Weather prediction device, weather prediction method, and weather prediction program

Abstract

A weather prediction device 101 includes: an acquisition unit 11 for acquiring water vapor information indicating the amount of water vapor in the atmosphere measured by a water vapor sensor; a prediction unit 12 for performing prediction processing for calculating the predicted value of the amount of water vapor in the atmosphere in the future based on the water vapor information; and a determination unit 13 for performing determination processing regarding future rainfall based on the predicted value.

Description

WEATHER PREDICTION DEVICE, WEATHER PREDICTION METHOD, AND WEATHER PREDICTION PROGRAM

[0001] This disclosure relates to weather prediction devices, weather prediction method, and weather prediction program.

[0002] Conventionally, technology has been developed to perform weather predictions by simulating future weather conditions using observation data on weather conditions in the sky obtained by a radar device or the like. For example, Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2019 -45146) discloses the following technology. Namely, the weather prediction device includes a precipitation risk derivation unit for deriving the risk of precipitation on the ground based on the weather conditions in the sky obtained by the radar device, and an output unit for outputting information based on the risk of precipitation derived by the precipitation risk derivation unit.

[0003] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2019-45146Summary

[0004] In weather forecasting, the timing of rainfall is sometimes predicted. When the timing of rainfall is predicted using a radar device as in the technology described in Patent Document 1, it is necessary to deploy a large-scale radar device. In the technology described in Patent Document 1, since the observation data acquired by the radar apparatus shows the observation results of each area when the sky is divided into a plurality of areas, much calculation time and labor are required when simulation is performed using the observation data.

[0005] The present disclosure has been made in order to solve the above-mentioned problems, and an object thereof is to provide a weather prediction device, a weather prediction method, and a weather prediction program which may easily predict rainfall.

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

[0007] By using the predicted value based on the measurement result of the water vapor sensor in this way, compared with a configuration in which the determination is performed by simulation using, for example, the observation result of the weather condition in the sky, it is not necessary to deploy a large-scale radar apparatus for observing the weather condition in the sky, and the equipment for determining the rainfall may be miniaturized. In addition, calculation time and labor required to obtain the determination result may be reduced. Therefore, it is possible to easily predict the rainfall.

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

[0009] The precipitable amount is a physical quantity representing the amount of precipitation when it is assumed that the water vapor contained in the atmosphere from the ground surface to the sky is combined into rain. Since the foregoing configuration makes it possible to calculate the predicted value of the precipitable amount in the future based on the measurement result of the precipitable amount by the water vapor sensor, it is possible to more accurately determine the future rainfall.

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

[0011] Since the foregoing configuration makes it possible to consider the trend of the water vapor amount in the atmosphere, it is possible to more accurately calculate the predicted value of the water vapor amount.

[0012] (4) In the foregoing (3), the acquisition unit may acquire the first water vapor information indicating the water vapor amount at 1:00 and the second water vapor information indicating the water vapor amount at 2:00, which is a time before 1:00, as the plurality of water vapor information, and the prediction unit may calculate the predicted value at a time after 1:00 in the prediction process by using the relational expression based on the first water vapor information and the second water vapor information and indicating the relationship between the time and the water vapor amount.

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

[0014] (5) In (3) or (4), the acquisition unit acquires the first water vapor information indicating the amount of water vapor at 1:00 and the second water vapor information indicating the water vapor amount at 2:00, which is a time before 1:00, and the prediction unit may perform the prediction process using at least one of the difference between the water vapor amount indicated by the first water vapor information and the water vapor amount indicated by the second water vapor information and the time difference between the 1:00 and 2:00.

[0015] With such a configuration, the predicted value of the amount of water vapor may be calculated simply using the past change of the amount of water vapor in the atmosphere. In addition, the timing when the amount of water vapor reaches the predicted value may be easily predicted using the time difference between the 1:00 and 2:00.

[0016] (6) In any of (1) to (5), the determination unit may perform the determination process based on the comparison result between the predicted value and the threshold.

[0017] In this manner, it is possible to easily determine whether rainfall is expected or not by comparing the prediction result of the amount of water vapor with the threshold value.

[0018] (7) In (6), the threshold value may be a value corresponding to at least one of the seasons and the location where the water vapor sensor is installed.

[0019] In this manner, the determination process may be performed by using an appropriate threshold value corresponding to either or both of the timing and the location where the water vapor sensor is installed.

[0020] (8) In (6) or (7), the acquisition unit may acquire a plurality of water vapor information indicating a plurality of amounts of water vapor having different measurement times, and the weather prediction device may further comprise a threshold setting unit for updating the threshold value based on the statistical value of the plurality of amount of water vapor.

[0021] In this manner, the threshold value may be updated to a more appropriate threshold 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 prediction apparatus comprises the weather prediction device that may further comprising a notification unit that performs notification processing for notifying the determination result of the determination unit when the determination unit makes a positive determination about the rainfall.

[0023] With such a configuration, the user of the weather prediction device may recognize that there is a possibility of rain soon.

[0024] (10) In (9) above, the acquisition unit may further acquire the water vapor information indicating the amount of water vapor at a time which is the time after the notification processing is performed by the notification unit, the determination unit may periodically or irregularly perform the determination processing, and the notification unit may perform the notification processing again when the water vapor amount at the time after the notification satisfies a predetermined condition and the result of the determination processing is again positive for the future rainfall.

[0025] With such a configuration, the timing of notifying the determination result again may be adjusted according to the water vapor amount after notifying the positive determination result about the rainfall, so that frequent notification to the user of the weather prediction device may be suppressed.

[0026] (11) In (10) above, the predetermined condition may be that the water vapor amount at the time after the notification time is not more than a reference value.

[0027] With such a configuration, since the notification process may be performed again when the amount of water vapor at the time after the notification has decreased to a reference value or less, frequent notification to the user may be suppressed, for example, during a period when the determination result is positive.

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

[0029] With such a configuration, since the notification process may be performed again after a predetermined time has elapsed from the notification process, frequent notification to the user of the weather prediction device may be suppressed.

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

[0031] With such a configuration, since the timing at which the determination result needs to be notified again may be adjusted according to the weather at the target point after the positive determination result about the rainfall has been notified, frequent notification to the user of the weather prediction device may be suppressed.

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

[0033] By using the predicted value based on the measurement result of the water vapor sensor in this manner, it is not necessary to deploy a large-scale radar device for observing the weather condition in the sky as compared with a configuration in which the determination is made by simulation using, for example, the observation result of the weather condition in the sky, and the equipment for judging the rainfall may be miniaturized. In addition, calculation time and labor required to acquire the determination result may be reduced. Therefore, it is possible to easily predict the rainfall.

[0034] (15) The weather prediction program according to the embodiment of the present disclosure is a weather prediction program used in a weather prediction device, and is a program for making a computer execute a process for acquiring water vapor information indicating the amount of water vapor in the atmosphere measured by the water vapor sensor, a process for calculating the predicted value of the amount of water vapor in the atmosphere in the future based on the water vapor information, and a process for judging the future rainfall based on the predicted value.

[0035] In this configuration for judging the future rainfall using the predicted value based on the measurement result of the water vapor sensor, the equipment for judging the rainfall may be miniaturized because it is not necessary to deploy a large-scale radar device for observing the weather condition in the sky as compared with a configuration for judging the weather condition in the sky by simulation using the observation result of the weather condition in the sky. In addition, the calculation time and labor required to obtain the determination result may be reduced. Therefore, it is possible to easily predict rainfall.

[0036] According to the present disclosure, it is possible to easily predict rainfall.

[0037] The illustrated embodiments of the subject matter will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and processes that are consistent with the subject matter as claimed herein.FIG. 1 is a diagram showing an example of the configuration of a weather prediction system according to an embodiment of the present disclosure.FIG. 2 is a diagram showing an example of precipitable water vapor measured by a microwave radiometer according to an embodiment of the present disclosure.FIG. 3 is a diagram showing an example of precipitable water vapor data generated by a weather prediction device according to an embodiment of the present disclosure.FIG. 4 is a diagram for explaining an example of prediction processing by a weather prediction device according to an embodiment of the present disclosure.FIG. 5 is a diagram showing an example of prediction results of prediction processing by a weather prediction device according to an embodiment of the present disclosure.FIG. 6 is a diagram for explaining an example of determination results of determination processing by a weather prediction device according to an embodiment of the present disclosure.FIG. 7 is a flowchart showing an example of an operation procedure when a weather prediction device according to an embodiment of the present disclosure performs determination processing.FIG. 8 is a flowchart showing an example of an operation procedure when a weather prediction device according to an embodiment of the present disclosure performs determination processing.DETAILED DESCRIPTION

[0038] An embodiment of the present disclosure will be described below with reference to the drawings. The same reference numerals are assigned to the same or equivalent parts in the drawings, and the description thereof will not be repeated. At least a part of the following embodiments may be optionally combined.

[0039] Weather Prediction System: FIG. 1 is a diagram showing an example of the configuration of a weather prediction system according to an embodiment of the present disclosure. Referring to FIG. 1, the weather prediction system 501 includes a weather prediction 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 prediction device 101 predicts rainfall at a certain point (Hereinafter, it is also referred to as “target point Q”). The weather prediction device 101 is, for example, a server.

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

[0042] Microwave radiometer: The microwave radiometer 201 is fixed, for example, at a predetermined place. The microwave radiometer 201 performs wireless communication with a weather prediction device 101, for example.

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

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

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

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

[0047] When the precipitable amount is measured, the microwave radiometer 201 transmits water vapor information C indicating the measurement result and measurement time to the weather prediction device 101. The microwave radiometer 201 calculates the precipitable amount and transmits the water vapor information C periodically, for example. In this embodiment, the microwave radiometer 201 calculates the precipitable amount and transmits the water vapor information C every 1 minute, for example.

[0048] The weather prediction 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. A part or all of the acquisition unit 11, prediction unit 12, determination unit 13, notification unit 14, and threshold setting unit 15 are realized by a processing circuit (circuit) including, for example, 1 or a plurality of processors. The storage unit 16 is, for example, a nonvolatile memory included in the processing circuit.

[0049] Acquisition unit: The acquisition unit 11 acquires water vapor information C indicating the amount of water vapor in the atmosphere, for example, precipitable amount, 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. The acquisition unit 11 stores the received water vapor information C in the storage unit 16.

[0051] Decision processing: For example, the prediction unit 12 performs prediction processing for calculating the predicted value Wp of the future precipitable amount in the atmosphere based on the plurality of water vapor information C indicating the plurality of water vapor amounts each having different measurement times, obtained by the acquisition unit 11. For example, the prediction unit 12 performs prediction processing periodically or irregularly.

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

[0053] More specifically, for example, when the processing timing T1 of the prediction processing arrives, the prediction unit 12 acquires a plurality of amount of water vapor information C accumulated in period A from the previous processing timing T1 to the current processing timing T1 from the storage unit 16. Then, based on the plurality of amount of water vapor information C, the prediction unit 12 creates precipitable amount data K showing the time series change of precipitable amount in period A. The length of period A is, for example, 3 hours.

[0054] FIG. 3 is a diagram showing an example of precipitable amount data generated by the weather prediction device according to the embodiment of the present disclosure. In FIG. 3, the horizontal axis is the time, and the vertical axis is the precipitable amount. FIG. 3 shows precipitable amount data K during the period from 9:00 to 12:00 on January 1, 2024.

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

[0056] For example, when the precipitable amount data K is created, the prediction unit 12 calculates the difference Dw between the precipitable amount at the latest measurement time ta indicated by the precipitable amount data K and the precipitable amount at the measurement time tc earlier than the measurement time ta. The measurement time ta is an example of the 1:00 hour, and the measurement time tc is an example of the 2:00 hour.

[0057] In this embodiment, for example, the measurement time tc is 3 hours before the measurement time ta. That is, the time difference Dt1 between the measurement time ta and the measurement time tc is 3 hours. Note that the time difference Dt1 is not limited to 3 hours and may be any other length of time.

[0058] FIG. 4 is a diagram for explaining an example of prediction processing by the weather prediction device according to the embodiment of the present disclosure.

[0059] Referring to FIG. 4, for example, the prediction unit 12 performs prediction processing using at least one of the differences Dw between the precipitable amount at the measurement time ta and the precipitable amount 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 prediction processing using both the difference Dw and the time difference Dt1.

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

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

[0062] The graph shown in FIG. 4 illustrates an example of the relational expression F derived by the prediction unit 12. In FIG. 4, the horizontal axis represents the time, and the vertical axis represents the precipitable amount. In the example shown in FIG. 4, the precipitable amount at the measurement time ta and the precipitable amount at the measurement time tc are “Wa” mm and “Wc” mm, respectively. In the example shown in FIG. 4, the relational expression F is a linear function.

[0063] Using the derived relational expression F, the prediction unit 12 calculates the predicted value Wp of the precipitable amount at the time tp after the measurement time ta in the prediction process.

[0064] For example, the time difference Dt2 between the time tp and the measurement time ta is the same as the time difference Dt1 between the measurement time ta and the measurement time tc. That is, in the example shown in FIG. 4, the time tp is the time 3 hours after the measurement time ta.

[0065] In the relational expression F which is a linear function, if the time difference Dt2 is the same as the time difference Dt1, the amount of change in precipitable water vapor during the period from the measurement time ta to the time tp is the same as the amount of change in precipitable water vapor during the period from the measurement time tc to the measurement time ta, that is, the difference Dw. Therefore, if the time difference Dt2 is the same as the time difference Dt1, the prediction unit 12 calculates the predicted value Wp by substituting the amount of precipitable water vapor at the measurement time ta, that is, "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 value obtained by multiplying the ratio of the time difference Dt2 to the time difference Dt1 by the difference Dw as the amount of change in precipitable water vapor during the period from the measurement time ta to the time tp. Then, the prediction unit 12 calculates the sum of the amount of precipitable water vapor at the measurement time ta and the calculated amount of change as the predicted value Wp.

[0067] In addition to the water vapor information C indicating the amount of precipitable water vapor at the measurement time ta and the water vapor information C indicating the amount of precipitable water vapor at the measurement time tc, the prediction unit 12 may use the water vapor information C indicating the amount of precipitable water vapor at other measurement times other than the measurement times ta and tc, that is, it may use three or more water vapor information C to derive the relational expression F. In this case, for example, the prediction unit 12 derives the relational expression F of a linear function using the least square method or the like. When the prediction unit 12 derives the relational expression F using three or more water vapor information C, it may be configured not only to derive the relational expression F of a linear function but also to derive the relational expression F of a high-order function such as a quadratic function.

[0068] FIG. 5 is a diagram showing an example of the prediction result of the prediction process by the weather prediction device according to the embodiment of the present disclosure. FIG. 5 shows the time-series change of the predicted value Wp corresponding to the time-series change of the precipitable amount shown in FIG. 2. In FIG. 5, the horizontal axis indicates the time, and the vertical axis indicates the predicted value Wp.

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

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

[0071] For example, the determination unit 13 performs a determination process based on the comparison result between the prediction value Wp and the 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 corresponding to the season. For example, the threshold value Th1 corresponding to each month in the summer period is larger than the threshold value Th1 corresponding to each month in the winter period.

[0073] The threshold value Th1 is not limited to the value corresponding to the season but may be a value corresponding to the location of the microwave radiometer 201 shown in FIG. 1. In this case, for example, the threshold Th1 corresponding to an installation location where the average rainfall is larger than a predetermined reference value is larger than the threshold Th1 corresponding to an installation location where the average rainfall is smaller than the reference value. The threshold Th1 may be a value corresponding to both the season and the installation location of the microwave radiometer 201.

[0074] When the determination unit 13 receives the prediction result information from the prediction unit 12, it selects the threshold Th1 corresponding to the time tp indicated by the prediction result information from among the plurality of threshold 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 Th1 or higher. Here, it is assumed that the threshold Th1 is 18.8 mm.

[0076] When the predicted value Wp is equal to or greater than the threshold Th1, the determination unit 13 determines positively about future rainfall. Specifically, for example, the determination unit 13 determines that rainfall is likely to occur soon at the target point Q of the determination processing.

[0077] On the other hand, if the predicted value Wp is less than the threshold value Th1, the determination unit 13 makes a negative determination about future rainfall. Specifically, for example, the determination unit 13 determines that rainfall is unlikely to occur soon at the target point Q.

[0078] FIG. 6 is a diagram for explaining an example of the determination result of the determination processing by the weather prediction apparatus according to the embodiment of the present disclosure.

[0079] Referring to FIG. 6, the predicted value Wp1 corresponding to the precipitable amount "13.80" mm at 19:40 on January 2, 2024, is "19.18" mm. The predicted value Wp2 corresponding to the precipitable amount "17.64" mm at 15:18 on January 3, 2024, is "18.95" mm. The predicted value Wp3 corresponding to the precipitable amount "16.34" mm at 15:56 on January 6, 2024, is "18.81" mm. The predicted value Wp4 corresponding to the precipitable amount "18.15" mm at 8:56 on January 10, 2024, is "18.82" mm. The predicted value Wp5 corresponding to the precipitable amount "18.22" mm at 9:38 on January 10, 2024, is "18.83" mm.

[0080] In the example shown in FIG. 6, the predicted values Wp1, Wp2, Wp3, Wp4, and Wp5 are larger than the threshold value Th1, that is, "18.8" mm. In this case, the determination unit 13 makes a positive determination about future rainfall in the determination process.

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

[0082] In the determination processing using the precipitable amount at 15:18 on January 3, 2024, the determination unit 13 also made a positive determination. However, there was no rain on the same day.

[0083] Referring again to FIG. 1, when the determination unit 13 made a positive determination about rainfall in the determination processing, it outputs the determination positive 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 processing to update the threshold Th1 by using a plurality of water vapor information C indicating a plurality of precipitable amounts with different measurement times acquired by the acquisition unit 11.

[0085] More specifically, for example, when the processing timing T2 of the update processing arrives, the threshold setting unit 15 acquires a plurality of water vapor information C (Hereinafter, it is also referred to as “a plurality of water vapor information Ca”.) accumulated in the period B from the previous processing timing T2 to the current processing timing T2 from the storage unit 16. The length of the period B is, for example, 3 months.

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

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

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

[0089] Notification Unit: For example, when the determination unit 13 makes a positive determination about rainfall, the notification unit 14 performs notification processing for notifying the determination result by the determination unit 13.

[0090] More specifically, for example, the notification unit 14 counts the number of times the determination affirmative information is received from the determination unit 13. When the notification unit 14 receives the determination affirmative information for the first time from the determination unit 13, it creates an HTML (Hyper Text Markup Language) format e-mail containing the determination affirmative information. Then, the notification unit 14 transmits the created e-mail to the terminal device 401.

[0091] By checking the e-mail received by the terminal device 401, the user recognizes that rainfall is likely to occur soon at the target point Q.

[0092] When the notification unit 14 transmits the created e-mail to the terminal device 401, it outputs notification completion information indicating completion of notification processing to the acquisition unit 11. For example, when the notification unit 14 transmits the e-mail to the terminal device 401, it starts a timer (not shown).

[0093] Note that the notification unit 14 may be configured to perform notification processing by another method other than sending an e-mail containing the decision affirmative information received from the determination unit 13. For example, the notification unit 14 may be configured to display the screen G showing the positive decision result by the determination unit 13 on the display unit of the terminal device 401. In this case, the notification unit 14 transmits the screen information showing the screen G to the terminal device 401. When the terminal device 401 receives the screen information from the weather prediction device 101, it draws the screen G on the Web browser displayed on its display unit based on the screen information.

[0094] Precipitable Amount at the Post-Notification Time: For example, the acquisition unit 11 acquires the water vapor information C showing the precipitable amount at the time (Hereinafter, it is also referred to as “time after notification”.) after the notification processing is performed by the notification unit 14.

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

[0096] Rainfall Information: Referring again to FIG. 1, the rainfall sensor 301 is fixed, for example, at the target point Q of the determination processing. The rainfall sensor 301 measures rainfall R at the target point Q. The rainfall sensor 301 performs wireless communication with the weather prediction device 101, for example.

[0097] In the weather prediction device 101, the acquisition unit 11 further acquires rainfall information indicating the rainfall R measured by the rainfall sensor 301 and the measurement time of the rainfall R.

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

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

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

[0101] Re-notification: (a) Example 1: For example, when the precipitable amount at the time after notification satisfies a predetermined condition A1 and the determination unit 13 determines positively about future rainfall in the determination process, the notification unit 14 performs the notification process again.

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

[0103] When the notification unit 14 receives the second and subsequent determination affirmative information from the determination unit 13, it compares the precipitable amount indicated by the water vapor information C received from the acquisition unit 11 with the reference value S. Specifically, for example, when the first water vapour information C is received from the acquisition unit 11 after receiving the determination affirmative information from the determination unit 13, the notification unit 14 compares the precipitable amount (Hereinafter, it is also referred to as “Precipitable Amount We”.) indicated by the water vapor information C with the reference value S.

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

[0105] Note that the weather prediction device 101 may be configured to update the reference value S in the storage unit 16. In this case, for example, the weather prediction device 101 updates the reference value S by using statistical values of a plurality of precipitable amounts in a predetermined period prior to the time when rain started falling at the target point Q.

[0106] Specifically, for example, when the rainfall information received from the rainfall sensor 301 indicates a rainfall amount R that is equal to or greater than a predetermined threshold, the weather prediction device 101 acquires from the storage unit 16 a plurality of water vapor information C accumulated in a period from the time 3 hours before the measurement time of the rainfall amount R to the measurement time. Then, the weather prediction device 101 calculates statistical values of a plurality of precipitable amounts indicated by the plurality of water vapor information C and calculates the reference value S by substituting the calculated statistical values into a predetermined arithmetic expression. The weather prediction device 101 stores the calculated reference value S as a new reference value S in the storage unit 16.

[0107] (b) Example 2: For example, when a predetermined time has passed since the notification time and the determination unit 13 makes a positive determination about rainfall in the determination process, the notification unit 14 performs the notification process again.

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

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

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

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

[0112] On the other hand, if the rainfall Ra is greater than or equal to the threshold 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] The rainfall sensor 301 shown in FIG. 1 may be configured to perform a detection process for qualitatively detecting 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 prediction device 101, it performs a detection process in a period until a predetermined time elapses after receiving the request information. Then, the rainfall sensor 301 transmits information indicating the detection result to the weather prediction device 101 as rainfall information. In the weather prediction device 101, when the detection result indicated by the rainfall information received from the rainfall sensor 301 via the acquisition unit 11 indicates that there is no rain at the target point Q, the notification unit 14 performs notification processing again.

[0115] Flow of Operation: The weather prediction device 101 according to the embodiment of the present disclosure is provided with a computer including a memory, and a processor such as a CPU (Central Processing Unit) in the computer reads and executes a program including part or all of the steps of the following flowchart from the memory. The program of the apparatus may be installed externally. The program of this apparatus is distributed in a state stored in a recording medium or via a communication line.

[0116] FIGS. 7 and 8 are flowcharts showing an example of an operation procedure when the weather prediction device according to the embodiment of the present disclosure performs determination processing.

[0117] Referring to FIGS. 7 and 8, first, the weather prediction device 101 waits for the reception of the water vapor information C from the microwave radiometer 201 (NO in step ST 101).

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

[0119] Until the processing timing T1 arrives (NO in step ST 103), the weather prediction device 101 stores the new water vapor information C received from the microwave radiometer 201 in the storage unit 16 (step ST101 and step ST102).

[0120] Then, when the processing timing T1 arrives (YES in step ST 103), the weather prediction device 101 creates precipitable amount data K showing the time series change of precipitable amount in the period A from the previous processing timing T1 to the current processing timing T1. For example, as described above, the weather prediction device 101 creates precipitable amount data K using the plurality of water vapor information C stored in the storage unit 16 in the period A (step ST104).

[0121] Next, when the weather prediction device 101 creates precipitable amount data K, it derives a relational expression F showing the relationship between time and precipitable amount. For example, as described above, when the weather prediction device 101 creates precipitable amount data K, it calculates the difference Dw between the precipitable amount at the latest measurement time ta indicated by the precipitable amount data K and the precipitable amount at the measurement time tc before the measurement time ta. Then, the weather prediction device 101 derives a relational expression F using the calculated difference Dw and the time difference Dt1 between the measurement time ta and the measurement time tc (step ST105).

[0122] Next, when the weather prediction device 101 derives the relational expression F, it calculates the predicted precipitable amount Wp at the time tp after the measurement time ta using the derived relational expression F (step ST106).

[0123] Next, the weather prediction device 101 selects a threshold Th1 corresponding to the month including the time tp from the threshold Th1 for each month stored in the storage unit 16 (step ST107).

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

[0125] If the predicted value Wp is less than the threshold Th1 (NO in step ST 108), the weather prediction device 101 makes a negative determination about future rainfall. Specifically, the weather prediction device 101 judges that rainfall is unlikely to occur soon at the target point Q (step ST109) and waits for the arrival of the next processing timing T1 (NO in step ST 103).

[0126] On the other hand, if the predicted value Wp is greater than or equal to the threshold Th1 (YES in step ST 108), the weather prediction device 101 makes a positive determination about future rainfall. Specifically, the weather prediction device 101 judges that rainfall is likely to occur soon at the target point Q (step ST110).

[0127] Next, if the number of times that the weather prediction device has made a positive determination about rainfall is the first time (YES in step ST 111), the weather prediction device 101 decides to perform notification processing (step ST112).

[0128] Next, the weather prediction device 101 performs notification processing. For example, as described above, the weather prediction device 101 sends an e-mail indicating that rainfall is expected at the target point Q to the terminal device 401 (step ST113), starts the timer (step ST114), and waits for the arrival of the next processing timing T1 (NO at step ST 103).

[0129] On the other hand, if the number of times that the weather prediction device 101 has made a positive determination about rainfall is the second or later time (NO at step ST 111), 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 at step ST 115), the weather prediction device 101 decides not to perform notification processing (step ST116) and waits for the arrival of the next processing timing T1 (NO at step ST 103).

[0131] On the other hand, if 24 hours or more have passed since the timer was started (YES at step ST 115), the weather prediction device 101 acquires water vapor information C indicating the precipitable amount We at the time after notification, which is the time after the previous notification processing (step ST117).

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

[0133] If the precipitable amount We is greater than the reference value S (YES in step ST 118), the weather prediction device 101 decides not to perform notification processing (step ST116) and waits for the arrival of the next processing timing T1 (NO in step ST 103).

[0134] On the other hand, if the precipitable amount We is less than the reference value S (NO in step ST 118), the weather prediction device 101 acquires rainfall information indicating the rainfall R at the target point Q (step ST119).

[0135] Next, when the weather prediction device 101 acquires rainfall information, it compares the rainfall R indicated by the rainfall information with the threshold Th2 (step ST120).

[0136] If the rainfall R is greater than or equal to the threshold Th2 (NO in step ST 120), the weather prediction device 101 decides not to perform notification processing (step ST116) and waits for the arrival of the next processing timing T1 (NO in step ST 103).

[0137] On the other hand, if the rainfall amount R is less than the threshold value Th2 (YES in step ST 120), the weather prediction device 101 decides to perform notification processing (step ST112) and performs notification processing again (step ST113).

[0138] Next, when performing notification processing again, the weather prediction device 101 resets the timer and restarts it (step ST114) and waits for the arrival of the next processing timing T1 (NO in step ST 103).

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

[0140] The above embodiment should be considered to be exemplary in all respects and not restrictive. The scope of the present invention is indicated by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims.

[0141] (Description of the Code) 11 Acquisition unit 12 Prediction unit 13 Determination unit 14 Notification unit 15 Threshold setting unit 16 Storage unit 101 Weather prediction device 201 Microwave radiometer 301 Rainfall sensor 401 Terminal device 501 Weather prediction system

[0142] It is to be understood that not necessarily all objects or advantages may be achieved in accordance with any particular embodiment described herein. Thus, for example, those skilled in the art will recognize that certain embodiments may be configured to operate in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other objects or advantages as may be taught or suggested herein.

[0143] All of the processes described herein may be embodied in, and fully automated via, software code modules executed by a computing system that includes one or more computers or processors. The code modules may be stored in any type of non-transitory computer-readable medium or other computer storage device. Some or all the methods may be embodied in specialized computer hardware.

[0144] Many other variations than those described herein will be apparent from this disclosure. For example, depending on the embodiment, certain acts, events, or functions of any of the algorithms described herein may be performed in a different sequence, may be added, merged, or left out altogether (e.g., not all described acts or events are necessary for the practice of the algorithms). Moreover, in certain embodiments, acts or events may be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially. In addition, different tasks or processes may be performed by different machines and / or computing systems that may function together.

[0145] The various illustrative logical blocks and modules described in connection with the embodiments disclosed herein may be implemented or performed by a machine, such as a processor. A processor may be a microprocessor, but in the alternative, the processor may be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor may include electrical circuitry configured to process computer-executable instructions. In another embodiment, a processor includes an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable device that performs logic operations without processing computer-executable instructions. A processor may also be implemented as a combination of computing devices, e.g., a combination of a digital signal processor (DSP) and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily with respect to digital technology, a processor may also include primarily analog components. For example, some or all of the signal processing algorithms described herein may be implemented in analog circuitry or mixed analog and digital circuitry. A computing environment may include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.

[0146] Conditional language such as, among others, "can”, "could”, "might" or "may” unless specifically stated otherwise, are otherwise understood within the context as used in general to convey that certain embodiments include, while other embodiments do not include, certain features, elements and / or steps. Thus, such conditional language is not generally intended to imply that features, elements and / or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and / or steps are included or are to be performed in any particular embodiment.

[0147] Disjunctive language such as the phrase "at least one of X, Y, or Z”, unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and / or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.

[0148] Any process descriptions, elements or blocks in the flow diagrams described herein and / or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or elements in the process. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, executed out of order from that shown, or discussed, including substantially concurrently or in reverse order, depending on the functionality involved as would be understood by those skilled in the art.

[0149] Unless otherwise explicitly stated, articles such as "a" or "an" should generally be interpreted to include one or more described items. Accordingly, phrases such as "a device configured to" are intended to include one or more recited devices. Such one or more recited devices may also be collectively configured to carry out the stated recitations. For example, "a processor configured to carry out recitations A, B and C" may include a first processor configured to carry out recitation A working in conjunction with a second processor configured to carry out recitations B and C. The same holds true for the use of definite articles used to introduce embodiment recitations. In addition, even if a specific number of an introduced embodiment recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations”, without other modifiers, typically means at least two recitations, or two or more recitations).

[0150] It will be understood by those within the art that, in general, terms used herein, are generally intended as "open" terms (e.g., the term "including" should be interpreted as "including but not limited" to the term "having" should be interpreted as "having at least", the term "includes" should be interpreted as "includes but is not limited to", etc.).

[0151] For expository purposes, the term "horizontal" as used herein is defined as a plane parallel to the plane or surface of the floor of the area in which the system being described is used or the method being described is performed, regardless of its orientation. The term "floor" may be interchanged with the term "ground" or "water surface." The term "vertical" refers to a direction perpendicular to the horizontal as just defined. Terms such as "above", "below", "bottom", "top", "side", "higher", "lower", "upper", "over", and "under" are defined with respect to the horizontal plane.

[0152] As used herein, the terms "attached", "connected", "mated", and other such relational terms should be construed, unless otherwise noted, to include removable, moveable, fixed, adjustable, and / or releasable connections or attachments. The connections / attachments may include direct connections and / or connections having intermediate structure between the two components discussed.

[0153] Numbers preceded by a term such as "approximately”, "about”, and "substantially" as used herein include the recited numbers, and also represent an amount close to the stated amount that still performs a desired function or achieves a desired result. For example, the terms "approximately”, "about", and "substantially" may refer to an amount that is less than 10% of the stated amount. Features of embodiments disclosed herein preceded by a term such as "approximately”, "about”, and "substantially" as used herein represent the feature with some variability that still performs a desired function or achieves a desired result for that feature.

[0154] It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure and protected by the following claims.

Claims

1. A weather prediction device 101, comprising: an acquisition unit 11 configured to acquire water vapor information indicating an amount of water vapor in the atmosphere measured by a water vapor sensor; a prediction unit 12 configured to calculate a predicted value of the amount of water vapor in the atmosphere in the future based on the water vapor information; and a determination unit 13 configured to perform determination processing regarding future rainfall based on the predicted value.

2. The weather prediction device 101 of claim 1, wherein the water vapor information indicates the precipitable water vapor in the atmosphere as the amount of water vapor.

3. The weather prediction device 101 of claim 2, wherein the acquisition unit 11 is further configured to acquire a plurality of the water vapor information indicating a plurality of the amounts of the water vapor at different measurement times, and the prediction unit 12 is further configured to calculate the predicted value based on the plurality of the water vapor information.

4. The weather prediction device 101 of claim 3, wherein the acquisition unit 11 is further configured to acquire a first water vapor information indicating the amount of water vapor at a first time and a second water vapor information indicating the amount of water vapor at a second time which is a time before the first time as the plurality of water vapor information, and the prediction unit 12 is further configured to calculate 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, which indicates a relationship between the time and the amount of water vapor.

5. The weather prediction device 101 of claim 3 or claim 4, wherein the acquisition unit 11 is further configured to acquire a first water vapor information indicating the amount of water vapor at a first time and a second water vapor information indicating the amount of water vapor at a second time before the first time as the plurality of water vapor information, and the prediction unit 12 is further configured to calculate the predicted value using a 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, or a time difference between the first time and the second time.

6. The weather prediction device 101 of any one of claims 1 to 5, wherein the determination unit 13 is further configured to perform the determination processing based on a comparison result between the predicted value and a threshold value.

7. The weather prediction device 101 of claim 6, wherein the threshold value is a value corresponding to a season or a location where the water vapor sensor is installed.

8. The weather prediction device 101 of claim 6 or claim 7, wherein the acquisition unit 11 is further configured to acquire a plurality of the water vapor information indicating a plurality of the amounts of the water vapor at different measurement times, and the weather prediction device 101 further comprises a threshold setting unit 15 configured to set a threshold value based on a statistical value of a plurality of the amounts of water vapor.

9. The weather prediction device 101 of any one of claims 1 to 8, further comprising: a notification unit 14 configured to provide a notification regarding a result of the determination processing in case the result of the determination processing is positive for the future rainfall.

10. The weather prediction device 101 of claim 9, wherein the acquisition unit 11 is further configured to acquire the water vapor information indicating the amount of water vapor at a time after the notification, the determination unit 13 is further configured to perform the determination processing periodically or irregularly, and the notification unit 14 is further configured to provide the notification again in case the amount of water vapor at the time after the notification satisfies a predetermined condition and the result of the determination processing is again positive for the future rainfall.

11. The weather prediction device 101 of claim 10, wherein the predetermined condition is that the amount of water vapor at the time after the notification is not more than a reference value.

12. The weather prediction device 101 of any one of claims 9 to 11, wherein the determination unit 13 is further configured to perform the determination processing periodically or irregularly, and the notification unit 14 is further configured to provide the notification again in case a predetermined time elapses from the time when the notification is provided and the result of the determination processing is positive again for the future rainfall.

13. The weather prediction device 101 of any one of claims 9 to 12, wherein the acquisition unit 11 is further configured to acquire rainfall information regarding rainfall at a target position of the determination processing, the determination unit 13 is further configured to perform the determination processing periodically or irregularly, and the notification unit 14 is further configured to provide the notification again in case the rainfall information satisfies a predetermined condition and the result of the determination processing is positive again for the future rainfall.

14. The weather prediction method, comprising: acquiring water vapor information indicating an amount of water vapor in the atmosphere measured by a water vapor sensor; calculating a predicted value of the amount of water vapor in the atmosphere in the future based on the water vapor information; and performing determination processing regarding future rainfall based on the predicted value.

15. The weather prediction program, comprising: acquiring water vapor information indicating an amount of water vapor in the atmosphere measured by a water vapor sensor; calculating a predicted value of the amount of water vapor in the atmosphere in the future based on the water vapor information; and performing determination processing regarding future rainfall based on the predicted value.

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