Weather Management System

Abstract

To realize to control output of weather alerts by using weather-related posted information that is posted by users.SOLUTION: A weather management system of the embodiment analyzes weather observation data, performs an analysis process for outputting precipitation particles that will fall to the ground based on a predetermined criterion, and outputs alert information according to the result of the analysis process. The predetermined criterion used in the analysis process can be changed based on weather-related posted information posted via a poster terminal. Here, the effective time and effective area set according to a predetermined posting time zone are stored for each predetermined posting area. By performing the analysis process applying the revised predetermined criterion to the observation data located within the effective area from the posting location of the weather-related posted information during the effective time corresponding to the posting time of the weather-related posted information, appropriate disaster prevention calls can be made taking into account the posting frequency of the weather-related posted information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to a technology for outputting an alert for a meteorological phenomenon based on observation data of a weather radar. [Background technology]

[0002] Weather radar emits radio waves (microwaves) and observes rain or snow within a specified range. It measures the distance to the rain or snow from the time it takes for the emitted radio waves to return, and can observe the intensity of the rain or snow from the strength of the returned radio waves.

[0003] In recent years, dual-polarized meteorological Doppler radar has been introduced, which makes it possible to more accurately estimate the types of precipitation particles in clouds and the intensity of precipitation by using radio waves that vibrate horizontally (horizontal polarization) and radio waves that vibrate vertically (vertical polarization). [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Park, H. -S and AV Ryzhkov, DS Zrnic and K. -E Kim 2009: The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D:Description and Application to an MCS. Wea. Forecasting., 24, 730-748 [Non-Patent Document 2] Hideaki Kagesawa (and 5 others), Title: "Proposal and Consideration of Sensing System Using Twitter", Published: July 2, 2014, URL: https: / / ipsj.ixsq.nii.ac.jp / ej / ?action=pages_view_main&active_action=repository_view_main_item_detail&item_id=104972&item_no=1&page_id=13&block_id=8 Summary of the Invention [Problem to be solved by the invention]

[0005] The objective of the present invention is to provide a mechanism for controlling the output of alerts using weather-related posted information submitted by contributors in a weather management system that outputs alerts for meteorological phenomena based on observation data from a weather radar. [Means for solving the problem]

[0006] The weather management system of the embodiment uses observation data of a weather radar. of Based on given criteria Classify, An analysis unit that performs an analysis process to output precipitation particles falling on the ground; an alert control unit that outputs alert information based on the result of the analysis process; and weather-related posted information posted from a poster terminal. A weather phenomenon grasped from the weather-related posted information that matches observation data observed by a weather radar. and a storage unit that stores, for each predetermined posting area, a valid time and a valid area that are set according to a predetermined posting time zone. The analysis unit performs the analysis process by applying the changed predetermined criterion to observation data located within the valid area from the posting position of the weather-related posted information during the valid time period that corresponds to the posting time of the weather-related posted information. [Brief description of the drawings]

[0007] [Figure 1] 1 is a diagram illustrating a functional block and network configuration of a weather management system according to a first embodiment. [Diagram 2]10 is a diagram for explaining a process of generating true value information in which meteorological phenomena identified from posted information are linked to meteorological phenomena corresponding to meteorological observation data in the first embodiment. FIG. [Diagram 3] 11 is a diagram for explaining a process of changing type classification criteria in the first embodiment. FIG. [Figure 4] 4 is a diagram for explaining the relationship between the posting interval of weather-related posted information and an alert to be output in the first embodiment. FIG. [Diagram 5] FIG. 11 is a diagram showing an example of setting an effective time and an effective area for each posting area in the first embodiment. [Figure 6] FIG. 11 is an explanatory diagram illustrating the application of criteria change control for each posting area and posting time period according to the first embodiment. [Figure 7] FIG. 2 is a diagram showing a process flow executed by the weather management system of the first embodiment. [Figure 8] FIG. 13 is a diagram showing an example of setting an effective time and an effective area for each posting area in the second embodiment. [Figure 9] FIG. 13 is a diagram showing an example of setting a valid time and a valid area for each posting area in the third embodiment, and is a diagram showing an example of dynamically changing the valid time and the valid area. [Figure 10] 13 is a diagram for explaining the process of expanding the effective area using the motion vector of the cloud in the fourth embodiment. FIG. BEST MODE FOR CARRYING OUT THEINVENTION

[0008] Hereinafter, an embodiment will be described with reference to the drawings.

[0009] As mentioned above, weather radars such as dual-polarized meteorological Doppler radars have made it possible to accurately estimate the types of precipitation particles in clouds and the intensity of precipitation. Based on weather radar observation data (weather observation data), the Japan Meteorological Agency issues disaster prevention weather information such as weather warnings and advisories to prevent and mitigate disasters caused by heavy rain and strong winds.

[0010] Here, the analysis results based on meteorological observation data are merely "estimates". For this reason, they may differ from the meteorological phenomena that actually occurred at the site (surface). Therefore, the Japan Meteorological Agency is working to improve the accuracy of estimates based on meteorological observation data by combining data from observation equipment such as rain gauges owned by the Japan Meteorological Agency, the Ministry of Land, Infrastructure, Transport and Tourism, and local governments nationwide, in addition to meteorological observation data, and using meteorological phenomena actually observed at or near the site.

[0011] However, for example, meteorological phenomena such as hail and sleet are difficult to observe using observation equipment because they occur infrequently and in a localized and narrow range. Also, while there are observation equipment (such as disdrometers (precipitation particle size and velocity distribution measuring devices)) that can observe hail and sleet, it is not realistic to deploy such dedicated observation equipment for meteorological phenomena that occur infrequently and are rarely observable on the ground. The same is true for meteorological phenomena such as tornadoes and whirlwinds, which are gusts of wind. Therefore, it has been difficult to improve the accuracy of estimations based on meteorological observation data for meteorological phenomena such as hail and sleet.

[0012] On the other hand, with the recent development of smartphones and the enrichment of SNS services, there are more opportunities for users to post weather-related information (including still images and videos). By using this posted information, it is possible to accurately grasp meteorological phenomena such as hailstones and sleet that have occurred on the ground without using observation equipment.

[0013] Therefore, in a weather management system that outputs alerts regarding weather phenomena identified from meteorological observation data, a mechanism is realized that controls the output of alerts using weather-related posted information posted by contributors.

[0014] In particular, it is known that the posting interval of posted information by a poster varies depending on the time of day and the location. Therefore, in controlling the output of alerts using weather-related posted information, it is possible to make a call for disaster prevention taking into account the posting frequency of weather-related posted information, etc.

[0015] (First embodiment) 1 to 7 are diagrams for explaining the first embodiment. Fig. 1 is a diagram showing the functional blocks and network configuration of a weather management system 100 of the present embodiment.

[0016] The weather management system 100 receives observation data from a weather radar and receives posted information posted by contributors from a web server 300.

[0017] Weather radar, for example, emits radio waves (microwaves) and observes rain or snow. It measures the distance to the rain or snow from the time it takes for the emitted radio waves to return, and observes the intensity of the rain or snow from the strength of the returned radio waves. As mentioned above, dual-polarized meteorological Doppler radar has also been introduced, and by using radio waves that vibrate horizontally and vertically (horizontal polarization, vertical polarization), it is possible to distinguish the type of precipitation particles in clouds and estimate the intensity of precipitation (precipitation state).

[0018] Dual-polarized meteorological Doppler radar can estimate the shape of precipitation particles from the ratio of amplitudes. The larger the precipitation particles, the more air resistance they experience and the flatter they become. This is observed using horizontal and vertical polarization, and the shape of the precipitation particles is estimated from the amplitude ratio of the reflected waves. The intensity of rain can also be estimated from the phase difference. When radio waves travel through water such as raindrops, their speed is slightly slower than in empty atmosphere. Taking advantage of the fact that the heavier the rain, the slower the speed of horizontally polarized waves, observations are made using horizontal and vertical polarization, and the precipitation intensity (precipitation state) is estimated from the phase difference of the reflected waves (strength of the reflected waves).

[0019] The estimation methods for estimating the shape of precipitation particles and the precipitation intensity are not limited to the amplitude of the reflected wave, and may be known methods using other information obtained from meteorological observation data. For example, the shape of precipitation particles and the precipitation intensity may be estimated based on the cross-correlation coefficient between horizontal and vertical polarization, the intensity ratio between horizontal and vertical polarization, etc. Also, an estimation method that combines the amplitude of the reflected wave with the cross-correlation coefficient between horizontal and vertical polarization, or the intensity ratio between horizontal and vertical polarization may be applied.

[0020] In estimating precipitation particles based on the amplitude ratio, categories such as wet snow, dry snow, ice crystals, drizzle, rain, graupel, hail, and heavy rain are prepared in advance. For example, if the amplitude ratio is equal to or greater than a predetermined value, the precipitation particles are determined (categorized) as hail. The amplitude ratio of each precipitation particle is set as a classification standard, and the weather phenomenon in the observation area is estimated based on meteorological observation data. Hail is ice particles with a diameter of 5 mm or more that fall from cumulonimbus clouds, and ice particles with a diameter of less than 5 mm are defined as graupel.

[0021] The weather management system 100 uses the weather observation data to perform analysis processes including a precipitation particle estimation process and a precipitation state determination process, and outputs the precipitation particles that will fall on the ground.

[0022] The web server 300 accepts posted information from the poster terminal T and provides a website that publishes the accepted posted information on the web. A poster is a user registered with the web server 300, and includes an unspecified number of posters. As an example, information posted to a social networking service (SNS) such as X (formerly Twitter (registered trademark)) or Facebook (registered trademark) can be used. In this case, posted information other than weather-related posted information is also stored in the web server 300.

[0023] As another example, information posted to a website that accepts weather-related posted information can be used. For example, a contributor can be a weather reporter or observer and post daily weather information. In this case, only weather-related posted information is stored in the web server 300.

[0024] As yet another example, the weather management system 100 of this embodiment may be configured to acquire weather-related posted information directly from the poster terminal T without going through the web server 300.

[0025] The weather management system 100 can also acquire weather-related posted information by connecting to one or more websites 300. The poster terminal T is a mobile terminal such as a multi-function mobile phone such as a smartphone or a tablet computer, and is equipped with a data communication function via an IP (Internet protocol) network or a mobile communication network, a calculation function (CPU, etc.), and a storage device (memory, auxiliary storage device, etc.).

[0026] The poster terminal T may also include a display control application such as a browser, a photographing device for photographing still images and moving images, a touch panel display input device, and a GPS device. As will be described later, the posted information posted from the poster terminal T includes the posted content as well as location information and time information acquired by the GPS device.

[0027] 1, the weather management system 100 includes a communication device 110, a first control device 120, a second control device 130, a first storage device 140, and a second storage device 150. The communication device 110 is a data communication interface, and the weather management system 100 obtains various information from a weather radar or a website 300 via an IP network or a dedicated line through the communication device 100, and provides alert information.

[0028] <Explanation of true value information using weather-related posted information> 2 is a diagram for explaining true value information generated by linking weather-related posted information with meteorological observation data corresponding to the weather-related posted information. The functions of managing the weather-related posted information and generating the true value information are mainly performed by the second control device 130 and the second storage device 150. The second control device 130 includes a posted information management unit 131 and a true value information generation unit 132.

[0029] Posted information posted to the web server 300 includes a posted article and / or a posted image, location information, time information, and poster information. A posted article is a posted text, and a posted image is an image taken by a photographing device provided in the poster terminal T, or an image taken by a photographing device other than the poster terminal T. The location information is the current location (posting location) of the poster (poster terminal T). The location information may include address information corresponding to the current location. The posting time is date and time information when the web server 300 accepts the posted information. The poster information is a user identifier such as a user ID registered in the web server 300.

[0030] A contributor inputs a post article and a post image on a posting screen provided by the web server 300 through the contributor terminal T, and transmits the post information to the web server 300. The web server 300 accepts the post information transmitted from the contributor terminal T, and posts the post information on the posting website provided by the web server 300, making it publicly available.

[0031] In this embodiment, the weather management system 100 acquires the posted information from the web server 300, but the present invention is not limited to this. For example, the posted information may be acquired via a search server (search site). The search site can collect posted information related to a search key such as a keyword from a plurality of different posting websites (a plurality of different websites 300). Thus, the weather management system 100 can acquire the posted information posted to the web server 300 from the website 300 or from a search site that can collect posted information from the website 300.

[0032] As shown in FIG. 2, the posted information management unit 131 acquires weather-related posted information from multiple posted information posted to the web server 300 based on the similarity of a keyword related to weather or an image related to weather. One or multiple pieces of weather-related posted information can be acquired. For example, posted information including the keyword "hail" can be acquired as weather-related information, or posted information having a posted image similar to a reference image showing "hail" can be acquired as weather-related posted information. Although "hail" has been described as an example, weather-related posted information related to "graupel" can be collected in a similar manner. Note that an image recognition AI model can also be used as a process for extracting posted information having posted images related to "hail". For example, a group of images showing "hail" can be input in advance as learning data, and a learning process can be performed to generate a "hail image recognition" AI model. Then, the generated AI model can be used to calculate the similarity of the posted image to "hail", and posted information having a posted image with a similarity equal to or greater than a predetermined value can be acquired as weather-related information.

[0033] Next, the true value information generating unit 132 extracts weather-related posted information that matches the observation area and observation time of the weather observation data.

[0034] For example, the results of the analysis of meteorological observation data, i.e., the process of estimating precipitation particles based on the amplitude ratio, are matched with the observation area and observation time determined to be hail and the location information and posting time of the weather-related posted information related to "hail". The true value information generating unit 132 determines whether the location information and posting time of the weather-related posted information related to "hail" are within a predetermined range that is sufficiently close to the observation area and observation time, and extracts the weather-related posted information related to "hail" that is within the sufficiently close predetermined range.

[0035] The true value information generating unit 132 links the weather-related posted information that matches the weather observation data as a weather phenomenon corresponding to the weather observation data. The true value information generating unit 132 stores the weather observation data linked to the weather phenomenon grasped from the weather-related posted information as true value information in the second storage device 150 (true value information 153).

[0036] In the above example, a mode has been described in which observation data determined to be hail is matched with meteorological posted information related to "hail" in the precipitation particle estimation process using meteorological observation data, but the present invention is not limited to this. For example, the location information and posting time of meteorological posted information related to "hail" may match the observation area and observation time of meteorological observation data in which precipitation particles were determined to be hail in the precipitation particle estimation process. In this case, "hail" is linked as true value information to the meteorological observation data for the observation area and observation time determined to be hail. The same is true vice versa.

[0037] In this way, the true value information is generated as a correct answer label for the analysis process. In other words, it is possible to check the analysis results of observation data for meteorological phenomena such as hailstones, which occur infrequently and are rarely observed on the ground. By feeding back the true value information, it is possible to improve the accuracy of analysis based on meteorological observation data.

[0038] <Weather observation data analysis function and alert output function> Next, a weather management function including a weather observation data analysis function and an alert output function will be described.

[0039] 1, the weather management function of this embodiment is mainly performed by the first control device 120 and the first storage device 140. The first control device 120 includes an analysis unit 121, an alert control unit 122, and a criteria control unit 123.

[0040] The analysis unit 121 classifies the meteorological observation data based on a type classification criterion, and outputs an analysis result based on the type classification criterion. As described above, the analysis unit 121 can perform a precipitation particle estimation process based on an amplitude ratio, and categories (classifications) such as wet snow, dry snow, ice crystals, drizzle, rain, hail, and heavy rain are prepared in advance. A predetermined amplitude ratio is set as the type classification criterion for each type of precipitation particle, and the analysis unit 121 estimates a meteorological phenomenon in an observation area from the meteorological observation data based on the type classification criterion.

[0041] The analysis unit 121 can also perform a precipitation state determination process using the precipitation intensity. As described above, the precipitation intensity is an index for estimating the amount (intensity) of precipitation based on the intensity of the reflected wave, and if the precipitation intensity is high, there is a lot of precipitation, and if the precipitation intensity is low, there is little precipitation. Here, the precipitation intensity is used in two main ways. The first is a case where it is used as an index representing a danger level. In other words, when it is estimated that the precipitation intensity is high and there is a lot of precipitation, it can be understood that it is a meteorological phenomenon that requires caution from the viewpoint of disaster prevention. The second is a case where it is used as an index for determining whether or not the precipitation particles in the sky grasped by the precipitation particle estimation process will actually fall on the ground. In other words, if the precipitation intensity is low, it can be determined that even if precipitation particles exist in the sky, they will not fall on the ground.

[0042] The analysis unit 121 of this embodiment performs analysis processing including a precipitation particle estimation processing and a precipitation state discrimination processing based on a predetermined criterion, and outputs precipitation particles falling to the ground. The predetermined criterion includes the above-mentioned type classification criterion used in the precipitation particle estimation processing and the precipitation state discrimination criterion used in the precipitation state discrimination processing. The type classification criterion and the precipitation state discrimination criterion are stored in the first storage device 140 as criterion information 142.

[0043] The precipitation state discrimination criterion includes a first precipitation state discrimination criterion for classifying the strength (abundance) of precipitation particles falling on the ground, and a second precipitation state discrimination criterion for determining whether precipitation particles in the sky will fall on the ground. When the precipitation intensity is greater than the second precipitation state discrimination criterion (threshold), the analysis unit 121 determines that the precipitation particles grasped in the precipitation particle estimation process will fall on the ground. On the other hand, when the precipitation intensity is less than the second precipitation state discrimination criterion (threshold), the analysis unit 121 determines that the precipitation particles grasped in the precipitation particle estimation process will not fall on the ground.

[0044] The analysis process of this embodiment classifies meteorological observation data based on a type classification criterion, determines the type of precipitation particles in the clouds in the sky, and judges whether the determined precipitation particles will rain down to the ground by comparing the precipitation intensity with a second precipitation state discrimination criterion. If it is determined that the precipitation particles will rain down, the analysis unit 121 outputs the determined precipitation particles in the clouds in the sky as precipitation particles that will rain down to the ground. At this time, the analysis unit 121 may be configured to also output the intensity (amount) of the precipitation particles that will rain down to the ground using the first precipitation state discrimination criterion.

[0045] Next, the alert output function will be described. The alert control unit 122 outputs alert information based on the analysis result of the analysis unit 121. For example, the alert information can be output to an information distribution system in which multiple users are registered, or to a web server that publishes information on a website. The alert information can also be provided to users (user terminals) registered in the weather management system 100.

[0046] Alert information is a message that calls for caution, vigilance, confirmation, etc. regarding meteorological phenomena. Alert information can include forecasts of meteorological phenomena that may occur in the future as well as currently occurring meteorological phenomena. Examples of alert information include caution alerts and caution alerts. A caution alert is disaster prevention-related information that calls for caution when there is a risk of a serious disaster occurring. A caution alert is disaster prevention-related information that calls for caution when there is a risk of a disaster occurring. Note that alert information can be configured in any way, not limited to caution alerts and caution alerts.

[0047] Each piece of alert information can be managed based on preset reference information for issuing a warning alert / attention alert. The alert control unit 122 can determine whether the analysis result (type of precipitation particles and precipitation intensity) of the analysis unit 121 corresponds to any of the alert information in the reference information for issuing a warning alert / attention alert, and control so that the corresponding alert information is output. The reference information for issuing a warning alert / attention alert is information in which a plurality of various alerts are specified according to the type of meteorological phenomenon (type of precipitation particles) and the intensity of the meteorological phenomenon (precipitation intensity).

[0048] This embodiment includes a criterion control unit 123, which changes the type classification criteria and the precipitation condition discrimination criteria based on meteorological phenomena (true value information) grasped from weather-related posted information corresponding to the meteorological observation data.

[0049] FIG. 3 is a diagram for explaining the process of changing the type classification criteria in this embodiment.

[0050] The weather management system 100 performs precipitation particle estimation processing using the weather observation data A. The weather observation data A is observed at 15:31 on July 21, 2023, in the observation area of ​​City A. The analysis unit 121 outputs a particle diameter of "3 mm" as the analysis result of the weather observation data A, and also outputs a meteorological phenomenon "hail (diameter less than 5 mm)" that corresponds to a particle diameter of "3 mm" based on the type classification standard. The alert control unit 122 outputs alert information (caution alert), for example, "Hail may be falling in City A. Please be careful."

[0051] Meanwhile, this meteorological observation data A is provided to the second control device 130 in real time in parallel with the analysis process of the meteorological management system 100, and the true value information generating unit 132 performs a true value information generating process based on the weather-related posted information. In the example of Fig. 3, the analysis result based on the meteorological observation data A is "hail", and the meteorological related posted information corresponding to the observation time and observation area of ​​the meteorological observation data A is "hail", so the meteorological phenomenon "hail" is generated as the true value information of the meteorological observation data A. Note that if the analysis result based on the meteorological observation data A and the meteorological phenomenon in the meteorological related posted information match, true value information may or may not be generated.

[0052] When the analysis result based on the meteorological observation data A differs from the meteorological phenomenon in the weather-related posted information, the true value information generating unit 132 outputs the analysis result of the meteorological observation data A and the generated true value information to the criteria control unit 123. As shown in Fig. 3, the criteria control unit 123 determines that the analysis result of the meteorological observation data A is "graupel" and the true value information is "hail", so that they differ, and changes the type classification criteria.

[0053] For example, the classification criteria for the precipitation particle estimation process is that when the amplitude ratio is equal to or greater than a predetermined value X and less than a predetermined value Y, it is determined to be "graupel," and when the amplitude ratio is equal to or greater than the predetermined value Y, it is determined to be "hail," and outputs "graupel" or "hailstone" as the analysis result of the meteorological phenomenon. In the example of FIG. 3, the criteria control unit 123 outputs "graupel" as the analysis result because the amplitude ratio of the meteorological observation data A was equal to or greater than the predetermined value X and less than the predetermined value Y, but since "hailstone" actually fell, the criteria control unit 123 changes the predetermined value Y, which is the boundary threshold between "graupel" and "hailstone," to a predetermined value Y1. The predetermined value Y1 is a value smaller than the predetermined value Y, and performs a threshold change to expand the area in the observation data that is determined to be "hailstone."

[0054] In this way, the threshold value is changed in the type classification criteria to temporarily narrow the area determined to be "graupel" and to widen the area determined to be "hail." The changed type classification criteria are then applied to the analysis process of meteorological observation data B observed after meteorological observation data A.

[0055] The weather observation data B is observed at 15:42 on January 5, 2023, in the observation area of ​​B City (next to A City). At this time, the weather observation data B is the same observation data as the weather observation data A, and the analysis result using the type classification standard before the change is determined to be "graupel", but the weather phenomenon "hail" is output as the analysis result of the weather observation data B in the type classification standard after the change based on the true value information based on the weather-related post information. The alert control unit 122 generates and outputs alert information (warning alert) such as "Hail may be falling in B City. Please be careful". Note that the weather radar observes precipitation particles in the sky, so it can output alert information several minutes to several tens of minutes before they fall to the ground. Therefore, it can also be configured to output alert information (warning alert) such as "Hail may fall in B City soon. Please be careful".

[0056] Next, a process of changing the precipitation condition discrimination criterion (second precipitation condition discrimination criterion) will be described. Specifically, when the analysis result of the meteorological observation data X is "no precipitation" and the meteorological phenomenon of the weather-related posted information corresponding to the observation time and observation area of ​​the meteorological observation data X is "hail", true value information "hail" is generated for the meteorological observation data X. At this time, the criterion control unit 123 temporarily changes the second precipitation condition discrimination criterion to a smaller value so that it is more likely to be determined that precipitation particles in the sky will rain down to the ground in the precipitation condition discrimination process.

[0057] That is, in the analysis process based on the meteorological observation data X, in the precipitation particle estimation process and the precipitation state discrimination process, there are cases where the precipitation particle estimation process determines that precipitation particles (hail) are present in the clouds in the sky, but since the precipitation intensity is smaller than the second precipitation state discrimination criterion, it is determined that the precipitation will not fall to the ground. Therefore, the criterion control unit 123 changes the second precipitation state discrimination criterion to a smaller value based on the true value information "hail" of the meteorological observation data X, so that it is determined that the precipitation particles (hail) detected in the sky will fall to the ground for meteorological observation data similar to the meteorological observation data X.

[0058] The criteria control unit 123 can also change both the type classification criteria and the precipitation state discrimination criteria. For example, weather-related posted information may contain information about precipitation intensity. "It's raining really hard" or "It's heavy rain" from a posted article of weather-related posted information can be extracted as information about precipitation intensity. In addition, the precipitation state can be discriminated using a posted image to estimate (extract) the precipitation intensity. The true value information can be configured to include information about precipitation intensity ascertained from the weather-related posted information, along with the weather phenomenon "hail."

[0059] Therefore, the criteria control unit 123 can be configured to change the type classification criteria when the result of the precipitation particle estimation processing of the weather observation data differs from the weather phenomenon of the weather-related posted information corresponding to the observation time and observation area of ​​the weather observation data, and to also change the precipitation condition discrimination criteria when the result of the precipitation state discrimination processing of the weather observation data differs from the information regarding precipitation intensity of the weather-related posted information.

[0060] In this embodiment, an analysis process is performed to analyze meteorological observation data and output precipitation particles that will fall on the ground based on a predetermined criterion, and alert information is output based on the result of the analysis process. Then, the predetermined criterion is changed based on the weather-related posted information posted from the poster terminal. At this time, the analysis process includes a precipitation particle estimation process and a precipitation state discrimination process, and the predetermined criterion includes a type classification criterion and a precipitation state discrimination criterion. Then, the criterion control unit 123 can change the type classification criterion, or both the type classification criterion and the precipitation state discrimination criterion, based on the weather-related posted information posted from the poster terminal T.

[0061] <Changing standards for posting areas and posting times> The weather management system 100 of this embodiment changes the predetermined criteria used in the analysis process of weather observation data when weather-related posted information is triggered. This makes it easier to output an alert or to switch from a caution alert to a warning alert.

[0062] As described above, hail is a special weather phenomenon that is observed infrequently, and is not a weather phenomenon that lasts for a long time or over a wide area. For this reason, the area in which the predetermined criteria are changed (area to which the changed value is applied) can be set based on the posting location of the weather-related posted information used as true value information, or the observation area of ​​the weather observation data corresponding to the weather-related posted information (true value information). The period in which the changed value is applied can also be set to a short period such as 30 minutes or 1 hour. After the period in which the changed value is applied has passed, the criteria control unit 123 initializes the changed value and controls the analysis process to be performed using the criteria value before the change (default value).

[0063] This configuration makes it easier to issue alerts for meteorological phenomena that cause serious damage as natural disasters, while also making it possible to appropriately limit the time and area for which hail alerts are issued. In other words, the time and area for which hail alerts are issued can be prevented from being unnecessarily broadened, thereby reducing confusion caused by the alerts.

[0064] On the other hand, the criteria change control of this embodiment is triggered by the posting of weather-related posted information. Therefore, if no weather-related posted information is posted, the predetermined criteria applied to the analysis process are not changed. Fig. 4 is a diagram for explaining the relationship between the posting interval of weather-related posted information and the alert that is output.

[0065] As shown in FIG. 4, the specified criteria are temporarily changed by weather-related posted information 1, but return to the default value after the criteria change period has elapsed. The specified criteria are not changed thereafter until weather-related posted information 2 is posted. Therefore, even if similar meteorological observation data is observed at point X, a warning alert for "hail" cannot be issued because the criteria have not been changed. Also, even if meteorological observation data similar to the meteorological observation data corresponding to weather-related posted information 1 is observed at point Y near point X, a warning alert for "hail" cannot be issued because the criteria have not been changed.

[0066] In other words, if no weather-related posted information is posted and no true value information is provided, the precipitation particles falling to the ground must be identified only by the analysis results based on meteorological observation data. For example, if there is no weather-related posted information from point X or Y, the predetermined criteria cannot be changed, and a situation occurs in which a warning alert for "hail" cannot be issued. In addition, a situation occurs in which a warning alert for "hail" cannot be issued even when it is preferable to issue a warning alert rather than a caution alert.

[0067] Since weather-related posted information is information posted by the poster, the frequency of posting is important. If the interval between postings of weather-related posted information is long, there will be a discrepancy between the precipitation particles in the sky based on meteorological observation data and the precipitation particles falling to the ground, and it will be impossible to issue a warning alert even if you want to.

[0068] Furthermore, the posting frequency (posting interval) differs depending on the location and time of day, for example, the posting frequency differs between downtown and residential areas, and between daytime and nighttime. Downtown areas are crowded even at night, and the posting frequency is higher than in residential areas, but in residential areas, the posting frequency is lower at night when people are asleep, and the posting interval for weather-related information is longer.

[0069] Therefore, in this embodiment, in the output control of an alert using weather-related posted information, a disaster prevention call is made taking into consideration the posting frequency of weather-related posted information, etc. Specifically, for each predetermined posting area, an effective time and an effective area according to a predetermined posting time period are set, and the time and area to which the change value of the predetermined criterion changed by the criterion control unit 123 is applied are managed.

[0070] Figure 5 shows an example of setting valid times and valid areas for each posting area, where posting time periods are divided into multiple periods and valid times and valid areas are set for each posting time period. The example in Figure 5 shows an example of setting valid times and valid areas for ABC City, which has many residential areas.

[0071] Setting 1 is a nighttime period. During the nighttime period, posting frequency is low and there are few weather-related posts. For this reason, the valid time is set to six hours, and the valid area is set to a 40km radius from the posting location of the weather-related post. In contrast, setting 2 is a daytime period, and posting frequency is higher than the nighttime period of setting 1. In the time period of setting 2, the valid time is set to two hours, and the valid area is set to a 20km radius from the posting location.

[0072] The effective time and effective area are the application time and application area of ​​the predetermined criteria that are changed based on the weather-related posted information, and during the effective time, the analysis process using the changed values ​​continues in the effective area without restoring the changed values. In other words, the time and area affected by the weather-related posted information are set as the effective time and effective area, the time during which the analysis process using the changed predetermined criteria continues is the effective time, and the area to which the analysis process using the changed predetermined criteria is applied is the effective area.

[0073] In addition, the effective time and the effective area can be set arbitrarily. For example, a plurality of posting time periods can be set for each region where weather-related posted information is posted, and the effective time and the effective area can be set for each posting time period taking into account the regional characteristics of the region.

[0074] In the weather management system 100, the second control device 130 is provided with a valid time / valid area management unit 133. The valid time / valid area management unit 133 receives input of a posting area, a plurality of posting time periods for the posting area, and a valid time and valid area for each posting time period. The valid time and valid area set for each predetermined posting area according to the predetermined posting time period are stored in the second storage device 150.

[0075] When changing the predetermined criteria, the criteria control unit 123 identifies a predetermined posting area corresponding to the posting position of the weather-related posted information that triggered the change of the predetermined criteria, identifies a predetermined posting time period corresponding to the posting time of the weather-related posted information, and extracts the valid time and valid area associated with the identified predetermined posting area and predetermined posting time period. The analysis unit 121 performs an analysis process applying the changed predetermined criteria to meteorological observation data located within the valid area from the posting position of the weather-related posted information during the valid time period corresponding to the posting time of the weather-related posted information.

[0076] FIG. 6 is an explanatory diagram in which the criteria change control for each posting area and posting time period of this embodiment is applied. As shown in FIG. 6, when weather-related posted information is posted, an alert output is performed in a range of 40 km radius centered on point X, switching from a "caution alert" to a "caution alert". If meteorological observation data similar to the meteorological observation data corresponding to the weather-related posted information is observed for 6 hours from the posting time (23:41), the weather phenomenon is determined to be "hail" and a caution alert is output. Note that, if the next weather-related posted information is posted during the valid time period, the change value of the currently used predetermined criteria may be further changed. In this case, the valid time and valid area are not changed, and the analysis process is performed with the latest change value applied.

[0077] By configuring it in this manner, even during times when the posting frequency is low and the intervals between postings of weather-related posted information are long, the modified predetermined criteria based on the most recent weather-related posted information are applied, thereby avoiding a situation in which it is not possible to issue an alert even if one wishes to do so, and enabling an alert to be issued when it is preferable to do so.

[0078] FIG. 7 is a diagram showing a process flow executed by the weather management system 100 of the present embodiment.

[0079] The weather management system 100 receives input of the valid time and valid area set for each specified posting area according to a specified posting time period through the valid time / valid area management unit 133, and stores the valid time and valid area in the second storage device 150 (S151).

[0080] The weather management system 100 performs true value information provision processing and alert output processing independently of each other. The weather radar performs continuous observation in time series at a predetermined interval and outputs meteorological observation data. The weather management system 100 (the analysis unit 121 of the first control device 120) performs analysis processing of the input meteorological observation data (S101). At this time, the same meteorological observation data as that input to the analysis unit 121 of the first control device 120 is also provided to the true value information generation unit 132 of the second control device 130.

[0081] The weather management system 100 stores the analysis results in the first storage device 140 (S102), and controls the output of alert information based on the analysis results (S103).

[0082] Meanwhile, the weather management system 100 performs true value information provision processing. The posted information management unit 131 extracts weather-related posted information from a plurality of posted information items posted to the web server 300 based on similarities between weather-related keywords or weather-related images (S131). For example, posted information stored in the web server 300 is searched using keywords such as "hail" or "graupel" or sample images of "hail" or "graupel" as extraction keys. The extraction keys are set arbitrarily by the operator of the weather management system 100.

[0083] The weather-related posted information is posted information that matches either one of a keyword and a sample image related to weather, or posted information that matches both a keyword and a sample image related to weather.

[0084] The true value information generating unit 132 extracts weather-related posted information that matches the observation area and observation time of the weather observation data (S132). The true value information generating unit 132 outputs the weather phenomenon understood from the weather-related posted information that matches the weather observation data as true value information of the weather phenomenon corresponding to the weather observation data (S133). The true value information based on the weather-related posted information is stored in the first storage device 140 and is also output to the reference control unit 123 of the first control device 120.

[0085] Upon receiving the true value information, the reference control unit 123 starts the reference change process (S104). The reference control unit 123 compares the analysis result of the meteorological observation data corresponding to the true value information with the provided true value information, and judges whether the meteorological phenomena differ from each other. If it is judged that they do not differ (match), the reference change process is not performed (NO in S105). On the other hand, if it is judged that the meteorological phenomena are different (YES in S105), the reference change process is performed based on the true value information (weather-related posted information) (S106).

[0086] In the criteria change process, the criteria control unit 123 identifies a predetermined posting area corresponding to the posting position of the weather-related posted information that triggered the change in the predetermined criteria, identifies a predetermined posting time period corresponding to the posting time of the weather-related posted information, and extracts a valid time and valid area associated with the identified predetermined posting area and predetermined posting time period (S107). The criteria control unit 123 sets the extracted valid time and valid area as the time and area to which the changed value is to be applied (S108). The analysis unit 121 performs analysis process applying the changed predetermined criteria (changed value) to meteorological observation data located within the valid area from the posting position of the weather-related posted information during the valid time period corresponding to the posting time of the weather-related posted information.

[0087] The criterion control unit 123 monitors the effective time for which the changed predetermined criterion is applied, and judges whether the effective time of the applied changed value has elapsed (S109). If it is judged that the effective time has elapsed, the criterion control unit 123 resets the applied changed value to return it to the original criterion (S110). After the effective time period has elapsed, the analysis unit 121 performs an analysis process in which the original criterion before the change is applied. In other words, an analysis process in which the original criterion before the change is applied is performed on the effective area linked to the effective time, as with other areas to which the changed value is not applied. The weather management system 100 repeatedly performs the analysis process on the subsequent weather observation data (from NO in S111 to S101).

[0088] In this embodiment, true value information based on weather-related posted information is applied in real time to the analysis processing of weather observation data in the weather management system 100, and is reflected in the subsequent analysis processing of the weather observation data. If the analysis result of the weather observation data and the true value information based on the weather-related posted information differ from each other, the predetermined criterion used in the analysis processing can be changed to make the analysis result of the subsequent weather observation data more accurate.

[0089] Hail, in particular, is a natural disaster that causes great damage. Even if the analysis results of meteorological observation data indicate that graupel is falling rather than hail, there may be cases in which hail is actually falling (in the posted information). Therefore, in the subsequent analysis process of the meteorological observation data, even similar meteorological observation data that was determined to be graupel is determined to be hail more strictly as falling. In other words, the frequency with which it is determined to be hail is increased, and the number of times it is not determined to be hail is reduced. By configuring in this way, it is possible to easily issue alerts for meteorological phenomena that cause great damage as natural disasters, and to appropriately call attention to disaster prevention.

[0090] Even during periods when the intervals between postings of weather-related posted information become longer, the predetermined criteria changed based on the most recent weather-related posted information continue to be applied during the validity period. This provides a mechanism for appropriately calling for disaster prevention measures against meteorological phenomena when necessary.

[0091] Up to this point, the weather phenomenon of hail and sleet has been described as an example, but the weather management system 100 can output alerts for weather phenomena such as tornadoes and whirlwinds. For example, the weather-related posted information can include each posted information related to hail, sleet, tornadoes, or whirlwinds. Weather-related posted information containing tornadoes and whirlwinds as keywords and / or similar images can be acquired from the web server 300. Then, the true value information generating unit 132 extracts weather-related posted information that matches the observation area and observation time of the weather observation data. The weather phenomenon of tornadoes or whirlwinds identified from the weather-related posted information is linked as true value information corresponding to the weather observation data.

[0092] One method for observing tornadoes and whirlwinds is meteorological Doppler radar observation. In addition to the location and strength of precipitation, the Doppler effect of radio waves reflected from precipitation particles carried by the wind can be used to measure the components of wind approaching and receding from the weather radar. This is called the Doppler speed. If the approaching speed is equal to or greater than a predetermined value and the receding speed is equal to or greater than a predetermined value, it can be determined that a wind vortex (rotation in a developed cumulonimbus cloud that brings about a tornado; a mesocyclone) is occurring. For example, if the Doppler speed is equal to or greater than a predetermined value, it can be determined that a tornado is occurring. The weather management system 100 can obtain meteorological observation data of Doppler speed from the meteorological Doppler radar and perform analysis processing to determine whether a tornado or whirlwind is occurring.

[0093] The weather management system 100 can output alert information and change the predetermined criteria for tornadoes and whirlwinds based on weather-related posted information, targeting tornadoes and whirlwinds. In the process of changing the predetermined criteria, the threshold value of the Doppler speed for determining the occurrence of a tornado can be changed. For each predetermined posting area, an effective time and an effective area according to a predetermined posting time zone are set, and the time and area to which the change value of the predetermined criteria changed by the criteria control unit 123 is applied are managed.

[0094] In addition, the weather management system 100 of this embodiment may be configured to target at least one of hail, sleet, tornadoes, and whirlwinds, or may be configured to target all of hail, sleet, tornadoes, and whirlwinds, or any combination thereof.

[0095] Second embodiment Fig. 8 is a diagram for explaining the second embodiment. Fig. 8 is a diagram showing an example of setting the effective time and effective area for each posting area in this embodiment. This embodiment has a function of setting the effective time and effective area of ​​the first embodiment based on the posting history of past weather-related posted information.

[0096] The valid time / valid area management unit 133 performs a valid time calculation process (first process) in which, using statistical information on a group of past weather-related posted information, it calculates a posting interval for each posting time period for each specified posting area, and sets an effective time for each specified posting time period in the specified posting area based on the posting interval for each posting time period, and performs a valid area calculation process (third process) in which, using statistical information on a group of past weather-related posted information, it calculates a distance difference between posting positions for each posting time period for each specified posting area, and sets an effective area for each specified posting time period in the specified posting area based on the distance difference between the posting positions.

[0097] As shown in FIG. 8, for example, in DEF city, the posting interval is 30 minutes on average during the time period 6:00-14:00, 70 minutes on average during the time period 14:00-24:00, and 180 minutes on average during the time period 24:00-6:00.

[0098] Then, for example, the valid time and valid area management unit 133 sets the valid time for the time period 6:00-14:00 to 1 hour since the posting interval exceeds 30 minutes. For the time period 14:00-24:00, the posting interval exceeds 1 hour, so the valid time is set to 120 minutes. For the time period 24:00-6:00, the posting interval is long at 3 hours, so the valid time is set to 6 hours. Note that the time period to be set as the valid time is arbitrary based on the posting interval of each posting time period based on statistical information, but for example, it may be determined by adding a predetermined time to the posting interval, such as the posting interval + 30 minutes, the posting interval + 1 hour, or the posting interval + 180 minutes. Also, for example, a configuration may be used in which 1.5 or 2 times the posting interval is set as the valid time.

[0099] In this manner, in this embodiment, the posting interval for each posting time period is calculated using statistical information of past weather-related posted information, and the effective time for each posting time period for each predetermined posting area can be set based on the calculated posting interval for each posting time period. If the posting interval (time interval) is short, the effective time is set short, and if the posting interval is long, the effective time is set long.

[0100] Next, the effective area can be set based on the degree of dispersion of posting positions in DEF city. The degree of dispersion can be determined by using the distance difference of the posting positions. Specifically, the posting positions of past weather-related posted information are analyzed, and if the average value of the distance difference of the posting positions in DEF city is large, the effective area is set to be large, and if the distance difference of the posting positions is small, the effective area is set to be small.

[0101] Explaining with reference to FIG. 8, in the time period 6:00 to 14:00, the average distance difference between posting locations is 20 km, so the effective area is set to a radius of 20 km. In the time period 14:00 to 24:00, the average distance difference between posting locations is 40 km, so the effective area is set to a radius of 40 km. In the time period 24:00 to 6:00, the average distance difference between posting locations is 30 km, so the effective area is set to a radius of 30 km. Note that the effective area can be set to be the same as the distance difference between the posting locations or larger than the distance difference between the posting locations. If the distance between the posting locations is long, the effective time and effective area management unit 133 sets the effective area to be wide, and if the distance between the posting locations is short, the effective area is set to be narrow.

[0102] In summary, for each predetermined posting area, the valid time / valid area management unit 133 sets the valid area for posting to be wider and the valid time to be longer in time periods when the distance between posting locations is long and the number of posts is low. Also, the valid area is set wider and the valid time is set shorter in time periods when the distance between posting locations is long and the number of posts is high. Also, when the distance between posting locations is short and the number of posts is low, the valid area is narrower and the valid time is longer. And when the distance between posting locations is short and the number of posts is high, the valid area is narrower and the valid time is shorter.

[0103] In this embodiment, the effective time and effective area are set for each specified posting area based on statistical information for each posting area generated from accumulated past weather-related posting information, so that an appropriate effective time and effective area can be set according to the regionality and posting frequency of the posting area.

[0104] Third embodiment Fig. 9 is a diagram for explaining the third embodiment. Fig. 9 is a diagram showing an example of setting the effective time and the effective area for each posting area in the present embodiment, and is a diagram showing an example of dynamically changing the effective time and the effective area.

[0105] The valid time and valid area in the first and second embodiments are set based on a predetermined value or on past weather-related posted information, and are fixed values ​​that do not change during the relevant posting time period. The valid time / valid area management unit 133 in this embodiment has a function of dynamically changing the valid time and valid area based on multiple pieces of weather-related posted information posted during a specific posting time period that corresponds to the current time.

[0106] Fig. 9 shows an example of dynamically changing the effective time and effective area calculated based on statistical information of past weather-related posted information in the second embodiment. As shown in Fig. 9, weather-related posted information posted in a specific posting time period corresponding to the current time is monitored, and the effective time / effective area management unit 133 calculates the posting interval and distance difference between the posted positions of a group of weather-related posted information posted in real time at a fixed cycle (fixed interval). The calculated posting interval is used as the real-time posting interval, and the calculated distance difference between the posted positions is used as the real-time distance difference between the posted positions.

[0107] Then, the valid time / valid area management unit 133 compares the posting interval for each posting time period calculated based on the statistical information corresponding to the current valid time with the real-time posting interval, and varies the valid time being applied to the specific posting time period corresponding to the current time.

[0108] For example, in the time period of setting 2 from 14:00 to 23:00, if the posting interval by posting time period corresponding to the currently set valid time is an average of 70 minutes and the real-time posting interval is an average of 120 minutes, the valid time / valid area management unit 133 will change the valid time, which is set to 2 hours, to 3 hours.

[0109] In this way, the valid time / valid area management unit 133 performs a process (second process) of calculating, for each specified posting area, a real-time posting interval for multiple weather-related posting information posted during a specified posting time period corresponding to the current time, and compares the posting interval for each posting time period calculated based on statistical information with the real-time posting interval, thereby varying the valid time applied to the specified posting time period.

[0110] Similarly, the valid time / valid area management unit 133 performs a process (fourth process) of calculating, for each specified posting area, a real-time distance difference between the posting positions of multiple weather-related posting information items posted during a specified posting time period corresponding to the current time, and compares the distance difference between the posting positions calculated based on the statistical information with the real-time distance difference between the posting positions, thereby varying the valid area being applied to the specified posting time period corresponding to the current time.

[0111] In this embodiment, if the real-time posting interval is longer than the posting interval corresponding to the current valid time, the valid time is lengthened, and if the real-time posting interval is shorter than the posting interval corresponding to the current valid time, the valid time is shortened. Also, if the real-time distance difference of the posted positions is larger than the distance difference of the posted positions corresponding to the current effective area, the effective area is enlarged, and if the real-time distance difference of the posted positions is smaller than the distance difference of the posted positions corresponding to the current effective area, the effective area is shortened.

[0112] In this embodiment, the effective time and area of ​​the predetermined criteria, which are changed in response to weather-related posted information, are adjusted to an appropriate time width and area width according to changes in the posting frequency and posting location of the weather-related posted information. Therefore, it is possible to more appropriately issue a disaster prevention call (alert output) for a weather phenomenon using the predetermined criteria changed based on the weather-related posted information (true value information).

[0113] The process of dynamically changing the valid time and the process of dynamically changing the valid area may be configured as independent processes, or the process of changing the valid time and the process of changing the valid area may be configured to be performed in conjunction with each other as a set. In other words, it is possible to dynamically change either the valid time or the valid area, or to dynamically change both the valid time and the valid area.

[0114] Here, in the above description, the current valid time and current valid area are dynamically changed by a comparison process using statistical information (posting interval, distance difference between posting locations) of past weather-related posting information in the second embodiment, but this is not limited to this.

[0115] For example, if the preset valid time is one hour during the time period from 14:00 to 23:00 and the real-time posting interval is an average of 90 minutes, the preset valid time may be simply compared with the real-time posting interval and the valid time may be set longer.

[0116] Therefore, the function of dynamically changing the valid time and valid area of ​​this embodiment can also be applied to the above-mentioned first embodiment. The valid time / valid area management unit 113 can perform a process (fifth process) of calculating a real-time posting interval of a plurality of pieces of weather-related posted information posted during a predetermined posting time period corresponding to the current time for each predetermined posting area, and a process (sixth process) of calculating a real-time distance difference between the posted positions of a plurality of pieces of weather-related posted information posted during a predetermined posting time period corresponding to the current time for each predetermined posting area. Then, based on the calculated real-time posting interval, the current valid time applied to the predetermined posting time period corresponding to the current time can be changed, and the current valid area can be changed based on the calculated real-time distance difference between the posted positions.

[0117] (Fourth embodiment) Fig. 10 is a diagram for explaining the fourth embodiment. Fig. 10 is a diagram for explaining the process of enlarging the effective area using the motion vector of the cloud in this embodiment.

[0118] This embodiment has a function of expanding the effective area using the cloud motion vector. The analysis unit 121 calculates the cloud motion vector using a precipitation distribution image based on meteorological observation data, which is generated at a predetermined time interval. The precipitation distribution image is an image in which the distribution of precipitation particles in the sky grasped by the precipitation particle estimation process using the above-mentioned type classification criteria is plotted on a map, and is generated continuously at a certain time interval. The precipitation distribution image may be generated by the weather management system 100 (first control device 120), or may be obtained and used from an external weather information providing system.

[0119] The cloud motion vector can be calculated using known image processing techniques. For example, the cloud motion vector can be calculated by determining the speed and direction from the difference between precipitation distribution images transmitted at a certain time interval.

[0120] Then, the analysis unit 121 expands the effective area based on the cloud's motion vector. Specifically, for example, a circular area with a radius of 40 km from the posting position is expanded in the direction of the cloud's motion vector, as shown in Fig. 10. The analysis unit 121 controls to perform an analysis process applying the changed predetermined standard to meteorological observation data located within the effective area expanded from the posting position of the weather-related posted information during the effective time period according to the posting time of the weather-related posted information.

[0121] The expansion of the effective area using the cloud's motion vector may be performed, for example, when changing a predetermined criterion based on weather-related posted information (true value information), and after a predetermined time has elapsed, the effective area may be controlled to return to the effective area before expansion. Also, the cloud's motion vector may be calculated even during the expansion of the effective area, and the expansion direction of the expanded area may be adjusted to match the direction of the cloud's motion vector. Also, if the speed of the cloud's motion vector is fast, the expanded area may be controlled to be larger, and if the speed of the cloud's motion vector is slow, the expanded area may be controlled to be smaller. Also, regardless of the speed of the cloud's motion vector, a certain area may be controlled to be expanded relative to the effective area.

[0122] According to this embodiment, the scope of application of the specified criteria, which are changed based on weather-related posted information (true value information), can be expanded to match the actual movement of clouds, and calls for disaster prevention in response to meteorological phenomena can be made appropriately to the extent that they are necessary.

[0123] Although the embodiment has been described above, as mentioned above, the precipitation particle estimation process and the precipitation state determination process may be estimation methods using information other than the amplitude of the reflected wave. Therefore, the type classification criterion and the precipitation state determination criterion may be criteria related to the cross-correlation coefficient between the horizontal polarization and the vertical polarization or the intensity ratio between the horizontal polarization and the vertical polarization, instead of criteria related to the amplitude of the reflected wave. In other words, the criterion control unit 123 can vary one or more criteria used in any estimation method applied to the precipitation particle estimation process and the precipitation state determination process.

[0124] The analysis unit 121 can also be configured as a weather detection model. The weather detection model (analysis unit 121) performs precipitation particle estimation processing using the above-mentioned type classification criteria and precipitation state discrimination processing using the precipitation state discrimination criteria, and outputs precipitation particles that will rain down on the ground using the results of the precipitation particle estimation processing of precipitation particles in clouds in the sky. The weather detection model can be generated by performing a learning process using past weather observation data and true value information.

[0125] The weather detection model functions as a processing unit that performs analysis processing using the predetermined criteria before the change in the above-mentioned analysis unit 121, and serves as the basis for the weather detection processing. A plurality of different weather detection models can be prepared in advance, and the analysis processing can be performed by switching between the weather detection models. For example, it is possible to generate weather detection models tuned based on various concepts, such as a first weather detection model that can issue more alerts, a second weather detection model that can issue fewer alerts, and a third weather detection model that can issue fewer alerts than the first weather detection model and more alerts than the second weather detection model.

[0126] Taking the meteorological phenomenon of "hail" as an example, the first weather detection model is a weather detection model with both a high false positive rate (the rate at which things that are not actually hail are mistakenly determined to be hail) and a high true positive rate (the rate at which things that are actually hail are correctly determined to be hail). On the other hand, the second weather detection model is the opposite, being a weather detection model with both a low false positive rate and a low true positive rate, and the third weather detection model is a weather detection model with a false positive rate and true positive rate lower than the first weather detection model and higher than the second weather detection model.

[0127] That is, in the first to fourth embodiments, for example, an analysis process (weather detection model) in which the predetermined criteria are set loosely in advance and which easily judges that it is hail will have a high false positive rate and true positive rate, whereas an analysis process (weather detection model) in which the predetermined criteria are set tightly and which difficultly judges that it is hail will have a low false positive rate and true positive rate.

[0128] In the first to fourth embodiments, the analysis process is performed using a base weather detection model, and the criteria (type classification criteria, precipitation state discrimination criteria) for the precipitation particle estimation process and the precipitation state discrimination process are changed based on the weather-related posted information, while the base weather detection model may also be changed based on the weather-related posted information. For example, the analysis process using the third weather detection model may be switched to the first weather detection model when weather-related posted information (true value information) is posted.

[0129] By switching to the first weather detection model for analysis processing, it is possible to obtain analysis processing results with both a high false positive rate and a high true positive rate in response to the posting of weather-related posted information (true value information), making it easier to issue warning alerts regarding "hail." In addition, within the set effective area, the specified criteria are changed during the effective time period, creating an environment in which warning alerts regarding "hail" are even more likely to be issued.

[0130] In addition, the weather-related posted information in each of the above embodiments can be evaluated and extracted using predetermined evaluation information from multiple posted information posted to the web server 300 based on the similarity of weather-related keywords or weather-related images.

[0131] The first evaluation information is, for example, a poster evaluation value. The poster evaluation value can be calculated using evaluation parameters (evaluation criteria) such as the poster's number of past posts, the number of evaluations from other posters, and the number of cases in which past posted information was adopted as true value information. The poster's number of past posts and the number of evaluations from other posters can be acquired from the posting history managed by the web server 300. The number of cases in which past posted information was adopted as true value information can be retained in the weather management system 100 by posters of weather-related posted information that was adopted as true value information.

[0132] The second evaluation information is, for example, a posting accuracy evaluation value. Specifically, posted information (similar posted information) by other contributors that includes location information and location information and time information within a predetermined range close to the location information and posting time of the posted information and has similarity to weather-related keywords or weather-related images is extracted from a plurality of posted information posted to the web server 300. Then, based on the extracted similar posted information, a posting accuracy evaluation value for the candidate posted information can be generated. The posting accuracy evaluation value indicates the posting accuracy of the posted information based on the number of similar posted information by other contributors.

[0133] The third evaluation information is, for example, a weather phenomenon evaluation value. Specifically, the information accuracy of the posted information is evaluated using forecast information (forecast information generated by a predetermined weather forecast model) provided by an external weather forecast information providing service. A weather event evaluation value for the posted information is generated based on the location information of the posted information and the forecast information corresponding to the posted information. If the location information of the posted information and the weather phenomenon in the posted information are similar to the weather information in the forecast information, the weather phenomenon evaluation value is calculated to be high, and if the location information of the posted information and the weather phenomenon in the posted information are different from the weather information in the forecast information, the weather phenomenon evaluation value is calculated to be low.

[0134] The posted information management unit 131 performs various calculation processes for the poster evaluation value, the posting accuracy evaluation value, and the weather event evaluation value, and evaluates a plurality of posted information posted to the web server 300 with each of these evaluation values ​​based on the similarity of keywords related to weather or images related to weather, and extracts weather-related posted information from among the posted information with an evaluation value equal to or greater than a predetermined value. For example, posted information having each evaluation value equal to or greater than a predetermined value can be extracted as weather-related posted information, or posted information having a total of each evaluation value equal to or greater than a predetermined value can be extracted as weather-related posted information. In addition, weight values ​​may be applied to the poster evaluation value, the posting accuracy evaluation value, and the weather event evaluation value, and the weight values ​​of the poster evaluation value and the posting accuracy evaluation value may be set high and the weight value of the weather event evaluation value may be set low to calculate the total evaluation value. In this case, the weight values ​​may be set arbitrarily. Note that the posted information may be evaluated with at least one of the poster evaluation value, the posting accuracy evaluation value, and the weather event evaluation value, or with any combination of these, to extract weather-related posted information.

[0135] Each function constituting the above-mentioned weather control system 100 can be realized by a program, and a computer program prepared in advance to realize each function is stored in an auxiliary storage device. A control unit such as a CPU reads the program stored in the auxiliary storage device into a main storage device, and the control unit executes the program read into the main storage device, thereby operating the functions of each unit.

[0136] The above program can also be provided to a computer in a state in which it is recorded on a computer-readable recording medium. Examples of computer-readable recording media include optical disks such as CD-ROMs and Blu-ray (registered trademark) Disc Rewritable, phase-change optical disks such as DVD-ROMs, magneto-optical disks such as MO (Magneto Optical), magnetic disks such as floppy (registered trademark) disks and hard disks, and memory cards such as SD memory cards and USB flash drives. Also included as recording media are hardware devices such as integrated circuits (IC chips such as ROM and RAM) specially designed and configured for the purpose of the present invention. Furthermore, the present invention, including the above-mentioned program, is not limited to being executed on the architecture of a von Neumann-type computer, but may be executed on the architecture of a so-called non-von Neumann-type computer, such as a neurocomputer based on the mechanism of neural circuits in the brain or a quantum computer that applies quantum mechanics to information processing.

[0137] Although the embodiment of the present invention has been described, the embodiment is presented as an example and is not intended to limit the scope of the invention. This new embodiment can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0138] 100 Weather Management System 110 Communication equipment 120 First control device 121 Analysis Department 122 Alert control section 123 Standard Control Section 130 Second control device 131 Posting Information Management Department 132 True value information generation unit 133 Valid Time and Area Management Department 140 1st storage device 141 Meteorological Observation Data 142 Standard Information 150 2nd storage device 151 Posts 152 True Value Information 153 Valid time and area information 300 Web Server T terminal (submitter's terminal)

Claims

1. 1. A weather management system comprising: An analysis unit that performs an analysis process to classify the observation data of the weather radar based on a predetermined criterion and output the precipitation particles that will fall to the ground; an alert control unit that outputs alert information based on a result of the analysis process; a criterion control unit that changes the predetermined criterion based on a meteorological phenomenon identified from weather-related posted information that is posted from a poster terminal and matches observation data observed by a weather radar; and A storage unit that stores a valid time and a valid area set according to a predetermined posting time period for each predetermined posting area, A weather management system characterized in that the analysis unit performs the analysis processing by applying the changed specified criteria to observation data located within the effective area from the posting location of the weather-related posted information during the effective time period corresponding to the posting time of the weather-related posted information.

2. The weather management system described in claim 1, characterized in that, when changing the specified criteria, the criteria control unit identifies the specified posting area corresponding to the posting location of the weather-related posted information that triggered the change of the specified criteria, and identifies the specified posting time period corresponding to the posting time of the weather-related posted information, and extracts the effective time and effective area linked to the identified specified posting area and specified posting time period.

3. a valid time / valid area management unit that sets the valid time and the valid area; The effective time and effective area management unit The weather management system described in claim 1, characterized in that a first process is performed in which a posting interval for each posting time period is calculated for each specified posting area using statistical information of a group of past weather-related posted information, and the effective time for each specified posting time period in the specified posting area is set based on the posting interval for each posting time period.

4. The effective time and effective area management unit performing a second process of calculating, for each predetermined posting area, a real-time posting interval of the plurality of pieces of weather-related posted information posted during the predetermined posting time period corresponding to the current time; A weather management system as described in claim 3, characterized in that the posting interval for each posting time period calculated based on the statistical information is compared with the real-time posting interval, and the effective time applied to the specified posting time period is changed.

5. a valid time / valid area management unit that sets the valid time and the valid area; The effective time and effective area management unit The weather management system described in claim 1, characterized in that a third process is performed in which statistical information of past weather-related posted information is used to calculate the distance difference between the posting positions for each posting time period for each specified posting area, and the effective area for each specified posting time period in the specified posting area is set based on the distance difference between the posting positions.

6. The effective time and effective area management unit performing a fourth process of calculating, for each predetermined posting area, a real-time distance difference between posting positions of the plurality of pieces of weather-related posted information posted during the predetermined posting time period corresponding to the current time; The weather management system described in claim 5, characterized in that the distance difference of the posting position calculated based on the statistical information is compared with the real-time distance difference of the posting position, and the effective area applied to the specified posting time period is changed.

7. a valid time / valid area management unit that sets the valid time and the valid area; The effective time and effective area management unit A fifth process of calculating a real-time posting interval of the plurality of pieces of weather-related posted information posted during a predetermined posting time period corresponding to a current time for each predetermined posting area; a sixth process of calculating, for each predetermined posting area, a real-time distance difference between posting positions of the plurality of pieces of weather-related posted information posted during a predetermined posting time period corresponding to the current time; The weather management system described in claim 1, characterized in that the effective time applied to a specified posting time period corresponding to the current time is varied based on the real-time posting interval, and the effective area is varied based on a real-time distance difference of the posting position.

8. The weather management system according to claim 1 , wherein the analysis unit performs the analysis process by returning the predetermined standard to the pre-change standard after the valid time period has elapsed.

9. The analysis unit classifies the observation data of the weather radar based on a classification criterion, performs a precipitation particle estimation process to estimate precipitation particles in the clouds in the sky, and performs the analysis process to output the precipitation particles that will fall to the ground; The weather management system according to claim 1 , wherein the criteria control unit changes the category classification criteria.

10. the analysis unit performs the precipitation particle estimation process, as well as a precipitation state discrimination process for discriminating a precipitation state on the ground based on a precipitation intensity grasped from observation data, and performs the analysis process for outputting precipitation particles falling on the ground based on the results of the precipitation particle estimation process and the precipitation state discrimination process; The weather management system according to claim 9 , wherein the criteria control unit changes the type classification criteria, or both the type classification criteria and the precipitation condition discrimination criteria for precipitation intensity used in the precipitation condition discrimination process.

11. The analysis unit calculates a cloud motion vector using a precipitation distribution image based on observation data of a weather radar, the precipitation distribution image being generated at a predetermined time interval; The weather management system of claim 1, characterized in that the analysis unit expands the effective area based on the cloud movement vector, and performs the analysis process by applying the changed predetermined criteria to observation data located within the expanded effective area from the posting position of the weather-related posted information during the effective time period corresponding to the posting time of the weather-related posted information.

12. The weather management system according to claim 1 , wherein the weather-related posted information is posted information related to hail, sleet, tornadoes, or whirlwinds.

13. A program executed by a weather management device, the weather management device comprising: A first function of performing an analysis process of classifying the observation data of the weather radar based on a predetermined criterion and outputting the precipitation particles that fall to the ground; A second function of outputting alert information based on a result of the analysis process; a third function of changing the predetermined criterion based on a meteorological phenomenon identified from the weather-related posted information posted from a poster terminal and matching observation data observed by a weather radar; and A fourth function of storing a valid time and a valid area set according to a predetermined posting time period for each predetermined posting area, The first function is a program characterized by performing the analysis process by applying the modified specified criteria to observation data located within the valid area from the posting location of the weather-related posting information during the valid time period corresponding to the posting time of the weather-related posting information.

14. A weather management method comprising: A step of performing an analysis process of classifying the observation data of the weather radar based on a predetermined criterion and outputting precipitation particles; outputting alert information based on a result of the analysis processing; changing the predetermined criterion based on a meteorological phenomenon identified from weather-related posted information posted from a poster terminal and matching observation data observed by a weather radar; The step of performing the analysis processing is a weather management method in which the analysis processing is performed by applying the modified specified criteria to observation data located within a specified area from the posting location of the weather-related posted information during a specified period of time corresponding to the posting time of the weather-related posted information.

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