A temporal and spatial fusion method of satellite altimeter significant wave height considering wave characteristics

Abstract

The present invention proposes a space-time fusion method for effective wave height of satellite altimeter taking into account wave characteristics, the method comprising: spatially and temporally matching the effective wave height data of satellite altimeter and the effective wave height data of buoy; performing accuracy evaluation and linear correction on the effective wave height data of satellite altimeter; based on the space-time inverse distance weighted fusion method, introducing water depth parameters that affect wave characteristics to obtain an improved space-time inverse distance weighted fusion method; based on the improved space-time inverse distance weighted fusion method, performing effective wave height fusion on the corrected satellite altimeter effective wave height data. The method improves the fusion accuracy of effective wave height in areas where water depth and terrain change dramatically and near the shore.

Description

Technical Field

[0001] The invention belongs to the technical field of wave observation and relates to a satellite altimeter effective wave height spatiotemporal fusion method taking wave characteristics into consideration. Background Art

[0002] Significant wave height (SWH) is an important parameter to characterize wave conditions, and accurate and high-resolution effective wave height field data plays an important role in marine engineering planning and design, ocean energy utilization, marine disaster warning and protection, and other fields.

[0003] The main means of wave observation include field observation and satellite remote sensing measurement. Field observation, such as buoys, has high observation accuracy, but the observation points are unevenly distributed, mainly sparsely distributed in coastal areas, and the observation period is short. Satellite remote sensing can obtain sub-satellite point data along the orbit through sensors carried by satellites. It has the characteristics of all-day and large-scale coverage, which effectively makes up for the shortcomings of ocean observations. However, single satellite observations are limited by orbits, with a long repetition period (up to more than 10 days), and the orbital spacing can reach hundreds of kilometers. It is impossible to provide evenly distributed observation data with wide coverage and high temporal and spatial resolution in a timely manner. Therefore, large-scale observation data requires the use of multi-source satellite altimeters.

[0004] In the prior art, the inverse distance weighted method, the Kriging interpolation method and the stepwise correction method are provided to fuse the effective wave height data of three satellite altimeters. The results show that the effects of different fusion methods are not much different, and the inverse distance weighted method has the highest efficiency. In addition, the related art further fuses the corrected data of multiple satellite altimeters on the basis of the inverse distance weighted method, and explores the probability distribution characteristics of wave height. However, the current fusion of multi-source satellite altimeters only considers the single factor of spatial distance. The fusion accuracy is poor in areas with drastic changes in water depth and terrain and nearshore areas, and the fusion resolution is not high. Therefore, when fusing multi-source satellite height aggregate data, considering the influence of other factors and improving the fusion accuracy are the main technical problems solved by the present invention. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention proposes a spatiotemporal fusion method of satellite altimeter effective wave heights that takes into account wave characteristics. The method improves the fusion accuracy of effective wave heights in areas where water depth and terrain change dramatically and near the coast.

[0006] In order to achieve the above object, the present invention provides a method for spatiotemporal fusion of effective wave height of satellite altimeter taking into account wave characteristics, comprising:

[0007] Match the satellite altimeter significant wave height data with the buoy significant wave height data in space and time;

[0008] Conduct accuracy evaluation and linear correction on the satellite altimeter effective wave height data;

[0009] Based on the time-space inverse distance weighted fusion method, the water depth parameter that affects the wave characteristics is introduced to obtain an improved time-space inverse distance weighted fusion method.

[0010] Based on the improved spatiotemporal inverse distance weighted fusion method, the corrected satellite altimeter significant wave height data are fused.

[0011] In some embodiments, spatially and temporally matching the satellite altimeter significant wave height data with the buoy significant wave height data comprises:

[0012] The effective wave height data of the satellite altimeter are averaged according to the space matching reference value and the time matching reference value;

[0013] The weighted averaged satellite altimeter significant wave height data is used to match the buoy significant wave height data;

[0014] Among them, the averaged satellite altimeter effective wave height data is expressed as:

[0015] ,

[0016] Where N is the total number of valid data within the matching reference value in the space around the buoy; is the effective wave height data of the satellite altimeter; is the Gaussian weight function,

[0017] ,

[0018] in, , , are the geographical location and the corresponding time value of the buoy position respectively; , , They are the geographical location and corresponding time of the effective wave height data of the satellite altimeter near the buoy, and the spatial matching reference value and time matching reference value set by X, Y, and T.

[0019] In some embodiments, performing accuracy evaluation on the satellite altimeter effective wave height data comprises:

[0020] The performance score and Pearson correlation coefficient were used as evaluation indicators to evaluate the accuracy of the satellite altimeter significant wave height data. The performance score indicator integrates bias, root mean square error, and scatter index.

[0021] Among them, the performance score indicator is expressed as:

[0022] ,

[0023] Yi Represents the satellite altimeter effective wave height data, X i Indicates the buoy effective wave height data; represents the average value of the effective wave height data of the satellite altimeter, It represents the average value of the buoy significant wave height data; N Indicates the total number of data. Orms is the root mean square of the buoy effective wave height data, and the four different statistical parameters are: BIAS For deviation, RMSE is the root mean square error, SI is the scatter index, r is the Pearson correlation coefficient.

[0024] In some embodiments, performing linear correction on the satellite altimeter significant wave height data comprises:

[0025] The effective wave height data of the satellite altimeter to be corrected is regarded as an independent variable, and the effective wave height data of the buoy is regarded as a dependent variable. The least square method is used to perform regression analysis to obtain the regression coefficient and construct a regression equation.

[0026] The regression equation is used to perform linear regression correction on the satellite altimeter significant wave height data.

[0027] In some embodiments, the formula of the improved spatiotemporal inverse distance weighted fusion method is:

[0028] ,

[0029] Among them, Z is the result to be interpolated at the grid point; is the observation value at the corresponding moment of the satellite trajectory observation point; It is a weight factor that comprehensively weighs the distance factor, time factor and water depth parameter; is the difference between the water depth at the grid point to be interpolated and the water depth at the satellite altimeter sample; is the distance between the grid point and the satellite trajectory observation point considering the time factor; is the balance water depth difference and distance The adjustable factor of is the balance coefficient; x , y , t is the latitude and longitude coordinates of the grid point and the corresponding time value; , , is the latitude and longitude coordinates of the satellite trajectory observation point i and the corresponding time value, i∈(1,N), N and m are parameters; c It is a factor used to define the relationship between spatial units and time units, which is the ratio of spatial units to time units.

[0030] In some embodiments, before spatially and temporally matching the satellite altimeter significant wave height data with the buoy significant wave height data, the method further comprises:

[0031] Pre-processing the collected satellite altimeter wave height data in advance to obtain the effective wave height data of the satellite altimeter;

[0032] The collected buoy wave height data is preprocessed in advance to obtain the valid buoy wave height data.

[0033] In some embodiments, the satellite altimeter wave height data is preprocessed, comprising:

[0034] According to the first upper limit threshold, preliminarily eliminating abnormal values ​​in the satellite altimeter wave height data that exceed the first upper limit threshold;

[0035] The satellite altimeter wave height data with outliers initially removed are divided into multiple blocks, and outliers in each block are identified and removed;

[0036] Subdivide the block with outliers into multiple sub-blocks, identify and remove outliers in each sub-block;

[0037] The ratio of the standard deviation to the average value of each sub-block data is calculated, and if the ratio is greater than a second preset threshold, the entire sub-block is deleted.

[0038] In some embodiments, the buoy wave height data is preprocessed, comprising:

[0039] According to the third upper limit threshold, outliers exceeding the third upper limit threshold in the buoy wave height data are first eliminated;

[0040] Determine whether the buoy wave height data corresponding to the first preset time period exceeds a fourth preset threshold, and perform a second elimination on abnormal values ​​exceeding the fourth upper threshold;

[0041] The average of the buoy wave height data after the second elimination of outliers is taken as the benchmark climatic wave height value of the target sea area, and the outliers that deviate from the benchmark climatic wave height value by the fifth preset threshold are eliminated for the third time.

[0042] It can be seen from the above scheme that the advantages of the present invention are:

[0043] The present invention discloses a method for spatiotemporal fusion of effective wave height of satellite altimeter taking into account wave characteristics. The method realizes effective wave height fusion based on spatiotemporal inverse distance weighting improved by water depth. The satellite altimeter effective wave height data and the buoy effective wave height data are spatially and temporally matched to ensure accuracy evaluation and unified calibration, and then the satellite altimeter effective wave height data is subjected to accuracy evaluation and linear correction. The spatiotemporal inverse distance weighted fusion method is improved by considering the joint influence of spatial distance, time and water depth; and the corrected satellite altimeter effective wave height data is subjected to effective wave height fusion by using the improved spatiotemporal inverse distance weighted fusion method. The method considers the joint influence of spatial distance, time and water depth, improves the fusion accuracy of effective wave height in areas where water depth and terrain change dramatically and near the shore, and has high fusion resolution. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The overall flow chart of the method for spatiotemporal fusion of effective wave height of a satellite altimeter taking into account wave characteristics provided by one embodiment of the present invention is shown;

[0045] Figure 2 A comparison diagram of the fusion results of the inverse distance weighted method (IDW-ST) of the related art and the method of the present invention (D-IDW-ST) far from the coast is shown; wherein: (a) and (b) respectively show the fusion results of the related art and the present invention far from the coast and without a sudden change in water depth and terrain, and (c) and (d) respectively show the fusion results of the related art and the present invention far from the coast and with a sudden change in water depth and terrain;

[0046] Figure 3 A comparison diagram of the fusion results of the inverse distance weighted method (IDW-ST) of the related art and the method of the present invention (D-IDW-ST) near the shore is shown; wherein: (a) and (b) respectively show the fusion results of the related art and the present invention near the shore where there is no sudden change in water depth and topography, and (c) and (d) respectively show the fusion results of the related art and the present invention near the shore where there is a sudden change in water depth and topography. DETAILED DESCRIPTION

[0047] In order to make the above features and effects of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings.

[0048] See also Figure 1 As shown, Figure 1 The figure shows the overall flow chart of a method for spatiotemporal fusion of effective wave height of a satellite altimeter taking into account wave characteristics provided by an embodiment of the present invention.

[0049] The satellite altimeter effective wave height spatiotemporal fusion method taking into account wave characteristics specifically comprises the following steps:

[0050] Step S1, spatially and temporally matching the satellite altimeter effective wave height data and the buoy effective wave height data.

[0051] In this embodiment, accuracy evaluation and unified calibration can only be performed by matching the satellite altimeter effective wave height data and the buoy effective wave height data in space and time.

[0052] Specifically, set the spatial matching reference value and the temporal matching reference value. Generally speaking, the matching of 50 km in space and 30 min in time is widely used. In one embodiment, the spatial matching reference values ​​X and Y can be set to 50 km, and the temporal matching reference value T can be set to 30 min. According to the set spatial matching reference value and temporal matching reference value, average the effective wave height data of the satellite altimeter; and use the weighted averaged effective wave height data of the satellite altimeter to match the effective wave height data of the buoy. Among them, the averaged effective wave height data of the satellite altimeter is expressed as:

[0053] ,

[0054] Where N is the total number of valid data within the matching reference value in the space around the buoy; is the effective wave height data of the satellite altimeter; is the Gaussian weight function,

[0055] ,

[0056] in, , , are the geographical location and the corresponding time value of the buoy position respectively; , , They are the geographical location and corresponding time of the effective wave height data of the satellite altimeter near the buoy, and the spatial matching reference value and time matching reference value set by X, Y, and T.

[0057] In addition, in some embodiments, before spatially and temporally matching the satellite altimeter effective wave height data and the buoy effective wave height data, it is necessary to preprocess the collected satellite altimeter wave height data in advance to obtain the satellite altimeter effective wave height data; and to preprocess the collected buoy wave height data in advance to obtain the buoy wave height effective data.

[0058] By pre-processing the collected satellite altimeter wave height data in advance, unqualified wave data, such as wave data under land, rain, sea ice, etc., are eliminated to maintain the consistency of the wave height of the satellite altimeter effective wave height data. In some embodiments, the pre-processing operation on the satellite altimeter wave height data includes a process of identifying and eliminating abnormal values ​​multiple times.

[0059] Specifically: First, based on the first upper threshold, the outliers in the satellite altimeter wave height data that exceed the first upper threshold are preliminarily eliminated. For example, the first upper threshold is set to 25m. Then, the satellite altimeter wave height data with preliminarily eliminated outliers is divided into multiple blocks, which can form a sufficiently long segment to ensure the reliability of data statistics, and further identify and eliminate outliers in each block. In one embodiment, outliers in each block are identified and eliminated based on the median absolute deviation. Specifically: MAD is defined as: ,in, , is the data of the ith block; b is the scaling factor of the Gaussian distribution, which is 1.4826; k is the threshold, which is usually 3. The values ​​that do not meet the median absolute deviation condition are classified as outliers. The median absolute deviation condition is set as: Next, the blocks with outliers are further subdivided into multiple sub-blocks. Specifically, a certain area around each outlier can be divided into a sub-block. According to the above-mentioned identification standard of outliers in the block, check whether there are any outliers in each sub-block, identify the outliers in each sub-block and remove them.

[0060] Finally, the ratio of the standard deviation and the average value of each sub-block data is calculated, and if the ratio is greater than a second preset threshold (eg, 0.5), the entire sub-block is deleted. Thus, the satellite altimeter effective wave height data is obtained through the above preprocessing process.

[0061] In some embodiments, the preprocessing operation performed on the buoy wave height data is similar to the preprocessing operation performed on the satellite altimeter wave height data, and also includes a process of identifying and eliminating abnormal values ​​multiple times.

[0062] Specifically: First, set the third upper limit threshold, for example, the third upper limit threshold is set to 25m, but the present invention is not limited to this. The third upper limit threshold and the first upper limit threshold are both set according to actual needs, and there is no actual constraint relationship between the two. According to the third upper limit threshold, the abnormal values ​​in the buoy wave height data that exceed the third upper limit threshold are eliminated for the first time. Next, further determine whether the corresponding buoy wave height data within the first preset time period exceeds the fourth preset threshold. Here, the fourth upper limit threshold is set to be less than the third upper limit threshold, for example, 10m, and the abnormal values ​​that exceed the fourth upper limit threshold are eliminated for the second time. Finally, the average value of the buoy wave height data after the second elimination of abnormal values ​​is taken as the benchmark climate state wave height value of the target sea area, and the abnormal values ​​that deviate from the benchmark climate state wave height value by the fifth preset threshold are eliminated for the third time. In this way, the valid data of the buoy wave height is obtained by the above preprocessing process.

[0063] Step S2: performing accuracy evaluation and linear correction on the satellite altimeter effective wave height data.

[0064] In one embodiment, in order to analyze the accuracy of the satellite altimeter effective wave height data, four different statistical parameters are selected, namely, bias (BIAS), root mean square error (RMSE), scatter index (SI) and Pearson correlation coefficient (r). At the same time, in order to better describe the comprehensive performance of each fusion method, the performance score (Ps) indicator is further introduced. The performance score indicator integrates bias, root mean square error and scatter index. Then, the performance score and Pearson correlation coefficient are used as evaluation indicators to evaluate the accuracy of the satellite altimeter effective wave height data.

[0065] Among them, the performance score indicator is expressed as:

[0066] ,

[0067] The performance score Ps is a non-directional index ranging from 0 to 1, with 0 indicating a perfect result.

[0068] Among them, Y i Indicates the effective wave height data of the satellite altimeter, X i Indicates the buoy effective wave height data; represents the average value of the effective wave height data of the satellite altimeter, It represents the average value of the buoy effective wave height data; N represents the total number of data, Orms is the root mean square of the buoy effective wave height data, and the four different statistical parameters are: BIAS is the bias, RMSE is the root mean square error, SI is the scatter index, and r is the Pearson correlation coefficient.

[0069] In some embodiments, the least squares method is used to perform regression analysis on the satellite altimeter effective wave height data to achieve linear correction and ensure data consistency. First, the satellite altimeter effective wave height data to be corrected is regarded as an independent variable, and the buoy effective wave height data is regarded as a dependent variable. The least squares method is used to perform regression analysis to obtain the regression coefficient and construct a regression equation; the regression equation is used to perform linear regression correction on the satellite altimeter effective wave height data. The regression equation is expressed as: , where a and b are linear regression coefficients; x i is the effective wave height data of the satellite altimeter before correction; i It is the corrected satellite altimeter effective wave height data.

[0070] Step S3: Based on the time-space inverse distance weighted fusion method, a water depth parameter that affects wave characteristics is introduced to obtain an improved time-space inverse distance weighted fusion method.

[0071] The initial spatiotemporal inverse distance weighted fusion method is expressed as:

[0072] ,

[0073] In this embodiment, a water depth parameter that affects wave characteristics is introduced, and the combined effects of spatial distance, time, and water depth are considered. The improved spatiotemporal inverse distance weighted fusion method is expressed as:

[0074] ,

[0075] Among them, Z is the result to be interpolated at the grid point; is the observation value at the corresponding moment of the satellite trajectory observation point; It is a weight factor that comprehensively weighs the distance factor, time factor and water depth parameter; is the difference between the water depth at the grid point to be interpolated and the water depth at the satellite altimeter sample; is the distance between the grid point and the satellite trajectory observation point considering the time factor; is the balance water depth difference and distance The adjustable factor of is the balance coefficient; x , y , t is the latitude and longitude coordinates of the grid point and the corresponding time value; , , is the latitude and longitude coordinates of the satellite trajectory observation point i and the corresponding time value, i∈(1,N), N and m are parameters; c It is a factor used to define the relationship between spatial units and time units, which is the ratio of spatial units to time units.

[0076] Step S4: Based on the improved spatiotemporal inverse distance weighted fusion method, the corrected satellite altimeter effective wave height data is fused with effective wave height.

[0077] In this embodiment, after obtaining the corrected satellite altimeter effective wave height data through step S3 and obtaining the improved space-time inverse distance weighted fusion method through step S4, the improved space-time inverse distance weighted fusion method is further used to perform effective wave height fusion on the corrected satellite altimeter effective wave height data.

[0078] In order to verify the effect of the spatiotemporal fusion method of satellite altimeter effective wave height taking into account wave characteristics, the spatiotemporal inverse distance weighted method of the related art and the method of the present invention are compared in the case of abrupt changes in water depth and topography and in the case of no obvious changes in water depth and topography. The results are shown in Figure 2 and Figure 3 middle.

[0079] in, Figure 2A comparison chart of the fusion results of the related art inverse distance weighted method (IDW-ST) and the method of the present invention (D-IDW-ST) far from the coast is given. Figure 2 Figures (a) and (b) show the fusion results of the related technology and the present invention at a location far from the coast and without a sudden change in water depth and terrain, respectively. Figure (a) shows the fusion effect of the related technology, and Figure (b) shows the fusion effect of the present invention; Figures (c) and (d) show the fusion results of the related technology and the present invention at a location far from the coast and with a sudden change in water depth and terrain, respectively. Figure (c) shows the fusion effect of the related technology, and Figure (d) shows the fusion effect of the present invention. It can be seen that in the case of being far from the coast and without a sudden change in water depth and terrain, the fusion results of the method of the present invention and the related technology are not much different. However, at the location where the water depth and terrain suddenly change, the fusion accuracy of the method of the present invention is better than that of the related technology, reducing the trend of overestimation of the effective wave height, and the performance is improved by 34.03%.

[0080] Figure 3 A comparison chart of the fusion results of the related art inverse distance weighted method (IDW-ST) and the method of the present invention (D-IDW-ST) in the nearshore is given. Figure 3 Figures (a) and (b) show the fusion results of the related technology and the present invention near the shore where there is no sudden change in water depth and terrain, respectively. Figure (a) shows the fusion effect of the related technology, and Figure (b) shows the fusion effect of the present invention; Figures (c) and (d) show the fusion results of the related technology and the present invention near the shore where there is a sudden change in water depth and terrain, respectively. Figure (c) shows the fusion effect of the related technology, and Figure (d) shows the fusion effect of the present invention. It can be seen that the fusion accuracy of the method of the present invention is better than that of the related technology regardless of whether there is a sudden change in water depth or not. In the case of a sudden change in water depth and terrain, the effect of the present invention is more obvious. Experiments have shown that the method of the present invention improves the fusion accuracy of the effective wave height in areas where the water depth and terrain change dramatically and near the shore.

[0081] In view of this, the present invention aims at the problem that the current multi-source satellite fusion method considers a single factor and the fusion accuracy is poor in the sudden change of water depth and terrain and nearshore areas. A method for spatiotemporal fusion of effective wave height of satellite altimeter taking into account wave characteristics is disclosed. The method realizes effective wave height fusion based on the spatiotemporal inverse distance weighting improved by water depth. The satellite altimeter effective wave height data and the buoy effective wave height data are matched in space and time to ensure accuracy evaluation and unified calibration, and then the satellite altimeter effective wave height data is accurately evaluated and linearly corrected. And considering the joint influence of spatial distance, time and water depth, the spatiotemporal inverse distance weighted fusion method is improved; and the corrected satellite altimeter effective wave height data is fused with effective wave height by using the improved spatiotemporal inverse distance weighted fusion method. The method considers the joint influence of spatial distance, time and water depth, improves the fusion accuracy of effective wave height in areas with drastic changes in water depth and terrain and nearshore, and has high fusion resolution. The method plays an important role in the fields of marine meteorological forecasting, marine engineering planning and design, marine energy utilization, marine disaster warning and protection.

[0082] In addition, it should be noted that the method for spatiotemporal fusion of satellite altimeter effective wave height taking into account wave characteristics disclosed in the present invention is not limited to being executed in the order of the above steps S1-S4. The steps can be reordered, added or deleted. As long as the expected results of the technical solution of the present invention can be achieved, the present invention is not limited here.

[0083] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for spatiotemporal fusion of effective wave height of satellite altimeter taking into account wave characteristics, characterized in that: Include: Match the satellite altimeter significant wave height data with the buoy significant wave height data in space and time; Conduct accuracy evaluation and linear correction on the satellite altimeter effective wave height data; Based on the time-space inverse distance weighted fusion method, the water depth parameter that affects the wave characteristics is introduced to obtain an improved time-space inverse distance weighted fusion method; the formula of the improved time-space inverse distance weighted fusion method is: ， Among them, Z is the result to be interpolated at the grid point; is the observation value at the corresponding moment of the satellite trajectory observation point; It is a weight factor that comprehensively weighs the distance factor, time factor and water depth parameter; is the difference between the water depth at the grid point to be interpolated and the water depth at the satellite altimeter sample; is the distance between the grid point and the satellite trajectory observation point considering the time factor; is the balance water depth difference and distance The adjustable factor of is the balance coefficient; x , y , t is the latitude and longitude coordinates of the grid point and the corresponding time value; , , is the latitude and longitude coordinates of the satellite trajectory observation point i and the corresponding time value, i∈(1,N), N and m are parameters; c It is a factor used to define the relationship between space units and time units, which is the ratio of space units to time units; Based on the improved spatiotemporal inverse distance weighted fusion method, the corrected satellite altimeter significant wave height data are fused.

2. The method according to claim 1, characterized in that Spatial and temporal matching of satellite altimeter effective wave height data and buoy effective wave height data, including: The effective wave height data of the satellite altimeter are averaged according to the space matching reference value and the time matching reference value; The weighted averaged satellite altimeter significant wave height data is used to match the buoy significant wave height data; Among them, the averaged satellite altimeter effective wave height data is expressed as: ， Where N is the total number of valid data within the matching reference value in the space around the buoy; is the effective wave height data of the satellite altimeter; is the Gaussian weight function, ， in, , , are the geographical location and the corresponding time value of the buoy position respectively; , , They are the geographical location and corresponding time of the effective wave height data of the satellite altimeter near the buoy, and the spatial matching reference value and time matching reference value set by X, Y, and T.

3. The method according to claim 1, characterized in that in, The accuracy of the satellite altimeter effective wave height data is evaluated, including: The performance score and Pearson correlation coefficient were used as evaluation indicators to evaluate the accuracy of the satellite altimeter significant wave height data. The performance score indicator integrates bias, root mean square error, and scatter index. Among them, the performance score indicator is expressed as: ， Among them, Y i Represents the satellite altimeter effective wave height data, X i Indicates the buoy effective wave height data; represents the average value of the effective wave height data of the satellite altimeter, It represents the average value of the buoy significant wave height data; N Indicates the total number of data. Orms is the root mean square of the buoy effective wave height data, and the four different statistical parameters are: BIAS For deviation, RMSE is the root mean square error, SI is the scatter index, r is the Pearson correlation coefficient.

4. The method according to claim 2 or 3, characterized in that: in, The effective wave height data of the satellite altimeter is linearly corrected, including: The effective wave height data of the satellite altimeter to be corrected is regarded as an independent variable, and the effective wave height data of the buoy is regarded as a dependent variable. The least square method is used to perform regression analysis to obtain the regression coefficient and construct a regression equation. The regression equation is used to perform linear regression correction on the satellite altimeter effective wave height data.

5. The method according to claim 1, characterized in that: Before spatially and temporally matching the satellite altimeter significant wave height data with the buoy significant wave height data, it also includes: Pre-processing the collected satellite altimeter wave height data in advance to obtain the effective wave height data of the satellite altimeter; The collected buoy wave height data is preprocessed in advance to obtain the valid buoy wave height data.

6. The method according to claim 5, characterized in that The satellite altimeter wave height data is preprocessed, including: According to the first upper limit threshold, preliminarily eliminating abnormal values ​​in the satellite altimeter wave height data that exceed the first upper limit threshold; The satellite altimeter wave height data with outliers initially removed are divided into multiple blocks, and outliers in each block are identified and removed; Subdivide the block with outliers into multiple sub-blocks, identify and remove outliers in each sub-block; The ratio of the standard deviation to the average value of each sub-block data is calculated, and if the ratio is greater than a second preset threshold, the entire sub-block is deleted.

7. The method according to claim 6, characterized in that The buoy wave height data is preprocessed, including: According to the third upper limit threshold, outliers exceeding the third upper limit threshold in the buoy wave height data are first eliminated; Determine whether the buoy wave height data corresponding to the first preset time period exceeds a fourth upper threshold, and perform a second elimination on abnormal values ​​exceeding the fourth upper threshold; The average of the buoy wave height data after the second elimination of outliers is taken as the benchmark climatic wave height value of the target sea area, and the outliers that deviate from the benchmark climatic wave height value by the fifth preset threshold are eliminated for the third time.

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