurality of two-dimensional polar coordinate system data) for one cycle, the radar data analysis unit 124 is activated and executes radar data analysis. .. The analysis result is stored in the analysis data storage unit 125. For example, the output result of the numerical weather prediction model, the ground weather observation data, the remote sensing meteorological instrument data, the weather information posted on the SNS (Social Networking Service), or the like may be input to the radar data analysis calculation unit 124. ..

FIG. 3 is a block diagram showing the configuration of the snow cover amount distribution estimation device 13 according to the present embodiment. Of the analysis data stored in the analysis data storage unit 125 in the data analysis device 12, the precipitation particle discrimination result is input to the particle discrimination result correction unit 131, and the rainfall intensity analysis result is input to the snow cover estimation unit 132. Further, the one-dimensional snow cover observation data obtained by the road snow cover observation device 14 is input to the particle determination result correction unit 131 and the snow cover amount estimation unit 132.

The particle determination result correction unit 131 corrects the precipitation particle determination result based on the one-dimensional snow cover observation data and outputs it to the snow cover estimation unit 132. The snow cover estimation unit 132 estimates the snow cover distribution on the runway based on the corrected precipitation particle discrimination result, the rainfall intensity analysis result, and the one-dimensional snow cover observation data, and provides the user as snow cover information.

In the above configuration, the specific operation of the present embodiment will be described with reference to FIGS. 4 and 5.
FIG. 4 is a conceptual diagram showing how the meteorological observation system according to the present embodiment is applied. In FIG. 4, the weather radar 11 is arranged near the runway, and the observation area of the weather radar 11 is set above the runway. Further, in the runway, snow cover observation sensors 141 to 14N are embedded in the center line and three places on both sides thereof at predetermined distance intervals. The road snow cover observation device 14 periodically collects individual one-dimensional snow cover observation data output from the sensors 141 to 14N, and the particle discrimination result correction unit 131 of the snow cover distribution estimation device 13 and the rainfall intensity analysis result are the snow cover. It is sent to the estimation unit 132.

Here, in the conventional meteorological observation of the amount of snowfall or snowfall on the runway, the above-mentioned "buried runway snow / ice monitoring sensor" (applicable to the above-mentioned snowfall observation sensors 141 to 14N) is used to determine the snow quality and snowfall directly above the installation point. The quantity is observed by an optical method to obtain one-dimensional and highly accurate information. However, in this method, the information at a specific point is acquired as spatially sparse information, and it is often necessary to obtain flat snowfall / snow cover information (hereinafter referred to as area information) in a certain range. Point observation and analysis processing is required. On the other hand, the advantage of weather radar is that it can acquire surface information, but the particle discrimination results and rainfall intensity (or snowfall intensity) obtained from radar information are information above a certain level above the ground, so they are on the ground. Often the situation is different from what is observed. Therefore, in the present embodiment, the surface information obtained by the weather radar is not treated as it is as the information on the ground, but one-dimensional from the sensors 141 to 14N distributed on the runway obtained by the on-road snow observation device 14. The radar observation results are corrected based on the snow cover observation data.

FIG. 5 is a flowchart showing the flow of the estimation process in the snow cover estimation device 13 of the meteorological observation system. In FIG. 5, when the start request of the estimation process is received (step S11), the precipitation particle discrimination result and the rainfall intensity (snowfall intensity) analysis result are input (steps S12 and S13). When the precipitation particle discrimination result is input in step S12, the input of the sensor information (one-dimensional snow observation data from the snow observation sensors 141 to 14N) on the runway at the same time as the analysis time of the radar observation data is awaited. (Step S14). If the sensor information can be acquired, the precipitation particle discrimination result is corrected based on the sensor information (step S15). Subsequently, the amount of snowfall per radar observation mesh is estimated from the particle discrimination correction result in step S15 and the rainfall intensity analysis result in step S13 (step S16), and the snowfall amount distribution data is created and output (step S17). Move to cycle processing.

Here, for the above-mentioned precipitation particle discrimination, for example, a method of discriminating precipitation particles by using a fuzzy theory from a preset membership function can be used. In precipitation particle discrimination, information on temperature and humidity obtained from ground-based observation data, high-rise observation data, or model data is given. This temperature and humidity information may be given uniformly to the observation meshes, or different values may be given to all meshes. In the precipitation particle discrimination, for example, hail / hail / ice crystals / dry snow / wet snow / rain / non-precipitation echo is discriminated and classified for each mesh.

In the above rainfall intensity (snowfall intensity) analysis, the radar data mesh was described.
R [mm / h] = a × Z ^b
The rainfall intensity R is calculated using. For example, for a mesh determined to be dry / wet snow, the snowfall intensity may be calculated. Here, Z is a radar reflection factor [mm ⁶ m ^-3 ]. As the parameters of a and b, preset values may be used as they are, or may be dynamically changed by, for example, parameter optimization. For example, the parameter values may be applied uniformly within the observation range, or different values may be given for each mesh.

In the estimation device 13, in the correction of the precipitation particle discrimination result in step S15, the mesh data closest to the ground is extracted from the three-dimensional analysis data (particle discrimination result), and the precipitation particle discrimination result is corrected. .. For correction, for example, the actual observation result (dry snow, wet snow) obtained from the sensor installed on the runway is compared with the particle discrimination result obtained by the radar, and the mesh directly above the sensor is first corrected to the actual observation result. do. After that, from the corrected direct mesh, the correction processing of the discrimination result is laterally expanded by using techniques such as interpolation and extrapolation. The range of radar data to be corrected may be, for example, only the mesh corresponding to the plane on which the snow cover distribution is to be obtained. When the correction is completed for all the meshes to be corrected in this way, the process proceeds to the next step.

Next, in the estimation of the amount of snow in step S16, the amount of snow in the mesh on the ground plane corresponding to each mesh is estimated from the rainfall intensity (or snowfall intensity) analyzed for each mesh. The amount of snow cover is calculated by, for example, the following equation.
Snowfall = α x β x rainfall intensity (or snowfall intensity)
Here, α is a conversion coefficient indicating the relationship between the increase in the amount of snowfall obtained from the sensors 141 to 14N on the ground per unit time and the rainfall intensity obtained by the weather radar 11 and the data analysis device 12. This conversion coefficient is first obtained in the radar observation mesh directly above the ground sensor, and then using techniques such as averaging, interpolation, and extrapolation, the coefficient is calculated for all radar observation meshes required to obtain the snowfall distribution. Ask. β is a conversion coefficient based on the result of discrimination of precipitation particles. By changing the coefficient for wet or dry snow, it is possible to express "easiness of stacking due to snow quality". Further, when the particle discrimination result is rain, it is possible to express no increase or decrease in the amount of snow by setting the same coefficient to "0", and it is also possible to express a decrease in the amount of snow by setting the same coefficient to minus.

As described above, the meteorological observation system using the snow cover distribution estimation device according to the present embodiment uses the data observed in a two-dimensional plane obtained from the dual polarization type weather radar 11. It is possible to estimate the distribution of snowfall and temporal changes that are continuous in time and space with high frequency and high accuracy. By using such a method, it is possible to accurately estimate the amount of snow cover on a flat surface even in a place such as a runway where only snow cover observation at a certain point can be performed. More specifically, as shown in FIG. 4, by constructing a system that integrates the weather radar 11 and the buried sensors 141 to 14N on the runway, it is very useful information for air traffic control and runway maintenance. It is possible to provide.

The present invention is not limited to the above-described embodiment as it is, and at the implementation stage, the components can be modified and embodied within a range that does not deviate from the gist thereof. In addition, various inventions can be formed by an appropriate combination of the plurality of components disclosed in the above-described embodiment. For example, some components may be removed from all the components shown in the embodiments. In addition, components across different embodiments may be combined as appropriate.

11 ... Meteorological radar, 111 ... Dually polarized antenna unit, 112 ... Radar signal processing unit,
12 ... Data analysis device, 121 ... Communication interface unit, 122 ... RAW data processing unit, 123 ... RAW data storage unit, 124 ... Radar data analysis calculation unit, 125 ... Analysis data storage unit,
13 ... Snow cover distribution estimation device, 131 ... Particle discrimination result correction unit, 132 ... Snow cover estimation unit,
14 ... Road snow cover observation device, 141-14N ... Snow cover observation sensor.

Claims (4)

A weather radar that sends a dually polarized radar wave over the target area, receives the reflected wave, and outputs weather radar data.
The weather radar data from the weather radar is input, the observation data of the three-dimensional volume is generated from the weather radar data, and the precipitation particles in the sky above the target area are discriminated from this observation data in mesh units, and the rainfall and snowfall intensity are also determined. A data analyzer that analyzes
The one-dimensional snow observation data obtained by a plurality of snow observation sensors dispersed and buried on the ground in the target area is collated with the precipitation particle discrimination result in the sky obtained by the data analyzer, and the true value of the snow observation sensor is obtained. A correction unit that corrects the precipitation particle discrimination result, which is the above mesh data, to the actual observation result,
A snow cover distribution estimation device including an estimation unit that estimates the above-ground snow cover distribution in the target region based on the corrected actual observation result and the analysis result of the rainfall / snowfall intensity. The correction unit extracts the mesh data closest to the ground from the precipitation particle discrimination results, collates the precipitation particle discrimination result with the actual observation result obtained from the snow observation sensor, and directly above the snow observation sensor. The snow accumulation amount distribution estimation device according to claim 1, wherein the mesh data of the above is corrected to the actual observation result, and the correction processing of the discrimination result is extended from the corrected mesh data directly above. The estimation unit calculates the amount of snow on the mesh on the ground plane corresponding to each mesh from the rainfall intensity analyzed for each mesh.
Snowfall = α x β x rainfall intensity (or snowfall intensity)
Here, α: a conversion coefficient indicating the relationship between the increase in the amount of snowfall obtained from the snow cover observation sensor per unit time and the rainfall intensity, and β are claims estimated by calculating the conversion coefficient based on the precipitation particle discrimination result. Item 1. The snow cover distribution estimation device according to Item 1. A dually polarized radar wave is sent over the target area, the reflected wave is received, and weather radar data is acquired.
Observation data of three-dimensional volume is generated from the weather radar data, and precipitation particles in the sky above the target area are discriminated from this observation data in mesh units, and rainfall and snowfall intensity are data-analyzed .
The one-dimensional snow observation data obtained by a plurality of snow observation sensors dispersed and buried on the ground in the target area is collated with the precipitation particle discrimination result in the sky obtained by the data analysis, and directly above the snow observation sensor. The precipitation particle discrimination result, which is the mesh data of, is corrected to the actual observation result.
A snow cover distribution estimation method for estimating the above-ground snow cover distribution in the target area based on the corrected actual observation result and the analysis result of rainfall / snowfall intensity.

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