Information processing device, weather radar system, information processing method, and program

Abstract

To provide an information processing device, a weather radar system, an information processing method, and a program capable of calculating precipitation intensity with high accuracy and high distance resolution.SOLUTION: The information processing device comprises: an acquisition unit that acquires reception power and an inter-polarized wave phase difference; and a processing unit. The processing unit calculates a reflection factor on the basis of the reception factor, calculates an inter-polarized wave phase difference change rate within a second space range wider than a first space range on the basis of the inter-polarized wave phase difference, calculates first precipitation intensity on the basis of the inter-polarized wave phase difference change rate, estimates one of a first coefficient and a second coefficient about a third space range wider than the second space range on the basis of the reflection factor and the first precipitation intensity, estimates the other of the first coefficient and the second coefficient about a fourth space range wider than the third space range on the basis of the reflection factor and the first precipitation intensity, and calculates second precipitation intensity on the basis of an estimated value of the first coefficient or the second coefficient within the third space range and an estimated value of the first coefficient or the second coefficient within the fourth space range.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] An embodiment of the present invention relates to an information processing device, a weather radar system, an information processing method, and a program for analyzing weather radar data. [Background technology]

[0002] Due to recent climate change, large-scale flood disasters caused by localized torrential rains and tornadoes have become a social issue. To predict the occurrence of flood disasters, there is a demand for more accurate weather radars that measure precipitation intensity (amount of precipitation per unit time). Weather radars transmit radio waves from an antenna and receive the radio waves that are reflected back by raindrops. Weather radars are meteorological observation devices that observe precipitation intensity based on the received radio waves. Conventional weather radars calculate precipitation intensity from either the rate of change of inter-polarized phase difference or the reflectivity factor.

[0003] The precipitation intensity calculated from the reflectance factor has lower accuracy but higher resolution than the precipitation intensity calculated from the rate of change in the phase difference between polarizations.The precipitation intensity calculated from the rate of change in the phase difference between polarizations has higher accuracy but lower resolution than the precipitation intensity calculated from the reflectance factor. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2011-47742 A [Non-patent literature]

[0005] [Non-Patent Document 1] Shuichi Tsuchiya and two others, "Study materials on practical technology for XRAIN rainfall observation", National Institute for Land and Infrastructure Management Document, No. 909, May 2016 Summary of the Invention [Problem to be solved by the invention]

[0006] An object of the present invention is to provide an information processing device, a weather radar system, an information processing method, and a program that are capable of calculating precipitation intensity with high accuracy and high resolution. [Means for solving the problem]

[0007] The information processing device according to the embodiment includes an acquisition unit that acquires a received power and an inter-polarized phase difference in a first spatial range transmitted from a radar, and a processing unit that processes the received power and the inter-polarized phase difference. The processing unit calculates a reflection factor for a first spatial range based on the received power, calculates a rate of change of inter-polarization phase difference for the first spatial range for a second spatial range wider than the first spatial range based on the inter-polarization phase difference, calculates a first precipitation intensity for the first spatial range for the second spatial range based on the rate of change of inter-polarization phase difference, estimates one of a first coefficient and a second coefficient for determining a second precipitation intensity for the first spatial range from the reflection factor for a third spatial range wider than the second spatial range based on the reflection factor and the first precipitation intensity, estimates the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflection factor and the first precipitation intensity, and calculates a second precipitation intensity based on the estimated value of one of the first coefficient and the second coefficient for the third spatial range, the estimated value of the other of the first coefficient and the second coefficient for the fourth spatial range, and the reflection factor. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram illustrating an example of an information processing apparatus according to a first embodiment. [Diagram 2] FIG. 2 is a block diagram for explaining an example of a processing unit according to the first embodiment. [Diagram 3] 5A and 5B are diagrams for explaining an example of a calculation range of a rate of change of a polarization phase difference and an estimation range of a coefficient according to the first embodiment. [Figure 4] FIG. 3 is a diagram for explaining an example of a data set of precipitation intensity and average reflectance factor at grid points according to the first embodiment. [Diagram 5] FIG. 4 is a diagram for explaining an example of precipitation intensity according to the first embodiment. [Figure 6] FIG. 4 is a diagram for explaining an example of the action of a processing unit according to the first embodiment. [Figure 7] FIG. 11 is a diagram for explaining a modified example of a processing unit according to the first embodiment. [Figure 8] FIG. 11 is a block diagram for explaining an example of a processing unit according to the second embodiment. [Figure 9] FIG. 11 is a diagram for explaining an example of a selection principle of a selection unit according to the second embodiment. [Figure 10] FIG. 11 is a block diagram for explaining an example of a processing unit according to the third embodiment. [Figure 11] FIG. 13 is a diagram for explaining an example of data of the current time and past time stored in a memory according to the third embodiment. [Figure 12] FIG. 13 is a block diagram for explaining an example of a processing unit according to a modified example of the third embodiment. [Figure 13] FIG. 13 is a diagram for explaining an example of an estimation space of coefficients according to the fourth embodiment. [Figure 14] FIG. 13 is a diagram for explaining an example of a processing unit according to the fifth embodiment. [Figure 15] FIG. 13 is a diagram for explaining an example of a ZR characteristic obtained by a processing unit according to the fifth embodiment. [Figure 16] FIG. 13 is a diagram for explaining an example of a weather radar system according to a sixth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the embodiments will be described with reference to the drawings. The following description is an example of an apparatus and method for embodying the technical idea of ​​the embodiment, and the technical idea of ​​the embodiment is not limited to the structure, shape, arrangement, material, etc. of the components described below. Modifications that a person skilled in the art can easily conceive are naturally included in the scope of the disclosure. In order to make the description clearer, the size, thickness, planar dimensions, or shape of each element may be changed from the actual embodiment and shown diagrammatically. Elements having different dimensional relationships or ratios may be included in multiple drawings. In multiple drawings, corresponding elements may be given the same reference numerals and duplicated descriptions may be omitted. Some elements may be given multiple names, but these examples of names are merely examples and do not deny the use of other names for these elements. In addition, it is not denied that elements not given multiple names may be given other names. In the following description, "connection" may include not only direct connection but also connection via other elements.

[0010] An outline of the calculation of precipitation intensity in the embodiment will be described.

[0011] The following formula is generally used to calculate the precipitation intensity R [mm / h] from the rate of change of the polarization phase difference KDP [° / km].

[0012]

number

[0013] a1 and a2 are constants. The precipitation intensity R calculated from the polarization phase difference change rate KDP is KDP It is called.

[0014] If the real number of the reflectivity factor Z is ζ, the relationship between the reflectivity factor Z [dBZ] and the precipitation rate R is expressed by the ZR relationship shown in Equation 2.

[0015]

number

[0016]

number

[0017] B and β are coefficients. The precipitation rate R calculated from the reflectance factor Z is the precipitation rate R Z It is called.

[0018] The precipitation intensity R is calculated using the reflectance factor Z. Z When calculating, Equation 4, which is a modification of Equation 2, is used.

[0019]

number

[0020] The appropriate coefficients B and β vary depending on the size distribution of raindrops. If the coefficient B is fixed to a certain value and the coefficient β is fixed to another value, the precipitation rate R Z , the precipitation intensity R Z The accuracy may be low.

[0021] The observed value of the reflection factor Z is affected by radio wave attenuation due to rainfall. Even if the rain attenuation amount is compensated for, the observed value of the reflection factor Z far from the rainfall area contains a large error. For this reason, the precipitation intensity R Z is the precipitation intensity R KDP Compared to, the observation error is large and the accuracy is low.

[0022] In general, precipitation intensity R Z Compared with the precipitation intensity R KDP If the distance used to calculate the rate of change in the polarization phase difference KDP (hereinafter referred to as the calculation section) is too short, the polarization phase difference Φ DP The effect of noise on the rate of change of polarization phase difference KDP, which is the slope of the line, becomes large, and an appropriate rate of change of polarization phase difference KDP cannot be calculated. Therefore, in order to calculate an appropriate rate of change of polarization phase difference KDP, it is necessary to set the calculation interval to be long. If the calculation interval is long, the distance resolution is low.

[0023] As mentioned above, the precipitation intensity R Z has high distance resolution but low accuracy. On the other hand, precipitation intensity R KDP While it has high accuracy, its distance resolution is poor.

[0024] Conventional weather radar systems use two types of precipitation intensity R, which have advantages and disadvantages depending on the strength of precipitation and observation conditions. Z , precipitation intensity R KDP However, it is not possible to obtain precipitation intensity with high accuracy and high distance resolution. It is desirable to obtain precipitation intensity with high accuracy and high distance resolution.

[0025] For example, low-resolution precipitation intensity R KDP The coefficients B and β are estimated in real time from the reflectance factor Z, and the high-resolution precipitation rate R is calculated from the estimated coefficients B and β and the reflectance factor Z. Z Consider calculating:

[0026] As a method for estimating both coefficients, (1) one of the coefficients B is fixed at a value such as 200, and the low-resolution precipitation rate R KDP (2) deriving the other coefficient β from the ZR relation (equation 2) based on the reflection factor Z and the precipitation intensity R KDP We consider a method to simultaneously estimate

[0027] As mentioned above, the appropriate coefficients B and β vary depending on the size distribution of raindrops. Therefore, the appropriate coefficients B and β vary for each observation point. However, in method (1), the coefficient B is fixed, and it is not possible to select an appropriate coefficient B depending on the situation. In method (2), in order to simultaneously estimate the coefficients B and β, the precipitation intensity R KDPIn order to achieve this, multiple data samples are required that pair the reflectivity factor Z in the KDP calculation section with the KDP. However, with a small number of data samples, the effect of noise increases, and the estimation accuracy of the coefficients B and β decreases. On the other hand, if data from a wide area is used to increase the number of data samples, the spatial resolution for estimating the coefficients B and β decreases, resulting in a trade-off between the accuracy of the coefficients B and β and the spatial resolution. As a result, it is not possible to obtain coefficients B and β with high spatial resolution and high accuracy, and as a result, the estimation accuracy of the precipitation intensity decreases. There is a need for a precipitation intensity estimation method that can calculate coefficients B and β with high spatial resolution and high accuracy in real time.

[0028] First embodiment 1 is a block diagram for explaining an example of an information processing device 10 according to a first embodiment. The information processing device 10 is connected to a first database 4 and a second database 6. The first database 4 and the second database 6 are connected to a weather radar 2.

[0029] The weather radar 2 includes an antenna and a transmission / reception circuit. The antenna is connected to a motor and rotated. While the antenna is rotating, the transmission / reception circuit transmits radio waves to an observation range of a predetermined radius (e.g., several tens to several hundreds of kilometers) centered on the installation location, and receives the radio waves reflected by raindrops within the observation range. Examples of radio waves include X-band and C-band microwaves. Hereinafter, the radio waves will be referred to as microwaves. The microwaves transmitted by the transmission / reception circuit include horizontally polarized waves and vertically polarized waves.

[0030] The weather radar 2 outputs data corresponding to the reflected waves. The data is obtained for each lattice point, which is the smallest unit of the observation range expressed in polar coordinates with the position of the weather radar 2 as the origin. An example of the data output by the weather radar 2 is the inter-polarized phase difference Φ DP and the received power P. The first database 4 includes the inter-polarized phase difference Φ DP The second database 6 stores the received power P.

[0031] The information processing device 10 includes a first acquisition unit 12, a second acquisition unit 14, a processing unit 16, and an output unit 18. The first acquisition unit 12 is connected to a first database 4. The first acquisition unit 12 acquires the inter-polarized phase difference Φ DP and obtain the inter-polarization phase difference Φ DP to the processing unit 16. The second acquisition unit 14 is connected to the second database 6. The second acquisition unit 14 acquires the reception power P from the second database 6, and supplies the reception power P to the processing unit 16. The processing unit 16 acquires the inter-polarization phase difference Φ DP and the received power P, and supplies the processing result to the output unit 18.

[0032] The processing unit 16 includes a CPU 22, a storage 24, and a memory 26. The CPU 22, the storage 24, and the memory 26 are connected to a bus line 28. The first acquisition unit 12, the second acquisition unit 14, and the output unit 18 are also connected to the bus line 28. The storage 24 stores a calculation processing program for the processing unit 16. The CPU 22 executes the calculation processing program. The memory 26 stores data during calculation processing. The processing unit 16 is implemented in software by the CPU 22 executing the calculation processing program.

[0033] 1 illustrates the first database 4, the second database 6, the weather radar 2, and the information processing device 10 as separate entities, but some of these may include some of the others. For example, the weather radar 2 may include the first database 4 and the second database. The weather radar 2 may include the information processing device 10. The information processing device 10 may include the first database 4 and the second database 6.

[0034] A single weather radar 2 collects two data (inter-polarization phase difference Φ DP and the received power P), but two weather radars are installed, and one of the weather radars has an inter-polarization phase difference Φ DP and another weather radar may output the received power P.

[0035] Instead of having two databases 2 and 4, the inter-polarization phase difference Φ DPand the received power P may be stored in a single database.

[0036] 2 is a block diagram for explaining an example of the processing unit 16 according to the first embodiment. The processing unit 16 includes a polarization phase difference change rate calculation unit (KDP calculation unit) 34, a precipitation intensity calculation unit (R KDP calculation unit) 36, a reflectance factor calculation unit (Z calculation unit) 38, a statistics calculation unit (Za calculation unit) 40, a first coefficient estimation unit 42, a second coefficient estimation unit 44, and a precipitation intensity calculation unit (R KDP,Z The device is equipped with a calculation unit 46.

[0037] The processing unit 16 may be implemented by a plurality of hardware blocks that realize each functional block shown in Fig. 2, instead of being implemented in software by the CPU 22. For example, the processing unit 16 may be realized by one or more processing circuits such as a CPU, a microprocessor, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or an electronic circuit including these circuits. The processing unit 16 may also be realized by an information processing device such as a computer, a computer system configured by multiple computers or servers communicating with each other via a network, or a PC cluster in which multiple computers cooperate to execute information processing. The processing unit 16 may also be implemented by multiple CPUs that realize at least a part of the multiple functional blocks, instead of one CPU 22.

[0038] Reflection factor Z, phase difference between polarizations Φ DP, the rate of change of polarization phase difference KDP, the coefficients B, and β are data of lattice points in the observation range of the weather radar 2. The rate of change of polarization phase difference KDP, the coefficients B, and β are not calculated and estimated for all lattice points in the observation range of the weather radar 2, but are calculated and estimated for a spatial range narrower than the observation range. Fig. 3 is a diagram for explaining an example of the calculation range of the rate of change of polarization phase difference KDP and the estimation ranges of the coefficients B and β according to the first embodiment. The calculation range and the estimation range are spatial ranges defined by the distance direction and the azimuth direction (or the elevation angle direction).

[0039] Reflection factor Z and inter-polarized phase difference Φ DP is calculated in the first spatial range (grid point). Reflection factor Z and inter-polarization phase difference Φ DP is calculated for the entire observation range.

[0040] The rate of change of polarization phase difference KDP is calculated for a second spatial range. The second spatial range is wider than the first spatial range in the distance direction and is the same as the first spatial range in the azimuth direction. The rate of change of polarization phase difference KDP is calculated while shifting the center of the second spatial range to the first spatial range.

[0041] One of the coefficients B and β is calculated for a third spatial range. The third spatial range is wider than the second spatial range in both the distance direction and the azimuth direction. An example of the third spatial range is the entire observation range.

[0042] The other of the coefficients B and β is calculated for a fourth spatial range. The fourth spatial range is narrower than the third spatial range in both the distance direction and the azimuth direction. An example of the fourth spatial range is the first spatial range.

[0043] The first spatial range is narrower than the second spatial range in the distance direction and equal to the second spatial range in the azimuth direction. The first spatial range is narrower than the third spatial range in both the distance direction and the azimuth direction. The first spatial range is equal to or narrower than the fourth spatial range in both the distance direction and the azimuth direction.

[0044] When the third spatial range or the fourth spatial range is wider than the first spatial range, the coefficients β or B of all the first spatial ranges included in the third spatial range or the fourth spatial range are the same.

[0045] Returning to the explanation of FIG. 2, the KDP calculation unit 34 calculates the inter-polarized phase difference Φ DP The inter-polarization phase difference change rate KDP is calculated for the second spatial range based on the inter-polarization phase difference Φ DP Φ DP (r1), Φ DP When (r2), it is defined as follows:

[0046]

number

[0047] The KDP calculation unit 34 calculates the inter-polarized phase difference Φ DP After quality control such as aliasing correction and smoothing in the distance direction are performed on the DP Calculate the second spatial range to be used for calculating the rate of change in the polarization phase difference KDP at the observation grid points of DP A regression line is found from the above by the least squares method, and the slope of the regression line is taken as the rate of change in the phase difference between polarizations KDP.

[0048] Reflection factor Z and inter-polarized phase difference Φ DP is calculated in the first spatial range. The rate of change of polarization phase difference KDP is calculated in the second spatial range. In this way, the calculation range of the rate of change of polarization phase difference KDP does not coincide with the observation grid points.

[0049] The inter-polarization phase difference change rate KDP may be calculated as follows. First, (1) an approximate KDP is calculated in a fixed section (fixed second spatial range: KDP calculation section). Next, (2) the KDP calculation section is varied for each grid point based on the approximate KDP, and the final KDP is calculated. In (1), regardless of the magnitude of the KDP, the KDP is calculated in a fixed section (for example, a distance grid point range of ±15 from the central grid point where the KDP is calculated). In (2), the KDP calculation section (second spatial range) is varied depending on the grid point (central grid point) used for calculation. For example, in a region with a large KDP in a heavy rain area, the inter-polarization phase difference Φ DP In the light rain area where the KDP is small, the inter-polarization phase difference Φ DP In this case, the approximate KDP calculated in (1) or the KDP calculated in (2) may be used.

[0050] The RKDP calculation unit 36 ​​calculates the precipitation intensity RKDP for the second spatial range from the rate of change of polarized phase difference KDP for the second spatial range using Equation 1.

[0051] The Z calculation unit 38 calculates the reflection factor Z for the second spatial range based on the radar equation from the reception power P observed by the weather radar 2. The Z calculation unit 38 may estimate the amount of radio wave attenuation (rain attenuation) due to rainfall up to the region, and may also perform rain attenuation correction processing on the reflection factor Z calculated from the radar equation. For example, the Z calculation unit 38 may calculate an integrated value of rain attenuation (Path Integrated Attenuation: PIA) from the inter-polarized phase difference change rate KDP using Equation 6 and Equation 7. The Z calculation unit 38 may correct the rain attenuation for the reflection factor Z by adding the PIA to the observation value of the reflection factor Z.

[0052]

number

[0053]

number

[0054] N is the number of data points in the range direction from the radar to the corresponding grid, dr is the radar's range resolution [km], and ah1 and ah2 are constants. In Figure 3, the radar is located at the left end. Figure 3 shows a two-dimensional grid of distance x direction.

[0055] The rain attenuation correction process may be performed by other known techniques. Hereinafter, the reflectance factor Z after the rain attenuation correction process will be simply referred to as the reflectance factor Z.

[0056] The Za calculation unit 40 calculates a statistic Za of the reflectance factor Z. An example of the statistic Za is KDP The average value Za of the reflectance factor Z in the same section as the calculation section (second spatial range) of the rate of change of the polarized phase difference KDP used in the calculation of the reflectance factor Z in the second spatial range is hereinafter referred to as the average reflectance factor Za.

[0057] The first coefficient estimation unit 42 estimates the precipitation intensity R KDP From the average reflectance factor Za, the coefficients B and β are estimated for a third spatial range that is wider than the second spatial range. The third spatial range is the entire observation range (the entire Plan Position Indicator: PPI).

[0058] The first coefficient estimation unit 42 first estimates the precipitation rate R KDP The relationship between the average reflectance factor Za and the precipitation intensity R KDP The pair of the mean reflectance factor Za and the precipitation intensity R are stored in the internal memory in a data set-like format. KDP A set of pairs of the average reflectance factor Za and the average reflectance factor Z is called a data set. KDP FIG. 13 is a diagram for explaining an example of a data set of the average reflectance factor Za.

[0059] Next, the first coefficient estimation unit 42 divides the average reflectance factor Za into intensities at intervals of 1 [dBZ] in the data set, and estimates the precipitation intensity RKDP The average value of Ra KDP The average value Zaa of the average reflectance factor Za is calculated, and the intensity range Ra KDP The relationship between the average reflectance factor Za and Zaa is as follows: The average reflectance factor Za corresponds to a range of 1 [dBZ] for z1, z2, z3, and z4, and the average reflectance factor Za corresponds to a range of 1 [dBZ] for z5, z6, z7, z8, and z9.

[0060] Finally, the first coefficient estimation unit 42 estimates the precipitation rate R KDP The average value of Ra KDP Based on the relationship between and the average value Zaa of the average reflectance factor Za, the coefficients B and β are estimated by the least squares method. Specifically, as shown in Equation 8, both sides of Equation 2 are subjected to a logarithmic calculation, and the coefficients B and β are estimated by finding a regression line with a slope β and an intercept logB. Here, ζa is the antilogarithm of the average value Zaa of the average reflectance factor Za.

[0061]

number

[0062] The coefficient B can be calculated from the intercept logB using Equation 9.

[0063]

number

[0064] The coefficients B and β estimated for the third spatial range by the first coefficient estimation unit 42 are respectively B w , β w It is called.

[0065] The first coefficient estimation unit 42 estimates the precipitation intensity R KDP The average value of Ra KDP The coefficients B and β may be calculated directly from the data set by the least squares method without calculating the average value Zaa of the average reflectance factors Za and Za.

[0066] The second coefficient estimation unit 44 estimates the coefficients β w, the average reflectance factor Za, and the precipitation intensity R KDP From the above, for the fourth spatial range, which is narrower than the third spatial range, coefficient B n The second coefficient estimation unit 44 calculates the coefficient B w Since the coefficient B is not used in the calculation, the first coefficient estimation unit 42 w In this embodiment, the lattice point interval (first resolution) of the reflectance factor Z is set as the fourth spatial range, and the coefficient B is calculated by the following formula. n Calculate.

[0067]

number

[0068]

number

[0069] The output unit 18 outputs the precipitation intensity R KDP,Z Examples of the form of output include displaying the information on a screen, printing the information in a list format, and transmitting the information to another device.

[0070] Precipitation intensity R KDP,Z is based on the rate of change in the phase difference between polarizations KDP, so it has high accuracy. KDP,Z is calculated in a narrow first spatial range, the distance resolution is high. Therefore, according to the first embodiment, the precipitation intensity is estimated with high spatial resolution and high accuracy.

[0071] FIG. 5 shows the precipitation intensity R KDP,Z FIG. 5(a) is a diagram for explaining an example of a low-resolution precipitation rate R calculated for a second spatial range from the rate of change of the polarization phase difference KDP. KDP Figure 5(b) shows an example of the precipitation intensity RKDP,Z An example of precipitation intensity R KDP,Z So, precipitation intensity R KDP Compared to (a), the spatial resolution of the heavy rain area in the center of the figure has been improved, allowing detailed observation of the rainfall conditions in the heavy rain area.

[0072] Instead of a single weather radar 2, two weather radars are provided, and one of the weather radars detects the inter-polarization phase difference Φ DP When the first weather radar outputs the received power P and the other weather radar outputs the received power P, the processing unit 16 may include a coordinate conversion unit to compensate for the difference in coordinates between the two radars. The coordinate conversion unit may be connected between the first acquisition unit and the KDP calculation unit or between the second acquisition unit and the Z calculation unit. The coordinate conversion unit converts the inter-polarized phase difference Φ DP and the coordinates of the received power P are the same, so that the polarization phase difference Φ DP Or the coordinate of the received power P is converted.

[0073] The first coefficient estimation unit 42 estimates the coefficient B w , β w The second coefficient estimation unit 44 estimates the coefficient B n However, the order of estimating the coefficients may be reversed. That is, first, the first coefficient estimator 42 estimates the coefficient B n Then, the second coefficient estimation unit 44 estimates the coefficient B w , β w The output of the Za calculation unit 40 may be supplied to a second coefficient estimation unit 44, and the output of the second coefficient estimation unit 44 may be supplied to the first coefficient estimation unit .

[0074] 6 is a diagram for explaining an example of the operation of the processing unit 16 according to the first embodiment. The fourth spatial range in which the coefficient B is estimated is assumed to be the same as the first spatial range which is the observation lattice point of the weather radar 2. The precipitation intensity R KDP The reflectance factor Z is calculated. The average reflectance factor Za is calculated for the grid points in the second spatial range. The precipitation intensity R KDP and the average reflectance factor Za is calculated. In the first spatial range (grid points), coefficients B and β with high accuracy and distance resolution are calculated.

[0075] FIG. 7 is a diagram for explaining a modified example of the processing unit 16 according to the first embodiment. In the modified example, the processing unit 16 according to the first embodiment is divided into two processing units 161 and 162. The first processing unit 161 includes a KDP calculation unit 34 and a Z calculation unit 38. The second processing unit 162 calculates R KDP calculation unit 36, Za calculation unit 40, first coefficient estimation unit 42, second coefficient estimation unit 44, and R KDP,Z The weather radar 2 includes a calculation unit 46. The first processing unit 161 may be provided in a plurality of weather radars 2, and the second processing unit 162 may be provided in common to the plurality of weather radars 2 (first processing units 161). In this case, the second processing unit 162 may be provided on a cloud and connected to the plurality of first processing units 161 via a network. In this case, there is no need to provide the second processing unit 162 in the weather radar 2, and the cost of the entire system is reduced.

[0076] Second embodiment Regarding the second embodiment, detailed description of the same parts as those in the first embodiment will be omitted, and the following mainly describes the parts that are different from the first embodiment.

[0077] The processing unit 16 according to the first embodiment calculates the average reflectance factor Za, the precipitation intensity R KDP and the low-resolution coefficient β calculated for the third spatial range w From the fourth spatial range, the high-resolution coefficient B n For this purpose, the processing unit 16 calculates the precipitation intensity R KDP,Z However, in light rain areas, the rate of change in the polarization phase difference KDP cannot be calculated, and the precipitation intensity R KDP In this case, the processing unit 16 calculates the high-resolution coefficient B n The precipitation intensity R KDP,Z In the light rain area, the processing unit 16 according to the first embodiment is unable to calculate a low-precision precipitation intensity R from the reflection factor Z using Equation 4 based on the coefficients B and β, which are set as fixed constants, as in the conventional method. Z may be calculated.

[0078] The second embodiment aims to improve the accuracy of precipitation intensity in a light rain region where the rate of change of polarization phase difference KDP cannot be calculated.

[0079] FIG. 8 is a block diagram for explaining an example of a processing unit 16B according to the second embodiment. The processing unit 16B includes a precipitation intensity calculation unit (R Z It comprises a calculation unit 52 and a selection unit 54.

[0080] R Z The calculation unit 52 calculates the reflectance factor Z and the coefficient B w , β w Using Equation 12, the precipitation rate R Z Calculate.

[0081]

number

[0082] Coefficient B used in Equation 12 w and coefficient β w Although R is a low-resolution coefficient calculated for the third spatial range, it is a coefficient that corresponds to the average raindrop size distribution in each area (third spatial range) at the observation time of the data. Z The calculation unit 52 calculates the precipitation intensity R with high accuracy compared to the case where the coefficients B and β, which have been set as fixed constants in the past, are used as they are. Z can be calculated.

[0083] The selection unit 54 selects the precipitation intensity R KDP,Z and precipitation intensity R Z and transmits the selected precipitation intensity to the output unit 18. FIG. 9 is a diagram for explaining an example of the selection principle of the selector 54 according to the second embodiment. The observation range of the weather radar 2 includes a heavy rain region 102 and a light rain region 104. In the heavy rain region 102, the precipitation intensity R KDP Therefore, the selection unit 54 selects the precipitation intensity R KDP,Z In the light rain area 104, the precipitation intensity RKDP Since the rainfall intensity R Z The selection unit 54 selects the precipitation intensity R KDP If is greater than or equal to the threshold, the precipitation intensity R KDP,Z The selection unit 54 selects the precipitation intensity R KDP If is less than the threshold, the precipitation intensity R Z Select .

[0084] According to the second embodiment, the precipitation intensity R KDP,Z For the light rain area 104 where the precipitation intensity R KDP,Z Instead of precipitation intensity R Z Therefore, it is possible to calculate the precipitation intensity even in light rain areas. Furthermore, the coefficient B w , β w Since it corresponds to the average raindrop size distribution at the observation time of the data, the precipitation intensity R Z High accuracy.

[0085] Third embodiment Regarding the third embodiment, detailed description of the same parts as those in the first embodiment will be omitted, and the following mainly describes the parts that are different from the first embodiment.

[0086] 10 is a block diagram for explaining an example of a processing unit 16C according to the third embodiment. The processing unit 16C includes a coefficient estimation unit 62 instead of the first coefficient estimation unit 42 and the second coefficient estimation unit 44 of the first embodiment.

[0087] In the third embodiment, the coefficient B of the third spatial range is calculated by using data from the past in addition to the data from the current time. w , β w This embodiment differs from the first embodiment in that the above is estimated.

[0088] The coefficient estimation unit 62 estimates the precipitation intensity R KDP and the data of the average reflectance factor Za and the past precipitation rate R KDP11 is a diagram for explaining an example of data of the current time and past time stored in the memory according to the third embodiment. KDP and the data of the average reflectance factor Za and the past precipitation rate R KDP An example of data for the average reflectivity factor Za is, for example, the inter-polarized phase difference Φ for 10 revolutions of the antenna observed at T=0 and past times T=-1, T=-2, ..., T=-9 in a weather radar 2 that mechanically rotates its antenna in the azimuth direction once per minute. DP Precipitation intensity R calculated from KDP and data on an average reflection factor Za calculated from the received power P for 10 revolutions of the antenna. The shaded area indicates a third spatial range in which the coefficients B and β are estimated. In the first embodiment, the third spatial range, which is the estimation area for the coefficient B or β, is the entire observation range. In the third embodiment, the coefficients B and β are estimated for the same spatial range (third spatial range). The third spatial range in the third embodiment is narrower than the third spatial range in the first embodiment.

[0089] The coefficient estimation unit 62 estimates the precipitation intensity R KDP Based on the data of the average reflectance factor Za, the precipitation intensity R KDP A data set is created that summarizes the relationship between the average reflectance factor Za and the coefficient B for the third spatial range based on the created data set in a manner similar to that of the first coefficient estimation unit 42 of the first embodiment. w , β w Estimate.

[0090] According to the third embodiment, by utilizing past data, the coefficient B w , β w This reduces the spatial range required to obtain a data set for estimating the coefficient B w , β w Even if the third spatial range, which is the estimated space of the w , β w This allows us to obtain R KDP,ZThe calculation unit 46 calculates the precipitation intensity R KDP,Z can be calculated.

[0091] The third embodiment, in which the use of past data is combined with the first embodiment, can be modified by combining the use of past data with the second embodiment. FIG. 12 is a block diagram for explaining an example of a processing unit 16D according to a modified example of the third embodiment. The processing unit 16D includes a coefficient estimation unit 62 instead of the first coefficient estimation unit 42 and the second coefficient estimation unit 44 of the second embodiment. The coefficient estimation unit 62 derives a coefficient B w , β w The coefficient estimation unit 62 estimates the coefficient B n Do not estimate R Z The calculation unit 52 calculates the coefficient B n Instead, the coefficient B w , β w From Equation 12, the precipitation intensity R Z Calculate.

[0092] Fourth embodiment Regarding the fourth embodiment, detailed description of the same parts as those of the first to third embodiments will be omitted, and the following mainly describes the parts that are different from those of the first to third embodiments.

[0093] In the first to third embodiments, the coefficients B and β are the same for each first spatial range in the third or fourth spatial range. In the fourth embodiment, the third or fourth spatial range is divided into a plurality of first spatial range groups according to the level of the reflectivity factor Z, and coefficients B and β having different values ​​according to the level of the reflectivity factor Z are estimated for each of the plurality of first spatial range groups.

[0094] The configuration of the processing unit 16 according to the fourth embodiment is similar to that of the processing unit 16 according to the first to third embodiments, and therefore is not shown in the drawings.

[0095] In the third embodiment, a fourth embodiment will be described in which coefficients B and β having different values ​​are estimated for each of a plurality of first spatial range groups according to the level of the average reflectance factor Za. Fig. 13 is a diagram for explaining an example of an estimation space of coefficients B and β according to the fourth embodiment.

[0096] For convenience, the fourth embodiment will be described with reference to FIG. 10 according to the third embodiment. The coefficient estimation unit 62 estimates the precipitation intensity R KDP A data set is created that organizes the relationship between the average reflectance factor Za and the average reflectance factor Za, and the data set is divided into a plurality of groups according to the intensity range of the average reflectance factor Za. The coefficient estimation unit 62 estimates the coefficient B w , β w For example, the coefficient estimation unit 62 divides the data set into group 1 in which the average reflectance factor Za is 35 [dBZ] or less, group 2 in which the average reflectance factor Za is greater than 35 [dBZ] and less than 60 [dBZ], and group 3 in which the average reflectance factor Za is greater than 60 [dBZ]. KDP The average value of Ra KDP Based on the relationship between the average value Zaa of the average reflectance factor Za and the average reflectance factor Za, the regression line of Equation 8 is obtained, and B w ,β w Estimate.

[0097] The coefficients of the fourth spatial range estimated from the data set of group 1 are B w1 , β w1 Let the coefficient of the fourth spatial range estimated from the data set of group 2 be B w2 , β w2 Let the coefficient of the fourth spatial range estimated from the data set of group 3 be B w3 , β w3 The number of divisions of the data set is not limited to three, but may be any number equal to or greater than two.

[0098] R Z The calculation unit 52 selects one of the pairs of coefficients B and β estimated by the coefficient estimation unit 62, and calculates the precipitation rate R ZIn this embodiment, the coefficients of group 1, in which the average reflectance factor Za is 35 dBZ or less, group 2, in which the average reflectance factor Za is greater than 35 dBZ and less than 60 dBZ, and group 3, in which the average reflectance factor Za is greater than 60 dBZ (group 1: B w1 , β w1 , Group 2:B w2 , β w2 , Group 3:B w3 , β w3 ) based on the precipitation intensity R Z is calculated using the following formula:

[0099]

number

[0100] In the fourth embodiment, by estimating the coefficients B and β within the range of values ​​of the reflectivity factor Z, it becomes possible to calculate precipitation intensity appropriate for the range of precipitation intensity values, and precipitation intensity can be calculated with high spatial resolution and high accuracy.

[0101] The fourth embodiment, which combines the estimation of coefficients B and β for a range of values ​​of the reflectivity factor Z with the third embodiment, can be modified by combining the estimation of coefficients B and β for a range of values ​​of the reflectivity factor Z with the first and second embodiments.

[0102] Fifth embodiment Regarding the fifth embodiment, detailed description of the same parts as those of the first to fourth embodiments will be omitted, and the following mainly describes the parts that are different from the first to fourth embodiments.

[0103] FIG. 14 is a diagram for explaining an example of a processing unit 16E according to the fifth embodiment. The processing unit 16E according to the fifth embodiment includes a coefficient memory 66 in addition to the configuration of the processing unit 16B (FIG. 8) according to the second embodiment. The coefficient memory 66 stores a fixed coefficient B c , β c The fixed coefficient B c , β c is the precipitation intensity R of the light rain area KDPWhen used to calculate, it is a coefficient that can maintain the calculation accuracy to a certain degree. c , β c is the precipitation intensity R calculated from the reflectivity factor Z based on the observation data of weather radar 2 in past precipitation cases. Z is the coefficient adjusted to fit the ground rain gauge data. Fixed coefficient B c , β c may be determined by machine learning.

[0104] In the first to fourth embodiments, the precipitation intensity R KDP Based on the data set that summarizes the relationship between the average reflection factor Za in the same section, the coefficient B w , β w is estimated for the third spatial range. The rate of change in polarization phase difference KDP can be calculated only for precipitation areas with a certain precipitation intensity or higher. Therefore, in light rain areas (for example, areas with precipitation of less than a few mm / h), the precipitation intensity R KDP The precipitation intensity R KDP The coefficient B of the third spatial range estimated from the data set that summarizes the relationship between the average reflectance factor Za of the same section and w , coefficient β w may not be suitable for light rain areas. In this case, the precipitation intensity R Z The accuracy of the measurement may be degraded.

[0105] The fifth embodiment aims to improve the accuracy of the precipitation intensity in the light rain area. The first coefficient estimator 42 of the processing unit 16E according to the fifth embodiment estimates the average reflectance factor Za and the precipitation intensity R KDP In addition to the fixed coefficient B stored in the coefficient memory 66, c , β c Also use coefficient B for the third spatial range w , β w Estimate.

[0106] First, the first coefficient estimation unit 42 estimates the precipitation rate R KDPA data set was created that summarizes the relationship between the average reflectance factor Za and the intensity of the precipitation R KDP The average value of Ra KDP The average value Zaa of the average reflectance factor Za is calculated, and the intensity range Ra KDP This is called Step 1.

[0107] Next, select several reflectance factors Z corresponding to very weak precipitation intensities (e.g., 0.5mm / h to 3mm / h) and compare the selected reflectance factors Z with the fixed coefficient B c , β c From the above, precipitation intensity R Z is calculated using Equation 4. The above is referred to as Step 2.

[0108] Next, the Ra calculated in step 1 KDP and Zaa, and the reflection factor Z of very light precipitation intensity and precipitation intensity R calculated in step 2 Z Based on the data obtained by combining both of the above data, the coefficient B is calculated for the third spatial range by the least squares method so that the reflectance factor Z fits the data obtained by combining the above quantity data in the same manner as in the first embodiment. w , coefficient β w The above is called step 3.

[0109] 15 is a diagram for explaining an example of the ZR characteristic obtained by the processing unit 16E according to the fifth embodiment. The vertical axis of FIG. 15 indicates the reflectance factor Z. The horizontal axis of FIG. 15 indicates the precipitation intensity R Z The black dots indicate the precipitation intensity R calculated in real time from the observation data (reflectance factor Z). Z The solid line shows the precipitation intensity R calculated in real time from the observation data. Z The white dots indicate the ZR line obtained from the fixed coefficient B c , β c The precipitation intensity R calculated using Z The dashed line indicates the coefficient B estimated in step 3. w , β w Precipitation intensity R calculated from ZThe ZR line obtained from the above is shown in Fig. 15. For the light rain area, the fixed coefficient B c , β c Using the coefficient B w , coefficient β w It can be seen that the accuracy of precipitation intensity in light rain areas is improved by estimating

[0110] The fifth embodiment, in which a coefficient memory 66 is added to the second embodiment, can be modified by adding the coefficient memory 66 to the first to fourth embodiments.

[0111] Sixth embodiment The first to fifth embodiments have described the information processing device 10 configured as a device separate from the weather radar 2 that observes precipitation intensity. The sixth embodiment will describe a system in which the information processing device 10 of the first to fifth embodiments is incorporated into the weather radar 2.

[0112] 16 is a diagram for explaining an example of a weather radar system 70 according to a sixth embodiment. The system 70 includes a transmitting / receiving device 72, a signal processing device 74, and an information processing device 80.

[0113] The transmitting / receiving device 72 corresponds to the weather radar 2 of the first to fifth embodiments. The transmitting / receiving device 72 includes an antenna and a motor. The transmitting / receiving device 72 drives the motor to rotate the antenna. The transmitting / receiving device 72 transmits microwaves from the antenna. The microwaves are reflected by raindrops 78 in a raincloud 76. The transmitting / receiving device 72 receives the reflected waves with the antenna.

[0114] The signal processing device 74 includes a storage unit corresponding to the first database 4 and the second database 6 of the first to fifth embodiments. The signal processing device 74 processes the signal of the reflected wave received by the transmitting / receiving device 72 to obtain observation data at each lattice point within the observation range, and calculates the inter-polarized phase difference Φ DP and the received power P. The information processing device 80 calculates the radar observation amount including the inter-polarized phase difference Φ DPThe radar observables of the received power P and the Doppler velocity V and the inter-polarization correlation coefficient ρhv generated by the signal processor 74 may also be calculated. DP and the received power P are output to the information processing device 80.

[0115] The information processing device 80 has the same configuration as the information processing device 10 described in the first to fifth embodiments. The sixth embodiment is similar to the first to fifth embodiments except that the information processing device 80 is incorporated in a weather radar system 70. Therefore, a description of the operation of the information processing device 80 will be omitted.

[0116] According to the sixth embodiment, there is provided a weather radar system including the information processing device described in the first to fifth embodiments. The weather radar system according to the sixth embodiment can also calculate precipitation intensity with high accuracy and high resolution as described in the first to fifth embodiments.

[0117] The first processing unit 161 and the second processing unit 162 according to the modification of the first embodiment shown in Fig. 7 are also applied to the second to sixth embodiments. The coefficient estimating unit 62 according to the modification of the third embodiment shown in Fig. 12 is also applied to the fifth and sixth embodiments.

[0118] According to at least one of the embodiments described above, it is possible to generate precipitation rate data with a wide spatial range and high accuracy.

[0119] According to at least one embodiment, the following information processing device, information processing method, program, and weather radar system are provided.

[0120] (1) an acquisition unit that acquires a received power and a polarized phase difference in a first spatial range transmitted from the radar; A processing unit that processes the received power and the inter-polarized phase difference, The processing unit includes: Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in the first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range that is wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; an information processing device that calculates the second precipitation intensity based on an estimated value of one of the first coefficient and the second coefficient in the third spatial range, an estimated value of the other of the first coefficient and the second coefficient in the fourth spatial range, and the reflectance factor.

[0121] (2) In the information processing device according to (1), The processing unit includes: One of the first coefficient and the second coefficient is estimated for the third spatial range so as to match the relationship between the reflectance factor and precipitation intensity, which is represented by fixed values ​​of the first coefficient and the second coefficient, in a range in which the reflectance factor is equal to or less than a first value.

[0122] (3) In the information processing device according to (1) or (2), The processing unit includes: estimating the first coefficients and the second coefficients for the third spatial range; Calculating a third precipitation rate for the first spatial range based on the first coefficient and the second coefficient; The second precipitation intensity or the third precipitation intensity is output.

[0123] (4) In the information processing device according to any one of (1) to (3), The processing unit includes: One of the first coefficient and the second coefficient is estimated for a third spatial range so as to match the relationship between the reflectance factor and precipitation intensity, which is represented by fixed values ​​of the first coefficient and the second coefficient, in a range in which the reflectance factor is equal to or less than a first value.

[0124] (5) In the information processing device according to any one of (1) to (4), The fourth spatial range is equal to the first spatial range.

[0125] (6) In the information processing device according to any one of (1) to (5), The processing unit includes: The first and second coefficients are estimated based on the reflectance factor and the first precipitation rate for a first period from the present to the past.

[0126] (7) In the information processing device according to any one of (1) to (6), The processing unit includes: The first and second coefficients are estimated for a plurality of ranges of the reflectance factor based on the reflectance factor and the first precipitation rate.

[0127] (8) In the information processing device according to any one of (1) to (6), The processing unit includes: The first and second coefficients are estimated for a plurality of ranges of the reflectance factor based on the reflectance factor and the first precipitation rate for a first period from the present to the past.

[0128] (9) In the information processing device according to any one of (1) to (8), The processing unit calculates a second precipitation intensity R in the first spatial range from the reflectance factor Z. KDP、Z Z=B×R KDP、Z β where B is the first coefficient and β is the second coefficient.

[0129] (10) A transceiver that transmits horizontally polarized and vertically polarized radio waves and receives reflected waves; a signal processing device that calculates a radar signal including a received power and an inter-polarized phase difference in a first spatial range based on the reflected wave signal output from the transmitting / receiving device; an information processing device that processes the received power and the inter-polarized phase difference, The information processing device includes: Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in the first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range that is wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; a weather radar system that calculates the second precipitation intensity based on an estimated value of one of the first coefficient and the second coefficient in the third spatial range, an estimated value of the other of the first coefficient and the second coefficient in the fourth spatial range, and the reflectivity factor.

[0130] (11) Obtaining a received power and an inter-polarized phase difference in a first spatial range transmitted from the radar; Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in the first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range that is wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; An information processing method for calculating the second precipitation intensity based on an estimated value of either the first coefficient or the second coefficient in the third spatial range, an estimated value of the other of the first coefficient or the second coefficient in the fourth spatial range, and the reflectance factor.

[0131] (12) Obtaining a received power and a phase difference between polarized waves in a first spatial range transmitted from a radar; Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change in inter-polarization phase difference in the first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; estimating, based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor, for a third spatial range that is wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; a program for calculating the second precipitation intensity based on an estimated value of one of the first coefficient and the second coefficient in the third spatial range, an estimated value of the other of the first coefficient and the second coefficient in the fourth spatial range, and the reflectance factor.

[0132] The present invention is not limited to the above-described embodiment, and the components can be modified and embodied in the implementation stage without departing from the gist of the invention. In addition, various inventions can be formed by appropriately combining the multiple components disclosed in the above-described embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0133] 2...weather radar, 34...cross-polarized phase difference change rate calculation unit, 36...precipitation intensity calculation unit, 38...reflection factor calculation unit, 40...statistics calculation unit, 42...first coefficient estimator, 44...second coefficient estimator, 46...precipitation intensity calculation unit

Claims

1. an acquisition unit that acquires a received power and an inter-polarized phase difference in a first spatial range transmitted from the radar; A processing unit that processes the received power and the inter-polarized phase difference, The processing unit includes: Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; An information processing device that calculates the second precipitation intensity based on an estimated value of either the first coefficient or the second coefficient in the third spatial range, an estimated value of the other of the first coefficient or the second coefficient in the fourth spatial range, and the reflectance factor.

2. The processing unit includes: The information processing device according to claim 1 , wherein either the first coefficient or the second coefficient is estimated for the third spatial range so as to conform to a relationship between the reflectance factor represented by the fixed first coefficient and the second coefficient and the precipitation intensity in a range in which the reflectance factor is equal to or less than a first value.

3. The processing unit includes: estimating the first coefficients and the second coefficients for the third spatial range; Calculating a third precipitation rate for the first spatial range based on the first coefficient and the second coefficient; The information processing apparatus according to claim 1 , further comprising: an output unit configured to output the second precipitation intensity or the third precipitation intensity.

4. The processing unit includes: The information processing device according to claim 3 , wherein either the first coefficient or the second coefficient is estimated for a third spatial range so as to conform to a relationship between the reflectance factor represented by fixed values ​​of the first coefficient and the second coefficient and precipitation intensity in a range in which the reflectance factor is equal to or less than a first value.

5. The information processing device according to claim 1 , wherein the fourth spatial range is equal to the first spatial range.

6. The processing unit includes: The information processing apparatus according to claim 1 , wherein the first coefficient and the second coefficient are estimated based on the reflectance factor and the first precipitation rate in a first period from the present to the past.

7. The processing unit includes: The information processing apparatus according to claim 1 , further comprising: estimating the first coefficient and the second coefficient for a plurality of ranges of the reflectance factor based on the reflectance factor and the first precipitation intensity.

8. The processing unit includes: The information processing device according to claim 1 , further comprising: estimating the first coefficient and the second coefficient for a plurality of ranges of the reflectance factor based on the reflectance factor and the first precipitation rate for a first period from the present to the past.

9. The processing unit calculates a second precipitation intensity R ＫＤＰ、Ｚ Z = B x R ＫＤＰ、Ｚ β 5. The information processing apparatus according to claim 1, wherein B is a first coefficient and β is a second coefficient.

10. A transceiver that transmits horizontally polarized and vertically polarized radio waves and receives reflected waves; a signal processing device that calculates a radar signal including a received power and an inter-polarized phase difference in a first spatial range based on the reflected wave signal output from the transmitting / receiving device; an information processing device that processes the received power and the inter-polarized phase difference, The information processing device includes: Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in a first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; A weather radar system that calculates the second precipitation intensity based on an estimated value of one of the first coefficient and the second coefficient in the third spatial range, an estimated value of the other of the first coefficient and the second coefficient in the fourth spatial range, and the reflectivity factor.

11. Acquire a received power and a phase difference between polarized waves in a first spatial range transmitted from the radar; Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of inter-polarization phase difference in a first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; Based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; An information processing method for calculating the second precipitation intensity based on an estimated value of either the first coefficient or the second coefficient in the third spatial range, an estimated value of the other of the first coefficient or the second coefficient in the fourth spatial range, and the reflectance factor.

12. acquiring a received power and a phase difference between polarized waves in a first spatial range transmitted from a radar; Calculating a reflectance factor of the first spatial range based on the received power; calculating a rate of change of the inter-polarization phase difference in the first spatial range for a second spatial range that is wider than the first spatial range based on the inter-polarization phase difference; calculating a first precipitation intensity in the first spatial range for the second spatial range based on the rate of change of the inter-polarized phase difference; based on the reflectance factor and the first precipitation rate, one of a first coefficient and a second coefficient for determining a second precipitation rate in the first spatial range from the reflectance factor is estimated for a third spatial range that is wider than the second spatial range; estimating the other of the first coefficient and the second coefficient for a fourth spatial range narrower than the third spatial range based on the reflectance factor and the first precipitation rate; A program that calculates the second precipitation intensity based on an estimated value of either the first coefficient or the second coefficient in the third spatial range, an estimated value of the other of the first coefficient or the second coefficient in the fourth spatial range, and the reflectance factor.

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