Dynamic radius and multi-source fusion method and system for evaluating offshore buoy under typhoon

Abstract

The application relates to the technical field of marine observation, and particularly discloses a typhoon offshore buoy evaluation method and system with dynamic radius and multi-source fusion, which comprises the following steps: determining the influence time of the sea area where the to-be-evaluated buoy station is located; collecting operation state data and observation data of the to-be-evaluated buoy station during a typhoon, and observation data of a plurality of other data sources; calculating the station operation tolerance; determining the effective influence radius of each element in the other data sources, and determining the dynamic spatial range; fusing the same element in the plurality of other data sources within the dynamic spatial range to obtain a fusion true value; calculating the data representation accuracy based on the observation data of the to-be-evaluated buoy station and the fusion true value of each element of the other data sources; and calculating the comprehensive score of the to-be-evaluated buoy station based on the station operation tolerance and the data representation accuracy. The application can dynamically adapt to different sea area environmental characteristics, and realizes comprehensive evaluation of an offshore buoy observation station.

Description

Technical Field

[0001] This invention relates to the field of marine observation technology, and more specifically to a method and system for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion. Background Technology

[0002] Currently, the existing operational evaluation methods for buoy sites only target the quality control results of operational evaluation observation data or the instrument's operational status, lacking a multi-dimensional comprehensive quantitative evaluation framework under extreme climatic conditions; data quality evaluation only uses the historical data of the evaluation buoy itself as a benchmark or compares with neighboring stations, and the selection of spatial reference range is relatively fixed, which cannot adapt to the spatial differences in different sea areas and has the problem of circular reasoning.

[0003] Therefore, how to comprehensively evaluate nearshore buoy observation stations by dynamically adapting to different marine environmental characteristics in typhoon scenarios is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of the above problems, the present invention proposes a method and system for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion, so as to overcome the above problems or at least partially solve them.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion, comprising the following steps: Determine the timing of typhoon impact on the sea area where the buoy site to be assessed is located; The system collects operational status and observation data from buoy sites to be evaluated during typhoons, and also collects independent observation data from multiple other data sources. The operational tolerance of the buoy sites to be evaluated is calculated based on their operational status data. Centered on the buoy site to be evaluated, expand outwards at equal distances and calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient. Fit the correlation coefficient at each distance gradient to an exponential decay curve, and take the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to the preset value as the effective influence radius of the k-th element in the i-th data source. Based on the effective influence radius of the kth element in the i-th data source, determine the dynamic spatial range of the kth element in the i-th data source. Data on the same elements within the dynamic spatial range from data sources other than the buoy sites to be evaluated are merged to obtain the fused true value; The accuracy of the data representation is calculated based on the fused true values ​​of various elements from the observation data of the buoy site to be evaluated and other data sources. The overall score of the buoy site to be evaluated is obtained by weighted summation of the site's operational tolerance and data representation accuracy.

[0007] Furthermore, the operational status data of the buoy sites to be evaluated should include at least the buoy location, data acquisition logs, and data transmission logs; the observation data should include at least air pressure, sea surface wind, and sea waves; other data sources include one or more of the following: surrounding reference buoy data sources, offshore oil platform data sources, shore-based observation station data sources, satellite remote sensing data sources, and reanalysis data sources.

[0008] Furthermore, the calculation process for site operational tolerance includes: The buoy retention rate is obtained by calculating the ratio of the time the buoy station under evaluation remains within the specified location radius during the typhoon to the total time during the typhoon. The data collection continuity rate is obtained by calculating the ratio of the number of valid data points collected by the buoy stations to be evaluated during the typhoon to the number of data points that should have been collected. The data transmission success rate is obtained by calculating the ratio of the number of data successfully transmitted by the buoy stations to be evaluated during the typhoon to the number of data that should have been transmitted. The buoy in-situ retention rate, data acquisition continuity rate, and data transmission success rate are weighted and summed to obtain the site operation tolerance of the buoy site to be evaluated.

[0009] Furthermore, the formula for calculating the correlation coefficient is:

[0010] in, This represents the correlation coefficient between the k-th element at the buoy site to be evaluated at a distance d and the k-th element data from the i-th data source; for Theoretical correlation coefficient at time; This is a spatial correlation length scale, representing the rate at which the correlation coefficient decays with distance; Will The distance corresponding to the time is used as the effective influence radius of the k-th element in the i-th data source.

[0011] Furthermore, the process of determining the dynamic spatial extent of the k-th element in the i-th data source includes: The characteristic scale of marine dynamic processes is determined based on the water depth of the area where the buoy site to be evaluated is located. ; Spatial radius for determining the minimum sample size required for a significance test of the correlation coefficient ; Determine the dynamic space range ,in, Let be the dynamic spatial extent of the k-th element of the i-th data source.

[0012] Furthermore, the formula for fusing independent observations from multiple other data sources is as follows:

[0013] in, This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated. This represents the total number of data sources other than the buoy sites to be evaluated. This represents the dynamic weights of the independent observations from the i-th data source. This represents the independent observation data of the k-th element from the i-th data source; Dynamic weights of independent observations from the i-th data source The calculation formula is:

[0014] in, Indicates the first Real-time credibility scores for each data source. Indicates the first The base weights of each data source.

[0015] Furthermore, real-time credibility scoring Different scoring methods are used depending on the type of data source; The real-time reliability score of the surrounding reference buoy data source is determined based on the buoy retention rate and data acquisition continuity rate. The real-time reliability scores of offshore oil platform data sources and shore-based observation station data sources are determined based on equipment availability and data acquisition continuity. The real-time reliability score of the satellite remote sensing data source is determined based on cloud coverage. The real-time reliability score of the data source is determined based on the water depth.

[0016] Furthermore, the formula for calculating the accuracy of data representation is as follows:

[0017] in, To improve the accuracy of data representation, As an indicator of the accuracy of element observation, As an indicator of the ability to characterize typhoon processes. As an indicator of spatial distribution characterization ability; The formula for calculating the accuracy index of element observation is:

[0018] in, Indicates the total number of elements. This represents the value of the k-th element at the buoy site to be evaluated. This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated; This represents the correction factor, which is determined based on the radius of influence of the typhoon. The typhoon process characterization capability index is used to characterize the time series similarity between the observed values ​​and the fused true values ​​of the buoy station to be evaluated. The calculation formula is as follows:

[0019] in, This represents the sequence of observations for the k-th element at the buoy site to be evaluated. This represents the fused truth sequence of the k-th element from data sources other than the buoy site to be evaluated. Represents the sequence of observations for the k-th element. With fusion truth sequence The dynamic time-normalized distance between them; Indicates the normalization parameter; The formula for calculating the spatial distribution characterization index is:

[0020] in, This represents the average correlation coefficient between the observation data of each element at the buoy site to be evaluated within the dynamic space and the observation data of each element from other data sources.

[0021] Furthermore, after obtaining the comprehensive score of the buoy site to be evaluated, the buoy site is also classified into five levels based on the comprehensive score results, and corresponding disposal recommendations are given according to different levels.

[0022] Secondly, the present invention provides a typhoon-induced nearshore buoy evaluation system based on dynamic radius and multi-source fusion, which employs the typhoon-induced nearshore buoy evaluation method based on dynamic radius and multi-source fusion as described above, including: The data acquisition module is used to determine the typhoon impact time of the sea area where the buoy station to be evaluated is located; to collect the operational status data and observation data of the buoy station to be evaluated during the typhoon, and to collect independent observation data from multiple other data sources; The tolerance calculation module is used to calculate the operational tolerance of the buoy site based on the operational status data of the buoy site to be evaluated. The effective influence radius determination module is used to calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient, taking the buoy site to be evaluated as the center and expanding outward at equal distance gradients; the correlation coefficient at each distance gradient is fitted into an exponential decay curve, and the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to a preset value is taken as the effective influence radius of the k-th element in the i-th data source. The dynamic spatial range determination module is used to determine the dynamic spatial range of the k-th element in the i-th data source based on the effective influence radius of the k-th element in the i-th data source. The multi-source fusion module is used to fuse data of the same elements that fall within the dynamic spatial range from data sources other than the buoy site to be evaluated, and obtain the fused true value. The data representation accuracy calculation module is used to calculate the data representation accuracy based on the observation data of the buoy site to be evaluated and the fused true values ​​of various elements from other data sources. The comprehensive evaluation module is used to perform a weighted summation of the site's operational tolerance and data representation accuracy to obtain a comprehensive score for the buoy site to be evaluated.

[0023] As can be seen from the above technical solution, compared with the prior art, the present invention has the following beneficial effects: 1. This invention first calculates the correlation coefficient between the observation data of each element of the buoy station to be evaluated and the corresponding element observation data of other data sources under different distance gradients. Then, based on the correlation coefficient, it determines the dynamic influence radius of each element in other data sources. After that, based on the dynamic influence radius, it determines the dynamic spatial range of different elements in different data sources, thus realizing the dynamic determination of the spatial range of multi-source independent observation data.

[0024] 2. Traditional methods often use the historical data of the buoy being evaluated as the truth benchmark, which leads to the logical flaw of using one's own data to verify one's own logic. This invention fuses the observation data of the same element from multiple other data sources within the dynamic space, while the data of the buoy being evaluated is not involved in the fusion, thus solving the problem of circular data verification and improving the objectivity of the evaluation results.

[0025] 3. This invention combines operational tolerance and data representation accuracy to comprehensively evaluate the buoy sites to be assessed, breaking through the limitations of a single evaluation dimension, ensuring the accuracy of the evaluation results, and filling the gap in the existing technology for comprehensive evaluation of buoy observation sites under the influence of typhoons. It can directly serve the comprehensive management of observation sites. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0027] Figure 1 This is a flowchart of the nearshore buoy evaluation method under typhoon conditions based on dynamic radius and multi-source fusion provided in an embodiment of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] like Figure 1 As shown in the figure, this invention discloses a method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion, including the following steps: S1. Determine the timing of typhoon impact on the sea area where the buoy site to be assessed is located; S2. Collect operational status data and observation data of the buoy stations to be evaluated during the typhoon, and collect independent observation data from multiple other data sources; S3. Calculate the operational tolerance of the buoy site based on its operational status data; S4. Taking the buoy site to be evaluated as the center, expand outward at equal distances and calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient. Fit the correlation coefficient at each distance gradient to an exponential decay curve, and take the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to the preset value as the effective influence radius of the k-th element in the i-th data source. S5. Based on the effective influence radius of the kth element in the i-th data source, determine the dynamic spatial range of the kth element in the i-th data source. S6. Merge the data of the same elements in other data sources that are within the dynamic space range, except for the buoy site to be evaluated, to obtain the fused true value of the corresponding element. S7. Calculate the accuracy of data representation based on the fused true values ​​of various elements from the observation data of the buoy site to be evaluated and other data sources. S8. The station's operational tolerance and data representation accuracy are weighted and summed to obtain the comprehensive score of the buoy station to be evaluated.

[0030] The following is a further explanation of the specific implementation process of each of the above steps.

[0031] S1. Determine the typhoon intensity level and impact time of the sea area where the buoy site to be evaluated is located. The typhoon intensity level and impact time are obtained from the typhoon best path dataset released by the meteorological bureau. The intensity level is classified into 1-5 according to the tropical cyclone classification standard.

[0032] S2. Collect operational status data and observation data of the buoy sites to be evaluated during the typhoon, and collect independent observation data from multiple other data sources. The operational status data of the buoy sites to be evaluated must include at least the buoy location, data acquisition log, and data transmission log; the observation data must include at least air pressure, sea surface wind, and sea waves. Other data sources include one or more of the following: surrounding reference buoy data sources (excluding the buoy sites to be evaluated), offshore oil platform data sources, shore-based observation station data sources, satellite remote sensing data sources, and reanalysis data sources.

[0033] S3. Calculate the operational tolerance of the buoy site based on its operational status data. The specific calculation process includes: 1) Calculate the ratio of the time the buoy to be evaluated remains within the specified position radius during the typhoon to the total time during the typhoon, to obtain the buoy retention rate. Assign a weight of 0.4 to the buoy retention rate to obtain the buoy stability index. :

[0034] in, This indicates the time during which the buoy site to be assessed will remain within a specified radius (500m) during a typhoon. This indicates the total time during which the typhoon affects the area.

[0035] 2) Calculate the ratio between the number of valid data entries collected by the buoy stations to be evaluated during the typhoon period and the number of data entries that should have been collected, to obtain the data collection continuity rate. Assign a weight of 0.35 to the data collection continuity rate to obtain the data transmission reliability index. :

[0036] in, This indicates the number of data entries effectively collected (sensors functioning normally, data values ​​within a reasonable physical range) by the buoy stations to be evaluated during the typhoon. This indicates the number of data points that should be collected from the buoy site to be evaluated.

[0037] 3) Calculate the ratio between the number of data successfully transmitted by the buoy stations to be evaluated during the typhoon to the number of data that should have been transmitted, to obtain the data transmission success rate. Assign a weight of 0.25 to the data transmission success rate to obtain the data transmission reliability index. :

[0038] in, This indicates the number of data successfully transmitted by buoy stations awaiting evaluation during the typhoon. This indicates the amount of data that the buoy site to be evaluated should transmit.

[0039] 4) Sum the buoy in-situ stability index, data transmission reliability index, and data transmission reliability index to obtain the site operational tolerance of the buoy site to be evaluated. :

[0040] S4. Taking the buoy site to be evaluated as the center, expand outwards at equal distances and calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient. Fit the correlation coefficient at each distance gradient to an exponential decay curve, and take the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to the preset value as the effective influence radius of the k-th element in the i-th data source.

[0041] Specifically, the correlation coefficient between the k-th element of the buoy station to be evaluated at each distance gradient and the k-th element of the i-th data source is calculated using the Pearson spatial correlation coefficient. Take the first drop in correlation coefficient on the exponential decay curve to... (When the data sample size n≥30 is used to calculate the correlation coefficient, the corresponding significance level is...) distance The effective influence radius of the k-th element from the i-th data source That is, when When, the fitted parameters and The solution obtained by substituting the exponential decay curve As the effective radius of influence In other words, when n≥30, exist The correlation coefficient is significantly different from 0 at the specified level, therefore, selecting 0.6 as the correlation coefficient threshold is statistically significant.

[0042] The formula for calculating the correlation coefficient is as follows:

[0043] in, This represents the correlation coefficient between the k-th element at the buoy site to be evaluated at a distance d and the k-th element data from the i-th data source; Indicates distance; for Theoretical correlation coefficient at time; The spatial correlation length scale characterizes the rate at which the correlation coefficient decays with distance, and is obtained by least squares fitting. Specifically, and The calculation method is as follows: Whenever trying a set of fitting coefficients and At that time, calculate different distances The squared errors between the measured Pearson spatial correlation coefficient and the correlation coefficient at the corresponding point on the current fitted curve are summed to obtain the sum of squared errors. The fitted coefficients that minimize the sum of squared errors are then selected. and As the final fitting coefficients.

[0044] S5. Based on the effective influence radius of the k-th element in the i-th data source, determine the dynamic spatial range of the k-th element in the i-th data source, specifically including: 1) Determine the characteristic scale of marine dynamic processes based on the water depth of the sea area where the buoy station to be evaluated is located. When the water depth is ≤200m, Taking a distance of 30km, when the water depth is greater than 200m, Take 50km.

[0045] 2) Determine the spatial radius of the minimum sample size required for the significance test of the correlation coefficient. .

[0046] 3) Based on the effective influence radius of the k-th element of the i-th data source. Marine dynamic process characteristic scale and spatial radius Determine the dynamic spatial extent of the k-th element from the i-th data source: This dynamic spatial range is used to select multi-source independent observation data during subsequent truth fusion.

[0047] S6. Merge identical feature data from other data sources (excluding the buoy site to be evaluated) that fall within the dynamic spatial range to obtain the fused true value of the corresponding feature. The fusion formula for the k-th feature data from multiple other data sources is:

[0048] in, This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated. This represents the total number of data sources other than the buoy sites to be evaluated. Represents the dynamic weights of independent observations from the i-th data source; This represents the k-th element of the i-th data source within its dynamic space. Independent observational data within the region are obtained through spatial interpolation.

[0049] Dynamic weights of independent observations from the i-th data source The calculation formula is:

[0050] in, Indicates the first The base weights of each data source are pre-set based on the long-term accuracy and reliability of the independent data source in historical comparison and verification. Indicates the first Real-time credibility scores for each data source. Different scoring methods are used depending on the data source type, specifically: ① The real-time reliability score of the surrounding reference buoy data source is determined based on the buoy retention rate and data acquisition continuity rate. The calculation formula is as follows:

[0051] in, This indicates the real-time reliability score of the surrounding reference buoy data source. This indicates the buoy retention rate. This indicates the data collection continuity rate.

[0052] ② The real-time reliability score of the data source from offshore oil platforms and the data acquisition continuity rate is determined based on the equipment availability rate and the data acquisition continuity rate. The calculation formula is as follows:

[0053] in, This indicates the real-time reliability score of data sources from offshore oil platforms or shore-based observation stations. This indicates the equipment availability rate (the proportion of core equipment that is fully functional during extreme events). This indicates the data collection continuity rate.

[0054] ③ Determine the real-time reliability score of the satellite remote sensing data source based on cloud coverage rate. The calculation formula is as follows:

[0055] in, This indicates the real-time reliability score of the satellite data source. This indicates the cloud coverage rate of the sea area within the dynamic spatial range.

[0056] ④ The real-time reliability score of the reanalysis data source is determined based on the water depth. The calculation formula is as follows:

[0057] in, This indicates the real-time credibility score of the data source being reanalyzed. This indicates the water depth at the location of the buoy to be evaluated. 0.3 is the attenuation coefficient, which can be set empirically based on historical data.

[0058] S7. Based on the observation data of the buoy station to be evaluated and the fused true values ​​of each element from other data sources, calculate the data representation accuracy. The data representation accuracy is the sum of the element observation accuracy index, the typhoon process representation capability index, and the spatial distribution representation capability index. The calculation process of the three indicators is as follows: 1) The formula for calculating the accuracy index of element observation is:

[0059] in, Indicators representing the accuracy of element observations Indicates the total number of elements. This represents the value of the k-th element at the buoy site to be evaluated. This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated; This represents the correction factor, which varies depending on the radius of the typhoon's wind circle.

[0060] The formula for determining the value of the correction factor is:

[0061] in, Represents the radius (km) of a 12-level wind circle. Represents the radius (km) of a level 10 wind circle. Represents the radius (km) of a level 7 wind circle. This represents the radius of the current typhoon's wind circle, which is positively correlated with the current typhoon intensity level.

[0062] 2) The typhoon process characterization capability index is used to characterize the time series similarity between the observed values ​​and the fused true values ​​of the buoy station to be evaluated. The calculation formula is as follows:

[0063] in, Indicators representing the ability to characterize typhoon processes; This represents the sequence of observations for the k-th element at the buoy site to be evaluated. This represents the fused truth sequence of the k-th element from data sources other than the buoy site to be evaluated. This represents the sequence of observations for the k-th element at the buoy site to be evaluated. The fused truth sequence of the k-th element from other data sources Dynamic Time Warping Distance (DTW) is a method for measuring the similarity between two time series. It finds the path that best matches the morphology of the two series by stretching or compressing the time axis. Its core is to find the optimal alignment path through dynamic programming and calculate the minimum cumulative distance. Because different data sources record differences in the passage time of typhoons, their evolution speed may vary. DTW can automatically align these differences and accurately assess morphological similarity. This represents the normalized parameter, obtained from historical data statistics. Specifically, it involves collecting DTW distance values ​​from multiple buoys during historical typhoon events and calculating the median or mean as the normalized parameter. .

[0064] 3) The formula for calculating the spatial distribution characterization index is:

[0065] in, Indicators representing the ability to characterize spatial distribution. This represents the average correlation coefficient between the observed data of each element at the buoy site to be evaluated within the dynamic space and the observed data of each element from other data sources. In other words, it represents the average correlation coefficient between the data of each element from each data source and the data of each element at the buoy site to be evaluated within the dynamic space.

[0066] 4) Calculate the accuracy of data representation : .

[0067] S8. The overall score of the buoy site to be evaluated is obtained by weighted summation of the site's operational tolerance and data representation accuracy. :

[0068] in, To determine the operating tolerance weight, an empirical weight is set based on the buoy's water depth, such as 0.45 when the water depth is ≤200m and 0.5 when the water depth is ≥200m. The weights for the accuracy of data representation satisfy... .

[0069] After obtaining the comprehensive score of the buoy site to be evaluated, a five-level classification is made based on the comprehensive score results. When the comprehensive score is ≥90, it is judged as excellent; when the score is 80-89, it is judged as good; when the score is 70-79, it is judged as qualified; when the score is 60-69, it is judged as unqualified; and when the score is below 60, it is judged as very poor. Corresponding handling suggestions are given according to different levels.

[0070] In other embodiments, the present invention also provides a nearshore buoy evaluation system based on dynamic radius and multi-source fusion under typhoon conditions, which employs the above-mentioned method, including: The data acquisition module is used to determine the typhoon impact time of the sea area where the buoy station to be evaluated is located; to collect the operational status data and observation data of the buoy station to be evaluated during the typhoon, and to collect independent observation data from multiple other data sources; The tolerance calculation module is used to calculate the operational tolerance of the buoy site based on the operational status data of the buoy site to be evaluated. The effective influence radius determination module is used to calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient, taking the buoy site to be evaluated as the center and expanding outward at equal distance gradients; the correlation coefficient at each distance gradient is fitted into an exponential decay curve, and the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to a preset value is taken as the effective influence radius of the k-th element in the i-th data source. The dynamic spatial range determination module is used to determine the dynamic spatial range of the k-th element in the i-th data source based on the effective influence radius of the k-th element in the i-th data source. The multi-source fusion module is used to fuse data of the same elements that fall within the dynamic spatial range from data sources other than the buoy site to be evaluated, and obtain the fused true value. The data representation accuracy calculation module is used to calculate the data representation accuracy based on the observation data of the buoy site to be evaluated and the fused true values ​​of various elements from other data sources. The comprehensive evaluation module is used to perform a weighted summation of the site's operational tolerance and data representation accuracy to obtain a comprehensive score for the buoy site to be evaluated.

[0071] Next, the method of the present invention will be described in detail using the comprehensive evaluation of buoy MF14002 during Typhoon Mangkhut as an example.

[0072] S1. Determine the typhoon impact time for the sea area where the buoy to be assessed is located. Among them, the nearshore buoy to be assessed is numbered MF14002, located in the northern part of the South China Sea (115.6°E, 20.5°N), with a water depth of 369m; according to the typhoon best path dataset released by the Meteorological Bureau, Typhoon Mangkhut is a super typhoon, and the buoy will be affected by the typhoon from 00:00 on September 14, 2018 to 24:00 on September 17, 2018.

[0073] S2. Collect operational status data and observation data of the buoy stations to be evaluated during the typhoon, and collect independent observation data from multiple other data sources. The specific collection process is as follows: 1) Extract the operational status data of the buoy MF14002 to be evaluated during the typhoon: the buoy observation frequency is 1 hour, and the time during which the buoy maintains the specified position radius (within 500m) during the typhoon is 90 hours, obtained through latitude and longitude information; the number of valid data collections is 88, and the number of successfully transmitted data is 82.

[0074] 2) Collect observation data of the buoy to be evaluated, including wind, air pressure and wave data, at a frequency of hourly.

[0075] 3) Initially collect possible independent reference data sources in the surrounding area, including: wind, air pressure and wave data observed by surrounding reference buoys MF14001, MF14003 and MF15001, effective wave height products observed by satellite altimeters, and sea surface wind, air pressure and wave data from ERA5 reanalysis data.

[0076] S3. Calculate the operational tolerance of the buoy station based on its operational status data. According to S1, the evaluation period is 96 hours, and the observation frequency is 1 hour, therefore 96 data points should be collected and transmitted to the data center. According to S2, if the buoy remains in place for 90 hours, 88 data points will be effectively collected, and 82 data points will be successfully transmitted. Calculate the station's operational tolerance using the following formula:

[0077]

[0078]

[0079]

[0080] S4. Determine the effective influence radius of different elements in different data sources. The specific determination process is as follows: 1) Centered on the buoy station MF14002 to be evaluated, data of each element in the ERA5 reanalysis data at each gradient along a 5km equidistant gradient were acquired during the typhoon. The Pearson spatial correlation coefficient between the observation data of the buoy MF14002 to be evaluated and the observation data from other reference data sources was calculated. Taking ocean wave data as an example, the correlation coefficients at different distance gradients are shown in Table 1: Table 1. Correlation coefficients of wave data at different distance gradients

[0081] 2) The least squares method was used to fit the correlation coefficient. When the sum of squared errors converged, the fitting coefficients were r≈0.98 and L≈210km.

[0082] The fitting coefficients were then substituted into the exponential decay curve. ,Right now The effective influence radius of the wave data in the ERA5 reanalysis data was found to be 100km. Similarly, the effective influence radius of the wave data of the surrounding buoy stations was calculated to be 80km.

[0083] S5. Determine the dynamic spatial range of each element in different data sources. The specific process is as follows: According to S1, the water depth at the location of the buoy MF14002 to be evaluated is 369m, therefore the scale of the marine dynamic characteristics is... .

[0084] The distance between the buoy MF14002 to be evaluated and the grid points of the ERA5 reanalysis data source is 10.4 km, and both are hourly data with 96 data points, satisfying the minimum sample size n≥30. Therefore... .

[0085] The dynamic spatial range of wave data in ERA5 reanalysis data is determined as follows: Similarly, the dynamic spatial range of wave data from surrounding buoy stations was calculated to be 80km.

[0086] S6. Merge the data of the same elements that fall within the dynamic spatial range from other data sources besides the buoy site to be evaluated to obtain the fused true value of the corresponding element. The specific process is as follows: 1) Determining the fusion dataset: After screening, buoy MF14001 is 50km away from buoy MF14002 to be evaluated, falling within the dynamic spatial range of the wave data (80km), and is eligible for fusion. Similarly, the nearest grid point in the ERA5 reanalysis data is 10.4km away from buoy MF14002 to be evaluated, falling within the dynamic spatial range of the wave data (100km), and is also eligible for fusion. Therefore, the wave data fusion process involves two independent observation data sources: buoy MF14001 and the ERA5 reanalysis data.

[0087] The ERA5 reanalysis data is gridded data with a spatial resolution of approximately 0.25° × 0.25° (approximately 25 km × 25 km). Within a dynamic spatial range of 100 km, there are 32 ERA5 reanalysis data grid points. Inverse distance weighted interpolation (or other spatial interpolation methods) is used to interpolate the data from each grid point to the location of the buoy to be evaluated, thereby obtaining simulated values ​​of the ERA5 reanalysis data at the buoy's location.

[0088] 2) Base weight: Based on historical data comparison and verification, the accuracy of observation of surrounding buoys is relatively high, so the base weight is set to 0.55; the accuracy of ERA5 reanalysis data is second, so the base weight is set to 0.45.

[0089] 3) Determine the real-time reliability score: Based on the in-situ retention rate and data acquisition continuity rate of buoy MF14001, the real-time reliability score of buoy MF14001 is determined to be 0.90, and the real-time reliability score of the reanalysis data source determined based on water depth is 0.756.

[0090] 4) Calculate the dynamic weight of buoy MF14001. Dynamic weights of ERA5 reanalysis data .

[0091] 5) The data collected by S2 at 21:00 on September 15, 2018, during the typhoon period is as follows: Observation from surrounding buoy MF14001: Wave height = 5.3m.

[0092] ERA5 reanalysis data: A total of 32 sets of data within a spatial radius of 100km were spatially interpolated to the location of the buoy to be evaluated and the average value was taken to obtain a wave height of 5.8m.

[0093] The true value of the combined wave height is 5.3 × 0.593 + 5.8 × 0.407 ≈ 5.50m.

[0094] Using the same method, the true values ​​of the combined air pressure and wind speed were calculated to be 949.87 hPa and 45.73 m / s, respectively.

[0095] S7. Based on the observation data of the buoy site to be evaluated and the fused true values ​​of various elements from other data sources, calculate the accuracy of the data representation. The specific calculation process is as follows: 1) According to information released by the meteorological bureau, at 21:00 on September 15, 2018, the distance between the buoy to be evaluated MF14002 and the center of the typhoon (20.3°N, 116.1°E) was 56.7km, which was within the radius of the 12-level wind circle (the radii of the 12-level wind circle in the four quadrants were 123km, 81km, 85km and 77km respectively), and the correction factor was taken as γ=1.2.

[0096] 2) The accuracy index for element observation is: .

[0097] 3) Using the time series of observation data from the buoy MF14002 to be evaluated and the fused true time series, the dynamic time-normalized distance DTW was calculated to be 12.5. Based on historical typhoon data, the normalized parameter σ was obtained to be 15. The typhoon process characterization index is as follows: .

[0098] 4) Based on the results of S4, the average correlation coefficient within the dynamic space is calculated to be 0.77, and the spatial distribution characterization index is: .

[0099] 5) The accuracy of data representation is: .

[0100] S8. Calculate the comprehensive score of the buoy site to be evaluated. The specific process is as follows: 1) The water depth of the buoy MF14002 to be evaluated is 368m. Calculate the overall score:

[0101] 2) Based on the comprehensive score, the buoy MF14002 was rated as good during Typhoon Mangkhut. It is recommended to strengthen the monitoring of the site during the typhoon, improve the daily maintenance of the buoy and the calibration of the sensors, and further enhance the buoy's ability to resist abnormal disasters.

[0102] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion, characterized in that... Includes the following steps: Determine the timing of typhoon impact on the sea area where the buoy site to be assessed is located; The system collects operational status and observation data from buoy sites to be evaluated during typhoons, and also collects independent observation data from multiple other data sources. The operational tolerance of the buoy sites to be evaluated is calculated based on their operational status data. Centered on the buoy site to be evaluated, expand outwards at equal distances and calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient. Fit the correlation coefficient at each distance gradient to an exponential decay curve, and take the distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to the preset value as the effective influence radius of the k-th element in the i-th data source. Based on the effective influence radius of the kth element in the i-th data source, determine the dynamic spatial range of the kth element in the i-th data source. Data on the same elements within the dynamic spatial range from data sources other than the buoy sites to be evaluated are merged to obtain the fused true values ​​of the corresponding elements. The accuracy of the data representation is calculated based on the fused true values ​​of various elements from the observation data of the buoy site to be evaluated and other data sources. The overall score of the buoy site to be evaluated is obtained by weighted summation of the site's operational tolerance and data representation accuracy.

2. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that, The operational status data of the buoy sites to be evaluated should include at least the buoy location, data acquisition log, and data transmission log, and the observation data should include at least air pressure, sea surface wind, and sea waves. Other data source types include one or more of the following: surrounding reference buoy data sources, offshore oil platform data sources, shore-based observation station data sources, satellite remote sensing data sources, and reanalysis data sources.

3. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... The calculation process for site operational tolerance includes: The buoy retention rate is obtained by calculating the ratio of the time the buoy station under evaluation remains within the specified location radius during the typhoon to the total time during the typhoon. The data collection continuity rate is obtained by calculating the ratio of the number of valid data points collected by the buoy stations to be evaluated during the typhoon to the number of data points that should have been collected. The data transmission success rate is obtained by calculating the ratio of the number of data successfully transmitted by the buoy stations to be evaluated during the typhoon to the number of data that should have been transmitted. The buoy in-situ retention rate, data acquisition continuity rate, and data transmission success rate are weighted and summed to obtain the site operation tolerance of the buoy site to be evaluated.

4. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... The formula for calculating the correlation coefficient is: in, This represents the correlation coefficient between the k-th element at the buoy site to be evaluated at a distance d and the k-th element data from the i-th data source; for Theoretical correlation coefficient at time; This is a spatial correlation length scale, representing the rate at which the correlation coefficient decays with distance; Will The distance corresponding to the time is used as the effective influence radius of the k-th element in the i-th data source.

5. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... The process of determining the dynamic spatial extent of the k-th element in the i-th data source includes: The characteristic scale of marine dynamic processes is determined based on the water depth of the area where the buoy site to be evaluated is located. ; Spatial radius for determining the minimum sample size required for a significance test of the correlation coefficient ; Determine the dynamic space range ,in, Let be the dynamic spatial extent of the k-th element of the i-th data source.

6. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... The formula for calculating the fusion truth value is: in, This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated. This represents the total number of data sources other than the buoy sites to be evaluated. This represents the dynamic weights of the independent observations from the i-th data source. This represents the independent observation data of the k-th element from the i-th data source; Dynamic weights of independent observations from the i-th data source The calculation formula is: in, Indicates the first Real-time credibility scores for each data source. Indicates the first The base weights of each data source.

7. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 6, characterized in that... Real-time credibility rating Different scoring methods are used depending on the type of data source; The real-time reliability score of the surrounding reference buoy data source is determined based on the buoy retention rate and data acquisition continuity rate. The real-time reliability scores of offshore oil platform data sources and shore-based observation station data sources are determined based on equipment availability and data acquisition continuity. The real-time reliability score of the satellite remote sensing data source is determined based on cloud coverage. The real-time reliability score of the data source is determined based on the water depth.

8. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... The formula for calculating the accuracy of data representation is: in, To improve the accuracy of data representation, As an indicator of the accuracy of element observation, As an indicator of the ability to characterize typhoon processes. As an indicator of spatial distribution characterization ability; The formula for calculating the accuracy index of element observation is: in, Indicates the total number of elements. This represents the value of the k-th element at the buoy site to be evaluated. This represents the fused truth value of the k-th element that conforms to the dynamic space range from data sources other than the buoy site to be evaluated; This represents the correction factor, which is determined based on the radius of influence of the typhoon. The typhoon process characterization capability index is used to characterize the time series similarity between the observed values ​​and the fused true values ​​of the buoy station to be evaluated. The calculation formula is as follows: in, This represents the sequence of observations for the k-th element at the buoy site to be evaluated. This represents the fused truth sequence of the k-th element from data sources other than the buoy site to be evaluated. Represents the sequence of observations for the k-th element. With fusion truth sequence The dynamic time-normalized distance between them; Indicates the normalization parameter; The formula for calculating the spatial distribution characterization index is: in, This represents the average correlation coefficient between the observation data of each element at the buoy site to be evaluated within the dynamic space and the observation data of each element from other data sources.

9. The method for evaluating nearshore buoys under typhoon conditions based on dynamic radius and multi-source fusion as described in claim 1, characterized in that... After obtaining the comprehensive score of the buoy site to be evaluated, the buoy site is also classified according to the comprehensive score result, and corresponding disposal suggestions are given according to different levels.

10. A nearshore buoy evaluation system based on dynamic radius and multi-source fusion under typhoon conditions, characterized in that... The method for evaluating nearshore buoys under typhoon conditions using dynamic radius and multi-source fusion as described in any one of claims 1-9 includes: The data acquisition module is used to determine the typhoon impact time of the sea area where the buoy station to be evaluated is located; to collect the operational status data and observation data of the buoy station to be evaluated during the typhoon, and to collect independent observation data from multiple other data sources; The tolerance calculation module is used to calculate the operational tolerance of the buoy site based on the operational status data of the buoy site to be evaluated. The effective influence radius determination module is used to calculate the correlation coefficient between the k-th element in the buoy site to be evaluated and the k-th element in the i-th data source at each distance gradient, taking the buoy site to be evaluated as the center and expanding outward at equal distance gradients. The correlation coefficient at each distance gradient is fitted to an exponential decay curve by the least squares method. The distance corresponding to the first drop of the correlation coefficient on the exponential decay curve to the preset value is taken as the effective influence radius of the k-th element in the i-th data source. The dynamic spatial range determination module is used to determine the dynamic spatial range of the k-th element in the i-th data source based on the effective influence radius of the k-th element in the i-th data source. The multi-source fusion module is used to fuse data of the same elements from other data sources besides the buoy site to be evaluated that are within the dynamic spatial range, and obtain the fused true value of the corresponding element. The data representation accuracy calculation module is used to calculate the data representation accuracy based on the observation data of the buoy site to be evaluated and the fused true values ​​of various elements from other data sources. The comprehensive evaluation module is used to perform a weighted summation of the site's operational tolerance and data representation accuracy to obtain a comprehensive score for the buoy site to be evaluated.

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