KR101982470B1 - Marine activity risk forecasting system - Google Patents

Abstract

The present invention relates to a marine activity risk forecasting system which constructs a model for predicting weather of a specific marine area, uses factors affecting marine activities to calculate risk for each marine activity and scheduling maritime activities related to operation of offshore wind farms through a weather forecast and an activity risk forecast, thereby effectively operating and managing the offshore wind farms. In addition, the marine activity risk forecasting system comprises an atmosphere modeling pretreatment unit, an atmosphere modeling unit, an atmosphere modeling posttreatment unit, a marine modeling pretreatment unit, a marine modeling unit, a marine modeling posttreatment unit, a risk calculation unit for each marine activity, and an output unit.

Description

Marine Activity Risk Forecasting System {MARINE ACTIVITY RISK FORECASTING SYSTEM}

The present invention relates to a maritime activity risk forecasting system, and more particularly, to a model for predicting the weather of a specific area in a maritime area, and a risk for each maritime activity is calculated using factors affecting marine activity, The present invention relates to a maritime activity risk forecasting system for scheduling maritime activities related to operation of offshore wind farms through activity risk forecasting, and for efficiently operating and managing offshore wind farms.

In general, offshore wind farms are located on the sea more than 5 km away from the coastline and O & M is performed at sea during the lifetime of the facility.

Various operational management systems (eg, HSE, Logistics, CMS, SCADA, vessel management, etc.) have been developed to overcome these geographical conditions in the operation of offshore wind farms.

However, the above-mentioned operation management system enables to remotely manage trouble prevention and diagnostics, but the majority of the actual physical works must be input by the work force to the site (that is, the offshore wind farm) There are restrictions on the access of ships and manpower to the marshals.

For example, the national average annual maritime workability is about 88.9%, and even if the solar time is taken into consideration, the time available for daily work is further reduced. Therefore, the number of working days is absolutely insufficient compared with the work requirement.

Conventionally, in order to overcome the shortage of workable days, a helicopter was used or a base facility capable of staying at the sea was constructed and easily improved. However, these methods have a problem of not only a high introduction cost but also a high cost of operation. do.

Therefore, it is necessary to overcome these geographical limitations of offshore wind farms and to effectively cope with them for efficient operation over a long period of time (eg 20 years).

In particular, maritime operations (or maritime activities) in offshore wind farms should be planned for maritime operations (or maritime activities) in consideration of movement, atmosphere, loading, unloading and working time.

In the determination of such maritime activities (or maritime activities), the weather condition has a great influence, and since the departure and return are legally determined according to weather conditions, the time of final maritime work is determined. This resulted in uncertainty in the operation of offshore wind farms and the difficulty in planning and proceeding with these uncertainties.

Therefore, by predicting weather conditions of offshore wind farms and determining the kinds of maritime activities (or maritime activities) that can be performed in the weather conditions, they can help the design of human and material resources. A system is needed to improve efficiency.

The background art of the present invention is disclosed in Korean Patent Laid-Open Publication No. 10-2013-0102325 (Published Mar. 17, 2013, Ship Safety Navigation Support System through Wave Prediction).

According to one aspect of the present invention, there is provided a method for predicting a weather in a specific area of a sea, which is created to solve the above problems, To provide a maritime activity risk forecasting system that can schedule maritime activities related to offshore wind farm operation through weather forecasting and activity risk forecasting and enable efficient operation and management of offshore wind farms .

A marine activity risk forecasting system according to one aspect of the present invention includes a pre-processing machine for an atmospheric gas phase model, which receives data for weather modeling from a pre-designated apparatus and processes the data as input data for performing weather modeling; An atmospheric vapor phase modeling unit for predicting the atmospheric vapor phase of an area to be modeled at predetermined intervals with respect to the target time using the input data; An atmospheric vapor phase modeling post-processing unit for generating atmospheric vapor phase output data including information predicting a fog and a lightning stroke in the resultant data by the atmospheric vapor modeling; A pre-processing unit for ocean weather modeling for extracting wind data from the atmospheric modeling result data and generating input data for ocean weather modeling; A marine meteorological modeling unit for predicting a meteorological phenomenon using data generated by the pre-processing unit; A marine meteorological model post-processing unit for extracting marine meteorological forecast information to be provided to a user from the marine meteorological modeling result to generate marine meteorological data; A risk assessment unit for each maritime activity that generates risk data for each maritime activity by calculating the risk according to the pre-designated maritime activity risk assessment standard using the atmospheric and oceanic weather prediction result data; And an output unit for generating and outputting web presentation data converted into a format for displaying web data produced through the weather modeling.

In the present invention, the air-conditioning model pre-processing unit receives data for weather modeling, converts the data into data of a first designated type, refers to setting data for weather modeling, And extracting weather information data by time and location at predetermined intervals; Generating terrain data in a file format according to the domain-specific grid information; And generating data in which the terrain information and the weather information are merged by merging the terrain information suitable for modeling of the region to be predicted and the corresponding weather information data by time and location with reference to the setting data for the weather modeling, .

In the present invention, the setting data for the weather modeling is data in a file format in which the number of domains, the forecast period, the number of grids, the size of grids, and the location information for performing atmospheric weather modeling are set.

In the present invention, the air-conditioner modeling pre-processing unit may receive geographical data of a region to be predicted in order to generate geographical data of a file format according to the domain-specific grid information, Convert to fit the local grid information; And the setting data for the weather modeling is referred to in order to convert the terrain data into the lattice information of the area to be weather modeled.

In the present invention, the air-conditioner modeling pre-processing unit may generate data in which the terrain information and the weather information are merged, and then use the additional observation data for correction of the area to be predicted to merge the generated terrain information and weather information And when the correction is completed, a plurality of file type input data is finally generated as input data for the weather modeling.

In the present invention, the atmospheric vapor phase modeling unit may be configured to use at least one of the atmospheric vapor phase modeling unit, the atmospheric vapor phase modeling unit, the atmospheric vapor phase modeling unit, In order to improve the accuracy of the prediction during the execution of the atmospheric air-conditioning modeling, a setting for setting physical options and vertical layers in addition to the boundary condition and domain of the region to be predicted is additionally performed. Data and additional observation data are referred to.

In the present invention, the atmospheric vapor phase modeling post-processing unit receives atmospheric weather modeling result data, extracts at least one weather element for calculating a mist and a lightning strike, selectively combines the extracted weather elements, To calculate input meteorological elements for the calculation of fog and lightning; The fog prediction is performed by using the input meteorological element for calculating the estimated fog and the lightning stroke to generate the fog prediction information and the lightning prediction is performed using the input meteorological element for calculating the calculated fog and the lightning stroke After generating the lightening prediction information; And outputs atmospheric weather output data (Atmosphere Output Data) as data of the atmospheric weather modeling execution result including the generated fog prediction information and lightning prediction information.

In the present invention, the marine meteorological modeling pre-processing unit generates meteorological input data related to the marine meteorological data by using Atmosphere Output data; A weather data input module for converting the weather data inputted from the weather data input module into data of a file type that can be input as ocean weather modeling data and generating a setting file for performing ocean weather modeling; The configuration file for performing the weather modeling is configuration data of a file type in which the number of domains, the modeling time, the number of grids, and the grid size are set.

In the present invention, the ocean-current weather modeling unit performs ocean weather modeling by receiving the wind direction and wind speed information data and the setting data for ocean weather modeling as data generated by the ocean weather modeling pre-processing unit, And the resultant data of the oceanic weather modeling result is generated, and the data of the oceanic weather modeling includes the wind direction, the wind speed, the wave height, the wave period, the wave direction, and the water depth data.

In the present invention, the post-processing unit for the marine meteorological modeling receives the marine meteorological modeling result data generated through the marine meteorological modeling, extracts the processed marine meteorological prediction information to be provided to the user, And outputting ocean output data (ocean output data) in the form of a file.

In the present invention, the risk-based risk calculation unit may include atmospheric output data (Atmosphere Output Data) including fog lightning prediction information generated at the post-processing unit of the atmospheric vapor phase modeling and oceanic weather output data the ocean output data and the atmospheric output data and the ocean output data to calculate a risk based on an evaluation index according to a predetermined risk assessment standard, And generating and outputting ocean activity risk data for each of the calculated maritime activities.

In the present invention, the output unit may include atmospheric output data, ocean output data, and ocean activity risk data produced through atmospheric and oceanic weather modeling, ), And combines these data to generate web display data converted into a format for displaying a web (WEB), and outputs the generated web display data through the web.

According to one aspect of the present invention, the present invention establishes a model for predicting the weather of a specific area in the sea, calculates the risk for each maritime activity by using factors affecting the maritime activity, Scheduling offshore activities related to offshore wind farm operations and enabling efficient operation and management of offshore wind farms.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a diagram showing a schematic configuration of a marine activity risk forecasting system according to an embodiment of the present invention; FIG.
FIG. 2 is an exemplary diagram for explaining the operation of the air-conditioner modeling preprocessing unit in FIG. 1; FIG.
3 is an exemplary diagram for explaining the operation of the air-conditioner modeling unit in FIG.
FIG. 4 is an exemplary diagram for explaining the operation of the air conditioner post-modeling post-processing unit in FIG. 1; FIG.
FIG. 5 is an exemplary diagram for explaining the operation of the pre-processing unit for ocean weather modeling in FIG. 1; FIG.
FIG. 6 is an exemplary diagram for explaining the operation of the marine vapor phase modeling unit in FIG. 1; FIG.
FIG. 7 is an exemplary diagram for explaining the operation of the processing unit after the ocean weather modeling in FIG. 1; FIG.
FIG. 8 is an exemplary view for explaining the operation of the risk assessment section for each maritime activity in FIG. 1; FIG.
FIG. 9 is an exemplary diagram for explaining the operation of the output unit in FIG. 1; FIG.
FIG. 10 is an exemplary diagram showing a screen for displaying weather prediction and risk assessment results in the form of a contour map for each layer in FIG. 1; FIG.
FIG. 11 is an exemplary diagram showing a screen for displaying weather prediction and risk assessment results in the form of a table and a graph in FIG. 1; FIG.

Hereinafter, an embodiment of a marine activity risk forecasting system according to the present invention will be described with reference to the accompanying drawings.

In this process, the thicknesses of the lines and the sizes of the components shown in the drawings may be exaggerated for clarity and convenience of explanation. In addition, the terms described below are defined in consideration of the functions of the present invention, which may vary depending on the intention or custom of the user, the operator. Therefore, definitions of these terms should be made based on the contents throughout this specification.

FIG. 1 is a diagram illustrating a schematic configuration of a maritime activity risk prediction system according to an embodiment of the present invention. The system includes a data receiving unit 110, an air-condition modeling pre-processing unit 120, A weather modeling post-processing unit 140, a marine meteorological model pre-processing unit 150, a marine meteorological modeling unit 160, a marine meteorological model post-processing unit 170, .

The data receiving unit 110 receives data (e.g., UM data, Unified Model data) for modeling of a weather (e.g., atmospheric or oceanic weather) from a designated device (e.g., weather observation system of a weather station). Here, the ocean phase is a meteorological phenomenon related to water (e.g., waves, water temperature, water depth, etc.), and the atmosphere phase refers to a meteorological phenomenon related to the atmosphere (e.g., wind, weather, temperature, etc.) excluding water .

The atmospheric vapor modeling preprocessing unit 120 processes the received data (i.e., data for weather modeling) into input data for performing a weather (e.g., atmospheric vapor or ocean vapor) modeling.

(For example, a six-hour period) with respect to a target time (for example, the preceding 48 hours for weather forecasting) using the input basic data processed as data for the weather modeling, To predict atmospheric meteorological phenomena.

The atmospheric vapor phase modeling post-processing unit 140 extracts meteorological elements for predicting fog and lightning from the result (i.e., atmospheric vapor phase modeling result data) after the atmospheric vapor phase modeling and predicts fog and lightning do.

Then, the fog and the lightening prediction information are stored as atmosphere output data.

The pre-processing unit 150 extracts wind data from the result of the atmospheric air-phase modeling and converts it into input data (or input data) for ocean weather modeling. At this time, in order to perform the ocean weather modeling, setting data (e.g., namelist.swn) (or file) in which the number of domains, the model time, the number of grids, and the grid size are set is generated (or produced).

The marine vapor phase modeling unit 160 predicts the oceanic vapor phase through the oceanic vapor phase modeling using the data generated (or produced) by the ocean phase modeling pre-processing unit 150. (Eg, wind. *, Hsign. *, Hswell. *, Pdir. *, Depth. *, Tps. *, And so on) (ie, atmospheric weather modeling result data) are generated through the above-described ocean weather modeling.

The post-processing unit 170 extracts ocean weather prediction information to be provided to the user from the ocean weather modeling result, and stores the ocean weather prediction data as ocean output data.

The risk-activity-by-maritime activity estimating unit 180 may be configured to estimate at least one of the maritime activity of the specified area (for example, offshore wind farm) using the atmospheric and ocean weather prediction result data through the weather modeling Activity (eg, activity, tourism, leisure activities, etc.). The risk (or risk index) is calculated (or calculated) based on the evaluation index according to the risk assessment criteria and stored as ocean activity risk data.

For example, the risk (or risk index) may be calculated using an evaluation index to which the predicted meteorological factors (for example, wind velocity, wave height, fog, lightning strike,

 The output unit 190 outputs data (e.g., atmospheric weather output data, ocean weather output data, and marine activity-specific risk data) generated through the weather modeling to a form for displaying (or outputting) Format) is generated and output.

At this time, the web presentation data includes a contour map image for web presentation according to weather elements (for example, atmospheric weather, marine weather, and maritime activity) (refer to FIG. 10) Each of the evaluation results is displayed on a map to provide a spatial distribution, and a weather distribution and a risk evaluation result are displayed in a table and a time series graph, and a time distribution is provided together (see FIG. 11).

FIG. 10 is a diagram showing a screen for displaying the weather prediction and the risk assessment result in the form of a contour map for each layer in FIG. 1, FIG. 11 is a graph showing the weather prediction and the risk evaluation result, Fig. 2 is a view showing a screen displayed in the form of a screen; In particular, FIG. 11 is characterized in that it displays ocean activity risk data (ie, magnified data) for each maritime activity (eg, maintenance vessel operations, fishing activities, tourism and leisure activities).

FIG. 2 is an exemplary diagram for explaining the operation of the pre-processing unit for the air-conditioner modeling in FIG. 1; FIG.

The air-condition modeling preprocessing unit 120 processes the received data (i.e., data for weather modeling, e.g., UM data) into input data for performing weathering (e.g., atmospheric gas phase, ocean gas phase) modeling.

More specifically, the air-conditioner modeling preprocessing unit 120 receives (UM) Unified Model data from a pre-designated device (for example, a meteorological observation system of a meteorological office) (S101) (S106), and converts it into a designated first format data (e.g., GRIBFILE. *) (S102). Then, referring to setting data for weather modeling (S106) (S103).

In step S108, weather information data (e.g., YYYY-MM-DD_HH) is extracted from the data of the second format at predetermined intervals.

At this time, decompression, decoding, and supplementation of missing data may be included for the data conversion (S102, S103).

The setting data S106 for the meteorological modeling includes data of a file type (e.g., namelist.wps) in which the number of domains, the prediction period, the number of grids, the size of grid, .

The pre-processing unit 120 generates geographical data (eg, geo_em_dxx.nc, xx: domain number) in the form of a file according to the domain-specific grid information (S107) The geographical data of the area to be predicted is received at a pre-designated device (for example, a meteorological observation system or a geographical information system of the meteorological office) (S104), and the terrain data is converted to match the grid information of the area to be weather modeled (S105).

At this time, in order to convert the terrain data into the grid information of the area to be weather modeled (S105), the setting data S106 for the weather modeling can be referred to.

The air-conditioner modeling preprocessing unit 120 refers to the setting data (S106) for the weather-phase modeling, merges the terrain information suitable for the modeling of the region to be predicted, and the corresponding weather- S109), and generates data (file type data) (e.g., met_em.d *) obtained by merging the terrain information and weather information (S110).

The air-conditioner modeling preprocessing unit 120 uses the observation data (e.g., namelist.oa) for correction (or data assimilation) of a region to be predicted, (Eg, OBS_DOMANINX01, metoa_em.d *, wrfsdda.) For the weather modeling are finally corrected (or data assimilation) is performed (S112). d *) (i.e., input data of a plurality of file types).

The input data for the weather modeling (that is, the input data of a plurality of file types) becomes the basic data for later modeling of weather (for example, atmospheric meteorological or ocean meteorological).

FIG. 3 is an exemplary diagram for explaining the operation of the atmospheric vapor modeling unit in FIG. 1; FIG.

The waiting-gas phase modeling unit 130 calculates a target time (for example, 48 hours preceding the weather prediction) using the basic data input by processing the input data for the weather modeling (that is, input data of a plurality of file types) (For example, six time periods) to predict the atmosphere phase.

3, the atmospheric air conditioner modeling unit 130 may include at least one of input data for the weather modeling (i.e., input data of a plurality of types of files), which is generated by the air conditioner modeling preprocessing unit 120, (S206) by using the preset first and second input data (e.g., OBS_DOMANINX01, wrfsdda.d *) S201 and predetermined third input data (e.g., metoa_em.d *) S202. (E.g., wrfout_d *) as a result of the atmospheric gas phase modeling (S207).

Here, the atmospheric vapor phase modeling is performed to numerically estimate the atmospheric vapor phase, and the atmospheric vapor phase modeling result data (e.g., wrfout_d *) is three-dimensional base phase data.

At this time, in order to improve the accuracy of prediction during the execution of the atmospheric air-surface modeling (S206), a file type setting for setting physical options and vertical layers in addition to the boundary conditions and domains of the region to be predicted, Data (e.g., namelist.input), and additional observation data (e.g., wrfbdy_d01, wrfinput_d *, wrffdda_d *) (S204, S205).

Here, in order to generate the additional observation data (e.g., wrfbdy_d01, wrfinput_d *, wrffdda_d *), the atmospheric vapor phase modeling unit 130 may generate the third input data (e.g., metoa_em.d Real-time data correction (or data assimilation) is performed on the additional setting data (e.g., *) S202 and additional setting data (e.g., namelist.input) S204 (E.g., wrfbdy_d01, wrfinput_d *, wrffdda_d *) (S205).

FIG. 4 is an exemplary diagram for explaining the operation of the post-atmosphere vapor phase modeling processing unit in FIG. 1; FIG.

The atmospheric vapor phase modeling post-processing unit 140 extracts a weather element for predicting the fog and the lightning stroke from the result of the atmospheric vapor phase modeling (i.e., the atmospheric vapor phase modeling result data), and predicts a fog and a lightning stroke And stores the fog and the lightening prediction information as atmosphere output data.

More specifically, the atmospheric vapor phase modeling post-processing unit 140 receives the atmospheric vapor phase modeling result data (e.g., wrfout_d *) (S301), and calculates a weather element (e.g., a solar radiation amount, an atmospheric pressure, (S302), and the extracted meteorological elements are selectively combined or processed to calculate an input meteorological element for calculating the fog and the lightning stroke (S303).

Next, the atmospheric air post-modeling post-processing unit 140 generates fog prediction information (S304) by performing fog prediction using input meteorological elements for calculating the estimated fog and lightning stroke (S305) And lightning prediction is performed using an input meteorological element for calculating the lightening stroke (S306) to generate lightning prediction information (S307).

In operation S308, the atmospheric weather modeling execution result data including the generated fog prediction information S305 and the generated lightening prediction information S307 (i.e., atmosphere output data, Atmosphere Output data) is output.

FIG. 5 is an exemplary diagram for explaining the operation of the pre-processing unit for ocean weather modeling in FIG.

The pre-processing unit 150 extracts wind data from the result of the atmospheric air-phase modeling and converts it into input data (or input data) for ocean weather modeling. At this time, in order to perform the ocean weather modeling, setting data (e.g., namelist.swn) (or file) in which the number of domains, the model time, the number of grids, and the grid size are set is generated (or produced).

More specifically, the marine meteorological modeling preprocessing unit 150 generates meteorological input data related to the marine meteorological phenomenon using the atmospheric weather modeling result data (i.e., Atmosphere Output data) (S401) (S402).

For example, wind data (e.g., wind direction and wind velocity) information data is extracted as weather input data related to the ocean environment, and converted into file type data that can be input as ocean weather modeling data (S403).

In addition, the pre-processing unit 150 generates a configuration file (i.e., configuration data in the form of a file) for performing ocean weather modeling (S404).

For example, the setting file (i.e., file setting data) for performing the above-described marine weather modeling includes setting data (e.g., namelist.swn) of a file in which the number of domains, modeling time, number of grids, (S405).

FIG. 6 is an exemplary diagram for explaining the operation of the ocean weather modeling unit in FIG. 1;

The marine vapor phase modeling unit 160 predicts the oceanic vapor phase through the oceanic vapor phase modeling using the data generated (or produced) by the ocean phase modeling pre-processing unit 150.

More specifically, the ocean-current weather modeling unit 160 receives data (e.g., wind direction and wind speed information data and setting data for ocean weather modeling) generated (or produced) by the ocean weather modeling preprocessing unit 150 (S501, S502), and ocean weather modeling is performed (S503).

(Eg, wind direction, wind velocity, wave height, wave period, wave direction, depth of water, etc.) (ie, ocean weather modeling result data) is generated through the above-described ocean weather modeling (S504).

*, Hswell. *, Pdir. *, Depth. *, Tps. *), Which are generated through the above-described ocean weather modeling (ie, ocean weather modeling result data) *). ≪ / RTI >

FIG. 7 is an exemplary diagram for explaining the operation of the post-ocean-water-vapor-phase-post-processing unit in FIG.

The post-processing unit 170 receives the result (i.e., the atmospheric vapor phase modeling result data) generated through the oceanic weather modeling in operation S601, extracts the ocean weather information in operation S602, (Or generates) marine weather prediction information processed in a form that can be provided to the user from the resultant modeling result, and stores (or outputs) the marine weather output data in a file form (S603 ).

FIG. 8 is an exemplary diagram for explaining the operation of the risk assessment section for each maritime activity in FIG. 1; FIG.

The risk-activity-by-maritime activity estimating unit 180 may be configured to estimate at least one of the maritime activity of the specified area (for example, offshore wind farm) using the atmospheric and ocean weather prediction result data through the weather modeling Activity (eg, activity, tourism, leisure activities, etc.). The risk (or risk index) is calculated (or calculated) based on the evaluation index according to the risk assessment criteria and stored as ocean activity risk data.

More specifically, the maritime activity-specific-risk calculation unit 180 receives atmospheric weather modeling result data (i.e., atmospheric weather output data, Atmosphere Output) including the mist lightening prediction information generated at the atmospheric air- data and ocean output data generated by the post-processing unit 170 (S701 and S702).

The maritime activity-specific risk assessment unit 180 uses the Atmosphere Output data and the ocean output data to calculate a risk index (or a score) based on the evaluation index according to a predetermined risk assessment standard (Or evaluates) the risk activity index (risk index) (S703), and generates ocean activity risk data for the calculated maritime activity (step S704).

FIG. 9 is an exemplary diagram for explaining the operation of the output unit in FIG. 1; FIG.

The output unit 190 outputs the data generated through the modeling of the weather (eg, atmospheric or oceanic weather) (eg, Atmosphere Output data, ocean output data, (Or an ocean activity risk data) (S801, S802, and S803) and combines these data to generate web display data converted into a form (or a format) for displaying (or outputting) (S804, S805).

The web presentation data output through the output unit 190 may be converted into a two-dimensional image or a contour map image (see FIGS. 10 and 11). For example, the above-mentioned risk by sea activity can be expressed in a visible form by dividing the safety stage and the risk stage into a plurality of stages (for example, safety, normal, cautionary risk, etc.). It should be noted that the size, position, and shape of the image may be modified according to the configuration format (or format) of the web.

As described above, according to the present embodiment, the working time is calculated using the weather information (for example, atmospheric weather information and ocean weather information) predicted through the weather modeling, the schedule of the ship which is waiting and returning is not generated, It is possible to improve the efficiency of construction and operation of the power generation complex by utilizing the energy saving and resource appropriately and improving the utilization efficiency.

In addition, this embodiment can be used not only for offshore wind farm but also for construction and operation of structures located on the sea, oil ring, scientific base, marine energy, and aquaculture, thereby preventing marine accidents and improving the efficiency It is effective to increase the amount of the water.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, I will understand the point. Accordingly, the technical scope of the present invention should be defined by the following claims.

110: Data receiving unit
120: atmosphere gas phase modeling pre-
130: atmospheric vapor modeling unit
140: After the atmospheric vapor phase modeling,
150: Pre-processing section for ocean weather modeling
160: Ocean weather modeling unit
170: After the ocean weather modeling,
180: Risks by maritime activities
190: Output section

Claims (12)

A pre-processing unit for the atmospheric gas phase model, which receives the data for the weather modeling from the meteorological observation system of the meteorological office and processes the input data for the meteorological modeling;
An atmospheric vapor phase modeling unit for predicting the atmospheric vapor phase of an area to be modeled at predetermined intervals with respect to the target time using the input data;
An atmospheric vapor phase modeling post-processing unit for generating atmospheric vapor phase output data including information predicting a fog and a lightning stroke in the resultant data by the atmospheric vapor modeling;
A pre-processing unit for ocean weather modeling for extracting wind data from the atmospheric modeling result data and generating input data for ocean weather modeling;
A marine meteorological modeling unit for predicting a meteorological phenomenon using data generated by the pre-processing unit;
A marine meteorological model post-processing unit for extracting marine meteorological forecast information to be provided to a user from the marine meteorological modeling result to generate marine meteorological data;
A risk assessment unit for each maritime activity that generates risk data for each maritime activity by calculating the risk according to the pre-designated maritime activity risk assessment standard using the atmospheric and oceanic weather prediction result data; And
And an output unit for generating and outputting web expression data converted into a form for displaying web data produced through the weather modeling,
The above-mentioned risk-
Atmosphere Atmosphere Modeling After receiving atmosphere output data including the lightning strike prediction information generated by the processing unit and ocean output data generated by the post-processing unit,
The risk is calculated based on the evaluation index according to the predetermined risk assessment standard using the atmosphere output data and the ocean output data and the risk data for each marine activity ocean activity risk data is generated and output,
Wherein the maritime activities include maintenance vessel operations, fishing activities, tourism and leisure activities, and the maritime activities are classified into a plurality of stages between a safety stage and a danger stage, Risk Forecasting System.
The air conditioner of claim 1,
Converts the data for the weather modeling into data of the first predetermined format, converts the data into the data of the second format designated for the extraction of the ground state with reference to the setting data for the weather modeling, And weather information data by location;
Generating terrain data in a file format according to the domain-specific grid information;
And the data combining the terrain information and the weather information is generated by merging the terrain information suitable for the modeling of the region to be predicted and the corresponding weather information data by time and location with reference to the setting data for the weather modeling Marine activity risk forecasting system.
3. The method according to claim 2, wherein the setting data for the weather-
Wherein the number of domains, the number of lattices, the size of lattices, and the location information for the atmospheric gas modeling are set in a file format.
[3] The air conditioner of claim 2,
The geographical data of the area to be predicted is received at the pre-designated device, and the geographical data is transformed according to the grid information of the area to be weather modeled to generate the terrain data of the file in accordance with the domain-
Wherein the setting data for weather modeling is referred to in order to convert the terrain data into the grid information of the area to be weather modeled.
[3] The air conditioner of claim 2,
After generating the data in which the terrain information and the weather information are merged,
The correction of the data in which the generated terrain information and the weather information are merged is performed using the additional observation data for the correction of the region to be predicted and, when the correction is completed, the input of the plurality of file types Wherein the water activity forecasting system generates data.
The air conditioner of claim 1,
The atmospheric vapor phase modeling preliminary processing unit performs the atmospheric vapor phase modeling using the input data of the plurality of file types for the weather phase modeling,
The marine activity risk forecasting system is further configured to refer to setting data and additional observation data for setting physical options and vertical layers in addition to boundary conditions and domains of a region to be predicted in order to improve prediction accuracy during execution of the air-conditioning modeling.
The air conditioner of claim 1, wherein the atmospheric vapor phase modeling post-
At least one weather element for calculating the fog and the lightning stroke is received, and the extracted weather elements are selectively combined or processed to obtain an input weather element for calculating the fog and the lightning stroke However,
The fog prediction is performed by using the input meteorological element for calculating the estimated fog and the lightning stroke to generate the fog prediction information and the lightning prediction is performed using the input meteorological element for calculating the calculated fog and the lightning stroke After generating the lightening prediction information,
And outputs atmospheric weather output data (Atmosphere Output Data) as data of atmospheric weather modeling execution result including the generated fog prediction information and lightning prediction information.
The method according to claim 1, wherein the pre-
Using the Atmosphere Output data, generate the meteorological input data related to the ocean weather,
A weather data input module for converting the weather data inputted from the weather data input module into a file type data for inputting the weather data and outputting the setting file for the weather data modeling,
Wherein the configuration file for performing the weather modeling is configuration data of a file format in which the number of domains, the modeling time, the number of grids, and the grid size are set.
The apparatus of claim 1, wherein the ocean-
The data generated by the pre-processing unit for the ocean-current weather model is input to the wind direction and wind velocity information data and the setting data for the ocean weather modeling to perform ocean weather modeling,
Wherein the ocean weather modeling result data is generated by the ocean weather modeling, wherein the ocean weather modeling result data includes a wind direction, a wind speed, a wave height, a wave period, a wave direction, .
The method of claim 1, wherein the post-
The data of the ocean weather modeling result obtained through the ocean weather modeling is inputted and the processed ocean weather forecast information is extracted to provide the user with the ocean output data in the form of file Wherein the water activity forecasting system comprises:
delete The image processing apparatus according to claim 1,
The system receives the atmospheric output data, the ocean output data, and the ocean activity risk data produced by the atmospheric and ocean meteorological modeling,
And generating the web display data converted into a form for displaying the web by combining the data, and outputting the generated web display data through the web.

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