JPWO2018168165A1 - Weather forecasting device, weather forecasting method, and program - Google Patents

Abstract

  The weather forecasting device of the embodiment has a determination unit and a risk deriving unit. The determination unit determines the type of precipitation band in the sky based on the meteorological observation data obtained by the radar device. The risk deriving unit derives the risk of disaster due to the precipitation band in accordance with the type of the precipitation band determined by the determination unit.

Description

  Embodiments of the present invention relate to a weather prediction device, a weather prediction method, and a program.

  In recent years, heavy rainfall disasters have been caused by dredging of rivers and large-scale slope failures. Such disasters are said to be caused by the linear precipitation zone stagnating at a certain point for a long time. Related to this, there is known a technique of observing rain clouds such as cumulonimbus clouds in the sky and deriving the precipitation intensity in the sky.

  However, in the prior art, it is difficult to accurately predict the risk such as heavy rain disaster caused by the linear precipitation zone.

JP, 2014-1974, A

  The problem to be solved by the present invention is to provide a weather prediction device, a weather prediction method, and a program capable of accurately predicting the risk due to a meteorological disaster.

  The weather forecasting device of the embodiment has a determination unit and a risk deriving unit. The determination unit determines the type of precipitation band in the sky based on the meteorological observation data obtained by the radar device. The risk deriving unit derives the risk of disaster due to the precipitation band in accordance with the type of the precipitation band determined by the determination unit.

BRIEF DESCRIPTION OF THE DRAWINGS The figure which shows an example of a structure of the weather prediction apparatus 100 in 1st Embodiment. The figure which shows an example of the meteorological observation data 132. FIG. 6 is a flowchart showing an example of a series of processes by the control unit 110 in the first embodiment. It illustrates an example of dividing the observation space virtually mesh area M _i. Diagram for explaining a method of extracting a mesh area M _i. The figure which shows an example of the precipitation zone characteristic information 136. FIG. The figure which shows an example of strike ST of a linear precipitation zone. The figure which shows the other example of strike ST of a linear precipitation zone. The figure which shows the other example of strike ST of a linear precipitation zone. The figure for demonstrating the method of scoring. The figure which shows an example of the screen displayed on a predetermined | prescribed apparatus. 9 is a flowchart showing an example of a series of processes by the control unit 110 in the second embodiment. The figure which shows an example of a process result.

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

First Embodiment
FIG. 1 is a diagram illustrating an example of the configuration of the weather prediction device 100 according to the first embodiment. The weather prediction device 100 in the first embodiment determines the type of linear precipitation band based on the weather observation data output from the weather radar device 200. A linear precipitation zone is a collection of precipitation clouds (for example, cumulonimbus clouds) having a linear form, which often stagnate in the sky and cause meteorological disasters such as heavy rain, heavy snow, hail, hail on the ground . The weather prediction apparatus 100 derives the risk of a meteorological disaster predicted to be caused by the precipitation band according to the type of the linear precipitation band.

  The weather radar device 200 includes, for example, a phased array antenna. The weather radar device 200 electronically varies the directivity angle by controlling the phase of a signal input to an array of antenna elements constituting a phased array antenna or a signal output from the antenna element. The weather radar device 200 transmits and receives radio waves while changing the directivity angle of the antenna. For example, the weather radar device 200 changes the directivity angle in the elevation direction (vertical direction) within a certain angular range (for example, 90 degrees) by electrical phase control. In addition, the weather radar device 200 mechanically varies the pointing angle in the azimuth direction (horizontal direction) by a drive mechanism (not shown). Also, the weather radar device 200 may change the pointing angle by electrical phase control in both the azimuth direction and the elevation direction.

  In addition to the phased array antenna described above, the weather radar device 200 may include a parabola antenna, a patch antenna, a pole antenna, a shunt feed antenna, a slot antenna, and the like. For example, when a parabola antenna is included, the weather radar device 200 transmits and receives radio waves while mechanically changing the directivity angle of the antenna by a drive mechanism (not shown).

  The weather radar device 200 converts the received radio wave into an electric signal, and performs signal processing such as demodulation, amplification of signal strength, and frequency conversion. Then, the weather radar device 200 transmits a signal subjected to signal processing (hereinafter, referred to as a processed signal) to the weather prediction device 100 as meteorological observation data.

For example, the weather radar device 200 transmits a plurality of processed signals generated during a predetermined search period (for example, a 30 second period) to the weather prediction device 100 as one piece of weather observation data. Meteorological data, for example, for each mesh area M _i, a volume data physical amount based on the radio wave is associated. The mesh area M _i is a three-dimensional space area in which a three-dimensional observation space irradiated with a radio wave is divided by a predetermined width in each of the distance direction, the horizontal direction, and the vertical direction. Incidentally, the observation target of the meteorological radar apparatus 200 (observation space) is made sufficiently distant from the weather radar system 200, in the following description, the mesh area M _i is assumed to be a cube.

  Hereinafter, the configuration of the weather prediction device 100 will be described. The weather prediction apparatus 100 includes a communication unit 102, a control unit 110, and a storage unit 130.

  The communication unit 102 communicates with the meteorological radar apparatus 200 and the like via a network such as a wide area network (WAN), and receives meteorological observation data 132 from the meteorological radar apparatus 200. The weather observation data 132 received by the communication unit 102 is stored in the storage unit 130.

  The control unit 110 includes, for example, a precipitation intensity calculation unit 111, a wind and wind speed calculation unit 112, a precipitation band type determination unit 113, an area derivation unit 114, a disaster risk derivation unit 115, and an output unit 116. Some or all of these components may be realized by a processor such as a CPU (Central Processing Unit) executing a program stored in the storage unit 130. Further, some or all of the components of the control unit 110 may be realized by hardware such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), or FPGA (Field-Programmable Gate Array). It may be realized by cooperation of software and hardware.

  The storage unit 130 may be realized by, for example, a read only memory (ROM), a flash memory, a hard disk drive (HDD), an SD card, a magnetoresistive random access memory (MRAM), a random access memory (RAM), a register, or the like. The storage unit 130 stores programs executed by the processor of the control unit 110, and also stores meteorological observation data 132, analysis data 134 described later, feature information 136 for each rainfall zone, and the like.

FIG. 2 is a view showing an example of the meteorological observation data 132. As shown in FIG. For example, meteorological data 132, the observation space containing high over the clouds for each mesh area M _i divided virtually, the radar reflectivity factor Z _i, a data is correlated and Doppler velocity D _i.

The radar reflection factor Z _i is a parameter that changes according to the particle size of particles that reflect radio waves. The particles that reflect radio waves are, for example, particles that constitute clouds (hereinafter, referred to as cloud particles). The cloud particles may include, for example, water droplets or ice crystals. For example, the radar reflectivity factor Z _i is the weather radar apparatus 200 is calculated based on the distance and received power when receiving radio waves, from the weather radar system 200 to cloud particles reflected radio waves. Incidentally, the weather observation data 132, instead of the radar reflectivity factor _{Z i,} radar reflection intensity (= _{10log 10 Z i)} may be associated.

The Doppler velocity D _i is a parameter representing the moving direction and the moving velocity of cloud particles in the mesh region M _i , and the transmission frequency when the weather radar device 200 transmits a radio wave, and the reception frequency when the radio wave is received Calculated based on the difference between Doppler velocity D _i is an index used to calculate the wind direction and wind speed of each mesh area M _i. These indices may be calculated as a result of signal processing in the weather radar device 200, or may be calculated in the weather prediction device 100.

The size of the mesh area M _i may be changed according to the time resolution and the spatial resolution of the weather radar device 200. Further, position coordinates of the orthogonal coordinate system having the position of the weather radar device 200 as an origin are associated with each mesh area M _i . For example, when the weather radar device 200 is installed at a high altitude, a hill or the like, the position coordinates of the mesh area M _i may have a negative value in the altitude direction. The coordinate system is not limited to the orthogonal coordinate system, but may be a polar coordinate system or another coordinate system.

  Hereinafter, a series of processes by the control unit 110 will be described using a flowchart. FIG. 3 is a flowchart showing an example of a series of processes by the control unit 110 in the first embodiment. The processing of this flowchart may be repeated, for example, in a predetermined cycle.

First, the precipitation intensity calculation unit 111 stands by until the communication unit 102 receives weather observation data 132 for one search cycle from the weather radar device 200 (step S100), and the weather for one search cycle is received. When observed data 132 is received, for each mesh area _{M i} of the weather observation data 132, it calculates the precipitation intensity _{R i} (step S102).

For example, precipitation intensity calculation unit 111 calculates the precipitation intensity R _i by substituting the radar reflectivity factor Z _i for each mesh area M _i in Equation (1). The precipitation intensity R _i may be calculated by another method.

In the above equation (1), B and β are, for example, constants determined from observed values by a rain gauge, and when the cloud particle is a water droplet, B is set to about 200 and β is set to about 1.6, and the cloud particle is When is an ice crystal, B is set to about 500 to about 2000, and β is set to about 2.0. Incidentally, each of the constants B and β is to the same value may be set in the entire mesh area M _i, may be set a different value for each mesh area M _i.

Then, Wind calculating unit 112, based on the radar reflectivity factor _{Z i} and Doppler velocity _{D i} for each mesh area _{M i,} and calculates the wind direction and wind speed for each mesh area _{M i} (step S104). For example, the wind direction and wind speed calculation unit 112 uses a three-dimensional wind analysis method such as VAD (Velocity Azimuth Display) method, VVP (Volume Velocity Processing) method, Gal-Chen method, Dual-Doppler method, etc. Calculate the wind direction and wind speed for each _i . Incidentally, Wind calculation unit 112 for the mesh area M _i which can not be calculated wind direction and wind speed, for example, may be used a representative value of wind direction and wind speed at other mesh area M _i. The representative value may be, for example, an average value, a median, or another statistic.

Figure 4 is a diagram showing an example of the observation space virtually divided mesh area M _i. In the figure, the Z-axis indicates the vertical direction, and the X-axis and the Y-axis indicate orthogonal components included in the horizontal direction. In the example of illustration, only the cross section of a certain XZ plane is represented among observation space (3 dimensional space). In each mesh area M _i , as an analysis result, the precipitation intensity R _i calculated by the precipitation intensity calculation unit 111 is associated with a vector (arrow V _i ) indicating the wind direction / speed calculated by the wind direction / wind calculation unit 112 Be In the drawing, the precipitation intensity R _i is expressed by R _xz in order to indicate the precipitation intensity R corresponding to the X axis and the Z axis. The direction of the vector indicated by the arrow V _i indicates the wind direction, and the magnitude of the vector indicates the wind speed. Information in which the precipitation intensity R _i and the vector direction V _i indicating the wind direction and the wind speed are associated with each other in each mesh area M _i virtually representing the observation space is stored in the storage unit 130 as the analysis data 134. It is memorized.

Next, precipitation band type determining section 113 refers to the analysis data 134 from the plurality of mesh areas M _i where the precipitation intensity R _i and direction and wind velocity associated, the observation space at a given altitude mesh The area M _i is extracted (step S106).

FIG. 5 is a diagram for explaining a method of extracting the mesh area M _i . In the figure, the vertical axis represents the height (vertical direction Z), and the horizontal axis represents the distance in one of the horizontal directions XY. For example, precipitation band type determining section 113, the observation space, the mesh area M _i in the vicinity of cloud base height H _a and the lower region, and the mesh area M _i in the vicinity of cloud height H _c and an upper region, cloud base height H _a A mesh area M _i near the middle height H _b between H and the cloud top height H _c is determined as the middle layer area.

Cloud base height H _a is the altitude of the bottom of the observable cloud by radio, for example, is highly configurable approximately 0.5 [miles] point from the ground. The cloud top height H _c is the height of the cloud top that can be observed by radio waves, and is set to, for example, a height of about 10 [km] from the ground. In the example in the figure, although the clouds above the cloud top height H _c are also schematically displayed, it is assumed that they are not observed. The intermediate height H _b is, for example, the height of the middle point between the height H _a and the height H _c . In the case of the numerical example described above, the intermediate height H _b is set to an altitude of about 4.75 [km] from the ground. In the present embodiment, each of these altitudes is assumed to be previously determined. Cloud base height H _a is an example of the "first high" intermediate altitude H _b is an example of the "second high" or "predetermined altitude."

Precipitation zone type determining section 113, from the analysis data 134, extracts the mesh area M _i corresponding to the lower region, and a mesh area M _i corresponding to the middle region. Then, the precipitation zone type determination unit 113 refers to the precipitation zone characteristic information 136 to extract the wind direction and the wind speed in the horizontal direction of the extracted lower layer area (hereinafter referred to as lower wind), the wind direction in the horizontal direction of the middle layer area, The type of linear precipitation zone in the observation space is determined by comparing the wind speed (hereinafter referred to as middle class wind) (step S108). Lower winds and middle winds may be representative wind directions and speeds of the area at each altitude. The representative wind direction and wind speed of each area may be represented by, for example, one combined vector obtained by synthesizing the wind direction and wind speed vector V _i associated with each of all the mesh areas M _i included in the area.

  FIG. 6 is a diagram showing an example of the precipitation band feature information 136. The linear precipitation zones to be discriminated in the present embodiment are a backbuilding linear precipitation zone (type B in the figure), a back and side building linear precipitation zone (type BS in the figure), and a squall line type linear form It is a precipitation zone (S type in the figure). In addition, the kind of these linear precipitation zones is an example, one part may be replaced with another kind, and another kind may be added to these kinds.

  In general, the backbuilding linear precipitation zone (type B) has the same direction as the direction of the lower layer wind and the direction of the middle layer wind, and the back-and-side building linear precipitation zone (type BS) has the lower layer wind It is known that the direction of the lower layer wind and the direction of the middle layer wind are opposite to each other in the direction of the lower layer wind and the direction of the middle layer wind in the squall line type linear precipitation zone (S type).

  Therefore, for example, when the angular difference between the wind direction (vector) of the lower layer wind and the middle layer wind is within ± 45 °, the precipitation band type determination unit 113 determines that the wind directions of the lower layer wind and the middle layer wind are "the same direction". And determine that the linear precipitation zone in the observation space is a "back building linear precipitation zone (type B)". Further, for example, when the angle difference between the wind direction (vector) of the lower layer wind and the middle layer wind is within the range of plus or minus 45 ° to 135 °, the precipitation band type determination unit 113 It is determined that the linear precipitation zone in the observation space is the "back and side building linear precipitation zone (BS type)". Further, for example, when the angle difference between the wind direction (vector) of the lower layer wind and the middle layer wind is within the range of plus or minus 135 ° to 180 °, the precipitation band type determination unit 113 It is determined that the direction is “direction”, and the linear precipitation zone in the observation space is determined to be “squall-line linear precipitation zone (S-type)”.

  In addition, the strike ST of the backbuilding linear precipitation zone (type B) is the same direction as the direction of the intermediate wind in the precipitation zone, and the strike ST of the back and side building linear precipitation zone (BS type) is It is known that the direction of the middle layer wind in the precipitation zone is substantially the same as the direction of the middle layer wind, and the strike ST of the squall line linear precipitation zone (S type) is orthogonal to the direction of the middle layer wind in the precipitation zone. There is.

  For example, instead of determining the kind of the linear precipitation zone by comparing the lower layer wind and the middle layer wind, the precipitation zone type determination unit 113 determines the strike direction ST of the linear precipitation zone whose type is undecided and The type of linear precipitation zone may be determined by comparing the wind direction of the middle layer wind in the linear precipitation zone.

FIG. 7 is a view showing an example of the strike ST of the linear precipitation zone. FIG arrow V _a represents the wind direction of the lower air, arrow V _b represents the wind direction middle wind. In the illustrated example, the wind direction V _a and direction V _b of the middle air level wind is the same direction, and strike ST of the linear precipitation zone is wind V _b in the same direction as the middle wind. For example, when the angular difference between the strike direction ST of the linear precipitation zone and the wind direction _Vb of the middle class wind is within plus or minus 45 °, the strike direction ST of the linear precipitation zone and the wind direction _{Vb of the} middle class wind are "same direction" May be considered. When the strike direction ST of the linear precipitation zone and the wind direction V _b of the intermediate wind are “the same direction”, the precipitation zone type determination unit 113 determines the type of linear precipitation zone as “backbuilding type linear precipitation zone (B type Decided to be

FIG. 8 is a diagram showing another example of the strike ST of the linear precipitation zone. In the illustrated example, the wind direction V _{a of the} lower layer wind and the wind direction V _{b of the} middle layer wind are orthogonal to each other, and the strike ST of the linear precipitation zone is the same as the wind direction V _{b of the} middle layer wind (approximately the same direction). It is. In this case, the precipitation zone type determination unit 113 determines the type of linear precipitation zone as “back and side building linear precipitation zone (BS type)”.

FIG. 9 is a diagram showing another example of the strike ST of the linear precipitation zone. In the illustrated example, a direction opposite to the wind direction V _a is the wind direction V _b of the middle air level wind, a and direction strike ST of linear precipitation band perpendicular to the wind direction V _b of the middle air. For example, when the angle difference between the wind direction V _b of strike ST and middle style linear precipitation zone is in the range of 135 ° from plus or minus 45 °, the wind direction V _b of strike ST and middle style linear precipitation zone " It may be considered as "orthogonal". When the strike direction ST of the linear precipitation band is a direction orthogonal to the wind direction V _{b of the} mid-layer wind, the precipitation band type determination unit 113 selects the type of linear precipitation band as “Square-line type linear precipitation band (S type) Decide on the

  In addition, the precipitation band type determination unit 113 determines the type of linear precipitation band based on both the comparison results of the wind direction of the lower layer wind and the middle layer wind and the comparison result of the strike direction ST of the linear precipitation band and the wind direction of the middle layer wind. You may decide For example, the precipitation band type determination unit 113 determines the type of linear precipitation band for each variation of the combination of the wind direction of the lower layer wind and the middle layer wind and for each variation of the combination of the strike direction ST of the linear precipitation band and the wind direction of the middle layer wind. The score is added to or multiplied by each of the three candidates, and the candidate with the largest sum of the added or multiplied scores is determined as the type of the linear precipitation band of interest.

FIG. 10 is a diagram for explaining a method of scoring. For example, if the wind direction of the level wind is the wind direction middle style "same direction", rain zone type determining section 113, the highest score S _B of the back building type linear precipitation zone (B type), back and sides Building type linear precipitation band higher following the score S _BS score S _B of (BS type) may be determined as the score S _S squall line type linear precipitation zone (S-type) is minimized. In the illustrated example, adding or multiplying a score such as (0.6, 0.3, 0.1) to each of three candidates (B type, BS type, S type) of linear precipitation zone types become.

Also, for example, when the wind direction of the lower layer wind is the “orthogonal direction” to the wind direction of the middle layer wind, the precipitation band type determination unit 113 has the highest score S _BS and the score S _B and the score S _S follow the score S _BS You may decide to go high. In the illustrated example, adding or multiplying a score such as (0.2, 0.6, 0.2) to each of three candidates (B type, BS type, S type) of linear precipitation zone types become.

For example, when the wind direction of the lower air is "opposite direction" with respect to the wind direction of the middle wind, rain zone type determining section 113, the highest score S _S, the score S _BS is high in the following score S _S, score it may be determined so that S _B minimized. In the illustrated example, adding or multiplying a score such as (0.1, 0.3, 0.6) to each of three candidates (B type, BS type, S type) of linear precipitation zone types become.

For example, when the strike ST linear rainfall zone is the wind direction middle style "same direction", rain zone type determining section 113, the highest score S _B and the score S _BS, the smallest score S _S You may decide to become In the illustrated example, a score such as (0.4, 0.4, 0.2) is added to or multiplied by each of three candidates (B type, BS type, S type) of linear precipitation zone types. become.

For example, when the strike ST linear rainfall zone is the "orthogonal direction" with respect to the wind direction of the middle wind, rain zone type determining section 113, the highest score S _S, the smallest score S _B and the score S _BS You may decide to become In the illustrated example, adding or multiplying a score such as (0.2, 0.2, 0.6) to each of three candidates (B type, BS type, S type) of linear precipitation zone types become.

Thus, the precipitation band type determination unit 113 assigns a score to the linear precipitation band type candidate for each case, and the candidate to which the score with the largest value is given as compared to other scores, Determined as the type of linear precipitation zone. For example, when the wind direction of the lower wind is "same direction" as the wind direction of the middle wind and the strike ST of the linear precipitation band is "orthogonal direction" to the wind direction of the middle wind, the score is calculated by the addition method, back Building type linear precipitation zone score S _B 0.8 next to (B-type), a back-and-side building type linear precipitation zone score S _BS 0.5 next (BS type), squall line type linear precipitation The band SS (S-type) score _SS is 0.7. In this case, the precipitation zone type determination unit 113 determines the type of linear precipitation zone as the back-building linear precipitation zone (B-type).

  In addition, the precipitation band type determination unit 113 may obtain vertical shear as a representative wind direction and wind speed of the lower layer region and the middle layer region, and use this vertical shear to determine the type of linear precipitation band. The vertical shear is represented by a value obtained by dividing the magnitude of the difference between the vectors indicating the wind direction and velocity of the lower layer wind and the middle layer wind by the height difference of the lower layer region and the middle layer region.

  In addition, the precipitation band type determination unit 113 may output data from a numerical weather forecasting model, data output from a ground weather observation apparatus (for example, a wind direction anemometer on the ground), a remote sensing meteorological instrument (for example, a flying object such as a balloon). The type of linear precipitation zone may be determined in consideration of the data output from the provided radiosonde). In this case, the communication unit 102 may communicate with each device to acquire output data and the like.

Then, the area deriving unit 114 refers to the precipitation intensity _{R i} of each mesh area _{M i,} cloud base altitude _{H a} and cloud height _H precipitation intensity _{R i} is equal to or larger than the threshold of a mesh area _{M i} between the _c A target area obtained by specifying the specified mesh areas M _i is derived (step S110). The threshold value of the precipitation intensity R _i is set to, for example, a precipitation intensity value when a linear precipitation band was observed at a past time point. Thus, the target area is derived as an area including a linear precipitation zone (a precipitation cloud).

  Next, the disaster risk deriving unit 115 determines, for each target area derived by the area deriving unit 114, the disaster due to the linear precipitation band according to the type of the linear precipitation band determined by the precipitation band type determination unit 113. The risk is derived (step S112).

For example, the disaster risk deriving unit 115 determines the ease with which the linear precipitation zone included in the target area is stagnated (the stagnation degree), and the rainfall intensity R _i of the mesh area M _i included in the target area The risk of disaster due to the linear precipitation zone is derived based on the representative precipitation intensity R _{i of} For example, as shown in the precipitation zone characteristic information 136, the backbuilding linear precipitation zone (B type) and the back and side building linear precipitation zone (BS type) are squall line type linear precipitation zones (S type). Because it tends to stagnate compared with), it brings precipitation etc. to the same point for a long time, and as a result the disaster tends to be more serious. That is, the backbuilding linear precipitation zone (type B) and the back-and-side building linear precipitation zone (BS type) have a higher risk of meteorological disasters than the squall line linear precipitation zone (S type). It can be judged. Disaster risk deriving unit 115, replacing the index value of the risk of the ease of stagnation of each linear precipitation zone (quantitative value), the product of the risk and precipitation intensity R _i, the degree of risk due to weather disasters Derived as a risk value representing

In addition, the disaster risk deriving unit 115 assigns a weight to the risk value to be derived, based on the strike direction ST of the linear precipitation band and the area on the ground where the linear precipitation band stagnates (hereinafter referred to as stagnant area). Good. For example, the disaster risk deriving unit 115 determines the product of the derived risk and the precipitation intensity R _i when it is estimated that the linear precipitation band will move to the sea or the mountain area from the strike position ST of the linear precipitation band. The risk value may be lowered by giving a weight that makes it smaller. On the other hand, the disaster risk deriving unit 115 determines the risk and the precipitation intensity R when the linear precipitation band is estimated to move to a city area or a region where landslide disasters frequently occur from the strike position ST of the linear precipitation band. _The risk value may be increased by giving a weight that increases the product of _i . That is, the disaster risk deriving unit 115 may weight the derived risk value based on the future stagnant area of the linear precipitation band. In addition, the disaster risk deriving unit 115 may assign a weight to the risk value to be derived based on the stagnant area where the linear precipitation band is currently located.

The data disaster risk deriving unit 115, in addition to the linear risk and precipitation intensity of each type of precipitation band R _i, which is output for example from the numerical weather prediction model output data and ground meteorological observation apparatus, remote sensing The risk value may be derived by combining weather information such as data output from the meteorological instrument, land use data, geology data, topography data, land surface information such as river basin data, and the like. When these various data are used, the disaster risk deriving unit 115 may digitize the above data and information, derive the risk value by addition / subtraction and division, or use the probability prediction model or the learning type model to calculate the risk value. It may be derived.

  Next, the output unit 116 outputs the information based on the result of the derivation of the risk value of the meteorological disaster derived by the disaster risk derivation unit 115 to the predetermined device using the communication unit 102 (step S114). The predetermined device may be, for example, a terminal device used by a general user, or a server device that provides an information providing service such as a weather forecast.

  FIG. 11 is a diagram showing an example of a screen displayed on the predetermined device. As in the illustrated example, on the screen of the predetermined device, target areas (R1 to R3 in the figure) are displayed superimposed on the map. The display mode of each target area may be changed according to the risk value. For example, the precipitation zone included in the target region R1 is a backbuilding linear precipitation zone (type B) or a back-and-side building linear precipitation zone (BS type), and the precipitation zones included in the target regions R2 and R3 In the case of the squall line type linear precipitation zone (S type), as shown, the target area R1 is expressed in a display mode corresponding to high risk, and the target areas R2 and R3 correspond to low risk. It may be expressed in a display manner.

  According to the first embodiment described above, the precipitation band type determination unit 113 that determines the type of the precipitation band in the sky based on the meteorological observation data obtained by the meteorological radar device 200, and the precipitation band type determination unit 113 By providing the disaster risk deriving unit 115 that derives the risk of disaster due to the linear precipitation band according to the type of precipitation band determined by the above, it is possible to accurately predict the risk of meteorological disaster.

  Further, according to the first embodiment described above, for example, when a phased array antenna is applied to the weather radar device 200, it is possible to use meteorological observation data observed with high frequency and without gaps. This makes it possible to continuously analyze the wind direction and wind speed distribution at that time point in a ternary direction in a short cycle, and combining the wind direction and wind speed data with the data of rainfall intensity etc. Features can be determined frequently and with high accuracy. As a result, the risk of a meteorological disaster such as heavy rain that may cause a huge disaster can be notified or provided quickly and with high accuracy. For example, when notifying the risk result of a meteorological disaster to the terminal device which a general user uses, alerting to a general citizen or evacuation can be performed.

Second Embodiment
The second embodiment will be described below. The second embodiment is different from the first embodiment described above in that the lower layer region and the middle layer region are determined in accordance with the shape of the target region. Hereinafter, differences from the first embodiment will be mainly described, and descriptions of points in common with the first embodiment will be omitted. In the description of the second embodiment, the same parts as those of the first embodiment are given the same reference numerals.

  FIG. 12 is a flowchart showing an example of a series of processes by the control unit 110 in the second embodiment. The process of this flowchart is repeatedly performed, for example, in a predetermined cycle.

  First, the precipitation intensity calculation unit 111 stands by until the communication unit 102 receives weather observation data 132 for one search cycle from the weather radar device 200 (step S200).

When the weather observation data 132 one search cycle is received, the precipitation intensity calculation unit 111, for each mesh area M _i of the weather observation data 132, calculates the precipitation intensity R _i and direction and wind speed (Step S202) .

Then, the area deriving unit 114 refers to the precipitation intensity R _i of each mesh area M _i, precipitation intensity R _i is to identify the threshold above the mesh area M _i, and combine this particular mesh area M _i A target area is derived (step S204).

Next, the precipitation band type determination unit 113 determines the maximum height of the target area derived by the area derivation unit 114 as the cloud top height H _c (step S206).

Next, the precipitation band type determination unit 113 determines whether the minimum height of the target area is less than or equal to a predetermined height (for example, about 0.5 [km]) (step S208), and the minimum height of the target area is If the predetermined height or less, determines the predetermined altitude cloud base height H _a (step S210), if the smallest target area altitude is greater than a predetermined altitude, the minimum altitude of the target region in the cloud base height H _a It determines (step S212). Incidentally, the cloud base is highly H _a is measured by Shirometa not shown (height of clouds meter), when the communication unit 102 acquires the measurement result of cloud base height H _a from this Shirometa is precipitation zone type determining section 113 , And S210 may be omitted.

Next, the precipitation band type determination unit 113 determines the intermediate height _Hb (step S214). For example, the precipitation band type determination unit 113 may determine the average height of the cloud top height H _c and the cloud bottom height H _a as the intermediate height H _b . The precipitation band type determination unit 113 also determines the volume of the entire target region based on the number and volume of mesh regions M _i included in the target region, and determines the height of the center of this volume as the intermediate height H _b Good. The precipitation zone type determining section 113 obtains the center of gravity of the target area from the precipitation intensity R _i of each mesh area M _i included in the target region to guess the weight of each mesh area M _i, intermediate the high center of gravity It may be determined as the altitude H _b .

Next, precipitation band type determining section 113 refers to the analysis data 134 from the plurality of mesh areas M _i where the precipitation intensity R _i and direction and wind velocity associated, corresponding to the lower region and intermediate region The mesh area M _i to be extracted is extracted (step S216).

  Next, the precipitation zone type determination unit 113 refers to the precipitation zone characteristic information 136 to compare the lower layer wind of the extracted lower layer region with the middle layer wind of the middle layer region, thereby obtaining a linear precipitation band in the observation space. The type of is determined (step S218).

  Next, the disaster risk deriving unit 115 derives, for each target area, the risk value of the disaster due to the linear precipitation band according to the type of the linear precipitation band determined by the precipitation band type determination unit 113 (step S220) ).

  Next, the output unit 116 outputs the information based on the result of the derivation of the risk value of disaster derived by the disaster risk derivation unit 115 to the predetermined device using the communication unit 102 (step S222). Thus, the processing of this flowchart is ended.

The precipitation band type determination unit 113 stores the processing results of S206 to S212 (the determined cloud base height H _a , the cloud top height H _c , and the intermediate height H _b ) in the storage unit 130 in the processing of the flowchart described above. Alternatively, the processing results of the past may be reflected in the processing of S206 to S212 after the next time.

FIG. 13 is a diagram showing an example of the processing result. As illustrated, the precipitation band type determination unit 113 processes, for example, the cloud base height H _a , the cloud top height H _c , and the intermediate height H _b determined in the processing of S206 to S212 for each type of linear precipitation band. Are stored in the storage unit 130 as Then, when the meteorological observation data is newly received as the process of S200 by machine learning of the processing result of the past, the precipitation band type determination unit 113 reflects the learning result, and the cloud base height H _a and the top of the cloud. Determine the height H _c and the middle height H _b . For example, a manager who manages the weather prediction apparatus 100 determines whether the type of linear precipitation band determined by the precipitation band type determination unit 113 is correct or incorrect in a certain observation period. In response to this, the precipitation band type determination unit 113 treats each altitude of the linear precipitation zone judged to be "correct" as the positive example data, and at each altitude of the linear precipitation zone judged to be "error". By treating it as negative example data, the cloud base height H _a , the cloud top height H _c , and the middle height H _b are learned.

In addition, the precipitation band type determination unit 113 may learn the cloud base height H _a , the cloud top height H _c , and the middle height H _b by applying a probabilistic inference model such as a Bayesian network to the past processing results. In addition, the precipitation zone type determination unit 113 stores the cloud base height H _a , the cloud top height H _c , and the intermediate height H _b determined in the processing of S206 to S212 as processing results for each stagnation area where the linear precipitation band stagnates. The cloud base height H _a , the cloud top height H _c , and the middle height H _b may be learned according to the tendency of the precipitation zone generated in each stagnation area by storing in the unit 130. Such processing can eliminate the results (cloud bottom height H _a , cloud top height H _c , and intermediate height H _b processing results) that deviate from the trend of the altitude of the past precipitation zone, and thus more accurate. Weather forecast can be made.

  According to the second embodiment described above, the risk due to a meteorological disaster can be accurately predicted, as in the first embodiment described above.

  According to at least one embodiment described above, the precipitation band type determination unit 113 that determines the type of the precipitation band in the sky based on the meteorological observation data obtained by the meteorological radar device 200, and the precipitation band type determination unit 113 By providing the disaster risk deriving unit 115 that derives the risk of disaster due to the linear precipitation band according to the type of precipitation band determined by the above, it is possible to accurately predict the risk of meteorological disaster.

The above embodiment can be expressed as follows.
Storage for storing information,
A processor that executes a program stored in the storage;
The processor executes the program to
Determine the type of precipitation band in the sky based on the meteorological observation data obtained by the radar device,
A weather forecasting device configured to derive a risk of disaster due to the precipitation band according to the type of the determined precipitation band.

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

Claims (15)

A determination unit that determines the type of precipitation band in the sky based on meteorological observation data obtained by the radar device;
A risk deriving unit that derives a risk of disaster due to the precipitation zone according to the type of the precipitation zone determined by the determination unit;
Weather forecasting device. The determination unit is
The type of the precipitation band is determined based on the wind direction of the first height included in the observation space observed by the radar device and the wind direction of the second height higher than the first height,
The weather forecasting device according to claim 1. The determination unit is
The type of the precipitation zone is determined by comparing the wind direction of at least the second altitude with the strike of the precipitation zone,
The weather forecasting device according to claim 2. The determination unit is
The type of the precipitation zone is determined by comparing the wind direction of a predetermined altitude included in the observation space observed by the radar device with the strike direction of the precipitation zone,
The weather forecasting device according to claim 1. The observation space further includes a region deriving unit that derives a target region including the precipitation band,
The determination unit determines the minimum height of the target area derived by the area derivation unit as the first height, and determines the second height based on the minimum height and the maximum height of the target area,
The weather forecasting device according to claim 2. The observation space further includes a region deriving unit that derives a target region including the precipitation band,
The determination unit determines the minimum height of the target region derived by the region derivation unit as the first height, and determines the height of the center of volume of the target region as the second height.
The weather forecasting device according to claim 2. The observation space further includes a region deriving unit that derives a target region including the precipitation band,
The determination unit determines the minimum height of the target area derived by the area derivation unit as the first height, and determines the height of the center of gravity of the target area as the second height.
The weather forecasting device according to claim 2. The determination unit determines the type of the precipitation band by machine learning the first height and the second height determined in the past.
The weather forecasting device according to claim 5. The determination unit determines the type of the precipitation band by machine learning the first height and the second height determined in the past.
The weather forecasting device according to claim 6. The determination unit determines the type of the precipitation band by machine learning the first height and the second height determined in the past.
The weather forecasting device according to claim 7. The risk deriving unit derives a risk of disaster due to the rain band based on the stagnation degree and the rain intensity of the rain band whose type is determined by the determination unit.
The weather forecasting device according to claim 1. The risk deriving unit derives a risk of disaster due to the precipitation band based on the strike of the precipitation band whose type is determined by the determination unit.
The weather forecasting device according to claim 1. The risk deriving unit derives a risk of disaster due to the rain band based on the above ground area where the rain band is stagnant determined by the determination unit.
The weather forecasting device according to claim 1. The computer is
Determine the type of precipitation band in the sky based on the meteorological observation data obtained by the radar device,
Deriving the risk of disaster due to the precipitation zone according to the type of the precipitation zone determined
Weather forecasting method. On the computer
Based on the meteorological observation data obtained by the radar device, determine the type of precipitation band in the sky,
According to the type of the determined precipitation band, the risk of disaster caused by the precipitation band is derived.
program.

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