JP2019219209A - Processing device, processing method, and program - Google Patents

Abstract

To provide a processing device, a processing method, and a program with which it is possible to derive information relating to ground rainfall with good accuracy.SOLUTION: The processing device of an embodiment comprises an acquisition unit, a selection unit, and a derivation unit. The acquisition unit acquires observation information that indicates an atmospheric state in each of a plurality of divided areas into which a prescribed area is divided in the horizontal and vertical directions and quality information that indicates the quality of observation information for each of the divided areas. The selection unit selects, on the basis of information acquired by the acquisition unit, a target divided area from among the divided areas where the location in the horizontal direction is included in a common divided area group. The derivation unit derives rainfall information on the basis of observation information for the target divided area having been selected by the selection unit.SELECTED DRAWING: Figure 1

Description

  An embodiment of the present invention relates to a processing device, a processing method, and a program.

  2. Description of the Related Art There is known an apparatus for analyzing ground precipitation intensity from reflection intensity information observed by a weather radar. In the related art, there were cases where it was not possible to accurately analyze the ground precipitation intensity.

JP-A-2003-344556

HYANGSUK PARK, AV RYZHKOV, D. S ZRNIC and KYUNG-EAK KIM, `` The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS '', WEATHER AND FORECASTING, American Meteorological Society, 2009, Volume24, p730- 748

  The problem to be solved by the present invention is to provide a processing device, a processing method, and a program that can more accurately derive information on the amount of ground rainfall.

  The processing device according to the embodiment includes an acquisition unit, a selection unit, and a derivation unit. The acquisition unit acquires observation information indicating the state of the atmosphere for each of a plurality of divided regions obtained by dividing a predetermined region in the horizontal direction and the vertical direction, and quality information indicating the quality of the observation information for each of the divided regions. The selection unit selects a target divided region from among the divided regions included in the divided region group having the same position in the horizontal direction based on the information acquired by the acquisition unit. The deriving unit derives rainfall information based on the observation information of the target divided region selected by the selecting unit.

FIG. 1 is a diagram showing a configuration of a processing system 1. FIG. 3 is a conceptual diagram of a radio wave emitted by the radar device 10. FIG. 2 is a diagram illustrating a configuration of a processing device 20 and a display information generation device 50. 5 is a flowchart illustrating a flow of a process executed by the processing device. The figure for demonstrating the observation information D. 9 is a flowchart illustrating a flow of a process performed by a selection unit. It is a figure showing an example of signs that a ground mesh is selected. 9 is a flowchart illustrating a flow of a process performed by a derivation unit 28. The conceptual diagram of the calculation method of the ground precipitation intensity set for every mesh block MB (ground mesh). FIG. 7 is a diagram illustrating an example of an image IM displayed on a display unit of the terminal device 60.

  Hereinafter, a processing device, a processing method, and a program according to an embodiment will be described with reference to the drawings.

(1st Embodiment)
FIG. 1 is a diagram illustrating a configuration of the processing system 1. The processing system 1 including the processing device 20 includes the radar device 10, the processing device 20, and the display information generation device 50. The radar device 10 and the processing device 20 communicate via a dedicated line or the like. The processing device 20 and the display information generating device 50 communicate via a network NW1 such as a LAN (Local Area Network). The display information generating device 50 communicates with the terminal device 60 via a network NW2 such as a WAN (Wide Area Network). Note that the processing device 20 and the display information generating device 50 may be formed integrally.

  The radar device 10 includes an antenna 12 and an antenna-side control device 14. The radar device 10 is, for example, a weather radar for observing the state of the atmosphere. The antenna 12 is, for example, a phased array antenna including a plurality of antenna elements and capable of electronically changing a directional angle. Note that the radar device 10 may be a parabolic radar device. The radar device 10 three-dimensionally observes the state of the atmosphere by rotating the antenna 12 in the horizontal direction while electronically scanning the elevation direction. The antenna 12 transmits and receives radio waves under the control of the antenna-side control device 14.

  In the following description, the radar device 10 will be described as a dual-polarization phased array radar device. However, a radar device that does not use dual polarization may be used instead, or a parabolic type radar device may be used. Radar device. The dual polarization phased array radar device transmits and receives radio waves that oscillate in the horizontal and vertical directions, and observes the state of the atmosphere based on the reception results.

  The antenna-side control device 14 includes a radar-side control unit 16 and an information storage unit 18. The radar control unit 16 causes the antenna 12 to transmit a fan beam having a wide elevation beam width. The radar control unit 16 performs a DBF (Digital Beam Forming) process. The radar-side control section 16 receives the reflected radio wave at a time when the transmitted fan beam hits a scatterer such as precipitation particles, and simultaneously generates observation information (polarization parameters) in a plurality of elevation ranges.

  The information accumulation unit 18 accumulates the observation information acquired by the radar-side control unit 16 and transmits the accumulated information to the processing device 20.

  Here, the characteristics of the dual polarization phased array radar device will be described. FIG. 2 is a conceptual diagram of a radio wave emitted by the radar device 10. For example, the radar device 10 radiates a horizontally polarized wave to the atmosphere as shown in the left diagram of FIG. 2 and a vertically polarized wave as shown in the right diagram of FIG. Then, the radar device 10 acquires the returned reflected radio waves when the emitted two types of radio waves hit the particles in the atmosphere. The radar apparatus 10 acquires information on the shape of the particles in the atmosphere in the vertical direction and the shape in the horizontal direction by acquiring reflected radio waves for two types of radio waves.

  For example, raindrops in the atmosphere have different shapes depending on the size. Hail, hail, snow, etc. have different shapes. For example, large raindrops may be flat. The radar device 10 obtains information indicating the shape of the raindrop in the horizontal direction from the reflected radio wave with respect to the horizontal polarization, and obtains not only the intensity (echo intensity) of the reflected radio wave but also the vertical direction of the raindrop with the reflected radio wave with respect to the vertical polarization. Information indicating the shape can be obtained. The radar apparatus 10 can acquire information such as a reflection factor difference, an inter-polarization correlation coefficient, and an inter-polarization phase difference change rate from the reflected radio waves. The reflection factor difference is a parameter relating to the aspect ratio of the particles. The polarization correlation coefficient is a correlation coefficient between the received power (received signal) of the horizontally polarized wave and the vertically polarized wave, which are reflected radio waves. The inter-polarization phase difference change rate is a parameter related to the phase difference between the phase of the horizontal polarization and the phase of the vertical polarization, which are reflected radio waves.

  Further, when two types of radio waves pass through particles having a flat shape or the like, a difference occurs in the phases of these radio waves. The radar device 10 can acquire the inter-polarization phase difference, which is the phase difference when the radar device 10 reciprocates between the particle and the particle for each of the horizontal polarization and the vertical polarization. The inter-polarization phase difference change rate is the amount of change or differentiation of the inter-polarization phase difference in the distance direction.

  FIG. 3 is a diagram showing the configuration of the processing device 20 and the display information generating device 50. The processing device 20 includes, for example, an acquisition unit 22, a processing unit 24, a selection unit 26, a derivation unit 28, an interpolation unit 30, an information transmission unit 32, and a storage unit 40. The acquisition unit 22, the processing unit 24, the selection unit 26, the derivation unit 28, the interpolation unit 30, and the information transmission unit 32 may be realized by a processor such as a CPU (Central Processing Unit) executing a program. These functional units may be realized by hardware such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), or the like. It may be realized by cooperation of software and hardware. Further, the above-described program may be stored in a storage device in advance, or may be stored in a removable storage medium such as a DVD or a CD-ROM, and the storage medium is mounted on a drive device of the processing device 20. May be installed in the storage device. The storage unit 40 is realized by a storage device such as a random access memory (RAM), a read only memory (ROM), a hard disk drive (HDD), and a flash memory.

  The acquisition unit 22 acquires observation information from the radar device 10. The obtained observation information is stored in the storage unit 40. The processing device 20 may be formed integrally with the radar device 10. In this case, the acquisition unit 22 acquires observation information from the information storage unit 18 using a communication bus or the like in the device.

  The processing unit 24 performs a process of determining precipitation particles and acquires quality information based on the observation information acquired by the acquiring unit 22. The information equivalent to the processing result of the processing unit 24 may be acquired by the acquiring unit 22 from another device. The details of the processing of the processing unit 24 and the function units (selection unit 26 and derivation unit 28) described later will be described later.

  The selection unit 26 selects a target divided region from among the divided regions included in the divided region group having a common horizontal position based on the information acquired by the acquisition unit 22.

  The deriving unit 28 derives rainfall information based on the observation information of the target divided region selected by the selecting unit 26. The interpolating unit 30 interpolates the target divided region with respect to the divided region group in which the selection unit 26 has not selected the target divided region in the divided region group. The information transmitting unit 32 transmits a processing result of the processing device 20 to the display information generating device 50.

  The display information generation device 50 includes a display information generation unit 52 and a display information transmission unit 54. The display information generating unit 52 generates display information (image information) for displaying information including the processing result on the display unit of the terminal device 60 based on the processing result transmitted from the information transmitting unit 32. The display information transmitting unit 54 transmits the display information generated by the display information generating unit 52 to the terminal device 60.

[Process for deriving ground precipitation intensity]
FIG. 4 is a flowchart illustrating a flow of a process performed by the processing device 20. First, it is determined whether the acquisition unit 22 has acquired the observation information D for one cycle stored in the information storage unit 18 of the radar device 10 (Step S100).

  The observation information D is information indicating the echo intensity acquired by the radar device 10 for each mesh (described later) and each observation cycle. The observation information D is not limited to the information indicating the echo intensity, but may be any information that can determine the type of the particle, the shape of the particle, the presence or absence of the particle, and the like.

  FIG. 5 is a diagram for explaining the observation information D. Hereinafter, description will be made using XYZ coordinates as necessary. The observation information D is information obtained during a period from the start point to the end point of the driving of the antenna 12 of the radar apparatus 10 in the horizontal direction. Observation information D acquired between the start point and the end point is observation information acquired in one cycle. The mesh M is a divided area divided by a predetermined width in the distance direction (Y direction), the azimuth direction (X direction), and the altitude direction (Z direction) from the radar device 10. In the illustrated example, the mesh M is approximated by a cube because the observation information D is a position sufficiently far from the radar device 10. A set of meshes M having the same horizontal direction (distance direction and azimuth direction) but different only in the altitude direction (vertical direction) is referred to as a “mesh block MB”. The mesh block MB is an example of “a group of divided regions having a common position in the horizontal direction”.

  Returning to the description of FIG. When the observation information D for one cycle is obtained (or when the observation information D of a predetermined area is obtained), the processing unit 24 performs a process of determining the precipitation particles (step S102). In this determination, it is determined whether the mesh M has a precipitation particle (for example, hail, hail, ice crystal, dry snow, wet snow, rain) or a non-precipitation echo (ground clutter). It is classified for each three-dimensional mesh.

  The processing unit 24 performs a process of determining precipitation particles using a known method. The processing unit 24 determines a precipitation particle by applying a preset membership function to fuzzy logic. The membership function is a function that outputs a degree indicating how much the element x of the set X belongs to the set A to which the fuzzy theory is applied. The set A is a set that expresses that an element x of a certain set X belongs to the set A with ambiguity, and is a set characterized by a membership function.

  For example, the membership function is a function that outputs a value closer to “1” as the degree of belonging to the set A is higher, and outputs a value closer to “0” as the degree of belonging to the set A is lower. For example, in the determination of precipitation particles, the processing unit 24 associates observation information on the ground, observation information on a high-rise building, or information on temperature and humidity obtained from model information with an observation target observation mesh. The ground observation information, the high-rise observation information, or the temperature and humidity information may be uniformly associated with the observation mesh, or different values may be associated with each observation mesh. Then, the processing unit 24 determines the precipitation particles included in the mesh using the information associated with the observation mesh and the fuzzy logic. In this flowchart, the process proceeds to the next step regardless of the determination result.

  Next, the processing unit 24 acquires various pieces of quality information for each mesh M (step S104). The quality information is, for example, an index such as a QIA (Quality Index Algorithm), an SNR (Signal Noise Ratio), and a CSR (Clutter Signal Ratio). A detailed calculation method for QIA is described in Park et al. (2009), which is Non-Patent Document 1, and can be used as an index for measuring data quality of observed polarization parameters. Since QIA is an index by which the quality of polarization parameter data can be estimated from its own observation data, it is effective to use QIA in a system in which processing is completed with information obtained from one radar device. . This data quality is influenced by radar calibration errors, radio wave attenuation, NBF (Nonuniform Beam Filling), partial beam blocking (Partial Beam Blockage), variations in correlation coefficient between polarizations in scattering cross section, and reception noise. Is taken into account. The polarization parameters of interest are the reflection intensity Z, the reflection factor difference ZDR, the inter-polarization correlation coefficient ρhv, and the inter-polarization phase difference change rate KDP. The input parameters (observation data) are horizontal reflection intensity, radar reflection factor difference, inter-polarization phase difference, and inter-polarization correlation coefficient, and the SNR (Signal Noise Ratio) may be directly input. , May be calculated from other input parameters. The QIA calculated for the reflection intensity Z is QIAZ, the QIA calculated for the reflection factor difference ZDR is QIAZDR, the QIA calculated for the inter-polarization correlation coefficient ρhv is QIAρhv, and the inter-polarization phase difference change rate KDP. Is calculated as QIAKDP. The smaller these values are, the lower the quality of the polarization parameter of interest is.

  “SNR” is an index obtained by subtracting the noise level from the received power received by the radar device 10. The smaller the value of “SNR”, the lower the quality of the information (the higher the level of noise included in the received power).

  “CSR” is obtained based on information on received power before and after processing the influence of reflected radio waves corresponding to clutter (objects not to be measured). The influence is an influence on the processing result of the embodiment. The larger the value of “CSR” is, the lower the quality of information is (the greater the influence of clutter on the mesh M).

  Next, the selection unit 26 selects a mesh (ground mesh) to be applied as ground rainfall information from the mesh blocks MB (step S106). The selection unit 26 selects the ground mesh to be used for deriving the ground precipitation intensity, by using the results of the precipitation particle determination and the quality information obtained in the processing of steps S102 and S104 and the received power as inputs. This processing will be described later (see FIG. 6).

  Next, the deriving unit 28 selects a calculation method used to calculate the ground precipitation intensity in the ground mesh selected in step S106 (step S108). Next, the deriving unit 28 derives the ground precipitation intensity in the ground mesh according to the ground precipitation intensity deriving method selected in step S108 (step S110). The processing in steps S108 and S110 will be described later (see FIGS. 6 and 8).

  Next, the deriving unit 28 outputs the derived mesh analysis information (the processing result of step S110) (step S112). The deriving unit 28 outputs, for example, the mesh analysis information to the information transmitting unit 32 or causes the storage unit 40 to store the information.

  Next, the interpolation unit 30 determines whether the ground precipitation intensity has been calculated for all ground meshes (Step S114). If the ground precipitation intensity has not been calculated for all the ground meshes (there is a mesh block MB having no mesh selected as the ground mesh), a missing point exists, so the interpolation unit 30 determines the missing point Perform interpolation processing. For example, the interpolation unit 30 performs a three-dimensional interpolation process on the missing points (step S116).

  For example, if the ground precipitation intensity is calculated around the mesh block MB at the missing point and the missing point is isolated, the interpolating unit 30 can obtain a continuous distribution. Surface precipitation intensity can be interpolated for points. In the interpolation, a mesh around the mesh block MB of the missing point is searched three-dimensionally (a two-dimensional search of real XY may be used), and a ground mesh whose ground precipitation intensity is calculated is included in the searched mesh. Interpolation is performed when there is more than the threshold. As the interpolation method, a method such as an extrapolation method, a nearest neighbor method, a linear interpolation method, and a Cressman interpolation method may be used.

  When the ground precipitation intensity has been calculated for all the ground meshes, the processing of one routine of this flowchart ends. However, if there is a missing point even after performing the processing in the interpolation unit 30, the processing may be terminated assuming that the ground precipitation intensities have been calculated for all ground meshes.

[Process for selecting ground mesh]
FIG. 6 is a flowchart illustrating a flow of a process performed by the selection unit 26. This is a process performed for each mesh block MB. First, the selection unit 26 acquires the quality information of the inspection target mesh block MB and the information on the mesh M (step S200). The information on the mesh is information on the position of the mesh M and observation information D on the mesh. In this processing, the lowest layer mesh of the mesh block MB is selected, and the processing is started sequentially from this mesh. Hereinafter, the processing target mesh M is referred to as a “target mesh”.

  Next, the selection unit 26 determines whether or not the target mesh is equal to or lower than the allowable altitude (Step S202). It is checked whether the height of the target mesh is located in the lower layer with respect to the height allowed as “ground precipitation”. When this is not satisfied (when the target mesh is not below the allowable altitude), it is determined that the mesh M corresponding to the ground mesh is absent (missing measurement). Then, the next processing target mesh block MB is selected, and the processing of this flowchart is performed. In the processing after step S204, the processing is performed using the input information values (such as the information acquired in steps S102 and S104 in FIG. 3).

  When the target mesh is equal to or less than the allowable altitude, the selection unit 26 determines whether or not the radar reception intensity Pr of the reflected radio wave received by the radar device 10 is equal to or greater than a threshold (Step S204).

  When the radar reception intensity Pr is equal to or larger than the threshold, the selection unit 26 determines whether or not the particle is determined to be a precipitation particle in the result of the particle determination (Step S206).

  When it is determined that the particles are precipitation particles as a result of the particle determination, the selecting unit 26 determines whether “SNR” is equal to or larger than a threshold (Step S208).

  When “SNR” is equal to or larger than the threshold, the selection unit 26 determines whether “CSR” is equal to or smaller than the threshold (Step S210).

  When “CSR” is equal to or smaller than the threshold, the selection unit 26 determines whether “QIA” is equal to or larger than the threshold (Step S212).

  When “QIA” is equal to or larger than the threshold, the selection unit 26 selects the target mesh as the ground mesh (Step S214). “QIA” in step S212 includes “QIAZ” calculated for the reflection intensity Z, “QIAZDR” calculated for the reflection factor difference ZDR, and “QIAρhv” calculated for the inter-polarization correlation coefficient ρhv. Of the “QIAKDP” calculated for the inter-polarization phase difference change rate KDP, at least one “QIA” may be used. When a plurality of “QIAs” are used for processing, a threshold is set for each “QIA”, and the threshold is compared with the QIA corresponding to the threshold.

  If a negative determination is made in the processing of steps S204 to S212, the selection unit 26 selects the next target mesh and repeats the above processing. Thus, the processing of one routine of this flowchart ends.

  The order of the above-described processes may be changed as appropriate. However, the process of step S202 is performed prior to the processes of steps S204 to S212, so that the processing load is reduced or the efficiency of the process is reduced. Or to improve. This is because information whose radar reception intensity Pr is not equal to or larger than the threshold is information that is not suitable for use as information in the first place.

  In the example shown in FIG. 6, the inspection is passed (selected as the ground mesh) when “AND” is satisfied for all the conditions. However, the conditions for the inspection pass are not limited to this. If the inspection fails in the middle, the inspection of the mesh M immediately above the inspection target mesh (target mesh) is performed. By repeating this, a ground mesh or missing data is defined for one mesh block MB in the vertical direction. Further, by developing this in the horizontal direction, a ground mesh is defined on a two-dimensional plane in the observation area of the radar device 10.

  FIG. 7 is a diagram illustrating an example of how a ground mesh is selected. For example, it is assumed that the processing has been executed from the mesh block MB1 in the minus X direction in FIG. For example, in the mesh block MB1, a mesh to which “〇” is added is selected as the ground mesh, in the mesh block MB2, it is determined that there is no ground mesh block, and in the mesh block MB10, “〇” is displayed. The assigned mesh is selected as the ground mesh.

[Process for determining calculation method]
FIG. 8 is a flowchart illustrating a flow of a process performed by the deriving unit 28. A specific example of the calculation method of the ground precipitation intensity determined in the processing of this flowchart will be described later.

  First, the deriving unit 28 determines whether or not the ground mesh is lower than the lower end height of the molten layer (step S300). Here, the altitude (upper end, lower end) of the melting layer derived from ground observation information, high-rise observation information, or temperature and humidity information obtained from model information is used. The processing device 20 may derive the altitude of the molten layer, or may obtain it from another device. Further, the processing device 20 may derive the altitude of the molten layer based on the observation information acquired from the radar device 10.

  When it is determined that the ground mesh is lower than the lower end altitude of the melting layer, the deriving unit 28 determines whether the determination result of the precipitation particles is rain (step S302). When the determination result of the precipitation particles is rain, the derivation unit 28 determines whether the reflection intensity Z and the rate of change in phase difference KDP between the polarizations are equal to or greater than the thresholds defined respectively (step S304). Note that the deriving unit 28 determines whether or not the comparison target (the reflection intensity Z and the inter-polarization phase difference change rate KDP) is included in a predetermined range defined respectively, instead of determining whether the difference is equal to or greater than the threshold value. May be determined.

  When the reflection intensity Z or the rate of change in polarization phase difference KDP is equal to or larger than the threshold, the derivation unit 28 determines to adopt the derivation method for the rainfall region 1 (step S306). The rainfall area 1 is an area where it is predicted that the amount of precipitation is relatively large.

  If the reflection intensity Z or the rate of change in polarization phase difference KDP is not greater than or equal to the threshold value, the deriving unit 28 determines to employ the deriving method for the rainfall region 2 (step S308). The rainfall area 2 is an area where the amount of precipitation is predicted to be relatively small.

  As described above, when the determination result of the precipitation particles derived based on the real-time observation information acquired from the radar device 10 in steps S302 to S308 is determined to be rain, the derivation unit 28 calculates the rainfall area. Select Further, in the rainfall area, the area is divided into a rainfall area 1 and a rainfall area 2 according to the threshold value of the reflection intensity Z and the phase difference change rate KDP between polarizations.

  When it is determined in step S300 that the altitude is lower than the lower end height of the melting layer (when it is determined that the altitude is lower than the lower end height of the melting layer), the surface precipitation is expected to be rain, but step S302. When the result of the determination of the precipitation particles is not rain (that is, when the particles in the solid phase are determined), the derivation unit 28 determines that the derivation method of the snowfall area is adopted, and the process of step S312 is performed. move on.

  When it is determined in the process of step S300 that the ground mesh is not lower than the lower end height of the molten layer, the deriving unit 28 determines whether the ground mesh is lower than the upper end height of the molten layer (step S310). If the ground mesh is equal to or lower than the upper end height of the melting layer, the deriving unit 28 determines to adopt the deriving method of the melting layer area (step S314).

  If the ground mesh is not lower than or equal to the upper end height of the melting layer, the deriving unit 28 determines to adopt the snowfall area deriving method (step S312). Thus, the processing of one routine of this flowchart ends.

[Specific example of calculation method of precipitation intensity]
(Rainfall area 1)
In the rainfall area 1, the ground precipitation intensity Rr is calculated by, for example, the following equation (1).
“Z” is the reflection intensity, “B” is the first parameter, and “β” is the second parameter.
Z = B × Rr ^β (1)

(Rainfall area 2)
In the rainfall area 2, the ground precipitation intensity R is calculated by, for example, the following equation (2).
“Α” is a third parameter, “b” is a fourth parameter, and “f” is a transmission frequency of a radio wave of the radar device 10. “KDP” is a rate of change in phase difference between polarized waves.
R = α × (KDP / f) ^b (2)

(Snowfall area)
In the snowfall area, the ground precipitation intensity Rs is calculated by, for example, the following equation (3). “Bs” is a fifth parameter, and “βs” is a sixth parameter.
Z = B _s × Rs ^βs (3)

(Melting layer area)
In the melting zone, the surface precipitation intensity is calculated using the values calculated from the ground mesh just below the upper end of the melting layer and just above the lower end of the melting layer (just before the lower end and just after the upper end when viewed in a two-dimensional plane). Desired. The calculation method may be, for example, Expression (4) using a weighted average method as described below, or a method using a linear interpolation method or the like. Here, “m” is the distance from the upper end of the melting layer in the ground mesh to be calculated, and “n” is the distance from the lower end of the melting layer in the ground mesh to be calculated.
Rm = (m / m + n) ^* Rr + (n / m + n) ^* Rs (4)

  As described above, for the selected ground mesh, the processing device 20 calculates the ground precipitation intensity by using the ground precipitation intensity calculation method suitable for the ground mesh. FIG. 9 is a conceptual diagram of a method of calculating the ground precipitation intensity set for each mesh block MB (ground mesh). As shown in FIG. 9, the calculation method of the ground precipitation intensity is set for each mesh block MB. Then, information to be provided to the terminal device 60 is generated based on the ground precipitation intensity calculated for each mesh block MB.

  The display information generation unit 52 of the display information generation device 50 generates information suitable for the end user with respect to the two-dimensional distribution of ground precipitation intensity within the observation range of the radar device 10. “Information suitable for the end user” includes, for example, integrated rainfall in the area, hourly rainfall integrated in the specified time, inflow rainfall flowing into a certain point or area (how much flows into a river or manhole), soil Effective rainfall, which indicates the effect on rainfall. Further, the processing device 20 may limit the amount of information flowing to the subsequent stage at this point in order to reduce the amount of information.

  In addition, the display information generation unit 52 generates rainfall information to be provided to the user using the ground precipitation intensity derived for each mesh block MB. In addition, the display information generation unit 52 determines, for example, whether or not the ground precipitation intensity in a local area is equal to or greater than a set threshold. Generates information indicating an alert indicating. The information indicating this alert is an example of rainfall information. Further, the information itself indicating the local ground precipitation intensity may be used as image information.

  Further, the display information generation unit 52 outputs the output result of the numerical weather forecast model, the ground weather observation information, the remote sensing weather instrument information, the land use information, the topographic information, the river basin information, the geological information, the route information, the traffic information, and the like. The information may be acquired, and the rainfall information may be generated by combining the information with the ground precipitation intensity in a local area. For example, the display information generating unit 52 generates information indicating that the transportation will be affected, information indicating that there is a possibility that danger will occur in an area where the ground is weak, information indicating that the river will increase, and the like.

  FIG. 10 is a diagram illustrating an example of an image IM displayed on the display unit of the terminal device 60. For example, as shown in FIG. 10, the image IM includes information indicating the intensity of rain and information indicating that there is a warning that the river may increase. The user can recognize the distribution of rain and the danger caused by rain by referring to the image IM.

[Summary]
According to the processing device 20 of the present embodiment, by using the information obtained from the dual-polarization phased array meteorological radar with high frequency and without gaps, the observation information continuously and spatiotemporally at a period of about 30 seconds. From this, it is possible to analyze the distribution and temporal change of the surface precipitation intensity with high frequency and high accuracy, and to provide the user with the rainfall information with high frequency. Furthermore, by combining local ground precipitation intensity as observation information with land information, route information, and traffic information to generate rainfall information, the risk of human and economic heavy snowfall can be accurately and quickly determined. It will be possible to notify and provide users with accurate information. Specifically, it is expected that providing information through general-purpose application software, SNS, etc. will help alert the general public and evacuation. It is also expected that local governments, road managers, railway operation managers, bus operation managers, etc. will effectively contribute to speeding up response to sudden heavy rainfall.

[Comparison]
Here, when obtaining the two-dimensional distribution of the surface precipitation intensity from the information observed by the weather radar, the information obtained by the plurality of radar devices is used, and the optimum surface precipitation intensity distribution is obtained by combining them. May be. However, for geographical reasons (geographical environment where multiple radar devices cannot be installed) and economical reasons (difficult to deploy multiple radar devices on a network), ground precipitation intensity is simply reduced. It is necessary to analyze with high accuracy by one radar device, but it is hard to say that a method for achieving this has been established.

  For example, when obtaining the ground precipitation intensity distribution with one parabola-type weather radar device, based on the information for each elevation angle that is spatially sparsely observed, the altitude information and a previously prepared map, “ Elevation angle information to be applied as "ground precipitation intensity" was defined and used as the surface precipitation intensity distribution.

  However, in this method of the parabolic radar device, since spatially sparse information is input, information distant from the ground in the altitude direction is also treated as ground precipitation intensity, and there is a problem in its accuracy.

  In addition, when the altitude information, the map, and the like are statically handled, a case may occur in which information of a mesh that is originally closest to the ground and of good quality is not applied. High temporal resolution information is needed to capture rapid weather phenomena. In the above method, three-dimensional information is required, and parabola-type weather radar generally acquires the three-dimensional information in 5 to 10 minutes, so it is difficult to provide the surface precipitation intensity in real time. There is.

  Heavy rain, which causes disasters and causes economic loss, often occurs in a short time and locally, and the two-dimensional spatially dense ground precipitation intensity obtained by meteorological radar can be accurately and accurately calculated. It is important to be able to analyze the frequency. However, for the reasons described above, there is a problem that it is difficult to provide ground precipitation intensity information with high accuracy and high temporal resolution, particularly using a single weather radar information.

  Also, with the information obtained by the single-polarization weather radar device, the rainfall intensity distribution behind the heavy rainfall area may not be observed due to rainfall attenuation. Furthermore, since the quality information (including particle discrimination and the like) that can be obtained is limited, it has been difficult to optimize application information using the quality information.

  On the other hand, in the present embodiment, observation information including the polarization parameter can be acquired using the dual-polarization weather radar, and effective rain attenuation correction and quality information can be calculated using the observation information. is there. Then, by effectively using the polarization parameter observation information obtained by the dual polarization phased array weather radar that is frequently observed without gaps and the quality information obtained from the obtained polarization parameter observation information, The method of analyzing the surface rainfall intensity with the weather radar of Japan has been improved, and it is possible to provide continuous and high-precision rainfall information based on the ground precipitation intensity distribution. As a result, it is expected that the accuracy of determining the risk of disaster and the risk of impeding economic activities will be improved.

  According to the embodiment described above, observation information indicating the state of the atmosphere for each of a plurality of divided regions in which a predetermined region is divided in the horizontal direction and the vertical direction, and quality information indicating the quality of the observation information for each of the divided regions And a selection unit that selects a target divided region from among the divided regions included in the divided region group having the same position in the horizontal direction based on the information acquired by the acquiring unit. With the deriving unit that derives rainfall information based on the observation information of the target divided region selected by the unit, it is possible to more accurately derive information about the amount of ground rainfall.

  While some embodiments of the invention have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. These embodiments can be implemented in other various forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the invention described in the claims and equivalents thereof.

1 processing system, 10 radar device, 20 processing device, 22 acquisition unit, 24 processing unit, 26 selection unit, 28 derivation unit, 30 interpolation unit, 32 information transmission unit, 40 storage unit , 50 ° display information generating device, 52: display information generating unit, 54: display information transmitting unit, 60 ° terminal device

Claims (11)

Obtaining information indicating the state of the atmosphere for each of a plurality of divided regions where the predetermined region is divided in the horizontal direction and the vertical direction, and an acquisition unit that acquires quality information indicating the quality of the observation information for each of the divided regions,
A selection unit that selects a target divided region from among the divided regions included in the divided region group having the common position in the horizontal direction based on the information acquired by the acquiring unit;
A deriving unit that derives rainfall information based on the observation information of the target divided region selected by the selecting unit,
A processing device comprising: The selection unit is configured to select the target divided region based on a comparison between a numerical value indicated by the quality information and a threshold,
The processing device according to claim 1. The quality information is an index indicating the quality of the reflection intensity, an index indicating the quality of the reflection factor difference, an index indicating the quality of the inter-polarization correlation coefficient, and an index indicating the quality of the inter-polarization phase difference change rate. , Including one or more indicators,
The processing device according to claim 1. The quality information, further, an index based on the received power received by the radar apparatus that has obtained the observation information and the noise included in the received power, before and after processing to exclude a signal indicating clutter from the observation information Including one or both of an index derived based on the received power of
The processing device according to claim 3. The acquisition unit further acquires a result of particle determination for each of the divided regions derived based on the observation information,
The selecting unit further selects the target divided region based on the result of the particle determination,
The processing device according to claim 1. The acquisition unit further acquires the radar reception intensity of the radar device that has acquired the observation information,
The selecting unit selects the target divided region based on the radar reception intensity obtained by the obtaining unit,
The processing device according to claim 1. The deriving unit derives rainfall information based on a comparison between the distribution of the molten layer and the position in the altitude direction of the target divided region selected by the selecting unit.
The processing device according to claim 1. The observation information is information obtained by a radar device that transmits and receives dual polarization.
The processing device according to claim 3. The selection unit, from each of the plurality of divided region group included in the observation region of the observation target, selects the target divided region,
The deriving unit derives rainfall information based on the observation information of the selected target divided region,
The processing device according to claim 1. Computer
Obtain observation information indicating the state of the atmosphere for each of a plurality of divided regions where the predetermined region is divided in the horizontal direction and the vertical direction, and obtain quality information indicating the quality of the observation information for each of the divided regions,
Based on the obtained information, select a target divided region from among the divided regions included in the divided region group having the same horizontal position,
Deriving rainfall information based on the observation information of the selected target divided region,
Processing method. On the computer,
Observation information indicating the state of the atmosphere for each of a plurality of divided regions where the predetermined region is divided in the horizontal direction and the vertical direction, and quality information indicating the quality of the observation information for each of the divided regions,
Based on the obtained information, the target position is selected from among the divided regions included in the divided region group having the same horizontal position,
Deriving rainfall information based on the observation information of the selected target divided region,
program.

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