Ocean condition prediction device, ocean condition prediction system, ocean condition prediction method and program

Abstract

Provided are a sea condition prediction device, a sea condition prediction system and a program with which it is possible to more effectively and more accurately display sea conditions in a high resolution on board a ship.　This sea condition prediction device (10) comprises: a sea condition data acquisition unit (101a) which acquires first predicted sea condition data for a predetermined area; an observation information acquisition unit (101b) which acquires seawater observation information from a detection unit (20) installed on a ship; and a sea condition data calculation unit (101c) which, on the basis of the first predicted sea condition data and the observation information, calculates second predicted sea condition data having a higher spatial resolution than the first predicted sea condition data.

Description

[Technical Field]

[0001] The present invention relates to a sea condition prediction device, a sea condition prediction system, and a sea condition prediction method for predicting sea conditions in a specified sea area, as well as a program for causing a computer to execute a process for predicting sea conditions in a specified sea area. [Background technology]

[0002] Conventionally, ocean condition prediction systems that predict ocean conditions in a specified sea area are known. For example, in this type of ocean condition prediction system, ocean information such as water temperature, sea surface height, and chlorophyll concentration is acquired from satellite images of the ocean and ocean distribution maps, and stored in an ocean information database. Then, predicted ocean condition data is generated from the stored ocean information through an ocean condition prediction simulation.

[0003] The following Patent Document 1 describes a sea state prediction system having the above configuration. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4849797 Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned sea condition prediction system, when displaying sea conditions on board at high resolution (fine distance intervals, i.e., high spatial resolution), a huge amount of predicted sea condition data needs to be transmitted from a database on land to the control device on board. Therefore, if there is a limit to the amount of data that can be transmitted, it is not possible to smoothly transmit all of the predicted sea condition data to the control device on board, making it difficult to display sea conditions on board at high resolution.

[0006] In view of these problems, the present invention aims to provide a sea condition prediction device, a sea condition prediction system, a sea condition prediction method, and a program that can display sea conditions more efficiently, accurately, and in high resolution on board a ship. [Means for solving the problem]

[0007] The first aspect of the present invention is a shipboard installed The sea condition prediction device according to this aspect comprises: Calculated by a sea condition data provider installed on land The device comprises a sea condition data acquisition unit that acquires first predicted sea condition data for a specified sea area, an observation information acquisition unit that acquires seawater observation information from a detection unit installed on the ship, and a sea condition data calculation unit that calculates second predicted sea condition data having higher spatial resolution than the first predicted sea condition data based on the first predicted sea condition data and the observation information.

[0008] According to the sea condition prediction device of this aspect, second predicted sea state data with higher spatial resolution is calculated by the onboard sea condition prediction device based on the first predicted sea state data and observation information. Therefore, the sea state prediction device can display the sea state around the ship at high resolution by displaying an image based on the second predicted sea state data on a monitor. Furthermore, because the calculation of the second predicted sea state data is performed by the onboard sea state prediction device, the first predicted sea state data provided to the sea state prediction device can be data with low spatial resolution. Therefore, there is no need to provide a large amount of predicted sea state data to the onboard sea state prediction device, and high-resolution sea state images can be displayed on board more efficiently. Furthermore, because the observation information is acquired from a detection unit installed on the ship, observation information tailored to the conditions around the ship can be acquired in real time. Therefore, the second predicted sea state data can be made closer to the sea state around the ship, allowing the sea state around the ship to be displayed more accurately.

[0009] In this way, the sea condition prediction device according to this embodiment can display sea conditions on board a ship more efficiently, accurately, and with high resolution.

[0010] Note that observation information acquired by means other than the detector installed on the ship may also be used in calculating the second predicted sea state data. This allows the second predicted sea state data to be calculated using more observation information, such as position and type observation information that cannot be acquired by the detector on the ship. This further improves the accuracy of the second predicted sea state data for the entire target sea area.

[0011] In the sea condition prediction device of this embodiment, the sea condition data calculation unit may be configured to apply predictive simulation to the first predicted sea condition data to calculate predicted sea condition data with higher spatial resolution than the first predicted sea condition data, and to assimilate the predicted sea condition data with the observation information to calculate the second predicted sea condition data.

[0012] With this configuration, observation information about the surroundings of the ship is used in data assimilation, so the second predicted sea state data can be made closer to the sea state around the ship, thereby enabling more accurate calculation of the sea state around the ship.

[0013] In the ocean condition prediction device according to this aspect, the observation information may include the water temperature and current speed of the surface layer.

[0014] This allows at least the water temperature and current speed (sea conditions) around the ship to be calculated with high accuracy.

[0015] In the sea condition prediction device according to this aspect, the sea condition data acquisition unit may be configured to acquire the first predicted sea condition data by wireless communication.

[0016] This configuration allows the first predicted sea state data to be easily transmitted from the land-based sea state data providing device to the onboard sea state prediction device. Also, as described above, the amount of first predicted sea state data can be reduced, so the first predicted sea state data can be transmitted to the onboard sea state prediction device smoothly and reliably.

[0017] The sea condition prediction device of this embodiment may be configured to further include a fishing information database that stores fishing information that corresponds to fishing records and sea conditions, and a fishing ground data calculation unit that calculates fishing ground prediction data based on the fishing information and the second predicted sea condition data.

[0018] According to this configuration, fishing grounds suitable for the current sea conditions can be displayed based on the fishing ground prediction data, thereby enabling the user to fish more efficiently in the sea area.

[0019] A second aspect of the present invention relates to a sea state prediction system. installed The system includes a sea condition prediction device and a sea condition data providing device installed on land. Here, the sea condition data providing device includes a predicted sea condition database that stores first predicted sea condition data, and an initial value calculation unit that calculates initial values ​​to be used in a prediction simulation. The sea condition prediction device also includes a sea condition data acquisition unit that acquires the first predicted sea condition data for a specified sea area calculated by the sea condition data providing device and the initial values, an observation information acquisition unit that acquires seawater observation information from a detection unit installed on the ship, and a sea condition data calculation unit that calculates second predicted sea condition data with higher spatial resolution than the first predicted sea condition data, based on the first predicted sea condition data, the initial values, and the observation information, through the predictive simulation.

[0020] According to the sea state prediction system of this aspect, as in the first aspect, the calculation of the second sea state prediction data is performed by the on-board sea state prediction device, so sea conditions can be displayed on board more efficiently and accurately, and with high resolution. Furthermore, the calculation of the initial values ​​required for calculating the second predicted sea state data is performed by the on-shore sea state data providing device, so the processing load on the on-board sea state prediction device can be reduced. Therefore, the calculation of the second predicted sea state data in the on-board sea state prediction device can be performed more quickly and efficiently.

[0021] In the sea condition prediction system of this embodiment, the sea condition data calculation unit may be configured to apply the initial values ​​and the prediction simulation to the first predicted sea condition data to calculate predicted sea condition data having a higher spatial resolution than the first predicted sea condition data, and to assimilate the predicted sea condition data with the observation information to calculate the second predicted sea condition data.

[0022] With this configuration, the predicted sea state data is assimilated with observation information about the ship's surroundings to calculate the second predicted sea state data, which allows the second predicted sea state data to be closer to the sea state around the ship, thereby allowing the sea state around the ship to be displayed with greater accuracy.

[0023] A third aspect of the present invention is a shipboard was installed in The present invention relates to a method for predicting sea conditions, which is carried out by a sea condition prediction device, comprising the steps of: Calculated by a sea condition data provider installed on land First predicted sea condition data for a specified sea area is obtained, seawater observation information is obtained from a detection unit installed on the ship, and second predicted sea condition data having higher spatial resolution than the first predicted sea condition data is calculated based on the first predicted sea condition data and the observation information.

[0024] According to the sea state prediction method of this aspect, the same effects as those of the first aspect can be achieved.

[0025] A fourth aspect of the present invention relates to a program. was installed in The control unit of the device Calculated by a sea condition data provider installed on land The ship executes the following functions: acquiring first predicted sea condition data for a specified sea area; acquiring seawater observation information from a detection unit installed on the ship; and calculating second predicted sea condition data having higher spatial resolution than the first predicted sea condition data based on the first predicted sea condition data and the observation information.

[0026] According to the program of this aspect, the same effects as those of the first aspect can be achieved. [Effects of the Invention]

[0027] As described above, according to the present invention, it is possible to provide a sea condition prediction device, a sea condition prediction system, a sea condition prediction method and a program that can display sea conditions more efficiently, accurately and in high resolution on board a ship.

[0028] The effects and significance of the present invention will become more apparent from the following description of the embodiments, however, the embodiments shown below are merely examples of how the present invention can be implemented, and the present invention is not limited to the embodiments described below. [Brief explanation of the drawings]

[0029] [Figure 1] FIG. 1 is a diagram showing the configuration of a sea condition prediction system according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the configuration of the sea condition prediction device according to the first embodiment. [Figure 3] FIG. 3 is a block diagram showing the configuration of the ocean condition data providing device according to the first embodiment. [Figure 4] Fig. 4(a) is a diagram showing the data structure of the observation information database according to the first embodiment. Fig. 4(b) is a diagram showing the data structure of the fish catch information database according to the first embodiment. [Figure 5] FIG. 5 is a flowchart showing the processing performed in the control unit of the sea condition prediction device according to the first embodiment. [Figure 6] FIG. 6 is a diagram schematically showing the relationship between the first predicted sea state data and the second predicted sea state data according to the first embodiment. [Figure 7] Fig. 7(a) is a diagram showing an example of the configuration of a prediction screen when displaying horizontal flow velocities according to embodiment 1. Fig. 7(b) is a diagram showing an example of the configuration of a prediction screen when displaying vertical flow velocities according to embodiment 1. [Figure 8] Fig. 8(a) is a diagram showing an example of the configuration of a prediction screen when displaying water temperature according to embodiment 1. Fig. 8(b) is a diagram showing an example of the configuration of a prediction screen when displaying salinity concentration according to embodiment 1. [Figure 9]Fig. 9(a) is a diagram showing a configuration example of a prediction screen when displaying sea surface altitude according to embodiment 1. Fig. 9(b) is a diagram showing a configuration example of a prediction screen when displaying a fishing ground prediction result according to embodiment 1. [Figure 10] FIG. 10 is a block diagram showing the configuration of a sea condition data providing device according to the second embodiment. [Figure 11] FIG. 11 is a flowchart showing the processing performed in the control unit of the sea condition data providing device according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0030] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0031] <Embodiment 1> FIG. 1 is a diagram showing the configuration of a sea condition prediction system 1. As shown in FIG.

[0032] 1, the sea condition prediction system 1 includes a sea condition prediction device 10 and a sea condition data providing device 30. The sea condition prediction device 10 is installed on a ship S1, and the sea condition data providing device 30 is installed on land.

[0033] In this embodiment, the sea condition prediction device 10 is made up of a personal computer 11 and a wireless communication module 12. A program for predicting sea conditions (hereinafter referred to as the "sea condition prediction program") is installed in the personal computer 11. The wireless communication module 12 is connected to the personal computer 11 via USB.

[0034] Other terminal devices such as a tablet may be used instead of the personal computer 11. Also, instead of the configuration of Fig. 1, the sea condition prediction device 10 may be configured by a dedicated device equipped with a wireless communication function.

[0035] The sea state prediction device 10 is connected to a detection unit 20 installed on the ship S1 via a communication cable. The detection unit 20 detects the sea state around the ship S1 and generates observation information. The observation information includes the water temperature of the ocean's surface layer and the flow of seawater around the ship S1 (flow speed, flow direction). In addition, the detection unit 20 detects the three-dimensional position of the ship S1 on Earth. The detection unit 20 transmits this information to the sea state prediction device 10 as needed.

[0036] The detection unit 20 does not necessarily have to be specialized for the sea state prediction device 10, but may be a general-purpose unit installed on the ship S1.

[0037] The ocean condition data providing device 30 is configured, for example, by a server. The ocean condition data providing device 30 is connected to a communication network 50 such as the Internet, and is capable of wireless communication with the wireless communication module 12 via a base station 60. For example, LTE (Long Term Evolution) is used as the wireless communication. Other communication methods may be used to communicate between the ocean condition prediction device 10 and the ocean condition data providing device 30. 30 may communicate with each other. For example, satellite communication may be used as the wireless communication.

[0038] An ocean model server 40 that provides predicted ocean condition data is connected to the communication network 50. The ocean model server 40 generates predicted ocean condition data for the entire Earth through predictive simulations using an ocean general circulation model (hereinafter referred to as the "ocean model"), and creates a database. The ocean model server 40 is managed, for example, by the Japan Meteorological Agency. The ocean condition prediction data is data that indicates predicted ocean condition values ​​(water temperature, current direction, current speed, salinity concentration, sea surface altitude, etc.) at each mesh position when the ocean is divided into a three-dimensional mesh.

[0039] In the ocean, ocean water movements (circulations) occur on various scales due to the replenishment of momentum by winds at the ocean surface and differences in seawater density depending on the location. Furthermore, heat exchange at the ocean surface, evaporation of seawater, precipitation into the ocean, and the inflow of freshwater from rivers cause changes in the temperature and salinity of ocean water. These factors, as well as the movement of seawater due to current direction and velocity, cause complex changes in seawater density. The ocean model described above is used as a means of representing these complexly changing conditions of ocean water temperature, salinity, current direction, and velocity. Ocean models use physical equations to represent changes in water temperature, salinity, current direction, and velocity.

[0040] The ocean model server 40 arranges three-dimensional meshes in the ocean and calculates the movement of seawater between the meshes, as well as the accompanying transfer and diffusion of heat and salt, using the above-mentioned physical equations to obtain predicted values ​​indicating the ocean's water temperature, salinity, current direction, current velocity, etc., and their changes over time, for each mesh position. Furthermore, the ocean model server 40 corrects the calculated predicted values ​​by assimilating data from observation information acquired by ships, buoys, Argo floats, etc. In this way, predicted values ​​of sea conditions (predicted sea condition data) at each mesh position and each time are obtained.

[0041] In the configuration of Figure 1, the sea condition data providing device 30 obtains successively updated sea condition prediction data from the ocean model server 40 and stores it in a database. The sea condition prediction device 10 sends a request to the sea condition data providing device 30 to send predicted sea condition data for a specific sea area specified by the user. The sea condition data providing device 30 extracts predicted sea condition data for the sea area corresponding to the transmission request from the database and sends it to the sea condition prediction device 10.

[0042] Here, the predicted sea state data generated by the ocean model server 40 has a spatial resolution (three-dimensional mesh pitch) of about 10 km and is updated every day. Based on the received predicted sea state data, the sea state prediction device 10 generates predicted sea state data with a higher spatial resolution (for example, 1 km) at shorter time intervals (for example, 2 minutes). Based on the predicted sea state data thus generated, the sea state prediction device 10 displays a screen showing sea conditions such as water temperature, current direction, current speed, and salinity concentration.

[0043] Hereinafter, the low-resolution predicted sea state data provided by the ocean model server 40 will be referred to as "first predicted sea state data," and the high-resolution predicted sea state data generated by the sea state prediction device 10 will be referred to as "second predicted sea state data." As described above, the first predicted sea state data is a data group of predicted sea state values ​​(water temperature, current direction, current speed, salinity concentration, etc.) distributed three-dimensionally at a predetermined spatial resolution (for example, 10 km pitch), and the second predicted sea state data is a data group of predicted sea state values ​​(water temperature, current direction, current speed, salinity concentration, etc.) distributed three-dimensionally at a predetermined spatial resolution (for example, 1 km pitch) higher than that of the first predicted sea state data.

[0044] FIG. 2 is a block diagram showing the configuration of the sea condition prediction device 10.

[0045] 2, the sea condition prediction device 10 includes a control unit 101, a storage unit 102, a display unit 103, an input unit 104, and a communication processing unit 105. The control unit 101 includes a calculation processing circuit such as a CPU (Central Processing Unit), and executes the sea condition prediction stored in the storage unit 102. Each unit is controlled by executing the program 102a. The memory unit 102 is composed of storage media such as a ROM (Read Only Memory), a RAM (Random Access Memory), and a hard disk. The memory unit 102 stores the sea condition prediction program 102a executed by the control unit 101, and is also used as a work area during control by the control unit 101.

[0046] In this embodiment, the sea condition prediction program 102a provides the control unit 101 with the functions of a sea condition data acquisition unit 101a, an observation information acquisition unit 101b, a sea condition data calculation unit 101c, and a fishing ground data calculation unit 101d, and a fishing catch information database 102b is constructed in the memory unit 102.

[0047] The sea condition data acquisition unit 101a acquires the first predicted sea condition data for a specific sea area specified by the user and other information (weather data, past observation information, etc.) used in the prediction simulation by the sea condition data calculation unit 101c from the sea condition data providing device 30 via wireless communication.

[0048] The observation information acquisition unit 101b acquires observation information around the ship S1 at any time via the detection unit 20, and further acquires observation information for the sea area at any time via wireless communication from the sea condition data providing device 30. The sea condition data calculation unit 101c calculates second predicted sea condition data for the sea area to be processed based on the first predicted sea condition data and other information acquired by the sea condition data acquisition unit 101a and the observation information acquired via the detection unit 20 and wireless communication.

[0049] The fishing ground data calculation unit 101d calculates a fishing ground (location range) where fishing is expected in the sea area based on the second predicted sea state data calculated by the sea state data calculation unit 101c and the fishing information stored in the fishing information database 102b. The fishing information database 102b stores the positions and times at which fishing has occurred, the sea state at those positions and times, and the fish species corresponding to the fishing information, in association with each other. The fishing information is input by the user via the input unit 104.

[0050] In the configuration of Figure 2, the functions of the sea condition data acquisition unit 101a, observation information acquisition unit 101b, sea condition data calculation unit 101c and fishing ground data calculation unit 101d are realized as software functions by the sea condition prediction program 102a, but if the sea condition prediction device 10 is a dedicated machine, at least some of these functions may be configured by hardware using logic circuits.

[0051] The display unit 103 is configured with a display such as a liquid crystal display, and displays predetermined information in accordance with control from the control unit 101. The input unit 104 has input means such as a mouse or keyboard, and transmits input results to the control unit 101. The display unit 103 and the input unit 104 may be configured with a touch panel that is capable of display and input. The communication processing unit 105 is a communication interface for performing communication via the wireless communication module 12, and performs communication in accordance with control from the control unit 101.

[0052] The detection unit 20 includes a water temperature detection unit 21, a flow direction and flow speed detection unit 22, and a position detection unit .

[0053] The water temperature detection unit 21 includes a temperature sensor and detects the water temperature near the surface of the ocean. If a net sonde is installed on the ship S1, the water depth and the water temperature at that depth detected by the net sonde may also be detected by the water temperature detection unit 21.

[0054] The current direction and velocity detection unit 22 detects the current (current velocity, current direction) of seawater at a predetermined depth. For example, the current direction and velocity detection unit 22 includes a transmitter that transmits ultrasonic waves into the sea and a receiver that receives the reflected waves of the ultrasonic waves reflected by floating objects in the sea, and detects the current (current velocity, current direction) of seawater at the depth where the reflected waves are generated from frequency fluctuations of the reflected waves based on the Doppler effect and the speed and traveling direction of the ship.

[0055] The position detection unit 23 is equipped with a GPS (Global Positioning System) and detects the position of a ship on the earth. The position detection unit 23 further acquires the current time using the GPS function.

[0056] The detection results of the water temperature detection unit 21, the current direction and speed detection unit 22, and the position detection unit 23 are transmitted as needed to the control unit 101. The detection unit 20 may further detect other parameters that can be used as observation information on sea conditions, such as salinity concentration.

[0057] FIG. 3 is a block diagram showing the configuration of the sea condition data providing device 30. As shown in FIG.

[0058] The ocean condition data providing device 30 includes a control unit 301 , a storage unit 302 , and a communication processing unit 303 .

[0059] The control unit 301 is equipped with a processing circuit such as a CPU, and controls each unit according to the programs stored in the memory unit 302. The memory unit 302 is equipped with storage media such as a ROM, RAM, and hard disk, and stores the programs executed by the control unit 301, and is also used as a work area when the programs are executed. The communication processing unit 303 communicates with the sea condition prediction device 10 and the ocean model server 40 under the control of the control unit 301.

[0060] The memory unit 302 stores a predicted sea state database 302a, an observation information database 302b, and a weather database 302c. The predicted sea state database 302a stores first predicted sea state data for the entire Earth, which the sea state data providing device 30 acquires from the ocean model server 40 as needed. The observation information database 302b stores observation information acquired from ships, buoys, Argo floats, etc. The weather database 302c stores weather data for the entire Earth (temperature, wind at sea, etc.), which the sea state data providing device 30 acquires from the ocean model server 40 as needed.

[0061] FIG. 4(a) is a diagram showing the data structure of the observation information database 302b shown in FIG.

[0062] As shown in FIG. 4(a), the observation information database 302b stores the "date and time," "location," and "water depth" at which an observation value was acquired, as well as the "type" of the observation value, in association with the observation value. The "location" is defined by latitude and longitude. The "type" includes water temperature, current direction, current speed, and salinity concentration. The "observation value" is the value obtained in the observation. If the "type" is current direction and current speed, the "observation value" includes the current direction Dn and current speed Vn.

[0063] This observation information is detected by detectors attached to observation vessels and installations such as buoys and Argo floats installed at predetermined locations, and is transmitted to the ocean model server 40 as needed.

[0064] The ocean condition data providing device 30 acquires, as needed, observation information acquired by the detection unit 20 of the ship S1 from the ocean condition prediction device 10 and stores it in the observation information database 302b. That is, the ocean condition prediction device 10 transmits, as needed, the observation information acquired via the detection unit 20 when calculating the second predicted ocean condition data (described below), together with information on the location and water depth, to the ocean condition data providing device 30 via wireless communication. The ocean condition data providing device 30 stores the observation information received from each ship S1 in the observation information database 302b. This allows a larger amount of observation information to be accumulated in the observation information database 302b.

[0065] FIG. 4(b) is a diagram showing the data structure of the fish catch information database 102b shown in FIG.

[0066] As shown in FIG. 4(b), the fish catch information database 102b stores the "date and time," "location," and "water depth" of the catch record, the sea conditions at the "location" and "water depth," and the "fish species" of the target fish of the catch record, all associated with one another. The "location" is defined by latitude and longitude. The "date and time," "location," "water depth," and "species" are input by the user via a predetermined input screen displayed on the display unit 103. Of these, the "location" may be input by the user specifying a desired location on the sea area image displayed on the input screen. The "sea conditions" stores predicted sea condition data calculated by the sea condition data calculation unit 101c of FIG. 2 that corresponds to the "date and time," "location," and "water depth" input by the user.

[0067] When fishing catch information is provided to the fishing catch information providing device 30 from a sea state prediction device 10 installed on another ship S1, the fishing catch information database 102b may further store the fishing catch information provided from the other ship S1. In this case, the sea state data providing device 30 transmits the fishing catch information received from the sea state prediction device 10 of each ship S1 to the sea state prediction device 10 of the other ship S1 as needed. This increases the amount of fishing catch information stored in each sea state prediction device 10, and more fishing catch information can be used for fishing ground prediction, which will be described later.

[0068] In this case, the fish catch information database 102b may include a flag that distinguishes between fish catch information input by the user himself / herself and fish catch information acquired from other vessels. Furthermore, when predicting a fishing ground, the user may be able to select whether to use his / her own fish catch information or that of other vessels (including the case where both are used). This allows for a wider variety of fishing ground predictions.

[0069] FIG. 5 is a flowchart showing the processing performed in the control unit 101 of the sea condition prediction device 10 shown in FIG.

[0070] In the flowchart of Fig. 5, step S101 is performed by the function of the oceanographic data acquisition unit 101a in Fig. 2, steps S102 to S107 and S109 are performed by the function of the oceanographic data calculation unit 101c in Fig. 2, step S108 is performed by the function of the observation information acquisition unit 101b in Fig. 2, and steps S110 to S112 are performed by the function of the fishing ground data calculation unit 101d in Fig. 2. For convenience, the following description will be given assuming that the control unit 101 performs the processing of Fig. 5 using these functions.

[0071] When the sea condition prediction process starts, the control unit 101 acquires first predicted sea condition data for a predetermined sea area designated by the user, as well as weather data and observation information for that sea area, from the sea condition data providing device 30 via wireless communication (S101).The control unit 101 then uses the acquired information to perform a run-up calculation to acquire the initial value of the current sea condition (S102 to S107).

[0072] FIG. 6 is a diagram schematically showing the relationship between the first predicted sea state data and the second predicted sea state data.

[0073] In Figure 6, M1 indicates the smallest unit mesh to which first predicted ocean state data is assigned. Hereinafter, this M1 will be referred to as the "first mesh M1." The first mesh M1 has a cubic shape with horizontal and vertical widths of P1. The width P1 is, for example, 10 km. Predicted values ​​such as water temperature, seawater flow (flow speed and direction), and salinity concentration are assigned to each first mesh M1 as first predicted ocean state data. In other words, the first predicted ocean state data is volume data with a spatial resolution of width P1.

[0074] In the process of FIG. 5, the first mesh M1 to be processed is subdivided into second meshes M10 with horizontal and vertical widths P2, and the time change in the oceanographic data for each second mesh M10 is calculated by predictive simulation. In the example of FIG. 6, for convenience, one first mesh M1 is set as the processing target. The width P2 of the second mesh M10 is, for example, 1 km. In this process, the control unit 101 first calculates the initial conditions for each second mesh M10 (S102). The initial conditions are estimated values ​​for each second mesh M10 estimated from the predicted oceanographic data for the first mesh M1 to be processed and its adjacent first meshes M1.

[0075] The initial conditions of each second mesh M10 are calculated by linear interpolation of predicted oceanographic data for the target first mesh M1 and its adjacent first meshes M1 to determine the parameter values ​​of the oceanographic data (water temperature, current direction, current speed, salinity concentration, etc.) at each position in the second mesh M10. This process is performed for all first meshes M1, and the parameter values ​​of the oceanographic data are calculated for each position in the second meshes M10 contained in each first mesh M1.

[0076] Next, the control unit 101 sets boundary conditions (S103). The boundary conditions refer to estimated values ​​of sea state at each outer boundary position that contacts a group of second meshes M10 included in the outer surface of the first mesh M1 to be processed. In FIG. 6, the boundary conditions correspond to predicted values ​​of sea state in the area of ​​difference between the cubic area (an area slightly larger than the first mesh M1) indicated by the dashed line and the first mesh M1 to be processed. Estimated values ​​of parameters (water temperature, current direction, current speed, salinity concentration, etc.) of the sea state data of the second mesh M10 included in this area of ​​difference are set as the boundary conditions.

[0077] Next, the control unit 101 calculates predicted sea state values ​​for each second mesh M10 at a point in time (hereinafter referred to as the "approach processing point") when a certain time (for example, two minutes) has elapsed since the point in time when the first predicted sea state data was generated (S104). Here, the predicted sea state values ​​at the approach processing point for the second mesh M10 to be calculated are calculated using a physical equation (prediction simulation) that takes into account the flow of seawater (flow speed, flow direction) and energy exchange between the second mesh M10 to be calculated and the adjacent second mesh M10. The control unit 101 calculates predicted sea state values ​​for all second meshes M10 included in the first mesh M1 to be processed.

[0078] Next, the control unit 101 performs data assimilation of the calculated prediction values ​​for each second mesh M10 with the observation information at the time of the run-up process (S105). In step S105, of the observation information acquired in step S101, observation information whose observation date and time coincide with the time of the run-up process and whose observation position is included in the second mesh M10 to be processed is used. If there is no observation information at the time of the run-up process, the control unit 101 skips the processing of step S105. Furthermore, if there are multiple pieces of observation information at different positions in the first mesh M1 to be processed at the time of the run-up process, the control unit 101 executes the processing of step S105 using all of these multiple pieces of observation information.

[0079] Next, the control unit 101 determines whether the run-up calculation has been completed (S106). That is, the control unit 101 determines whether the run-up processing time point matches the current date and time. If the determination in step S106 is NO, a certain time (for example, 2 minutes) is added to the current run-up processing time point to set a new run-up processing time point, and the process returns to step S104. Then, the control unit 101 calculates the current predicted value for each second mesh M10 by predictive simulation based on the predicted values ​​for each second mesh M10 calculated in the previous steps S104 and S105 (S104), and further assimilates the calculated predicted value for each second mesh M10 with the observation information at the time of the run-up processing (S105).

[0080] In this way, the control unit 101 executes the processes of steps S104 to S105 while gradually moving the run-up processing time closer to the current date and time. When the run-up processing time coincides with the current date and time, the control unit 101 determines that the run-up calculation has ended (S106: YES) and acquires the predicted sea state values ​​for each second mesh M10 calculated for that run-up processing time as initial values ​​for each second mesh M10 (S107). The control unit 101 then uses the acquired initial values ​​to calculate predicted sea state values ​​for each second mesh M10 at each time point from the present time to the future (S108, S109).

[0081] First, the control unit 101 acquires observation information via the detection unit 20 at the end of the run-up calculation, that is, at the point when a certain time (for example, 2 minutes) has passed since the last run-up processing point (hereinafter referred to as the "actual processing point") (S108). Furthermore, in step S108, the control unit 101 transmits a request to send observation information to the ocean condition data providing device 30, and acquires from the ocean condition data providing device 30 the observation information at the actual processing point that is included in the first mesh M1 to be processed.

[0082] Next, the control unit 101 calculates predicted values ​​of sea states for each second mesh M10 based on the initial values ​​acquired in step S107 and the observation information acquired in step S108, and acquires the calculation results as second predicted sea state data (S109). In step S109, the same processing as in steps S104 and S105 is performed. That is, using the initial values ​​for each second mesh M10, predicted values ​​for each second mesh M10 are calculated by predictive simulation, and these predicted values ​​are further assimilated with the observation information acquired in step S108. In this way, second predicted sea state data at the time of the actual processing is acquired.

[0083] After acquiring the second predicted sea state data in this way, the control unit 101 performs processing to display a predetermined screen based on the second predicted sea state data (S110 to S113).

[0084] First, the control unit 101 determines whether or not the user has performed an operation input to display the fishing ground prediction (S110). If the determination in step S110 is NO, the control unit 101 causes the display unit 103 to display sea state information based on the second predicted sea state data calculated in step S109 (S113). On the other hand, if the determination in step S110 is YES, the control unit 101 reads out, from the fishing catch information database 102b, fishing catch information whose fishing position is included in the first mesh M1 to be processed (S111), and calculates fishing ground prediction data based on the read fishing catch information and the second predicted sea state data calculated in step S109 (S112).

[0085] Specifically, in step S112, the control unit 101 identifies, by a predetermined simulation calculation, among the sea conditions of each second mesh M10 based on the second predicted sea condition data calculated in step S109, the sea conditions that match the sea conditions of the fishing information read out in step S112, and calculates the second mesh M10 having these sea conditions as fishing ground prediction data. For example, in this simulation calculation, the control unit 101 calculates the degree of matching for each sea condition parameter (seawater flow speed, flow direction, temperature, salinity concentration, etc.), and identifies the second mesh M10 where the sum of the calculated matching degrees exceeds a predetermined threshold as a fishing ground. In this case, a predetermined weight may be applied to each parameter.

[0086] Note that the user may specify a fish species in step S110. In this case, in step S111, catch information corresponding to the specified fish species is read out, and the sea conditions corresponding to this catch information are compared with the sea conditions based on the second predicted sea condition data in step S112.

[0087] If the determination in step S110 is YES, the control unit 101 causes the display unit 103 to display the fishing ground prediction data calculated in this manner in step S113. Thereafter, the control unit 101 determines whether or not the user has performed an operation to end the sea state and fishing ground prediction process (S114). If such an operation has not been performed (S114: NO), the control unit 101 executes the processing from step S108 onwards again at predetermined time intervals and updates the screen (sea state prediction and fishing ground prediction screen) to be displayed on the display unit 103. Thereafter, if the user has performed an operation to end the sea state and fishing ground prediction process (S114: YES), the control unit 101 ends the processing of FIG. 5.

[0088] If the first mesh M1 to be processed changes as the ship S1 moves forward, the control unit 101 executes the processes from step S102 onwards for the new first mesh M1 to be processed, and calculates second predicted sea state data for a second mesh M10 obtained by subdividing the first mesh M1. The control unit 101 then updates the screens (sea state prediction and fishing ground prediction screens) to be displayed on the display unit 103 based on the newly calculated second predicted sea state data.

[0089] 5 is limited to a small sea area around the ship S1, and the width P2 of the second mesh M10 is also about 1 km, and the number of layers in the second mesh M10 is not significantly large, so it is possible to calculate and update the second predicted sea state data every predetermined time (for example, 2 minutes) even with the processing capacity of the personal computer 11. The number of layers in the second mesh M10 (width P2 of the second mesh M10) may be adjusted in relation to the processing capacity of the personal computer 11 so that the second predicted sea state data can be calculated and updated every predetermined time.

[0090] 7(a), 7(b), 8(a), 8(b), 9(a) and 9(b) are diagrams showing examples of the configuration of the predicted screen 70 displayed in step S113 of FIG. 5.

[0091] As shown in FIG. 7(a), the prediction screen 70 includes a selection item 71, a date item 72, a time item 73, a water depth item 74, a fish species item 75, a button 76, a display area 77, and a scale 78.

[0092] The selection items 71 include a group of buttons 71a for selecting the sea conditions to be displayed and a button 71b for selecting the fishing ground display. The date item 72 and time item 73 are items for setting the date and time to be displayed, and the water depth item 74 is an item for setting the water depth to be displayed. The date item 72, time item 73, and water depth item 74 each have an operator on the right end for displaying the selection items.

[0093] The fish species item 75 is an item for selecting the target fish species when the button 71b for selecting the fishing ground display is operated. The button 76 is a button for returning the screen to the initial screen. The display area 77 is an area for displaying a screen corresponding to the item (sea conditions / fishing grounds) selected in the selection item 71.

[0094] The scale 78 indicates the correspondence between the color of the screen displayed in the display area 77 and the parameter value. For convenience, the display area 77 is displayed in grayscale in Fig. 7(a), but in reality the display area 77 is displayed in color. The scale 78 is used to associate this color with the parameter value (flow velocity, salinity concentration, etc.).

[0095] The user specifies the sea area to be displayed on the initial screen. After that, the user performs a confirmation operation on the initial screen, and a prediction screen 70 for the specified sea area is displayed as shown in Figure 7(a). In this example, the sea area off the coast of Shikoku is specified by the user.

[0096] FIG. 7(a) shows the prediction screen 70 when the topmost "horizontal current speed" button is selected from the button group 71a of the selection items 71. An image showing the horizontal current speed (second predicted sea condition data) calculated for the relevant sea area by the processing of FIG. 5 is displayed in the display area 77. In this image, the closer to white the color, the higher the horizontal current speed. An arrow indicating the current direction is also added to this image.

[0097] The user can use, for example, a mouse to zoom in on a specified position on the display area 77. This causes a higher resolution horizontal current velocity based on the second predicted sea state data to be displayed in the display area 77. The user can change the image in the display area 77 to an image of the desired water depth by operating the water depth item 74 as appropriate. The display area 77 may also display the position of the ship.

[0098] Figure 7(b) shows the prediction screen 70 when the second button from the top, "Vertical current speed," is selected from the group of buttons 71a of the selection item 71. An image showing the vertical current speed (second predicted sea condition data) calculated for the relevant sea area by the processing of Figure 5 is displayed in the display area 77. In this image, the closer to white the image, the higher the vertical current speed. The user can also enlarge this screen using the mouse, and can change the water depth of the displayed object as appropriate by operating the water depth item 74.

[0099] Figure 8(a) shows the forecast screen 70 when the third button from the top, "Water Temperature," is selected from the group of buttons 71a of the selection items 71. An image showing the water temperature (second forecasted sea condition data) calculated for the relevant sea area by the processing of Figure 5 is displayed in the display area 77. In this image, the closer to white the image, the higher the water temperature. The user can also enlarge this screen using the mouse, and can change the water depth of the displayed object as appropriate by operating the water depth item 74.

[0100] Figure 8(b) shows the prediction screen 70 when the fourth button from the top, "Salinity Concentration," is selected from the group of buttons 71a of the selection items 71. An image showing the salinity concentration (second predicted sea condition data) for the relevant sea area calculated by the processing of Figure 5 is displayed in the display area 77. In this image, the closer to white the image, the higher the salinity. The user can also enlarge this screen using the mouse, and can change the water depth of the displayed object as appropriate by operating the water depth item 74.

[0101] FIG. 9(a) shows the prediction screen 70 when the fifth button from the top, "Sea surface altitude," is selected from the group of buttons 71a of the selection items 71. An image showing the sea surface altitude (second predicted sea condition data) calculated for the relevant sea area by the processing of FIG. 5 is displayed in the display area 77. In this image, the closer to white the image, the higher the sea surface altitude. The user can also enlarge this screen using the mouse.

[0102] FIG. 9(b) shows the prediction screen 70 when the button 71b of the selection item 71 is selected and mackerel is selected in the fish species item 75. The display area 77 displays an image showing the fishing grounds (fishing ground prediction data) calculated for the relevant sea area by the processing of FIG. 5. In this image, the more suitable the fishing ground is for catching mackerel, the closer to white the color of the fishing ground is. The user can also enlarge this screen using the mouse. Furthermore, by operating the fish species item 75, fishing grounds suitable for catching other fish species can be displayed.

[0103] <Effects of the First Embodiment> According to the above embodiment, the following effects can be achieved.

[0104] Based on the first predicted sea state data and observation information, the onboard sea state prediction device 10 calculates second predicted sea state data with higher spatial resolution. Therefore, the sea state prediction device 10 can display the sea state around the ship S1 at high resolution by displaying a prediction screen 70 based on the second predicted sea state data on the display unit 103. Furthermore, because the calculation of the second predicted sea state data is performed by the onboard sea state prediction device 10, the first predicted sea state data provided to the sea state prediction device 10 can be data with low spatial resolution. Therefore, there is no need to provide a huge amount of predicted sea state data to the onboard sea state prediction device 10, and high-resolution sea state images can be displayed on board more efficiently. Furthermore, because observation information is acquired from the detection unit 20 installed on the ship S1, observation information tailored to the conditions around the ship S1 can be acquired in real time. Therefore, the second predicted sea state data can be made closer to the sea state around the ship S1, allowing the sea state around the ship S1 to be displayed more accurately. Furthermore, the sea condition prediction device 10 generates and displays predicted sea condition data with higher spatial resolution (e.g., 1 km) at shorter time intervals (e.g., 2 minutes) from the predicted sea condition data (time resolution: 1 day) received from the ocean model server 40, thereby enabling dynamically changing sea conditions to be displayed with high accuracy by increasing the time resolution.

[0105] As shown in Figure 5, the control unit 101 (sea condition data calculation unit 101c) applies predictive simulation to the first predicted sea condition data to calculate predicted sea condition data with higher spatial resolution than the first predicted sea condition data (S104, S109), and then assimilates the calculated predicted sea condition data with observation information about the surroundings of the ship S1 detected by the detection unit 20 to calculate second predicted sea condition data (S105, S109). In this way, because observation information about the surroundings of the ship is used in the data assimilation, the second predicted sea condition data can be made to approximate the sea conditions around the ship. Therefore, the sea conditions around the ship can be displayed on the display unit 103 with greater accuracy.

[0106] 2, the observation information acquired by the detection unit 20 may include the water temperature and current speed of the surface layer. This allows the display unit 103 to accurately display at least the predicted results of the water temperature and current speed (sea conditions) around the ship.

[0107] As shown in Figure 2, the control unit 101 (sea condition data acquisition unit 101a) acquires first predicted sea condition data from the sea condition data providing device 30 via wireless communication (communication processing unit 105, wireless communication module 12). This allows the first predicted sea condition data to be easily transmitted from the land-based sea condition data providing device 30 to the onboard sea condition prediction device 10. Furthermore, as described above, the amount of first predicted sea condition data can be reduced, so the first predicted sea condition data can be transmitted smoothly and reliably to the onboard sea condition prediction device 10.

[0108] As shown in Fig. 2, the sea condition prediction device 10 further includes a fishing information database 102b that stores fishing information that associates fishing records with sea conditions, and a control unit 101 (fishing ground data calculation unit 101d) that calculates fishing ground prediction data based on the fishing ground information and second predicted sea condition data. This allows fishing grounds suitable for the current sea conditions to be displayed on the prediction screen 70 (see Fig. 9(b)) based on the fishing ground prediction data. This allows the user to fish more efficiently in the sea area.

[0109] <Embodiment 2> In the above-described first embodiment, the initial value acquisition process in steps S101 to S107 in Fig. 5 was performed by the on-board sea condition prediction device 10. In contrast, in the second embodiment, the initial value acquisition process is performed by the on-shore sea condition data providing device 30, and the acquired initial values ​​are transmitted from the sea condition data providing device 30 to the on-board sea condition prediction device 10.

[0110] FIG. 10 is a block diagram showing the configuration of a sea condition data providing device 30 according to the second embodiment.

[0111] As shown in Fig. 10, in the second embodiment, the function of the initial value calculation unit 301a is assigned to the control unit 301 of the sea condition data providing device 30. The control unit 301 executes the function of the initial value calculation unit 301a by a control program stored in the storage unit 302. The initial value calculation unit 301a calculates initial values ​​for the second mesh M10 in the sea area requested by the on-board sea condition prediction device 10 by processing similar to steps S101 to S107 shown in Fig. 5, and transmits the calculated initial values ​​to the on-board sea condition prediction device 10 via the communication processing unit 303.

[0112] FIG. 11 is a flowchart showing the processing performed by the control unit 301 of the sea condition data providing device 30 according to the second embodiment.

[0113] In the flowchart of Fig. 11, the processes of steps S201 to S207 are executed by the function of the initial value calculation unit 301a in Fig. 10. For convenience, the following description will be given assuming that the process of Fig. 11 is performed by the control unit 301.

[0114] As described above, the processing in steps S201 to S207 is the same as steps S101 to S107 in Fig. 5. When the control unit 301 receives a request to send initial values ​​for a predetermined sea area from the onboard sea state prediction device 10 (hereinafter referred to as the "requesting sea state prediction device 10"), in step S201, it extracts first predicted sea state data, observation information, and weather forecast data for a first mesh M1 included in the sea area from the predicted sea state database 302a, observation information database 302b, and weather database 302c, respectively. Next, in step S202, the control unit 301 calculates initial conditions for a second mesh M10 included in the sea area from these data, and then performs the run-up calculation processing in steps S203 to S206.

[0115] Thereafter, when the approach calculation process is completed and the calculation of the initial values ​​for each second mesh M10 is completed (S206: YES), the control unit 301 transmits the calculated initial values ​​for each second mesh M10 together with the position information of each second mesh M10 to the requesting sea condition prediction device 10 (S207). At the same time, the control unit 301 transmits other information (weather data, etc.) necessary for the subsequent sea condition prediction in the second mesh M10 to the requesting sea condition prediction device 10.

[0116] Here, in the second embodiment, steps S101 to S107 are omitted from the flowchart of Fig. 5 and are instead performed by the control unit 101 of the requesting sea state prediction device 10. That is, the control unit 101 of the sea state prediction device 10 uses the initial values ​​and other information transmitted in step S207 of Fig. 11 to perform the processes from step S108 onwards in Fig. 5, and then calculates and displays the sea states of each second mesh M10 that change every predetermined time (for example, every two minutes) by predictive simulation.

[0117] At this time, in step S108, as described above, the control unit 101 not only acquires the observation information via the detection unit 20 installed on the ship, but also acquires, by communication as needed, observation information for the sea area from the onshore sea condition data providing device 30. The control unit 101 also transmits, by communication as needed, the observation information acquired via the detection unit 20 installed on the ship to the onshore sea condition data providing device 30, for use by the sea condition prediction devices 10 of other ships.

[0118] 11, after transmitting the initial values ​​in step S207, if the control unit 301 of the sea condition data providing device 30 acquires new observation information from the sea condition prediction device 10 of another ship or an observation facility in the sea area (S208: YES), it transmits the acquired observation information to the requesting sea condition prediction device 10 by communication as needed (S209). Also, if the control unit 301 receives observation information from the requesting sea condition prediction device 10 (S210: YES), it stores the received observation information in the observation information database 302b (S211) and makes it available for use by the sea condition prediction devices 10 of other ships.

[0119] Thereafter, the control unit 301 repeats the processing of steps S208 to S211 until it receives a notification of the end of the prediction processing for the relevant sea area from the requesting sea state prediction device 10 (step S212: NO). Then, when it receives a notification of the end of the prediction processing from the requesting sea state prediction device 10 (S212: YES), the control unit 301 ends the processing of Fig. 11. Furthermore, when the control unit 301 receives a request to send initial values ​​for a new sea area from the requesting sea state prediction device 10 as the ship S1 moves, it returns the processing to step S201 and executes the same processing.

[0120] <Effects of the Second Embodiment> According to the sea state prediction system 1 of the second embodiment, as in the first embodiment, the calculation of the second sea state prediction data is performed by the on-board sea state prediction device 10, so that sea conditions can be displayed on-board more efficiently, accurately, and with high resolution. Furthermore, the calculation of the initial values ​​required for calculating the second predicted sea state data is performed by the on-shore sea state data providing device 30, so that the processing load on the on-board sea state prediction device 10 can be reduced. Therefore, the calculation of the second predicted sea state data in the on-board sea state prediction device 10 can be performed more quickly and efficiently.

[0121] Also in the second embodiment, as described above, the onboard sea state prediction device 10 executes the processes of steps S108 to S114 in Fig. 5 based on the initial values ​​and other information received from the sea state data providing device 30. That is, in step S109 in Fig. 5, the control unit 101 (sea state data calculation unit 101c) applies the initial values ​​and prediction simulation to the first predicted sea state data to calculate predicted sea state data with higher spatial resolution than the first predicted sea state data, and assimilates the calculated predicted sea state data with observation information acquired by the detection unit 20 of the ship to calculate second predicted sea state data.

[0122] In this way, in the second embodiment as well, the predicted sea state data is assimilated with observation information around the ship to calculate the second predicted sea state data, so the second predicted sea state data can be made closer to the sea state around the ship, and therefore the sea state around the ship can be displayed with greater accuracy.

[0123] <Example of change> The present invention is not limited to the above-described embodiment, and various modifications to the embodiment of the present invention are possible in addition to the above-described configuration.

[0124] For example, in the above embodiment 1, the sea condition prediction device 10 obtained the first predicted sea condition data and other information from the sea condition data providing device 30, but the sea condition prediction device 10 may also obtain the first predicted sea condition data and other information directly from the ocean model server 40 without going through the sea condition data providing device 30.

[0125] Furthermore, if the vessel S1 is located in a distant ocean location where communication from the onshore ocean condition data providing device 30 is not possible, the recovery vessel that recovers the vessel S1's catch may provide the first predicted ocean condition data and other information. For example, while the recovery vessel is within a distance where communication with the ocean condition data providing device 30 is possible, the onshore ocean condition data providing device 30 may communicate with a device installed on the recovery vessel to transmit and store the first predicted ocean condition data and other information for the vicinity of the distant ocean location. When the recovery vessel approaches the vessel S1 to recover the catch, the recovery vessel may communicate with the ocean condition prediction device 10 on the vessel S1 to provide the first predicted ocean condition data and other information for the vicinity of the distant ocean location. This allows the ocean condition prediction device 10 to display high-resolution ocean conditions through the processing of FIG. 5 even when the recovery vessel is located in a distant ocean location where communication with the ocean condition prediction device 10 is not possible.

[0126] Furthermore, the first predicted sea state data and other information may be provided to the sea condition prediction device 10 by means other than communication. For example, the first predicted sea state data and other information for a specific sea area may be downloaded from the sea condition data providing device 30 to a storage medium such as a USB memory, and the first predicted sea state data and other information for that sea area may be provided to the onboard sea condition prediction device 10 via this storage medium. In this case, the sea condition data acquisition unit 101a in Fig. 2 accesses the storage medium such as a USB memory to acquire the first predicted sea state data and other information.

[0127] Furthermore, the resolution of the second mesh M10 is not limited to the resolution exemplified above (for example, 1 km), and may be another resolution as long as it is higher than the resolution of the first mesh M1. Furthermore, the time interval at which the second predicted sea state data is updated is not limited to the time interval exemplified above (for example, 2 minutes), and may be another time interval.

[0128] The resolution of the second mesh M10 may also be changeable. For example, the resolution of the second mesh M10 may be changed automatically so that the distance pitch of the second mesh M10 increases as the sea area to be processed expands, i.e., as the number of first meshes M1 included in the sea area to be processed increases, or the user may be able to change the resolution of the second mesh M10 at will. Similarly, the time interval at which the second predicted sea state data is updated may also be changeable.

[0129] Furthermore, in the first and second embodiments, the data assimilation process is performed as shown in FIG. 5, but the data assimilation process may be omitted.

[0130] Furthermore, in the above embodiments 1 and 2, observation information was acquired using a general-purpose detection unit 20 installed on the ship S1, but the detection unit 20 for acquiring observation information is not limited to a general-purpose one, and may also be a dedicated detection unit specialized for use with the sea condition prediction device 10.

[0131] Furthermore, the configuration of the prediction screen 70 and the content of the images displayed in the display area 77 are not limited to those shown in Figures 7(a) to 9(b) and can be changed as appropriate. For example, the types of buttons 71a for selecting sea conditions are not limited to the five types shown in Figure 7(a), and some sea condition types may be omitted, or other sea condition types may be selectable. Furthermore, on the prediction screen 70 of Figure 7(a), the predicted sea conditions and predicted fishing grounds can be displayed alternately on a single screen, but a screen for displaying the predicted sea conditions and a screen for displaying the predicted fishing grounds may be separately prepared, and the user may be able to select which screen to display on the initial screen.

[0132] In addition, in the above embodiment, a fishing ground prediction process is performed, but the fishing ground prediction process may be omitted and only the sea state prediction process may be performed. Furthermore, the communication method between the sea state prediction device 10 and the sea state data providing device 30 is not limited to LET, and other communication methods may be used.

[0133] Furthermore, when the sea condition prediction device 10 is configured as a dedicated product, the display unit 103 need not be mounted on the sea condition prediction device 10, and a general-purpose monitor may be used as the display unit 103. That is, the sea condition prediction device 10 may be provided with an interface for outputting display information, and this interface may be connected to a general-purpose monitor, and the prediction screen 70 may be displayed on the monitor. Similarly, when the sea condition prediction device 10 is configured as a dedicated product, the input unit 104 need not be mounted on the sea condition prediction device 10, and a general-purpose mouse or the like may be attached separately to the sea condition prediction device 10 and used as the input unit 104.

[0134] In addition, the embodiments of the present invention can be modified in various ways as appropriate within the scope of the claims. [Explanation of symbols]

[0135] 1. Ocean condition prediction system 10 Ocean condition forecasting device 20 Detector 30 Oceanographic data providing device 101 Control section 101a Oceanographic data acquisition section 101b Observation information acquisition unit 101c Oceanographic Data Calculation Section 101d Fishing Ground Data Calculation Section 102a Ocean Condition Forecast Program 102b Fishing Ground Information Database 301a Initial value calculation unit 302a Predicted Ocean Conditions Database

Claims

1. A sea condition prediction device installed on a ship, a sea condition data acquisition unit that acquires first predicted sea condition data for a predetermined sea area calculated by a sea condition data providing device installed on land; an observation information acquisition unit that acquires seawater observation information from a detection unit installed on the ship; and a sea condition data calculation unit that calculates second predicted sea condition data having a higher spatial resolution than the first predicted sea condition data based on the first predicted sea condition data and the observation information. A sea condition prediction device characterized by:

2. The sea condition prediction device according to claim 1, The sea condition data calculation unit Applying a predictive simulation to the first predicted sea state data to calculate predicted sea state data having a higher spatial resolution than the first predicted sea state data; assimilating the predicted sea state data with the observation information to calculate the second predicted sea state data; A sea condition prediction device characterized by:

3. The sea condition prediction device according to claim 1 or 2, The observation information includes surface water temperature and current speed. A sea condition prediction device characterized by:

4. The sea condition prediction device according to any one of claims 1 to 3, The sea condition data acquisition unit acquires the first predicted sea condition data by wireless communication. A sea condition prediction device characterized by:

5. The sea condition prediction device according to any one of claims 1 to 4, a fishing information database that stores fishing information that associates fishing records with sea conditions; a fishing ground data calculation unit that calculates fishing ground prediction data based on the catch information and the second predicted sea condition data, A sea condition prediction device characterized by:

6. A sea condition forecasting device installed on board the ship, A sea condition data providing device installed on land, The ocean condition data providing device is a predicted sea state database that stores first predicted sea state data; an initial value calculation unit that calculates an initial value used in the predictive simulation, The sea condition prediction device is a sea condition data acquisition unit that acquires the first predicted sea condition data and the initial value for a predetermined sea area calculated by the sea condition data providing device; an observation information acquisition unit that acquires seawater observation information from a detection unit installed on the ship; and a sea state data calculation unit that calculates second predicted sea state data having a higher spatial resolution than the first predicted sea state data by the prediction simulation based on the first predicted sea state data, the initial values, and the observation information. A sea condition forecasting system characterized by:

7. The sea condition prediction system according to claim 6, The sea condition data calculation unit applying the initial value and the prediction simulation to the first predicted sea state data to calculate predicted sea state data having a higher spatial resolution than the first predicted sea state data; assimilating the predicted sea state data with the observation information to calculate the second predicted sea state data; A sea condition forecasting system characterized by:

8. A method for predicting sea conditions performed by a device installed on a ship, comprising: Obtain first predicted sea state data for a predetermined sea area calculated by a sea state data providing device installed on land; Obtaining seawater observation information from a detection unit installed on the ship; calculating second predicted sea state data having a higher spatial resolution than the first predicted sea state data based on the first predicted sea state data and the observation information; A method for predicting sea conditions.

9. The control unit of the device installed on the ship A function of acquiring first predicted sea state data for a predetermined sea area calculated by a sea state data providing device installed on land; a function of acquiring seawater observation information from a detection unit installed on the ship; A program that executes a function of calculating second predicted sea state data having a higher spatial resolution than the first predicted sea state data based on the first predicted sea state data and the observation information.

Images