A nested grid water depth generation method based on the NEMO model

Abstract

The present invention discloses a nested grid water depth generation method based on the NEMO model. This method can nest and encrypt to form sub-grids on the basis of the model's parent grid according to a given arbitrary range and refinement coefficient, and calculate the water depth value at each grid point within the nested sub-grid to obtain the water depth data of the nested sub-grid. The present invention can quickly and conveniently give the nested grid water depth results with arbitrary range and arbitrary encryption degree, so as to provide necessary input conditions for the operation of the NEMO model.

Description

Technical Field

[0001] The present invention belongs to the field of ocean numerical models, and particularly relates to a nested grid water depth generation method based on the NEMO model. Background Art

[0002] Currently, globally used ocean numerical models such as HYCOM, NEMO, and MOM4 have been widely applied in meteorological and climate forecasting systems and scientific research of various countries and organizations. Under the current situation of increasingly frequent climate change, high-resolution requirements are put forward for ocean numerical models. However, high-resolution ocean numerical models often require a large amount of computing resources. Therefore, nested grid design for local key areas of concern, only increasing the resolution of the local area for model calculation, can effectively balance computing resources and research purposes, which is of great significance for the actual operational operation of the model.

[0003] As an open-source global ocean numerical model, NEMO is widely used in ocean forecasting and ocean research. The new generation of high-resolution global ocean numerical forecasting system in our country also uses the NEMO model. Currently, there are relatively few regional nested designs for the NEMO model at home and abroad. As one of the most critical input data for the nested model, water depth data will directly affect the final operational stability and result accuracy of the model. However, no one has given a complete method for specifically generating a custom nested grid water depth file. This method generates an encrypted nested grid using trinomial interpolation according to parameters such as the custom nested grid range and refinement coefficient, and then performs interpolation smoothing processing based on the publicly available high-resolution water depth data to form nested grid water depth data based on the NEMO model, which is of great help for the high-resolution nested design of ocean numerical models. Summary of the Invention

[0004] In order to conveniently and accurately produce the water depth data of the NEMO model nested grid according to custom parameters, the present invention provides a nested grid water depth generation method based on the NEMO model. This method can quickly and accurately generate nested grid water depth data with different resolution requirements for any regional range, thereby providing water depth data for the nested scheme design of the NEMO model.

[0005] The object of the present invention is achieved through the following technical solutions:

[0006] A nested grid water depth generation method based on the NEMO model, the method successively includes the following steps:

[0007] Step 1: Determine the number of meridional grid points nx and the number of zonal grid points ny of the nested sub-grid according to the given arbitrary range coefficient and refinement coefficient;

[0008] Step 2: Calculate the longitude range [lonmin child , lonmax child and the latitude range [latmin child , latmax child of the nested sub-grid to be constructed;

[0009] Step 3: Determine the longitude and latitude u(x0, y0) of the nested sub-grid using trinomial interpolation based on the number of nested sub-grid points obtained in Step 1 and the longitude and latitude range of the nested sub-grid obtained in Step 2;

[0010] Step 4: Interpolate to the grid points of the nested sub-grid using a high-precision water depth data set; among them, when the high-precision water depth resolution is higher than the nested sub-grid resolution, the water depth value is obtained; when the high-precision water depth resolution is comparable to or lower than the nested sub-grid resolution, the water depth value is obtained;

[0011] Step 5: Link the water depth G1 of the nested sub-grid and the water depth G0 of the parent grid using the linearly connected weight coefficient Wghts;

[0012] Step 6: Smooth the interpolated grid ;

[0013] Step 7: Remove the closed area.

[0014] Furthermore, the number of meridional grid points nx and the number of zonal grid points ny of the nested sub-grid determined in Step 1 according to the given arbitrary range coefficient and refinement coefficient are:

[0015]

[0016]

[0017] Among them, imax and imin are range coefficients, which are the positions of the maximum longitude and minimum longitude of the sub-grid in the parent grid respectively, jmax and jmin are range coefficients, which are the positions of the maximum latitude and minimum latitude of the sub-grid in the parent grid respectively, rho is the refinement coefficient, ghostcells is the number of transition units, and the default value is 2.

[0018] Furthermore, the calculation of the longitude range [lonmin child , lonmax child and the latitude range [latmin child , latmax child of the nested sub-grid described in Step 2 is:

[0019] [lonmin child ,lonmax child =[lon parent (imin,jmin),lon parent (imax,jmax)],

[0020] [latmin child ,latmax child =[lat parent (imin,jmin),lat parent (imax,jmax)];

[0021] where lonmin child , lonmax child and latmin child , latmax child are the minimum and maximum longitude and latitude values of the sub-grid respectively, and lon parent and lat parent are the longitude and latitude values of all grid points of the parent grid.

[0022] Furthermore, according to the number of nested sub-grid points obtained in step 1 and the longitude and latitude range of the nested sub-grid obtained in step 2 in step 3, the longitude and latitude of the nested sub-grid are determined by trinomial interpolation as:

[0023]

[0024] where is the longitude and latitude coordinate to be interpolated in the sub-grid, is the known longitude and latitude coordinate in the parent grid, and using Lagrange polynomials, and are the third-order interpolation coefficients.

[0025] Furthermore, if the high-precision water depth resolution used is higher than the nested sub-grid resolution, the water depth value obtained by interpolating the high-precision water depth dataset to the nested sub-grid grid points in step 4 is:

[0026]

[0027] where is the water depth value calculated after interpolation for the row-th row and col-th column of the sub-grid, is the set of all high-precision water depth data included in the longitude and latitude range from the (row - 1)-th row to the row-th row and from the (col - 1)-th column to the col-th column of the sub-grid, num is the number of elements in this set.

[0028] Further, if the high-precision water depth resolution used is equivalent to or lower than the nested sub-grid resolution, the water depth value obtained by interpolating the high-precision water depth data set to the nested sub-grid grid points described in step 4 is:

[0029]

[0030] where depth(P) is the water depth of any point P to be determined in the nested sub-grid, (a, b) are the longitude and latitude coordinate values of point P, and depth(A), depth(B), depth(C), and depth(D) are the water depth values of the high-precision water depth data points around point P, (a0, b0) are the longitude and latitude coordinate values of point A respectively, (a1, b0) are the longitude and latitude coordinate values of point B respectively, (a1, b1) are the longitude and latitude coordinate values of point C respectively, and (a0, b1) are the longitude and latitude coordinate values of point D respectively.

[0031] Further, the weight coefficient Wghts using linear connection described in step 5 to link the water depth value G1 of the nested sub-grid point and the water depth value G0 of the parent grid point is:

[0032] To ensure the correlation of water depth data between the internal high-resolution sub-grid boundary and the transition unit grid, the water depth data at the sub-grid boundary and the parent grid water depth data are mixed using a linear connection method, and the scheme is as follows:

[0033]

[0034]

[0035] where n is the row / column number where the current data point to be determined is located, nb_connection_pt s is the connected area grid value, rho is the refinement coefficient.

[0036] Further, the interpolation grid described in step 6 is smoothed:

[0037]

[0038] where h represents the water depth value of the current grid point, and ([[]] i, j ) represent the row and column where the current grid point is located respectively.

[0039] Further, the removal of the closed area described in step 7 is:

[0040] Remove the closed water area within the land area in the sub-grid, set its water depth value to zero, and obtain the nested sub-grid water depth.

[0041] The beneficial effects of the present invention are as follows: According to any custom range and refinement coefficient, the range and resolution of the nested sub-grid can be obtained. By combining high-resolution bathymetry data, the bathymetry value of each grid point in the nested sub-grid is calculated and linked to the parent grid, thereby obtaining the bathymetry data of the nested sub-grid. The present invention can be used for the production of bathymetry input files in the nested grid scheme design of the NEMO model. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is the flowchart of the method. DETAILED DESCRIPTION OF THE INVENTION

[0043] The present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments. The objectives and effects of the present invention will become more apparent. The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] The present invention takes the nested sub-grid design of the NEMO model in the western Pacific region as an example. The parent grid is a global ORCA 2°×2° resolution grid, and the sub-grid range coefficient is set to , , j , , and the refinement coefficient is . The high-resolution bathymetry data uses the publicly available ETOPO2 data.

[0045] The specific implementation of the present invention is as follows:

[0046] Step 1: Determine the number of grid points of the nested sub-grid according to the given arbitrary range coefficient and refinement coefficient;

[0047] Determining the number of grid points of the nested sub-grid according to the given arbitrary range coefficient and refinement coefficient as described in Step 1:

[0048]

[0049]

[0050] where nx and ny are the number of grid points in the meridional and zonal directions of the nested sub-grid respectively, imax and imin are the range coefficients, which are the positions of the maximum longitude and minimum longitude of the sub-grid in the parent grid respectively, jmax and jmin are the range coefficients, which are the positions of the maximum latitude and minimum latitude of the sub-grid in the parent grid respectively, rho is the refinement coefficient, ghostcellsis the number of transition units, with a default value of 2. According to the range coefficient and refinement coefficient set in this example, nx and ny can be obtained as 204 and 260 respectively.

[0051] Step 2: Calculate the longitude and latitude range of the nested sub-grid to be constructed;

[0052] The calculation of the longitude and latitude range of the nested sub-grid described in Step 2:

[0053]

[0054]

[0055] Among them, and are the minimum and maximum longitude and latitude values of the sub-grid respectively, and are the longitude and latitude values of all grid points of the parent grid. According to the longitude and latitude of the ORCA 2°×2° parent grid and the sub-grid range coefficient, and can be obtained.

[0056] Step 3: Determine the longitude and latitude of the nested sub-grid using trinomial interpolation based on the sub-grid longitude and latitude range and the number of grid points;

[0057] The determination of the longitude and latitude of the nested sub-grid using trinomial interpolation based on the sub-grid longitude and latitude range and the number of grid points described in Step 3:

[0058]

[0059] Among them, is the longitude and latitude coordinate to be interpolated in the sub-grid, is the known longitude and latitude coordinate in the parent grid. Using Lagrange polynomials, and are the third-order interpolation coefficients. According to the results of the number of sub-grid points and the longitude and latitude range in Step 1 and Step 2, the longitude and latitude values of all grid points of the sub-grid can be calculated.

[0060] Step 4: Interpolate the high-precision water depth data set to the grid points of the nested sub-grid;

[0061] In this case, the resolution of the high-precision water depth used is higher than the resolution of the nested sub-grid. The interpolation of the high-precision water depth data set to the grid points of the nested sub-grid described in Step 4:

[0062]

[0063] Among them, is the water depth value calculated after interpolation for the row row and column rol of the sub-grid, It is a set of all high-precision bathymetric data contained within the longitude and latitude range from the (row - 1)th row to the rowth row and from the (rol - 1)th column to the rolth column of the sub-grid. num is the number of elements in this set. The bathymetric values of each grid point of the nested sub-grid are calculated by looking up the bathymetric values that meet the conditions in the ETOPO2 high-precision bathymetric data according to the longitude and latitude values of each grid point of the sub-grid obtained in Step 3.

[0064] Step 5: Link the bathymetry of the nested sub-grid and the bathymetry of the parent grid;

[0065] Linking the bathymetry of the nested sub-grid and the bathymetry of the parent grid as described in Step 5:

[0066] To ensure the correlation of bathymetric data at the boundaries of the internal high-resolution sub-grid and between transitional unit grids, the bathymetric data at the sub-grid boundaries and the bathymetric data of the parent grid are mixed using a linear connection method. The scheme is as follows:

[0067]

[0068]

[0069] Among them, Wghts is the weight coefficient of the linear connection, n is the row / column number of the current data point to be calculated, nb_ connection_pt s is the grid value of the connection area, rho is the refinement coefficient, G1 represents the bathymetric value of the sub-grid point, and G0 represents the bathymetric value of the parent grid point. The bathymetric values of the sub-grid obtained in Step 4 and the bathymetric values of the parent grid are weighted and calculated in the edge range of the sub-grid to update the bathymetric values in the edge transition area of the sub-grid.

[0070] Step 6: Smooth the interpolated grid;

[0071] Smoothing the interpolated grid as described in Step 6:

[0072]

[0073] Among them, h represents the bathymetric value of the current grid point, ([[]] i, j ) represent the row and column where the current grid point is located respectively. The bathymetric values of the sub-grid obtained in Step 5 are smoothed and calculated to eliminate sudden changes or abnormal data that may occur due to encrypted interpolation of bathymetry.

[0074] Step 7: Remove closed areas;

[0075] Removing closed areas as described in Step 7:

[0076] Remove the enclosed water areas within the land areas in the sub-grid, set their water depth values to zero, and obtain the final nested sub-grid water depth.

[0077] By comparing the water depth distribution results of the nested sub-grid of the current instance with those of the original parent grid, the results show that the water depth within the nested sub-grid range is significantly densified, the resolution of the densified area reaches 0.25°×0.25°, and there is a transition area with the parent grid at the edge. Therefore, under this instance, the nested grid water depth data based on the NEMO model has been generated.

[0078] The above is the description of the embodiments of the present invention. Through the above description of the disclosed embodiments, those skilled in the art can implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel points disclosed herein.

Claims

1. A nested grid water depth generation method based on the NEMO model, characterized in that, The method sequentially includes the following steps: Step 1: Determine the number of meridional grid points nx and the number of zonal grid points ny of the nested sub-grid according to the given arbitrary range coefficient and refinement coefficient; Step 2: Calculate the longitude range [lonmin child , lonmax child and the latitude range [latmin child , latmax child ; Step 3: According to the number of nested sub-grid points obtained in Step 1 and the longitude and latitude range of the nested sub-grid obtained in Step 2, use trinomial interpolation to determine the longitude and latitude u(x0,y0) of the nested sub-grid; nested The longitude and latitude u(x0,y0) of the sub-grid is: ； Among them, u(x0,y0) is the longitude and latitude coordinates to be interpolated in the sub-grid, and u(x i ,y j ) are the known longitude and latitude coordinates in the parent grid. Using Lagrange polynomials, and ; is the third-order interpolation coefficient; Step 4: Interpolate the high-precision water depth data set to the nested sub-grid grid points; where, when the high-precision water depth resolution is higher than the nested sub-grid resolution, the water depth value depth(row,rol) is obtained; when the high-precision water depth resolution is the same as or lower than the nested sub-grid resolution, the water depth value depth(P) is obtained; The water depth value depth(row,rol) is: ； Among them, depth(row, rol) is the water depth value calculated after interpolation at the row-th row and rol-th column of the sub-grid, and depth high is the set of all high-precision water depth data included within the longitude and latitude range from the (row - 1)-th row to the row-th row and from the (rol - 1)-th column to the rol-th column of the sub-grid, and num is the number of elements in this set; The water depth value depth(P) is: ； where, depth(P) is the water depth of any point P to be determined in the nested sub-grid, (a,b) is the longitude and latitude coordinate value of point P, depth(A), depth(B), depth(C), depth(D) are the water depth values of the high-precision water depth data points around point P respectively, (a0,b0) are the longitude and latitude coordinate values of point A respectively, (a1,b0) are the longitude and latitude coordinate values of point B respectively, (a1,b1) are the longitude and latitude coordinate values of point C respectively, (a0,b1) are the longitude and latitude coordinate values of point D respectively; Step 5: Use the linearly connected weight coefficient Wghts to link the water depth value G1 of the nested sub-grid points and the water depth value G0 of the parent grid points; ； G1 = (1 - Wghts) × G1 + Wghts × G0 where, n is the row / column number of the current data point to be determined, nb_connection_pts is the grid value of the connection area, and rho is the refinement coefficient; Step 6: Smooth the interpolated grid h(i,j); ； where, h represents the water depth value of the current grid point, and (i,j) represent the row and column where the current grid point is located respectively; Step 7: Remove the closed area.

2. The nested grid water depth generation method based on the NEMO model according to claim 1, wherein: The number of meridional grid points nx and the number of zonal grid points ny are: nx = (imax - imin) × rho + ghostcells × 2, ny = (jmax - jmin) × rho + ghostcells × 2; where, imax and imin are range coefficients, which are the positions of the maximum longitude and minimum longitude of the sub-grid in the parent grid respectively, jmax and jmin are range coefficients, which are the positions of the maximum latitude and minimum latitude of the sub-grid in the parent grid respectively, rho is the refinement coefficient, and ghostcells is the number of transition units, defaulting to 2.

3. A nested grid water depth generation method based on the NEMO model according to claim 1, characterized in that: The calculation described in Step 2 requires constructing the longitude range [lonmin child , lonmax child and the latitude range [latmin child , latmax child as follows: [lonmin child ,lonmax child = [lon parent (imin,jmin),lon parent (imax,jmax)], [latmin child ,latmax child = [lat parent (imin,jmin),lat parent (imax,jmax)]; Among them, lonmin child , lonmax child and latmin child , latmax child are the minimum and maximum longitude and latitude values of the sub-grid respectively, and lon parent and lat parent are the longitude and latitude values of all grid points of the parent grid.

4. A nested grid water depth generation method based on the NEMO model according to claim 1, characterized in that: The removing of the closed area described in Step 7 is: Removing the closed water area within the land area in the sub-grid, setting its water depth value to zero, and obtaining the nested sub-grid water depth.

5. A computer device, comprising a memory, a processor, and a computer program stored on the memory, characterized in that, The processor executes the computer program to implement the method described in any one of claims 1-4.

6. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instruction is executed by a processor, it implements the method described in any one of claims 1-4.

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