Weather forecasting device, weather forecasting method, and weather forecasting program

Abstract

To enable easy prediction of rainfall.SOLUTION: A weather forecasting device includes: an acquisition unit that acquires vapor information indicating an amount of water vapor in the atmosphere, measured by a water vapor sensor; a prediction unit that performs a prediction process to calculate a predicted value of the future amount of water vapor in the atmosphere based on the vapor information; and a determination unit that performs a determination process regarding future rainfall based on the predicted value.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a weather forecasting device, a weather forecasting method, and a weather forecasting program. [Background technology]

[0002] Conventionally, a technology has been developed for forecasting weather by simulating future weather conditions using observation data on meteorological conditions in the sky acquired by a radar device or the like. For example, Patent Document 1 (JP 2019-45146 A) discloses the following technology: That is, a weather forecasting device includes a precipitation risk derivation unit that derives the risk of precipitation on the ground based on the meteorological conditions in the sky acquired by the radar device, and an output unit that outputs information based on the risk of precipitation derived by the precipitation risk derivation unit. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-45146 Summary of the Invention [Problem to be solved by the invention]

[0004] In weather forecasting, the timing of rainfall may be predicted. When predicting the timing of rainfall using a radar device, as in the technology described in Patent Document 1, a large-scale radar device must be deployed. Furthermore, in the technology described in Patent Document 1, the observation data acquired by the radar device indicates the observation results for each region when the sky is divided into multiple regions, so when performing a simulation using the observation data, a lot of calculation time and effort is required.

[0005] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a weather forecasting device, a weather forecasting method, and a weather forecasting program that can easily make predictions about rainfall. [Means for solving the problem]

[0006] (1) A weather forecasting device according to an embodiment of the present disclosure includes an acquisition unit that acquires water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor, a prediction unit that performs a prediction process to calculate a predicted value of the future amount of water vapor in the atmosphere based on the water vapor information, and a determination unit that performs a determination process regarding future rainfall based on the predicted value.

[0007] In this way, by using predicted values ​​based on the measurement results of the water vapor sensor to make a judgment about future rainfall, compared to a configuration in which the judgment is made by simulation using observation results of meteorological conditions in the sky, there is no need to deploy a large-scale radar device to observe meteorological conditions in the sky, so the equipment for making judgment about rainfall can be made smaller. In addition, the calculation time and effort required to obtain the judgment results can be reduced. Therefore, rainfall predictions can be made easily.

[0008] (2) In the above (1), the water vapor information may indicate the amount of precipitable water vapor in the atmosphere as the amount of water vapor.

[0009] Precipitable water vapor is a physical quantity that represents the amount of precipitation that would occur if water vapor contained in the atmosphere from the ground to the upper atmosphere were to condense and turn into rain. With the above-described configuration, it is possible to calculate a predicted value of future precipitable water vapor based on the measurement results of precipitable water vapor using the water vapor sensor, thereby enabling more accurate judgment of future rainfall.

[0010] (3) In the above (1) or (2), the acquisition unit may acquire a plurality of pieces of water vapor information each indicating a plurality of water vapor amounts measured at different times, and the prediction unit may perform the prediction process based on the plurality of pieces of water vapor information.

[0011] With this configuration, the tendency of the amount of water vapor in the atmosphere can be taken into consideration, and therefore the predicted value of the amount of water vapor can be calculated more accurately.

[0012] (4) In (3) above, the acquisition unit may acquire, as the plurality of pieces of water vapor information, a first piece of water vapor information indicating the amount of water vapor at a first time and a second piece of water vapor information indicating the amount of water vapor at a second time that is earlier than the first time, and the prediction unit may calculate, in the prediction process, the predicted value at a time later than the first time using a relational equation based on the first water vapor information and the second water vapor information, the relational equation indicating the relationship between time and the amount of water vapor.

[0013] With this configuration, prediction processing can be performed using a relational expression based on the tendency of the amount of water vapor in the atmosphere, so that the predicted value of the amount of water vapor can be calculated simply and more accurately.

[0014] (5) In (3) or (4) above, the acquisition unit may acquire first water vapor information indicating the amount of water vapor at a first time and second water vapor information indicating the amount of water vapor at a second time that is earlier than the first time, and the prediction unit may perform the prediction process using at least one of the difference between the amount of water vapor indicated by the first water vapor information and the amount of water vapor indicated by the second water vapor information, and the time difference between the first time and the second time.

[0015] With this configuration, it is possible to easily calculate a predicted value of the water vapor amount using the past change in the amount of water vapor in the atmosphere, and to easily predict the timing when the amount of water vapor will reach the predicted value using the time difference between the first time and the second time.

[0016] (6) In any one of (1) to (5) above, the determination unit may perform the determination process based on a result of comparing the predicted value with a threshold value.

[0017] In this way, by comparing the predicted water vapor amount with the threshold value, it is possible to easily determine whether or not rain is expected.

[0018] (7) In the above (6), the threshold value may be a value that depends on at least one of the season and the installation location of the water vapor sensor.

[0019] With this configuration, the determination process can be performed using an appropriate threshold value according to either or both of the time when the determination process is performed and the installation location of the water vapor sensor.

[0020] (8) In (6) or (7) above, the acquisition unit may acquire multiple pieces of water vapor information each indicating multiple amounts of water vapor measured at different times, and the weather forecasting device may further include a threshold setting unit that updates the threshold based on statistical values ​​of the multiple amounts of water vapor.

[0021] With this configuration, the threshold value can be updated to a more appropriate value based on the statistical value of the amount of water vapor in the atmosphere, thereby improving the accuracy of the determination result.

[0022] (9) In any of (1) to (8) above, the weather forecasting device may further include a notification unit that performs notification processing to notify the judgment result of the judgment unit when the judgment unit makes a positive judgment about the rainfall.

[0023] With this configuration, the user of the weather forecasting device can recognize that there is a possibility of rain in the near future.

[0024] (10) In (9) above, the acquisition unit may further acquire the water vapor information indicating the amount of water vapor at a post-notification time, which is the time after the notification process is performed by the notification unit, and the judgment unit may perform the judgment process periodically or irregularly, and the notification unit may perform the notification process again if the amount of water vapor at the post-notification time satisfies a predetermined condition and the judgment unit again makes a positive judgment about the rainfall in the judgment process.

[0025] With this configuration, the timing of notifying the judgment result again can be adjusted depending on the amount of water vapor after notifying a positive judgment result about rainfall, thereby reducing the frequency of notifications to users of the weather forecasting device.

[0026] (11) In the above (10), the predetermined condition may be that the amount of water vapor at the post-notification time is equal to or less than a reference value.

[0027] With this configuration, if the amount of water vapor at the time after notification has decreased to below the reference value, the notification process can be performed again, thereby preventing frequent notifications to the user during a period in which the judgment result is positive, for example.

[0028] (12) In any of (9) to (11) above, the judgment unit may perform the judgment process periodically or irregularly, and the notification unit may perform the notification process again when a predetermined time has elapsed since the time when the notification process was performed and the judgment unit again makes a positive judgment about the rainfall in the judgment process.

[0029] With this configuration, the notification process can be performed again after a predetermined time has elapsed since the notification process was performed, thereby preventing frequent notifications from being sent to the user of the weather forecasting device.

[0030] (13) In any of (9) to (12) above, the acquisition unit may further acquire rainfall information regarding rainfall at the target point of the judgment process, the judgment unit may perform the judgment process periodically or irregularly, and the notification unit may perform the notification process again if the rainfall information satisfies a predetermined condition and the judgment unit again makes a positive judgment about the rainfall in the judgment process.

[0031] With this configuration, after notifying a positive judgment result regarding rainfall, the timing at which the judgment result needs to be notified again can be adjusted depending on the weather at the target location, thereby reducing the frequency of notifications to users of the weather forecasting device.

[0032] (14) A weather forecasting method according to an embodiment of the present disclosure is a weather forecasting method for a weather forecasting device, which acquires water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor, performs a prediction process to calculate a predicted value of the future water vapor amount in the atmosphere based on the water vapor information, and performs a determination process regarding future rainfall based on the predicted value.

[0033] In this way, by using predicted values ​​based on the measurement results of a water vapor sensor to make a judgment about future rainfall, compared to a configuration in which the judgment is made by simulation using observation results of meteorological conditions in the sky, there is no need to deploy a large-scale radar device to observe meteorological conditions in the sky, so the equipment for making judgment about rainfall can be made smaller.In addition, the calculation time and effort required to obtain the judgment results can be reduced.As a result, rainfall predictions can be made easily.

[0034] (15) A weather forecasting program according to an embodiment of the present disclosure is a weather forecasting program used in a weather forecasting device, and is a program for causing a computer to execute the following processes: a process of acquiring water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor; a process of performing a prediction process of calculating a predicted value of the future amount of water vapor in the atmosphere based on the water vapor information; and a process of performing a determination process regarding future rainfall based on the predicted value.

[0035] In this way, by using predicted values ​​based on the measurement results of the water vapor sensor to make a judgment about future rainfall, compared to a configuration in which the judgment is made by simulation using observation results of meteorological conditions in the sky, there is no need to deploy a large-scale radar device to observe meteorological conditions in the sky, so the equipment for making judgment about rainfall can be made smaller. In addition, the calculation time and effort required to obtain the judgment results can be reduced. Therefore, rainfall predictions can be made easily. [Effects of the Invention]

[0036] According to the present disclosure, rainfall predictions can be easily made. [Brief explanation of the drawings]

[0037] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a weather forecasting system according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating an example of precipitable water vapor measured by the microwave radiometer according to the embodiment of the present disclosure. [Figure 3] FIG. 3 is a diagram illustrating an example of precipitable water vapor data generated by the weather forecasting device according to the embodiment of the present disclosure. [Figure 4] FIG. 4 is a diagram illustrating an example of a prediction process performed by the weather prediction device according to the embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram illustrating an example of a prediction result of a prediction process performed by the weather prediction device according to the embodiment of the present disclosure. [Figure 6] FIG. 6 is a diagram illustrating an example of a determination result of the determination process performed by the weather forecasting device according to the embodiment of the present disclosure. [Figure 7] FIG. 7 is a flowchart illustrating an example of an operation procedure when the weather forecasting device according to the embodiment of the present disclosure performs a determination process. [Figure 8] FIG. 8 is a flowchart illustrating an example of an operation procedure when the weather forecasting device according to the embodiment of the present disclosure performs the determination process. DETAILED DESCRIPTION OF THE INVENTION

[0038] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, identical or corresponding parts are designated by the same reference numerals, and their description will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any manner.

[0039] <Weather forecasting system> Fig. 1 is a diagram illustrating an example of a configuration of a weather forecasting system according to an embodiment of the present disclosure. Referring to Fig. 1, a weather forecasting system 501 includes a weather forecasting device 101, a microwave radiometer 201, a rainfall sensor 301, and a terminal device 401. The microwave radiometer 201 is an example of a water vapor sensor.

[0040] The weather forecasting device 101 makes a prediction regarding rainfall at a certain point (hereinafter also referred to as "target point Q"). The weather forecasting device 101 is, for example, a server.

[0041] The terminal device 401 is, for example, a PC (Personal Computer) owned by an employee of a local government (hereinafter also referred to as a user) in a region including the target point Q. Note that the terminal device 401 is not limited to a PC, and may be a communication terminal device such as a tablet.

[0042] [Microwave Radiometer] The microwave radiometer 201 is installed, for example, fixedly at a predetermined location. The microwave radiometer 201 communicates with the weather forecasting device 101, for example, wirelessly.

[0043] The microwave radiometer 201 measures the amount of water vapor in the atmosphere. Here, the microwave radiometer 201 measures, for example, precipitable water vapor as the amount of water vapor in the atmosphere.

[0044] More specifically, for example, the microwave radiometer 201 receives microwaves emitted by water vapor contained in the atmosphere and measures the intensity of the received microwaves. Then, the microwave radiometer 201 calculates the amount of precipitable water vapor in the atmosphere by substituting the measured microwave intensity into a predetermined arithmetic expression.

[0045] Fig. 2 is a diagram illustrating an example of precipitable water vapor measured by a microwave radiometer according to an embodiment of the present disclosure. Fig. 2 is a graph illustrating a time series change in precipitable water vapor measured by a microwave radiometer 201 from 9:00 on January 1, 2024 to around 14:00 on January 12, 2024. In Fig. 2, the horizontal axis represents time, and the vertical axis represents precipitable water vapor.

[0046] Referring to Figure 2, the amount of precipitable water at 15:56 on January 6, 2024 is 16.34 mm. The amount of precipitable water at 14:20 on January 12, 2024 is 10.74 mm.

[0047] When the microwave radiometer 201 measures precipitable water vapor, it transmits water vapor information C indicating the measurement result and the measurement time to the weather forecasting device 101. The microwave radiometer 201 calculates precipitable water vapor and transmits the water vapor information C, for example, periodically. In this embodiment, the microwave radiometer 201 calculates precipitable water vapor and transmits the water vapor information C, for example, every minute.

[0048] [Weather forecasting device] The weather forecasting device 101 includes an acquisition unit 11, a prediction unit 12, a determination unit 13, a notification unit 14, a threshold setting unit 15, and a storage unit 16. Some or all of the acquisition unit 11, the prediction unit 12, the determination unit 13, the notification unit 14, and the threshold setting unit 15 are realized by, for example, a processing circuit including one or more processors. The storage unit 16 is, for example, a non-volatile memory included in the processing circuit.

[0049] (Acquisition Department) The acquisition unit 11 acquires water vapor information C that indicates the amount of water vapor in the atmosphere, for example, the amount of precipitable water vapor, measured by the microwave radiometer 201.

[0050] More specifically, for example, the acquisition unit 11 receives the water vapor information C from the microwave radiometer 201. Then, the acquisition unit 11 stores the received water vapor information C in the storage unit 16.

[0051] (Determination process) For example, the prediction unit 12 performs a prediction process to calculate a predicted value Wp of future precipitable water vapor in the atmosphere based on a plurality of pieces of water vapor information C indicating a plurality of water vapor amounts measured at different times, which are acquired by the acquisition unit 11. For example, the prediction unit 12 performs the prediction process periodically or irregularly.

[0052] The determination unit 13 performs a determination process regarding future rainfall based on the predicted value Wp predicted by the prediction unit 12. For example, the determination unit 13 performs the determination process periodically or irregularly. Below, an example will be described in which the prediction unit 12 and the determination unit 13 perform the prediction process and the determination process, respectively, periodically.

[0053] More specifically, for example, when a processing timing T1 of the prediction process arrives, the prediction unit 12 acquires from the storage unit 16 a plurality of pieces of water vapor information C accumulated during a period A from the previous processing timing T1 to the current processing timing T1. Then, the prediction unit 12 generates precipitable water vapor data K indicating a time-series change in precipitable water vapor during the period A based on the plurality of pieces of water vapor information C. The length of the period A is, for example, three hours.

[0054] Fig. 3 is a diagram illustrating an example of precipitable water vapor data created by a weather forecasting device according to an embodiment of the present disclosure. In Fig. 3, the horizontal axis represents time, and the vertical axis represents precipitable water vapor. Fig. 3 shows precipitable water vapor data K for the period from 9:00 to 12:00 on January 1, 2024.

[0055] Referring to FIG. 3, the amount of precipitable water at 9:00 and 12:00 on January 1, 2024 is 8.89 mm and 8.42 mm, respectively.

[0056] For example, when the prediction unit 12 creates precipitable water vapor data K, it calculates the difference Dw between the precipitable water vapor at the most recent measurement time ta and the precipitable water vapor at a measurement time tc that precedes the measurement time ta, as indicated by the precipitable water vapor data K. The measurement time ta is an example of the first time, and the measurement time tc is an example of the second time.

[0057] In this embodiment, for example, the measurement time tc is three hours before the measurement time ta. That is, the time difference Dt1 between the measurement time ta and the measurement time tc is three hours. Note that the time difference Dt1 is not limited to three hours and can be any other length of time.

[0058] FIG. 4 is a diagram illustrating an example of a prediction process performed by the weather prediction device according to the embodiment of the present disclosure.

[0059] 4, for example, the prediction unit 12 performs the prediction process using at least one of the difference Dw between the precipitable water vapor at the measurement time ta and the precipitable water vapor at the measurement time tc, and the time difference Dt1 between the measurement time ta and the measurement time tc. In this embodiment, the prediction unit 12 performs the prediction process using both the difference Dw and the time difference Dt1.

[0060] More specifically, for example, the prediction unit 12 performs prediction processing using a relational expression F based on water vapor information C indicating the amount of precipitable water vapor at measurement time ta and water vapor information C indicating the amount of precipitable water vapor at measurement time tc. For example, the relational expression F indicates the relationship between time and the amount of precipitable water vapor.

[0061] Specifically, the prediction unit 12 calculates the difference Dw between the precipitable water vapor at measurement time ta and the precipitable water vapor at measurement time tc using the precipitable water vapor data K, and then derives the relational equation F using the calculated difference Dw and the time difference Dt1.

[0062] The graph shown in Fig. 4 is a graph for explaining an example of relational expression F derived by prediction unit 12. In Fig. 4, the horizontal axis represents time, and the vertical axis represents precipitable water vapor. In the example shown in Fig. 4, the precipitable water vapor at measurement time ta and the precipitable water vapor at measurement time tc are "Wa" mm and "Wc" mm, respectively. In the example shown in Fig. 4, relational expression F is a linear function.

[0063] The prediction unit 12 uses the derived relational expression F to calculate a predicted value Wp of precipitable water at a time tp after the measurement time ta in the prediction process.

[0064] For example, the time difference Dt2 between time tp and measurement time ta is the same as the time difference Dt1 between measurement time ta and measurement time tc. That is, in the example shown in FIG. 4, time tp is three hours after measurement time ta.

[0065] In relational expression F, which is a linear function, if the time difference Dt2 is the same as the time difference Dt1, the change in precipitable water vapor during the period from measurement time ta to time tp is the same as the change in precipitable water vapor during the period from measurement time tc to measurement time ta, i.e., the difference Dw. Therefore, when the time difference Dt2 is the same as the time difference Dt1, the prediction unit 12 calculates the predicted value Wp by substituting the precipitable water vapor at measurement time ta, i.e., "Wa" mm, and the difference Dw into the following equation (1). Wp = Wa + Dw (1)

[0066] Note that the time difference Dt2 may be different from the time difference Dt1. In this case, the prediction unit 12 calculates the change in precipitable water vapor during the period from measurement time ta to time tp as the value obtained by multiplying the difference Dw by the ratio of the time difference Dt2 to the time difference Dt1. The prediction unit 12 then calculates the predicted value Wp by adding the precipitable water vapor at measurement time ta and the calculated change.

[0067] Furthermore, the prediction unit 12 may be configured to derive the relational expression F using water vapor information C indicating the precipitable water vapor at measurement time ta and water vapor information C indicating the precipitable water vapor at measurement time tc, as well as water vapor information C indicating the precipitable water vapor at measurement times other than measurement times ta and tc, i.e., three or more pieces of water vapor information C. In this case, for example, the prediction unit 12 derives the relational expression F of a linear function using the least squares method or the like. Note that when deriving the relational expression F using three or more pieces of water vapor information C, the prediction unit 12 is not limited to the relational expression F of a linear function, and may be configured to derive the relational expression F of a higher-order function such as a quadratic function.

[0068] Fig. 5 is a diagram illustrating an example of a prediction result of a prediction process performed by a weather prediction device according to an embodiment of the present disclosure. Fig. 5 shows time-series changes in the predicted value Wp corresponding to the time-series changes in the precipitable water vapor shown in Fig. 2. In Fig. 5, the horizontal axis represents time, and the vertical axis represents the predicted value Wp.

[0069] 2 and 5, the predicted value Wp corresponding to 16.34 mm of precipitable water at 15:56 on January 6, 2024 is 18.81 mm. The predicted value Wp corresponding to 10.74 mm of precipitable water at 14:20 on January 12, 2024 is 10.18 mm.

[0070] Referring back to FIG. 1, after calculating the predicted value Wp, the prediction unit 12 outputs the calculation result and prediction result information indicating the time tp to the determination unit 13.

[0071] For example, the determination unit 13 performs the determination process based on the result of comparison between the predicted value Wp and a threshold value Th1.

[0072] For example, the storage unit 16 stores the threshold value Th1 for each month. That is, the threshold value Th1 is a value according to the season. For example, the threshold value Th1 corresponding to each month in the summer is greater than the threshold value Th1 corresponding to each month in the winter.

[0073] Note that threshold value Th1 is not limited to a value according to the season, and may be a value according to the installation location of microwave radiometer 201 shown in Fig. 1. In this case, for example, threshold value Th1 corresponding to an installation location where the average rainfall is greater than a predetermined reference value is greater than threshold value Th1 corresponding to an installation location where the average rainfall is less than the reference value. Furthermore, threshold value Th1 may be a value according to both the season and the installation location of microwave radiometer 201.

[0074] When the determination unit 13 receives prediction result information from the prediction unit 12, it selects a threshold value Th1 corresponding to the time tp indicated by the prediction result information from among the plurality of threshold values ​​Th1 stored in the storage unit 16.

[0075] Then, the determination unit 13 compares the predicted value Wp indicated by the prediction result information received from the prediction unit 12 with the selected threshold value Th1 or more. Here, it is assumed that the threshold value Th1 is 18.8 mm.

[0076] When the predicted value Wp is equal to or greater than the threshold value Th1, the determination unit 13 makes a positive determination regarding future rainfall. Specifically, for example, the determination unit 13 determines that there is a high possibility that rain will occur in the near future at the target point Q of the determination process.

[0077] On the other hand, when the predicted value Wp is less than the threshold value Th1, the determination unit 13 makes a negative determination regarding future rainfall. Specifically, for example, the determination unit 13 determines that there is a low possibility that rain will occur at the target point Q in the near future.

[0078] FIG. 6 is a diagram illustrating an example of a determination result of the determination process performed by the weather forecasting device according to the embodiment of the present disclosure.

[0079] Referring to FIG. 6, the predicted value Wp1 corresponding to 13.80 mm of precipitable water at 7:40 PM on January 2, 2024 is 19.18 mm. The predicted value Wp2 corresponding to 17.64 mm of precipitable water at 3:18 PM on January 3, 2024 is 18.95 mm. The predicted value Wp3 corresponding to 16.34 mm of precipitable water at 3:56 PM on January 6, 2024 is 18.81 mm. The predicted value Wp4 corresponding to 18.15 mm of precipitable water at 8:56 AM on January 10, 2024 is 18.82 mm. The predicted value Wp5 corresponding to 18.22 mm of precipitable water at 9:38 AM on January 10, 2024 is 18.83 mm.

[0080] 6, the predicted values ​​Wp1, Wp2, Wp3, Wp4, and Wp5 are greater than the threshold value Th1, i.e., 18.8 mm. In this case, the determination unit 13 makes a positive determination regarding future rainfall in the determination process.

[0081] FIG. 6 also shows the time when it actually started to rain at the target point Q. In the example shown in FIG. 6, in the determination process using the precipitable water mass at 15:18 on January 3, 2024, the determination unit 13 makes a positive determination, and rain started to fall at 20:31 on the same day. In the determination process using the precipitable water mass at 15:56 on January 6, 2024, the determination unit 13 makes a positive determination, and rain started to fall at 16:56 on the same day. In the determination process using the precipitable water mass at 8:56 on January 10, 2024, the determination unit 13 makes a positive determination, and rain started to fall at 11:28 on the same day. In the determination process using the precipitable water mass at 9:38 on January 10, 2024, the determination unit 13 makes a positive determination, and rain started to fall at 11:28 on the same day.

[0082] The determining unit 13 also made a positive determination in the determination process using the amount of precipitable water at 15:18 on January 3, 2024. However, it did not rain on that day.

[0083] Referring back to FIG. 1, when the determination unit 13 makes a positive determination about rainfall in the determination process, it outputs positive determination information indicating that rainfall is expected at the target point Q to the notification unit 14.

[0084] (Update of threshold Th1) For example, the threshold setting unit 15 performs an update process to update the threshold Th1 using a plurality of pieces of water vapor information C that are acquired by the acquisition unit 11 and indicate a plurality of amounts of precipitable water vapor measured at different times.

[0085] More specifically, for example, when processing timing T2 of the update process arrives, the threshold setting unit 15 acquires from the storage unit 16 a plurality of pieces of water vapor information C (hereinafter also referred to as "a plurality of pieces of water vapor information Ca") accumulated during a period B from the previous processing timing T2 to the current processing timing T2. The length of period B is, for example, three months.

[0086] For example, the threshold setting unit 15 updates the threshold Th1 based on the statistical values ​​E of the plurality of amounts of precipitable water vapor indicated by the plurality of pieces of water vapor information Ca acquired from the storage unit 16.

[0087] Specifically, for example, when the threshold setting unit 15 acquires a plurality of pieces of water vapor information Ca from the storage unit 16, it calculates the average value of the plurality of precipitable water vapor amounts indicated by the plurality of pieces of water vapor information Ca as the statistical value E. Note that the threshold setting unit 15 may be configured to calculate a representative value of the plurality of precipitable water vapor amounts as the statistical value E.

[0088] After calculating the statistical value E, the threshold setting unit 15 calculates the threshold Th1 by substituting the calculated statistical value E into a predetermined arithmetic expression. Then, the threshold setting unit 15 stores the calculated threshold Th1 in the storage unit 16 as a new threshold Th1.

[0089] (Notification Department) For example, when the determination unit 13 makes a positive determination regarding rainfall, the notification unit 14 performs a notification process of notifying the determination result by the determination unit 13 .

[0090] More specifically, for example, the notification unit 14 counts the number of times that the positive determination information is received from the determination unit 13. When the notification unit 14 receives the first positive determination information from the determination unit 13, the notification unit 14 creates an email in HTML (HyperText Markup Language) format that includes the positive determination information. Then, the notification unit 14 transmits the created email to the terminal device 401.

[0091] By checking the received email on the terminal device 401, the user recognizes that there is a high possibility that rain will occur at the target point Q in the near future.

[0092] When the notification unit 14 sends the created email to the terminal device 401, it outputs notification completion information indicating that the notification process has been completed to the acquisition unit 11. Furthermore, for example, when the notification unit 14 sends the email to the terminal device 401, it starts a timer (not shown).

[0093] The notification unit 14 may be configured to perform the notification process by a method other than sending an email including the positive determination information received from the determination unit 13. For example, the notification unit 14 may be configured to display a screen G indicating a positive determination result by the determination unit 13 on the display unit of the terminal device 401. In this case, the notification unit 14 transmits screen information indicating the screen G to the terminal device 401. Upon receiving the screen information from the weather forecasting device 101, the terminal device 401 draws the screen G on the web browser displayed on its own display unit based on the screen information.

[0094] (Precipitable water amount at the time of notification) For example, the acquisition unit 11 acquires water vapor information C indicating the amount of precipitable water vapor at the time after the notification unit 14 has performed the notification process (hereinafter also referred to as "post-notification time").

[0095] More specifically, for example, after receiving notification completion information from the notification unit 14, the acquisition unit 11 stores the received water vapor information C in the memory unit 16 and outputs the water vapor information C to the notification unit 14 each time it receives water vapor information C from the microwave radiometer 201.

[0096] (Rainfall information) 1 again, the rainfall sensor 301 is, for example, fixedly installed at a target point Q of the determination process. The rainfall sensor 301 measures the amount of rainfall R at the target point Q. The rainfall sensor 301 communicates with the weather forecasting device 101 by wireless communication, for example.

[0097] In the weather forecasting device 101, the acquisition unit 11 further acquires rainfall information indicating the amount of rainfall R measured by the rainfall sensor 301 and the time at which the amount of rainfall R was measured.

[0098] More specifically, for example, when the acquisition unit 11 receives notification completion information from the notification unit 14, the acquisition unit 11 transmits, to the rainfall sensor 301, request information requesting transmission of rainfall information.

[0099] When the rainfall sensor 301 receives the request information from the weather forecasting device 101, it measures the amount of rainfall R after receiving the request information. Then, the rainfall sensor 301 transmits rainfall information indicating the measurement result and the measurement time to the weather forecasting device 101. The rainfall sensor 301 measures the amount of rainfall R and transmits the rainfall information, for example, periodically.

[0100] In the weather forecasting device 101, the acquisition unit 11 outputs the received rainfall information to the notification unit 14 every time the acquisition unit 11 receives rainfall information from the rainfall sensor 301.

[0101] (re-notification) (a) Example 1 For example, if the amount of precipitable water at the post-notification time satisfies a predetermined condition A1 and the determination unit 13 makes a positive determination regarding future rainfall in the determination process, the notification unit 14 performs the notification process again.

[0102] For example, condition A1 is that the amount of precipitable water at the post-notification time is equal to or less than a reference value S. In this embodiment, for example, the reference value S is a value smaller than a threshold value Th1 that is the criterion for the determination process. The reference value S is, for example, registered in advance in the storage unit 16 by the user.

[0103] When the notification unit 14 receives the second or subsequent positive judgment information from the determination unit 13, it compares the precipitable water vapor indicated by the water vapor information C received from the acquisition unit 11 with the reference value S. Specifically, for example, when the notification unit 14 receives the first water vapor information C from the acquisition unit 11 after receiving the positive judgment information from the determination unit 13, it compares the precipitable water vapor indicated by the water vapor information C (hereinafter also referred to as "precipitable water vapor We") with the reference value S.

[0104] The notification unit 14 performs the notification process again when the amount of precipitable water We is equal to or less than the reference value S. On the other hand, when the amount of precipitable water We is greater than the reference value S, the notification unit 14 does not perform the notification process.

[0105] The weather forecasting device 101 may be configured to update the reference value S in the storage unit 16. In this case, for example, the weather forecasting device 101 updates the reference value S using statistical values ​​of multiple precipitable waterfalls for a predetermined period before the time when it starts to rain at the target point Q.

[0106] Specifically, for example, when rainfall information received from the rainfall sensor 301 indicates a rainfall amount R equal to or greater than a predetermined threshold, the weather forecasting device 101 acquires from the storage unit 16 a plurality of pieces of water vapor information C accumulated during a period from three hours before the measurement time of the rainfall amount R to the measurement time. The weather forecasting device 101 then calculates statistical values ​​of the precipitable water vapor indicated by the plurality of pieces of water vapor information C, and calculates the reference value S by substituting the calculated statistical values ​​into a predetermined arithmetic expression. The weather forecasting device 101 saves the calculated reference value S in the storage unit 16 as a new reference value S.

[0107] (b) Example 2 For example, if a predetermined time has elapsed since the post-notification time and the determination unit 13 has made a positive determination regarding rainfall in the determination process, the notification unit 14 performs the notification process again.

[0108] More specifically, for example, when notification unit 14 receives second or subsequent positive determination information from determination unit 13 after 24 hours or more have elapsed since the previous notification process, i.e., after 24 hours or more have elapsed since the timer was started, notification unit 14 performs notification process again. Then, notification unit 14 resets the timer and then restarts it. On the other hand, even if notification unit 14 receives second or subsequent positive determination information from determination unit 13 before 24 hours have elapsed since the timer was started, notification unit 14 does not perform notification process.

[0109] (c) Example 3 For example, if the rainfall information acquired by the acquisition unit 11 satisfies the predetermined condition A2 and the determination unit 13 makes a positive determination about rainfall in the determination process, the notification unit 14 performs the notification process again.

[0110] More specifically, for example, when the notification unit 14 receives the second or subsequent positive determination information from the determination unit 13, the notification unit 14 compares the rainfall amount R indicated by the rainfall information received from the acquisition unit 11 with the threshold value Th2. Specifically, for example, when the notification unit 14 receives the first rainfall information from the acquisition unit 11 after receiving the positive determination information from the determination unit 13, the notification unit 14 compares the rainfall amount R indicated by the rainfall information (hereinafter also referred to as "rainfall amount Ra") with the threshold value Th2. In this case, for example, the condition A2 is that the rainfall amount Ra is less than the threshold value Th2. The threshold value Th2 is, for example, registered in advance in the storage unit 16 by the user.

[0111] If the amount of rainfall Ra is less than the threshold value Th2, the notification unit 14 determines that the weather at the target point Q is not rainy. Then, the notification unit 14 performs the notification process again.

[0112] On the other hand, if the amount of rainfall Ra is equal to or greater than the threshold value Th2, the notification unit 14 determines that the weather at the target point Q is rainy. In this case, the notification unit 14 does not perform notification processing.

[0113] 1 may be configured to perform a detection process to qualitatively detect whether or not it is raining at the target point Q, instead of measuring the amount of rainfall R at the target point Q. In this case, for example, condition A2 is that the detection result of the rainfall sensor 301 indicates that it is not raining at the target point Q.

[0114] Specifically, for example, when the rainfall sensor 301 receives the request information from the weather forecasting device 101, it performs a detection process during a period from when the request information is received until a predetermined time has elapsed. Then, the rainfall sensor 301 transmits information indicating the detection result as rainfall information to the weather forecasting device 101. In the weather forecasting device 101, the notification unit 14 performs the notification process again when the detection result indicated by the rainfall information received from the rainfall sensor 301 via the acquisition unit 11 indicates that it is not raining at the target point Q.

[0115] <Operation flow> A weather forecasting device 101 according to an embodiment of the present disclosure includes a computer including a memory, and a processor such as a CPU (Central Processing Unit) in the computer reads from the memory and executes a program including some or all of the steps in the following flowchart. The program for this device can be installed externally. The program for this device is distributed in a state stored on a recording medium or via a communication line.

[0116] 7 and 8 are flowcharts defining an example of an operation procedure when the weather forecasting device according to the embodiment of the present disclosure performs the determination process.

[0117] 7 and 8, first, weather predicting apparatus 101 waits for reception of water vapor information C from microwave radiometer 201 (NO in step ST101).

[0118] Next, when the weather forecasting device 101 receives the water vapor information C from the microwave radiometer 201 (YES in step ST101), the weather forecasting device 101 stores the received water vapor information C in the storage unit 16 (step ST102).

[0119] The weather predicting device 101 stores new water vapor information C received from the microwave radiometer 201 in the storage unit 16 (steps ST101 and ST102) until the processing timing T1 arrives (NO in step ST103).

[0120] Then, when processing timing T1 arrives (YES in step ST103), weather forecasting device 101 creates precipitable water vapor data K that indicates a time-series change in precipitable water vapor during period A from the previous processing timing T1 to the current processing timing T1. For example, as described above, weather forecasting device 101 creates precipitable water vapor data K using the multiple pieces of water vapor information C accumulated in memory unit 16 during period A (step ST104).

[0121] Next, after creating the precipitable water vapor data K, the weather predicting device 101 derives a relational expression F that indicates the relationship between time and precipitable water vapor. For example, as described above, after creating the precipitable water vapor data K, the weather predicting device 101 calculates the difference Dw between the precipitable water vapor at the most recent measurement time ta indicated by the precipitable water vapor data K and the precipitable water vapor at a measurement time tc that precedes the measurement time ta. Then, the weather predicting device 101 derives the relational expression F using the calculated difference Dw and the time difference Dt1 between the measurement times ta and tc (step ST105).

[0122] Next, after deriving the relational expression F, the weather predicting device 101 uses the derived relational expression F to calculate a predicted value Wp of precipitable water at a time tp after the measurement time ta (step ST106).

[0123] Next, the weather predicting device 101 selects a threshold value Th1 corresponding to the month including the time tp from the monthly threshold values ​​Th1 stored in the storage unit 16 (step ST107).

[0124] Next, the weather predicting device 101 compares the calculated predicted value Wp with the selected threshold value Th1 (step ST108).

[0125] If the predicted value Wp is less than the threshold value Th1 (NO in step ST108), the weather predicting device 101 makes a negative determination about future rainfall. Specifically, the weather predicting device 101 determines that there is a low possibility that rain will occur at the target point Q in the near future (step ST109), and waits for the arrival of the next processing timing T1 (NO in step ST103).

[0126] On the other hand, if the predicted value Wp is equal to or greater than the threshold value Th1 (YES in step ST108), the weather predicting device 101 makes a positive determination regarding future rainfall. Specifically, the weather predicting device 101 determines that there is a high possibility that rain will occur at the target point Q in the near future (step ST110).

[0127] Next, if the number of times that a positive determination has been made regarding rainfall is the first time (YES in step ST111), the weather predicting device 101 decides to perform notification processing (step ST112).

[0128] Next, the weather forecasting device 101 performs notification processing. For example, as described above, the weather forecasting device 101 sends an email indicating that rainfall is expected at the target point Q to the terminal device 401 (step ST113), starts a timer (step ST114), and waits for the arrival of the next processing timing T1 (NO in step ST103).

[0129] On the other hand, if the weather forecasting device 101 has made a positive judgment about rainfall for the second time or later (NO in step ST111), it checks whether 24 hours or more have passed since the timer was started (step ST115).

[0130] If 24 hours have not passed since the timer was started (NO in step ST115), the weather forecasting device 101 decides not to perform notification processing (step ST116) and waits for the arrival of the next processing timing T1 (NO in step ST103).

[0131] On the other hand, if more than 24 hours have passed since the timer was started (YES in step ST115), the weather forecasting device 101 acquires water vapor information C indicating the precipitable water vapor We at the post-notification time, which is the time after the previous notification process was performed (step ST117).

[0132] Next, the weather predicting device 101 compares the precipitable water mass We with the reference value S (step ST118).

[0133] If the amount of precipitable water We is greater than the reference value S (YES in step ST118), the weather predicting device 101 decides not to perform notification processing (step ST116) and waits for the next processing timing T1 to arrive (NO in step ST103).

[0134] On the other hand, if the amount of precipitable water We is less than the reference value S (NO in step ST118), the weather predicting device 101 acquires rainfall information indicating the amount of rainfall R at the target point Q (step ST119).

[0135] Next, upon acquiring the rainfall information, the weather predicting device 101 compares the amount of rainfall R indicated by the rainfall information with a threshold value Th2 (step ST120).

[0136] If the amount of rainfall R is equal to or greater than the threshold value Th2 (NO in step ST120), the weather predicting device 101 determines not to perform notification processing (step ST116) and waits for the next processing timing T1 to arrive (NO in step ST103).

[0137] On the other hand, if the amount of rainfall R is less than the threshold value Th2 (YES in step ST120), the weather predicting device 101 decides to perform the notification process (step ST112) and performs the notification process again (step ST113).

[0138] Next, when weather predicting device 101 performs the notification process again, it resets the timer and then restarts it (step ST114), and waits for the arrival of the next processing timing T1 (NO in step ST103).

[0139] Note that some or all of the functions of the weather forecasting device 101 according to the embodiment of the present disclosure may be provided by cloud computing. That is, the weather forecasting device 101 according to the embodiment of the present disclosure may be a cloud server configured by multiple servers.

[0140] The above-described embodiments should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0141] 11 Acquisition Department 12 Prediction Department 13 Judgment section 14 Notification Department 15 Threshold setting section 16 Memory section 101 Weather forecasting device 201 Microwave Radiometer 301 Rainfall Sensor 401 Terminal Equipment 501 Weather Forecasting System

Claims

1. an acquisition unit that acquires water vapor information indicating the amount of water vapor in the atmosphere measured by the water vapor sensor; a prediction unit that performs a prediction process to calculate a predicted value of the future water vapor amount in the atmosphere based on the water vapor information; and a determination unit that performs a determination process regarding future rainfall based on the predicted value.

2. The weather forecasting device according to claim 1 , wherein the water vapor information indicates a precipitable amount of water vapor in the atmosphere.

3. the acquisition unit acquires a plurality of pieces of water vapor information each indicating a plurality of amounts of water vapor measured at different times; The weather forecasting device according to claim 1 , wherein the forecasting unit performs the forecasting process based on the plurality of pieces of water vapor information.

4. the acquisition unit acquires, as the plurality of pieces of water vapor information, first water vapor information indicating the amount of water vapor at a first time and second water vapor information indicating the amount of water vapor at a second time that is a time before the first time; The weather forecasting device of claim 3, wherein the prediction unit calculates the predicted value at a time later than the first time in the prediction process using a relational equation based on the first water vapor information and the second water vapor information, the relational equation indicating the relationship between time and the water vapor amount.

5. the acquisition unit acquires, as the plurality of pieces of water vapor information, first water vapor information indicating the amount of water vapor at a first time and second water vapor information indicating the amount of water vapor at a second time that is a time before the first time; The weather forecasting device of claim 3, wherein the prediction unit performs the prediction process using at least one of the difference between the amount of water vapor indicated by the first water vapor information and the amount of water vapor indicated by the second water vapor information, and the time difference between the first time and the second time.

6. The weather forecasting device according to claim 1 , wherein the determining unit performs the determination process based on a result of comparing the predicted value with a threshold value.

7. The weather forecasting device according to claim 6 , wherein the threshold value is a value that depends on at least one of a season and a location where the water vapor sensor is installed.

8. the acquisition unit acquires a plurality of pieces of water vapor information each indicating a plurality of amounts of water vapor measured at different times; The weather forecasting device further comprises: The weather forecasting device according to claim 6 , further comprising a threshold setting unit that updates the threshold based on statistical values ​​of the plurality of water vapor amounts.

9. The weather forecasting device further comprises: The weather forecasting device according to claim 1 , further comprising a notification unit that performs a notification process to notify the determination result of the determination unit when the determination unit makes a positive determination about the rainfall.

10. The acquisition unit further acquires the water vapor information indicating the amount of water vapor at a post-notification time, which is a time after the notification process is performed by the notification unit, the determination unit performs the determination process periodically or irregularly, The weather forecasting device of claim 9, wherein the notification unit performs the notification process again if the amount of water vapor at the post-notification time satisfies a predetermined condition and the judgment unit again makes a positive judgment about the rainfall in the judgment process.

11. The weather forecasting device according to claim 10 , wherein the predetermined condition is that the amount of water vapor at the post-notification time is equal to or less than a reference value.

12. the determination unit performs the determination process periodically or irregularly, The weather forecasting device of claim 9, wherein the notification unit performs the notification process again when a predetermined time has elapsed since the time the notification process was performed and the judgment unit again makes a positive judgment about the rainfall in the judgment process.

13. The acquisition unit further acquires rainfall information regarding rainfall at a target point of the determination process, the determination unit performs the determination process periodically or irregularly, The weather forecasting device according to claim 9 , wherein the notification unit performs the notification process again when the rainfall information satisfies a predetermined condition and the determination unit again makes a positive determination about the rainfall in the determination process.

14. A weather forecasting method for a weather forecasting device, comprising: Obtaining water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor; performing a prediction process for calculating a predicted value of the future amount of water vapor in the atmosphere based on the water vapor information; A weather forecasting method that performs a determination process regarding future rainfall based on the predicted value.

15. A weather forecasting program used in a weather forecasting device, A process of acquiring water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor; a process of performing a prediction process of calculating a predicted value of the future water vapor amount in the atmosphere based on the water vapor information; and performing a process of determining future rainfall based on the predicted value.

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