Sea-state estimation device, method for estimating sea-state, and program

Abstract

To provide a sea-state estimation device, a method for estimating a sea state, and a program capable of more appropriately performing data assimilation on estimated sea-state data.SOLUTION: A sea-state estimation device 10 includes: a sea-state data calculation unit configured to calculate estimated sea-state data of a predetermined sea area; a correction-amount calculation unit 112 configured to calculate a correction amount Δx of the estimated sea-state data on the basis of the estimated sea-state data x and observation data y of the sea area; a correction-amount adjustment unit 114 configured to adjust the correction amount Δx on the basis of estimated sea-state data after assimilation of data acquired in a previous process and observation data in a previous process; and a post-assimilation data acquisition unit 113 configured to acquire estimated sea-state data after assimilation of data in the current process, on the basis of the estimated sea-state data x calculated by the sea-state data calculation unit and the adjusted correction amount Δx'.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present invention relates to a sea state estimation device and a sea state estimation method for estimating sea states in a specified sea area, and a program for causing a computer to execute a function for estimating sea states in a specified sea area. [Background technology]

[0002] Conventionally, oceanographic condition estimation systems that estimate oceanographic conditions in a specified ocean area are known. For example, in this type of oceanographic condition estimation system, oceanographic information such as water temperature, sea surface height, and chlorophyll concentration is acquired from satellite images of the ocean and oceanographic maps, and stored in an oceanographic information database. Then, estimated oceanographic condition data for the specified ocean area is generated from the accumulated oceanographic information through an oceanographic condition estimation simulation. Furthermore, the estimated oceanographic condition data is assimilated based on observation data at the time and location at which the estimated oceanographic condition data was acquired. In this way, the estimated oceanographic condition data is brought closer to the oceanographic conditions at that time.

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

[0004] [Patent Document 1] International Publication No. 2022-230333 Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned data assimilation, for example, a correction amount is calculated by multiplying a preset assimilation gain by the difference between estimated ocean state data and observed data, and the calculated correction amount is added to the estimated ocean state data. However, the appropriate assimilation gain may change as ocean states change. Therefore, if data assimilation is performed using a preset fixed assimilation gain, it may not be possible to perform data assimilation appropriately if the assimilation gain does not correspond to the ocean state. In particular, if excessive corrections are continuously performed due to inappropriate data assimilation, the accuracy of the estimated ocean state data may decrease.

[0006] In view of the above problem, the present invention aims to provide a sea state estimation device, a method and a program that are capable of more appropriately performing data assimilation of estimated sea state data. [Means for solving the problem]

[0007] A first aspect of the present invention relates to a sea condition estimation device. The sea condition estimation device according to this aspect includes a sea condition data calculation unit that calculates estimated sea condition data for a predetermined sea area, a correction amount calculation unit that calculates a correction amount for the estimated sea condition data based on the estimated sea condition data and observation data for the sea area, a correction amount adjustment unit that adjusts the correction amount based on estimated sea condition data after data assimilation acquired in a previous process and the observation data at the time of the previous process, and a post-assimilation data acquisition unit that acquires current estimated sea condition data after data assimilation based on the estimated sea condition data calculated by the sea condition data calculation unit and the adjusted correction amount.

[0008] According to the oceanographic condition estimation device of this aspect, the correction amount used in the current data assimilation is adjusted based on the estimated oceanographic condition data after data assimilation acquired in the previous processing and the observation data during the previous processing, so the estimated oceanographic condition data after data assimilation can be made closer to the actual ocean conditions, thereby enabling more appropriate data assimilation of the estimated oceanographic condition data.

[0009] In the sea state estimation device according to this aspect, the correction amount adjustment unit may be configured to adjust the correction amount based on the amount of error between the estimated sea state data after assimilation of the past data and the past observation data.

[0010] According to this configuration, the correction amount can be adjusted so that the amount of error is suppressed.

[0011] In this configuration, the correction amount adjustment unit can be configured to adjust the correction amount based on the amount of error in the past several processes.

[0012] This configuration allows the amount of correction to be adjusted by comprehensively determining the amount of error in the past several processes, thereby preventing the adjustment of the amount of correction from being disrupted by a large amount of error that occurs accidentally.

[0013] In this configuration, the correction amount adjustment unit can be configured to adjust the correction amount based on an integrated value of the amount of error in the past several processes.

[0014] According to this configuration, the integrated value can be used to comprehensively determine the amount of error in the past several processes, and the correction amount can be smoothly adjusted based on the integrated value.

[0015] Furthermore, the correction amount adjustment unit may be configured to set an adjustment value for adjusting the correction amount based on the amount of error in the past several processes, apply the adjustment value to the correction amount, and obtain the adjusted correction amount.

[0016] According to this configuration, the correction amount can be smoothly adjusted using an adjustment value according to the amount of error in the past several processes.

[0017] In this case, the correction amount adjustment unit may be configured to calculate an adjustment coefficient as the adjustment value, and multiply the correction amount by the adjustment coefficient to obtain the adjusted correction amount.

[0018] According to this configuration, the adjusted correction amount can be obtained by a simple process of multiplying the correction amount by the adjustment coefficient.

[0019] In this configuration, the correction amount adjustment unit can be configured to obtain the degree of abnormality in data assimilation based on the amount of error in the past several processes, and to set the adjustment coefficient in a range where the degree of abnormality is large to be smaller than the adjustment coefficient in a range where the degree of abnormality is small.

[0020] By changing the adjustment coefficient in accordance with the magnitude of the degree of abnormality in this way, the amount of correction after adjustment can be made to efficiently approximate the actual sea conditions.

[0021] In the sea condition estimation device of this embodiment, the post-assimilation data acquisition unit can be configured to add the estimated sea condition data calculated by the sea condition data calculation unit to the adjusted correction amount to obtain the estimated sea condition data after the current data assimilation.

[0022] According to this configuration, the estimated oceanographic data after the current data assimilation can be smoothly obtained through simple processing.

[0023] The sea state estimation device according to this embodiment can be used on a ship.

[0024] With this configuration, estimated sea state data after data assimilation near the ship can be obtained on board the ship.

[0025] A second aspect of the present invention relates to a method for estimating sea conditions performed by a sea condition estimation device, which includes the steps of acquiring estimated sea condition data for a predetermined sea area, calculating a correction amount for the estimated sea condition data based on the estimated sea condition data, observation data for the sea area, and an assimilation gain, adjusting the correction amount based on estimated sea condition data after data assimilation acquired in a previous process and the observation data at the time of the previous process, and acquiring current estimated sea condition data after data assimilation based on the estimated sea condition data acquired in the step of acquiring sea condition data and the adjusted correction amount.

[0026] According to the sea state estimation method of this aspect, the same effects as those of the first aspect can be achieved.

[0027] A fourth aspect of the present invention relates to a program for causing a control unit of a sea state estimation device to execute predetermined functions. The program causes the control unit to execute the following functions: acquire estimated sea state data for a predetermined sea area; calculate a correction amount for the estimated sea state data based on the estimated sea state data, observation data for the sea area, and an assimilation gain; adjust the correction amount based on estimated sea state data after data assimilation acquired in a previous process and the observation data at the time of the previous process; and acquire current estimated sea state data after data assimilation based on the estimated sea state data acquired in the sea state data acquisition function and the adjusted correction amount.

[0028] According to the program of this aspect, the same effects as those of the first aspect can be achieved. [Effects of the Invention]

[0029] As described above, according to the present invention, it is possible to provide a sea state estimation device, a sea state estimation method, and a program that are capable of more appropriately performing data assimilation on estimated sea state data.

[0030] 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]

[0031] [Figure 1] FIG. 1 is a diagram showing the configuration of a sea state estimation system according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the configuration of the sea state estimation 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 an observation database according to the first embodiment. Fig. 4(b) is a diagram showing the data structure of a catch 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 estimation device according to the first embodiment. [Figure 6] FIG. 6 is a diagram schematically showing the relationship between the first estimated sea state data and the second estimated sea state data according to the first embodiment. [Figure 7] FIG. 7 is a diagram showing functional blocks for data assimilation according to a comparative example. [Figure 8] FIG. 8 is a diagram showing functional blocks for data assimilation according to the first embodiment. [Figure 9] 9(a) and 9(b) are graphs showing examples of the amount of error acquired in the past several processes according to the first embodiment. [Figure 10] Fig. 10(a) is a graph showing an example of a method for setting an adjustment coefficient according to embodiment 1. Fig. 10(b) is a graph showing another example of a method for setting an adjustment coefficient according to embodiment 1. [Figure 11] FIG. 11 is a flowchart showing the data assimilation process according to the first embodiment. [Figure 12] FIG. 12 is a block diagram showing the configuration of a sea condition data providing device according to the second embodiment. [Figure 13] FIG. 13 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

[0032] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0033] <Embodiment 1> FIG. 1 is a diagram showing the configuration of a sea state estimation system 1. As shown in FIG.

[0034] 1, the sea condition estimation system 1 includes a sea condition estimation device 10 and a sea condition data providing device 30. The sea condition estimation device 10 is installed on a ship S1, and the sea condition data providing device 30 is installed on land.

[0035] In this embodiment, the sea state estimation device 10 is made up of a personal computer 11 and a wireless communication module 12. A program for estimating sea states (hereinafter referred to as the "sea state estimation program") is installed in the personal computer 11. The wireless communication module 12 is connected to the personal computer 11 via USB.

[0036] 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 state estimation device 10 may be configured by a dedicated device equipped with a wireless communication function.

[0037] The oceanic condition estimation device 10 is connected to a detection unit 20 installed on the ship S1 via a communication cable. The detection unit 20 detects the oceanic conditions around the ship S1 and generates observation data. The observation data 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 oceanic condition estimation device 10 as needed.

[0038] The detection unit 20 does not necessarily have to be specialized for the sea state estimation device 10, but may be a general-purpose unit installed on the ship S1.

[0039] 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. The ocean condition estimation device 10 and the ocean condition data providing device 30 may communicate using other communication methods. For example, satellite communication may be used as the wireless communication.

[0040] An ocean model server 40 that provides estimated ocean condition data is connected to the communication network 50. The ocean model server 40 generates estimated ocean condition data for the entire Earth through estimation 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 estimated ocean condition data is data that indicates estimated ocean conditions (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.

[0041] 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.

[0042] 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 estimated 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 estimated values ​​by assimilating observation data acquired by ships, buoys, Argo floats, etc. In this way, estimated values ​​(estimated ocean condition data) of the sea conditions at each time at each mesh position are obtained.

[0043] In the configuration of Figure 1, the ocean condition data providing device 30 obtains successively updated ocean condition estimation data from the ocean model server 40 and stores it in a database. The ocean condition estimation device 10 sends a request to the ocean condition data providing device 30 to send estimated ocean condition data for a specific sea area specified by the user. The ocean condition data providing device 30 extracts the estimated ocean condition data for the sea area corresponding to the transmission request from the database and sends it to the ocean condition estimation device 10.

[0044] Here, the estimated ocean condition 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 estimated ocean condition data, the ocean condition estimation device 10 generates estimated ocean condition data with a higher spatial resolution (e.g., 1 km) at shorter time intervals (e.g., 2 minutes). Based on the estimated ocean condition data thus generated, the ocean condition estimation device 10 displays a screen showing ocean conditions such as water temperature, current direction, current speed, and salinity concentration.

[0045] Hereinafter, the low-resolution estimated ocean condition data provided by the ocean model server 40 will be referred to as "first estimated ocean condition data," and the high-resolution estimated ocean condition data generated by the ocean condition estimation device 10 will be referred to as "second estimated ocean condition data." As described above, the first estimated ocean condition data is a data group of estimated ocean condition 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 estimated ocean condition data is a data group of estimated ocean condition 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 estimated ocean condition data.

[0046] FIG. 2 is a block diagram showing the configuration of the sea state estimation device 10.

[0047] As shown in FIG. 2, the sea state estimation 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.

[0048] The control unit 101 is equipped with an arithmetic processing circuit such as a CPU (Central Processing Unit), and controls each unit by executing a sea state estimation program 102a stored in the memory unit 102. 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 state estimation program 102a executed by the control unit 101, and is also used as a work area when the control unit 101 performs control.

[0049] In this embodiment, the sea condition estimation program 102a provides the control unit 101 with the functions of a sea condition data acquisition unit 101a, an observation data acquisition unit 101b, a sea condition data calculation unit 101c, and a fishing ground data calculation unit 101d, and a catch database 102b is constructed in the memory unit 102.

[0050] The sea condition data acquisition unit 101a acquires the first estimated sea condition data for a specific sea area specified by the user and other information (weather data, past observation data, etc.) used during the estimation simulation in the sea condition data calculation unit 101c from the sea condition data providing device 30 via wireless communication.

[0051] The observation data acquisition unit 101b acquires observation data around the ship S1 at any time via the detection unit 20, and further acquires observation data 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 estimated sea condition data for the sea area to be processed based on the first estimated sea condition data and other information acquired by the sea condition data acquisition unit 101a and the observation data acquired via the detection unit 20 and wireless communication.

[0052] 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 estimated sea state data calculated by the sea state data calculation unit 101c and the fishing data stored in the fishing database 102b. The fishing 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 data, in association with each other. The fishing data is input by the user via the input unit 104.

[0053] In the configuration of Figure 2, the functions of the sea condition data acquisition unit 101a, observation data 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 estimation program 102a, but if the sea condition estimation device 10 is a dedicated machine, at least some of these functions may be configured by hardware using logic circuits.

[0054] 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.

[0055] 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 .

[0056] 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.

[0057] 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.

[0058] The position detection unit 23 includes a GPS (Global Positioning System) and detects the three-dimensional position of the ship S1 on the earth. The position detection unit 23 also acquires the current time using the GPS function.

[0059] 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 data for ocean conditions, such as salinity concentration.

[0060] FIG. 3 is a block diagram showing the configuration of the sea condition data providing device 30. As shown in FIG.

[0061] The ocean condition data providing device 30 includes a control unit 301 , a storage unit 302 , and a communication processing unit 303 .

[0062] The control unit 301 includes a processing circuit such as a CPU, and controls each unit according to a program stored in the memory unit 302. The memory unit 302 includes storage media such as a ROM, RAM, and hard disk, and stores the program executed by the control unit 301, and is also used as a work area when the program is executed. The communication processing unit 303 communicates with the sea state estimation device 10 and the ocean model server 40 under the control of the control unit 301.

[0063] The memory unit 302 stores an estimated ocean condition database 302a, an observation database 302b, and a weather database 302c. The estimated ocean condition database 302a stores first estimated ocean condition data for the entire Earth, which the ocean condition data providing device 30 acquires from the ocean model server 40 as needed. The observation database 302b stores observation data 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 ocean condition data providing device 30 acquires from the ocean model server 40 as needed.

[0064] FIG. 4(a) is a diagram showing the data structure of the observation database 302b shown in FIG.

[0065] As shown in FIG. 4(a), the observation 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.

[0066] These observation data are detected by detectors attached to observation vessels and installations such as buoys and Argo floats installed at predetermined locations, and are transmitted to the ocean model server 40 as needed.

[0067] The oceanographic data providing device 30 acquires, as needed, observation data acquired by the detection unit 20 of the ship S1 from the oceanographic condition estimation device 10 and stores it in the observation database 302b. That is, the oceanographic condition estimation device 10 transmits, as needed, observation data acquired via the detection unit 20 when calculating the second estimated oceanographic condition data (described later), together with information on the location and water depth, to the oceanographic condition data providing device 30 via wireless communication. The oceanographic condition data providing device 30 stores the observation data received from each ship S1 in the observation database 302b. This allows a larger amount of observation data to be accumulated in the observation database 302b.

[0068] FIG. 4(b) is a diagram showing the data structure of the catch database 102b shown in FIG.

[0069] As shown in FIG. 4(b), the catch database 102b stores the "date and time," "location," and "water depth" of the catch record, the ocean 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 ocean area image displayed on the input screen. The "ocean conditions" stores estimated ocean condition data calculated by the ocean condition data calculation unit 101c in FIG. 2 that corresponds to the "date and time," "location," and "water depth" input by the user.

[0070] When catch data is provided to the oceanographic data providing device 30 from an oceanographic data estimation device 10 installed on another ship S1, the catch database 102b may further store the catch data provided from the other ship S1. In this case, the oceanographic data providing device 30 transmits the catch data received from the oceanographic data estimation device 10 of each ship S1 to the oceanographic data estimation device 10 of the other ship S1 as needed. This increases the amount of catch data stored in each oceanographic data estimation device 10, allowing more catch data to be used for fishing ground estimation, which will be described later.

[0071] In this case, the catch database 102b may include a flag that distinguishes between catch data entered by the user himself / herself and catch data acquired from other vessels. Furthermore, when estimating a fishing ground, the user may be able to select whether to use his / her own catch data or catch data from other vessels (including the case where both are used). This allows for a wider variety of fishing ground estimations.

[0072] FIG. 5 is a flowchart showing the processing performed in the control unit 101 of the sea state estimation device 10 shown in FIG.

[0073] 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 data 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.

[0074] When the sea condition estimation process is started, the control unit 101 acquires first estimated sea condition data for a predetermined sea area designated by the user, as well as weather data and observation data 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 an initial value for the current sea condition (S102 to S107).

[0075] FIG. 6 is a diagram schematically showing the relationship between the first estimated sea state data and the second estimated sea state data.

[0076] In FIG. 6, M1 indicates the smallest unit mesh to which first estimated oceanographic 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. Estimated values ​​such as water temperature, seawater flow (flow speed and direction), and salinity concentration are assigned to each first mesh M1 as first estimated oceanographic state data. In other words, the first estimated oceanographic state data is volume data with a spatial resolution of width P1.

[0077] 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 of the oceanographic data of each second mesh M10 is calculated by an estimation 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 of each second mesh M10 (S102). The initial conditions are estimated values ​​of each second mesh M10 estimated from the estimated oceanographic data of the first mesh M1 to be processed and its adjacent first meshes M1.

[0078] The initial conditions of each second mesh M10 are calculated by linear interpolation of the estimated oceanographic data of the first mesh M1 to be processed 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 of 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 of the second meshes M10 included in each first mesh M1.

[0079] 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 estimated 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.

[0080] Next, the control unit 101 calculates estimated values ​​of sea conditions 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 estimated sea condition data was generated (S104). Here, the estimated values ​​of sea conditions at the approach processing point for the second mesh M10 to be calculated are calculated using a physical equation (estimation 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 estimated values ​​of sea conditions for all second meshes M10 included in the first mesh M1 to be processed.

[0081] Next, the control unit 101 assimilates the calculated estimates for each second mesh M10 with the observation data at the time of the run-up process (S105). In step S105, of the observation data acquired in step S101, observation data 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 data 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 data 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 data.

[0082] The control unit 101 may estimate observation data at the position of the second mesh M10 to be processed from observation data present in the vicinity of the second mesh M10 to be processed, and use the estimated observation data as the observation data for the second mesh M10 to be processed. In this case, the control unit 101 applies estimated values ​​of the observation data to the second mesh M10, for example, so that the observation data at one point transitions to the position of the second mesh M10 in a Gaussian distribution. In this way, by having observation data in every second mesh M10, the processing of step S105 can be performed for all second meshes M10.

[0083] 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 estimated value for each second mesh M10 by estimation simulation based on the estimated values ​​for each second mesh M10 calculated in the previous steps S104 and S105 (S104), and further assimilates the calculated estimated value for each second mesh M10 with the observation data at the time of the run-up processing (S105).

[0084] 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 estimated 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 estimated sea state values ​​for each second mesh M10 at each time point from the present time to the future (S108, S109).

[0085] First, the control unit 101 acquires observation data 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 elapsed 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 data to the ocean condition data providing device 30, and acquires from the ocean condition data providing device 30 the observation data at the actual processing point that is included in the first mesh M1 to be processed.

[0086] Next, the control unit 101 calculates estimated values ​​of sea conditions for each second mesh M10 based on the initial values ​​acquired in step S107 and the observation data acquired in step S108, and acquires the calculation results as second estimated sea condition 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, estimated values ​​for each second mesh M10 are calculated by estimation simulation, and these estimated values ​​are further assimilated with the observation data acquired in step S108. In this way, second estimated sea condition data at the time of the actual processing is acquired.

[0087] After acquiring the second estimated sea state data in this way, the control unit 101 performs processing to display a predetermined screen based on the second estimated sea state data (S110 to S113).

[0088] First, the control unit 101 determines whether or not the user has performed an operation input to display the fishing ground estimation (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 estimated 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 fish catch database 102b, catch data whose fishing position is included in the first mesh M1 to be processed (S111), and calculates fishing ground estimation data based on the read out fish catch data and the second estimated sea state data calculated in step S109 (S112).

[0089] 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 estimated sea condition data calculated in step S109, the sea conditions that match the sea conditions of the catch data read out in step S112, and calculates the second mesh M10 having these sea conditions as fishing ground estimation 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.

[0090] Note that the user may specify a fish species in step S110. In this case, in step S111, catch data corresponding to the specified fish species is read out, and the sea conditions corresponding to this catch data are compared with the sea conditions based on the second estimated sea condition data in step S112.

[0091] If the determination in step S110 is YES, the control unit 101 causes the display unit 103 to display the fishing ground estimation 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 estimation 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 estimation and fishing ground estimation 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 estimation process (S114: YES), the control unit 101 ends the processing of FIG. 5.

[0092] 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 estimated sea state data for a second mesh M10 obtained by subdividing the first mesh M1. Then, the control unit 101 updates the screens (sea state estimation screens and fishing ground estimation screens) to be displayed on the display unit 103 based on the newly calculated second estimated sea state data.

[0093] 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 estimated 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 estimated sea state data can be calculated and updated every predetermined time.

[0094] Incidentally, in the data assimilation in step S105 of Figure 5, for example, a process is performed in which a correction amount is calculated by multiplying a predetermined assimilation gain by the difference between the estimated sea state data and the observed data, and the calculated correction amount is added to the estimated sea state data.

[0095] FIG. 7 is a diagram showing functional blocks for data assimilation according to a comparative example.

[0096] The functional blocks in Figure 7 are included in the oceanographic data calculation unit 101c in Figure 2. Data assimilation using the functional blocks in Figure 7 is performed for each parameter of the second estimated oceanographic data (seawater flow velocity, flow direction, temperature, salinity concentration, etc.). Figure 7 shows the functional blocks when data assimilation is performed using the optimal interpolation method. However, other methods such as the three-dimensional variation method or the four-dimensional variation method may also be used for data assimilation.

[0097] The ocean condition data calculation unit 101c has an assimilation gain setting unit 111, a correction amount calculation unit 112, and a post-assimilation data acquisition unit 113 as data assimilation functions.

[0098] The assimilation gain setting unit 111 sets the observation error variance σ0 2 and model error variance σ b 2 The assimilation gain G is calculated based on the observation error variance σ0 2 is the error variance of the observation data used for assimilation. Model error variance σ b 2 is the error variance of the second estimated sea state data when generating the first estimated sea state data through an estimation simulation using an ocean model, and then generating the second estimated sea state data for each second mesh M10 from the first estimated sea state data. Observation error variance σ0 2 and model error variance σ b 2 is set to a fixed value in advance. The assimilation gain setting unit 111 calculates the assimilation gain G using the following formula.

[0099] G=σ b 2 / (σ0 2 +σ b 2 ) …(1)

[0100] In equation (1), the observation error variance σ0 2 Compared to the model error variance σ b 2 The larger the value, the larger the assimilation gain G.

[0101] The correction amount calculation unit 112 calculates the correction amount Δ for the second estimated sea state data based on the second estimated sea state data x of the second mesh M10 to be processed, the observation data y at the time of processing the second mesh M10, and the assimilation gain G, using the following formula.

[0102] Δx=G(yx) …(2)

[0103] The post-assimilation data acquisition unit 113 acquires post-assimilation second estimated sea state data xa based on the second estimated sea state data x and the correction amount Δx. Specifically, the post-assimilation data acquisition unit 113 adds the acquired correction amount Δx to the second estimated sea state data x to calculate the post-assimilation second estimated sea state data xa. In this way, data assimilation for the second estimated sea state data x to be processed is completed.

[0104] In the process of the comparative example shown in FIG. 7, the preset observation error variance σ0 2 and model error variance σ b 2 A fixed assimilation gain G calculated by the above formula is used for data assimilation. However, the appropriate assimilation gain may change as the sea state changes. For this reason, if data assimilation is performed using a preset fixed assimilation gain G, as in the comparative example, data assimilation may not be performed appropriately if the assimilation gain G does not correspond to the sea state. In particular, if excessive corrections are made continuously due to inappropriate data assimilation, this will result in a decrease in the accuracy of the second estimated sea state data.

[0105] Therefore, in the first embodiment, a process is performed to adjust the correction amount Δx in accordance with changes in sea conditions.

[0106] FIG. 8 is a diagram showing functional blocks for data assimilation according to the first embodiment.

[0107] The functional block of the first embodiment shown in FIG. 8 includes a correction amount adjustment unit 114 in addition to the comparative example shown in FIG.

[0108] The correction amount adjustment unit 114 adjusts the correction amount Δx based on the second estimated sea state data xa after data assimilation acquired in past processing and the observation data y during the past processing. More specifically, the correction amount adjustment unit 114 adjusts the correction amount Δx based on the amount of error between the second estimated sea state data xa after data assimilation acquired in past processing and the observation data y during the past processing. The amount of error is calculated by subtracting the second estimated sea state data after data assimilation from the observation data.

[0109] For example, the correction amount adjustment unit 114 adjusts the correction amount Δx based on the amount of error in the past few processes. For example, the correction amount adjustment unit 114 uses the integrated value of the amount of error in the past few processes to adjust the correction amount Δx. The correction amount adjustment unit 114 sets an adjustment value for adjusting the correction amount Δx based on the amount of error in the past few processes, and applies this adjustment value to the correction amount Δx to obtain the adjusted correction amount Δx'. For example, the correction amount adjustment unit 114 calculates an adjustment coefficient as the adjustment value, and multiplies the correction amount Δx by the adjustment coefficient to obtain the adjusted correction amount Δx'.

[0110] In the configuration of FIG. 8, the correction amount adjuster 114 includes an abnormality degree calculator 114a, an adjustment coefficient setter 114b, and a multiplier 114c.

[0111] The anomaly degree calculation unit 114a obtains the degree of anomaly in data assimilation based on the amount of error obtained in the past several processes. The adjustment coefficient setting unit 114b sets an adjustment coefficient based on this anomaly degree. The multiplication unit 114c multiplies the correction amount Δx by the adjustment coefficient to calculate the adjusted correction amount Δx'.

[0112] The assimilated data acquisition unit 113 acquires the second estimated sea state data xa after data assimilation based on the second estimated sea state data x and the adjusted correction amount Δx'. Specifically, the assimilated data acquisition unit 113 adds the adjusted correction amount Δx' to the second estimated sea state data x to calculate the second estimated sea state data xa after assimilation.

[0113] 9(a) and 9(b) are graphs showing examples of the amount of error acquired in the past several processes.

[0114] Figures 9(a) and (b) plot the error amounts obtained up to the fifth processing step. The further along the horizontal axis, the closer to the present. The plot on the far right shows the error amount obtained by the previous processing step. The position on the vertical axis where it intersects with the horizontal axis is where the error amount is 0.

[0115] In the example of Figure 9(a), the error amount does not converge to 0 and shows a tendency to gradually increase. In this example, data assimilation is not being performed properly, and the degree of data assimilation anomaly is high. In contrast, in the example of Figure 9(b), the error amount converges to 0. Therefore, in this example, data assimilation is being performed properly, and the degree of data assimilation anomaly is low.

[0116] 8 calculates the degree of abnormality from such a tendency of the amount of error. For example, the abnormality degree calculation unit 114a calculates the value of the degree of abnormality as the value obtained by accumulating the amounts of error for the past n times (n is an integer equal to or greater than 2, for example, n=5).

[0117] However, the method for calculating the degree of abnormality is not limited to this. For example, the abnormality degree calculation unit 114a may calculate, as the value of the degree of abnormality, the number, percentage, or frequency of error amounts that fall within a range outside a predetermined threshold range around 0, among the error amounts for the past n times. The abnormality degree calculation unit 114a may calculate, as the value of the degree of abnormality, the average value of the error amounts for the past n times. Alternatively, an index value indicating the degree of tendency of the error amounts for the past n times to move away from 0 may be calculated from these error amounts, and this index value may be calculated as the value of the degree of abnormality. For example, this index value may be a sum of values ​​obtained by subtracting the error amount for the kth time before (k is an integer greater than or equal to 1) from the error amount for the kth time before (k is an integer greater than or equal to 1), for the error amounts up to the nth time before.

[0118] Furthermore, when calculating the degree of abnormality, a predetermined weight may be assigned to the amount of error for each time. For example, a predetermined weight may be assigned to the amount of error for each time so that the weight is greater the more recent the time.

[0119] FIG. 10(a) is a graph showing an example of a method for setting the adjustment coefficient.

[0120] In the example of FIG. 10(a), the adjustment coefficient for a range where the degree of abnormality is large is set smaller than the adjustment coefficient for a range where the degree of abnormality is small. The maximum value of the adjustment coefficient is 1. When the adjustment coefficient is 1, the correction amount Δx in FIG. 8 is the same as the adjusted correction amount Δx'. In other words, when the adjustment coefficient is 1, it is equivalent to not adjusting the correction amount Δx.

[0121] In the example of Figure 10(a), as the degree of anomaly increases, the adjustment coefficient decreases linearly from 1. Therefore, the greater the degree of anomaly, the greater the decrease in the adjusted correction amount Δx' relative to the correction amount Δx. This prevents excessive data assimilation of the second estimated sea state data when the degree of anomaly is large. Therefore, as shown in Figure 9(a), the gradual increase in the amount of error can be prevented, and data assimilation of the second estimated sea state data can be performed appropriately.

[0122] However, the method for setting the adjustment coefficient is not limited to the example shown in FIG.

[0123] For example, as the degree of abnormality increases, the adjustment coefficient may decrease in a curved or stepped manner from 1. Furthermore, the adjustment coefficient may be calculated in a different manner for each depth or variable.

[0124] Alternatively, as shown in FIG. 9(b), the degree of anomaly may be divided into three ranges W1, W2, and W3. In the range W1, where the degree of anomaly is low, the adjustment coefficient is set to 1. In the range W2, where the degree of anomaly is intermediate, the adjustment coefficient decreases from 1 as the degree of anomaly increases. In the range W3, where the degree of anomaly is high, the adjustment coefficient is fixed at the minimum value of the adjustment coefficient for the intermediate range W2. In this case, too, in the intermediate range W2, the adjustment coefficient may decrease in a curved or stepped manner as the degree of anomaly increases. Furthermore, the number of divisions into the degree of anomaly does not have to be three. For example, the range W2 in FIG. 10(b) may be divided into two ranges W21 and W22, with the slopes of the lines in the ranges W21 and W22 being different. The relationship between the degree of anomaly and the adjustment coefficient may be set so that data assimilation is performed appropriately in response to changes in sea conditions.

[0125] FIG. 11 is a flowchart showing the data assimilation process in step S105 of FIG. is.

[0126] The control unit 101 calculates the difference between the second estimated sea state data x to be processed and the observation data y at the time of the processing (S121), and calculates the correction amount Δx by multiplying the calculated difference by the assimilation gain (S122). Steps S121 and S122 correspond to steps for calculating the correction amount Δx. The processing of steps S121 and S122 is executed by the function of the correction amount calculation unit 112 in FIG. 8.

[0127] The control unit 101 sets an adjustment coefficient based on the second estimated sea state data after past data assimilation and past observation data (S123). As described with reference to Figures 9(a) to (d), the control unit 101 calculates the amount of error between the second estimated sea state data after data assimilation and the observation data for the past several pieces of second estimated sea state data after data assimilation, calculates the degree of anomaly based on the calculated amount of error, and obtains an adjustment coefficient corresponding to the calculated degree of anomaly. The control unit 101 then multiplies the correction amount Δx by the set adjustment coefficient to calculate the adjusted correction amount Δx' (S124).

[0128] Steps S123 and S124 correspond to steps for adjusting the correction amount Δx. The processing of steps S123 and S124 is executed by the function of the correction amount adjustment unit 114 in FIG.

[0129] The control unit 101 adds the adjusted correction amount Δx' to the second estimated sea state data x to be processed to calculate the second estimated sea state data xa after data assimilation (S125). Step S125 corresponds to the step of acquiring the second estimated sea state data after data assimilation. The processing of step S125 is executed by the function of the post-assimilation data acquisition unit 113 in Figure 8.

[0130] The control unit 101 determines whether data assimilation has been completed for all of the second meshes M10 in the target range (S126). If data assimilation processing has not been completed for all of these second meshes M10 (S126: NO), the control unit 101 returns the processing to step S121 and performs data assimilation on the next second mesh M10 to be processed. When data assimilation has been completed for all of the second meshes M10 in the predetermined range (S126: YES), the control unit 101 terminates the data assimilation processing of FIG. 11.

[0131] <Effects of the First Embodiment> According to the above embodiment, the following effects can be achieved.

[0132] As shown in Figures 2 and 8, the sea condition estimation device 10 comprises a sea condition data calculation unit 101c that calculates second estimated sea condition data x for a specified sea area, a correction amount calculation unit 112 that calculates a correction amount Δx for the second estimated sea condition data x based on the second estimated sea condition data x, observation data y for the sea area, and an assimilation gain G, a correction amount adjustment unit 114 that adjusts the correction amount Δx based on the estimated sea condition data after data assimilation acquired in past processing and the observation data during past processing, and a post-assimilation data acquisition unit 113 that acquires second estimated sea condition data xa after this data assimilation based on the second estimated sea condition data x calculated by the sea condition data calculation unit 101c and the adjusted correction amount Δx'.

[0133] According to this configuration, the correction amount Δx used in the current data assimilation is adjusted based on the second estimated sea state data after data assimilation acquired in the previous processing and the observation data during the previous processing, so that the second estimated sea state data xa after the current data assimilation can be made closer to the actual sea state. Therefore, data assimilation of the second estimated sea state data x can be performed more appropriately.

[0134] As described with reference to FIGS. 9(a) to (d), the correction amount adjustment unit 114 adjusts the correction amount Δx based on the amount of error between the second estimated sea state data after past data assimilation and the past observation data.

[0135] According to this configuration, the correction amount Δx can be adjusted so that the amount of error is suppressed.

[0136] In this adjustment, the correction amount adjustment unit 114 adjusts the correction amount Δx based on the amount of error in the past several (n) processing operations, as described above.

[0137] This configuration allows the correction amount Δx to be adjusted by comprehensively determining the amount of error in the past several processes, thereby preventing the adjustment of the correction amount Δx from being disrupted by a large amount of error that occurs accidentally.

[0138] In this configuration, the correction amount adjustment section 114 can adjust the correction amount Δx based on the integrated value of the amount of error in the past several processes, as described above.

[0139] According to this configuration, the amount of error in the past several processes can be comprehensively determined based on the integrated value, and the correction amount Δx can be smoothly adjusted based on the integrated value.

[0140] Furthermore, as described above, the correction amount adjustment unit 114 sets an adjustment value (adjustment coefficient) for adjusting the correction amount based on the amount of error in the past several processes, and applies this adjustment value (adjustment coefficient) to the correction amount Δx to obtain the adjusted correction amount Δx'.

[0141] According to this configuration, the correction amount can be smoothly adjusted using an adjustment value according to the amount of error in the past several processes.

[0142] In this case, as shown in FIGS. 10(a) and 10(b), the correction amount adjuster 114 calculates an adjustment coefficient as an adjustment value, and multiplies the correction amount Δx by the adjustment coefficient to obtain the adjusted correction amount Δx′.

[0143] According to this configuration, the adjusted correction amount Δx′ can be obtained by a simple process of multiplying the correction amount Δx by the adjustment coefficient.

[0144] As shown in Figures 10(a) and (b), the correction amount adjustment unit 114 obtains the degree of anomaly in data assimilation based on the amount of error in the past few processes, and can set the adjustment coefficient for a range with a large degree of anomaly to be smaller than the adjustment coefficient for a range with a small degree of anomaly.

[0145] By changing the adjustment coefficient in accordance with the magnitude of the degree of abnormality in this way, the adjusted correction amount Δx′ can be made to efficiently approximate the actual sea state.

[0146] As shown in Figure 8, the post-assimilation data acquisition unit 113 adds the second estimated sea condition data calculated by the sea condition data calculation unit 101c to the adjusted correction amount Δx' to obtain the second estimated sea condition data xa after this data assimilation.

[0147] According to this configuration, the second estimated sea state data after the current data assimilation can be smoothly acquired through simple processing.

[0148] As shown in FIG. 1, the sea state estimation device 10 is used on a ship S1.

[0149] According to this configuration, observation data in the vicinity of the ship S1 can be acquired, so that the second estimated sea state data after data assimilation can be smoothly acquired.

[0150] <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 state estimation device 10. In contrast, in the second embodiment, the initial value acquisition process is performed by the on-shore sea state data providing device 30, and the acquired initial values ​​are transmitted from the sea state data providing device 30 to the on-board sea state estimation device 10.

[0151] In the second embodiment, the data assimilation process in the initial value acquisition process is performed by the ocean condition data providing device 30. Therefore, in the second embodiment, the ocean condition data providing device 30 corresponds to the ocean condition estimation device recited in the claims.

[0152] FIG. 12 is a block diagram showing the configuration of a sea condition data providing device 30 according to the second embodiment.

[0153] As shown in Fig. 12, in the second embodiment, the function of the initial value calculation unit 301a is assigned to the control unit 301 of the oceanographic 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 oceanographic condition estimation device 10 by processing similar to steps S101 to S107 shown in Fig. 5, and transmits the calculated initial values ​​to the on-board oceanographic condition estimation device 10 via the communication processing unit 303.

[0154] FIG. 13 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.

[0155] In the flowchart of Fig. 13, the processes of steps S201 to S207 are executed by the function of the initial value calculation unit 301a in Fig. 12. For convenience, the following description will be given assuming that the process of Fig. 13 is performed by the control unit 301.

[0156] 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 transmit initial values ​​for a predetermined sea area from the onboard sea state estimation device 10 (hereinafter referred to as the "requesting sea state estimation device 10"), in step S201, it extracts the first estimated sea state data, observation data, and estimated weather data for the first mesh M1 included in the sea area from the estimated sea state database 302a, observation database 302b, and weather database 302c, respectively. Next, in step S202, the control unit 301 calculates the initial conditions for the second mesh M10 included in the sea area from these data, and further executes the run-up calculation processing in steps S203 to S206. The data assimilation processing in step S205 is the same as in Fig. 11.

[0157] 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 estimation device 10 (S207). At the same time, the control unit 301 transmits other information (weather data, etc.) necessary for subsequent sea condition estimation in the second mesh M10 to the requesting sea condition estimation device 10.

[0158] 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 estimation device 10. That is, the control unit 101 of the sea state estimation device 10 uses the initial values ​​and other information transmitted in step S207 of Fig. 13 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 estimation simulation.

[0159] At this time, in step S108, as described above, the control unit 101 not only acquires observation data via the detection unit 20 installed on the ship, but also acquires observation data for the sea area by communication as needed from the onshore sea condition data providing device 30. The control unit 101 also transmits the observation data acquired via the detection unit 20 installed on the ship to the onshore sea condition data providing device 30 by communication as needed, for use by the sea condition estimation devices 10 of other ships.

[0160] 13, after transmitting the initial values ​​in step S207, if the control unit 301 of the ocean condition data providing device 30 acquires new observation data from the ocean condition estimation device 10 of another ship or from an observation facility in the sea area (S208: YES), it transmits the acquired observation data to the ocean condition estimation device 10 that made the request by communication as needed (S209). Also, if the control unit 301 receives observation data from the ocean condition estimation device 10 that made the request (S210: YES), it stores the received observation data in the observation database 302b (S211) and makes it available for use by the ocean condition estimation devices 10 of other ships.

[0161] Thereafter, the control unit 301 repeats the processing of steps S208 to S211 until it receives a notification of the end of the estimation processing for the relevant sea area from the requesting sea state estimation device 10 (step S212: NO). Then, when it receives a notification of the end of the estimation processing from the requesting sea state estimation device 10 (S212: YES), the control unit 301 ends the processing of Fig. 13. Furthermore, when the control unit 301 receives a request to send initial values ​​for a new sea area from the requesting sea state estimation device 10 as the ship S1 moves, it returns the processing to step S201 and executes the same processing.

[0162] <Effects of the Second Embodiment> According to the sea state estimation system 1 of the second embodiment, the data assimilation process in the process of acquiring the initial values ​​of the second sea state estimation data is performed in the same manner as in the above-described embodiment 1. Therefore, similar to the above-described embodiment 1, data assimilation of the second estimated sea state data can be performed more appropriately during the process of calculating the initial values.

[0163] Furthermore, in the second embodiment, the calculation of the initial values ​​required for calculating the second estimated sea state data is performed by the land-based sea state data providing device 30, thereby reducing the processing load on the onboard sea state estimation device 10. Therefore, the onboard sea state estimation device 10 can calculate the second estimated sea state data more quickly and efficiently.

[0164] Also in the second embodiment, as described above, the onboard sea condition estimation 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 condition data providing device 30. That is, in step S109 in Fig. 5, the control unit 101 (sea condition data calculation unit 101c) applies the initial values ​​and estimation simulation to the first estimated sea condition data to calculate estimated sea condition data with higher spatial resolution than the first estimated sea condition data, and assimilates the calculated estimated sea condition data with observation data acquired by the detection unit 20 of the ship to calculate second estimated sea condition data.

[0165] In this way, in the second embodiment as well, the estimated sea state data is assimilated with observation data around the ship to calculate the second estimated sea state data, so the second estimated 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.

[0166] <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.

[0167] For example, in the first and second embodiments, an adjustment coefficient is used as an adjustment value for adjusting the correction amount Δx, but the adjustment value is not limited to this. For example, a value added to the correction amount Δx may be used as the adjustment value.

[0168] In this case, the function of an additional value setting unit is included instead of the adjustment coefficient setting unit 114b in Fig. 8, and the function of an adding unit is included in the correction amount adjustment unit 114 instead of the multiplying unit 114c. The additional value setting unit sets the additional value so that the additional value increases in the negative direction from 0 as the degree of abnormality increases. The maximum value of the additional value is adjusted so as not to exceed the value of the correction amount Δx. The adding unit adds the additional value set by the additional value setting unit to the correction amount Δx to calculate the adjusted correction amount Δx'.

[0169] In the first and second embodiments, the correction amount Δx is adjusted based on the amount of error acquired in the past several processes. However, the amount of error used to adjust the correction amount Δx is not limited to this. For example, the correction amount Δx may be adjusted based only on the amount of error acquired in the process immediately preceding the current process. In this case, the amount of error may be used as a value indicating the degree of abnormality.

[0170] However, in this case, if the immediately preceding error amount is a large value that occurs by chance, the adjustment of the correction amount Δx may become somewhat unstable. Therefore, in order to adjust the correction amount Δx more stably, it is preferable to adjust the correction amount Δx based on the error amounts obtained in the past several processes, as described above.

[0171] In the above embodiment, the error amount obtained by subtracting the second estimated sea state data after data assimilation from the observation data is used to adjust the correction amount Δx, but the index value used to adjust the correction amount Δx is not limited to this. For example, other index values, such as the ratio of the second estimated sea state data after data assimilation to the observation data, may be used to adjust the correction amount Δx.

[0172] Furthermore, in the first embodiment, the process of FIG. 11 is used for the data assimilation in step S105 in FIG. 5, but the process of FIG. 11 may also be used for the data assimilation in step S109 in FIG.

[0173] Furthermore, in the second embodiment, the calculation of the initial values ​​is performed by the sea condition data providing device 30, but the calculation of second estimated sea condition data for the second mesh M10 may also be performed by the sea condition data providing device 30. In this case, a control device is arranged on the ship S1 side for receiving and displaying the second estimated sea condition data for a specified sea area from the sea condition data providing device 30. Then, the second estimated sea condition data for the sea area requested by this control device is sequentially transmitted from the sea condition data providing device 30 to the control device.

[0174] However, with this configuration, a huge amount of second estimated sea state data needs to be frequently transmitted from the sea state data providing device 30 to the sea state estimation device 10. Therefore, if there is a limit to the amount of data that can be communicated, it will not be possible to smoothly transmit all of the second estimated sea state data to the control device on the ship S1, making it difficult to smoothly display the sea states at high resolution on the ship S1. Therefore, in order to smoothly display the sea states on the ship S1, it is preferable to install the sea state estimation device 10 on the ship S1, as in the above-mentioned embodiments 1 and 2, and have this sea state estimation device 10 calculate the second estimated sea state data.

[0175] In addition, in the above embodiment 1, the sea condition estimation device 10 obtained the first estimated sea condition data and other information from the sea condition data providing device 30, but the sea condition estimation device 10 may also obtain the first estimated sea condition data and other information directly from the ocean model server 40 without going through the sea condition data providing device 30.

[0176] 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 estimated sea state data is updated is not limited to the time interval exemplified above (for example, 2 minutes), and may be another time interval.

[0177] 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 estimated sea state data is updated may also be changeable.

[0178] Furthermore, in the above embodiments 1 and 2, observation data was acquired using a general-purpose detection unit 20 installed on the ship S1, but the detection unit 20 for acquiring observation data is not limited to a general-purpose one, and may also be a dedicated detection unit specialized for use with the sea condition estimation device 10.

[0179] In addition, in the above embodiment, the fishing ground estimation process is performed, but the fishing ground estimation process may be omitted and only the sea state estimation process may be performed. Furthermore, the communication method between the sea state estimation device 10 and the sea state data providing device 30 is not limited to LET, and other communication methods may be used.

[0180] Furthermore, when the ocean condition estimation device 10 is configured as a dedicated product, the display unit 103 need not be mounted on the ocean condition estimation device 10, and a general-purpose monitor may be used as the display unit 103. That is, the ocean condition estimation device 10 may be provided with an interface for outputting display information, and this interface may be connected to a general-purpose monitor, and a screen based on estimated ocean condition data may be displayed on the monitor. Similarly, when the ocean condition estimation device 10 is configured as a dedicated product, the input unit 104 need not be mounted on the ocean condition estimation device 10, and a general-purpose mouse or the like may be attached separately to the ocean condition estimation device 10 and used as the input unit 104.

[0181] 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]

[0182] 1 Ocean condition estimation system 10 Sea state estimation device 30 Oceanographic data providing device 101 Control section 101c Oceanographic Data Calculation Section 112 Correction amount calculation section 113 Post-assimilation data acquisition section 114 Correction amount adjustment section

Claims

1. a sea condition data calculation unit that calculates estimated sea condition data for a predetermined sea area; a correction amount calculation unit that calculates a correction amount for the estimated sea state data based on the estimated sea state data and observation data for the sea area; a correction amount adjustment unit that adjusts the correction amount based on estimated sea state data after data assimilation acquired in past processing and observation data during the past processing; and a post-assimilation data acquisition unit that acquires the estimated sea state data after the current data assimilation based on the estimated sea state data calculated by the sea state data calculation unit and the adjusted correction amount. A sea state estimation device characterized by:

2. The sea state estimation device according to claim 1, the correction amount adjustment unit adjusts the correction amount based on an error amount of the estimated sea state data after the past data assimilation with respect to the past observation data. A sea state estimation device characterized by:

3. The sea state estimation device according to claim 2, the correction amount adjustment unit adjusts the correction amount based on the amount of error in the past several processes. A sea state estimation device characterized by:

4. The sea state estimation device according to claim 3, the correction amount adjustment unit adjusts the correction amount based on an integrated value of the amount of error in the past several processes. A sea state estimation device characterized by:

5. The sea state estimation device according to claim 3, the correction amount adjustment unit sets an adjustment value for adjusting the correction amount based on the amount of error in the past several processes, and applies the adjustment value to the correction amount to obtain the adjusted correction amount. A sea state estimation device characterized by:

6. The sea state estimation device according to claim 5, the correction amount adjustment unit sets an adjustment coefficient as the adjustment value, and multiplies the correction amount by the adjustment coefficient to obtain the adjusted correction amount. A sea state estimation device characterized by:

7. The sea state estimation device according to claim 6, the correction amount adjustment unit acquires an anomaly degree of data assimilation based on the error amount in the past several processes, and sets the adjustment coefficient in a range where the anomaly degree is large to be smaller than the adjustment coefficient in a range where the anomaly degree is small. A sea state estimation device characterized by:

8. The sea state estimation device according to claim 1, the post-assimilation data acquisition unit adds the estimated sea state data calculated by the sea state data calculation unit to the adjusted correction amount to acquire the estimated sea state data after the current data assimilation. A sea state estimation device characterized by:

9. The sea state estimation device according to claim 1, The sea state estimation device is used on a ship, A sea state estimation device characterized by:

10. A sea state estimation method performed by a sea state estimation device, A step of acquiring estimated sea state data for a predetermined sea area; calculating a correction amount for the estimated sea state data based on the estimated sea state data and observation data for the sea area; adjusting the correction amount based on estimated oceanographic data after data assimilation acquired in past processing and observation data during the past processing; and acquiring estimated sea state data after the current data assimilation based on the estimated sea state data acquired in the step of acquiring sea state data and the adjusted correction amount. A method for estimating sea conditions.

11. The control unit of the sea condition estimation device A function to obtain estimated ocean condition data for a specified sea area; a function of calculating a correction amount for the estimated sea state data based on the estimated sea state data and observation data for the sea area; a function of adjusting the correction amount based on estimated oceanographic data after data assimilation acquired in past processing and observation data during the past processing; A program that executes a function to acquire estimated sea state data after the current data assimilation based on the estimated sea state data acquired by the function to acquire sea state data and the correction amount after adjustment.

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