Sea level budget closure calculation method and system based on spherical harmonic domain adjustment inversion

Abstract

The application provides a sea level budget closure calculation method and system based on spherical harmonic domain adjustment inversion, and belongs to the technical field of sea level budget calculation; the method comprises the following steps: obtaining independent observation sea level data of each multivariate component in sea level rise; converting the independent observation sea level data of each multivariate component in the obtained sea level rise together with the overall sea level rise rate from a spatial domain to a spherical harmonic domain to obtain corresponding spherical harmonic coefficients; constructing an error equation based on the spherical harmonic coefficients, and solving the error equation based on indirect adjustment theory to obtain correction coefficients corresponding to each multivariate component; and correcting the observation values of each multivariate component and converting them back to the spatial domain to determine the budget results of the corrected sea level multivariate components. Through error distribution, the application can inversely obtain more accurate proportions of each multivariate component in the sea level rise process, thereby providing theoretical support for related research on sea level rise.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of sea level budget calculation, and particularly relates to a sea level budget closure calculation method and system based on spherical harmonic domain adjustment inversion. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute the prior art.

[0003] Sea level rise is one of the more serious environmental challenges under the current global climate change background, which will pose a serious threat to low-lying coastal areas. There are many factors causing sea level rise, including changes in seawater temperature and salinity, changes in seawater density, changes in seawater quality caused by mountain glaciers, polar ice caps, and land hydrology, and changes in vertical displacement of land. Therefore, in order to accurately assess the causes and future trends of sea level rise, it is necessary to accurately quantify various contributing components.

[0004] However, the existing technical means are mostly simple combinations of independent observation data sets of various contributing components, and the sea level budget results obtained by simply combining various independent observation data sets mostly have large closure differences, which is due to the errors of each independent observation method. Therefore, the existing technology cannot achieve the closure of the sea level budget and the accurate quantification of various contributing components causing sea level rise. SUMMARY

[0005] In order to overcome the shortcomings of the prior art, the present application provides a sea level budget closure calculation method and system based on spherical harmonic domain adjustment inversion, establishes an error equation, corrects the errors of various contributing components based on the indirect adjustment method, and through the error correction in the adjustment process, more accurate proportions of each multicomponent in the sea level rise process can be obtained by inversion, thereby providing theoretical support for related research on sea level rise.

[0006] To achieve the above object, one or more embodiments of the present application provide the following technical solutions:

[0007] The present application provides a sea level budget closure calculation method based on spherical harmonic domain adjustment inversion.

[0008] The sea level budget closure calculation method based on spherical harmonic domain adjustment inversion comprises:

[0009] Obtaining independent observation sea level data of each multicomponent in the sea level rise;

[0010] Converting each independent observation sea level data of the multicomponent together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain the corresponding spherical harmonic coefficients;

[0011] constructing an error equation based on the obtained spherical harmonic coefficients, and solving the error equation based on an indirect adjustment theory to obtain correction coefficients corresponding to each of the multiple components;

[0012] correcting the observation values of each of the multiple components by using the obtained correction coefficients and converting back to the spatial domain to determine the balance results of the corrected sea level of each of the multiple components, and realizing the closed calculation of the sea level balance.

[0013] Further, the multiple components include the Antarctic ice sheet, the Greenland ice sheet, the mountain glacier, the land hydrology and the dynamic sea level, wherein the dynamic sea level represents the sea level rise caused by the temperature and salinity changes of seawater and the ocean circulation.

[0014] Further, the conversion from the spatial domain to the spherical harmonic domain includes: setting a maximum expansion order, and using the spherical harmonic function expansion method to convert the independent observation sea level data of each of the multiple components in the spatial domain together with the overall sea level rise rate obtained by satellite altimetry observation to the spherical harmonic domain.

[0015] Further, the error equation is an indirect adjustment model, and specifically: the observation values of the indirect adjustment model are composed of satellite altimetry data, and the coefficient matrix of the indirect adjustment model is composed of the sea level height data of each of the multiple components.

[0016] Further, when solving the error equation based on the indirect adjustment theory, a regularization parameter is introduced to perform regularization processing on the error equation, so as to ensure that the result has statistical significance.

[0017] Further, the value of the regularization parameter is determined by a cross-validation method.

[0018] Further, solving the correction coefficients corresponding to each of the multiple components based on the indirect adjustment theory includes: forming an error equation by using the data of each grid point in the adjustment inversion process, so that all the marine grid points jointly form an equation group, and the least square adjustment method is used to solve the adjustment solution.

[0019] The second aspect of the present application provides a sea level balance closed calculation system based on spherical harmonic domain adjustment inversion.

[0020] The sea level balance closed calculation system based on spherical harmonic domain adjustment inversion includes:

[0021] The data acquisition module is configured to: acquire independent observation sea level data of each of the multiple components in the sea level rise;

[0022] The spherical harmonic domain conversion module is configured to: convert the independent observation sea level data of each of the multiple components together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain corresponding spherical harmonic coefficients;

[0023] The adjustment inversion module is configured to: construct an error equation based on the obtained spherical harmonic coefficients, and solve the error equation based on an indirect adjustment theory to obtain correction coefficients corresponding to each multi-element component;

[0024] The sea level balance calculation module is configured to: correct the observation values of each multi-element component and convert them back to the spatial domain by using the obtained correction coefficients, determine the balance results of each multi-element component of the corrected sea level, and realize sea level balance calculation.

[0025] The third aspect of the present application provides a computer readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the sea level balance calculation method based on spherical harmonic domain adjustment inversion as described in the first aspect of the present application.

[0026] The fourth aspect of the present application provides an electronic device comprising a memory, a processor, and a program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps in the sea level balance calculation method based on spherical harmonic domain adjustment inversion as described in the first aspect of the present application.

[0027] The above one or more technical solutions have the following beneficial effects:

[0028] The present application converts the obtained various independent observation data and the overall sea level rise rate of satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain corresponding spherical harmonic coefficients, constructs an error equation based on the obtained spherical harmonic coefficients, solves the error equation to obtain correction coefficients of each multi-element component, corrects each multi-element component, and thereby inversely obtains more accurate proportions of each multi-element component in the sea level rise process. The present application breaks through the limitation of the prior art that only data superposition is performed to estimate the component proportions, and the optimal correction coefficients of each component obtained by adjustment inversion can statistically and accurately evaluate the contribution proportions of the Antarctic ice sheet, the Greenland ice sheet, mountain glaciers, land hydrology, and dynamic sea level, thereby greatly improving the accuracy and reliability of sea level change attribution analysis.

[0029] The advantages of the additional aspects of the present application will be partially given in the following description, partially will become apparent from the following description, or will be understood by the practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings, which form a part of the specification, are included to provide a further understanding of the application and are incorporated herein for explanation by illustrating a preferred embodiment of the present application.

[0031] Figure 1 A flowchart of the sea level balance calculation method based on spherical harmonic domain adjustment inversion in the embodiment one of the present application.

[0032] Figure 2 Figure 4 is a diagram showing the change of correction coefficient with the regularization parameter for the embodiment one of the present application.

[0033] Figure 3 Figure 5 is a diagram showing the global mean sea level budget in the satellite altimetry era in the prior art.

[0034] Figure 4 Figure 6 is a diagram showing the global mean sea level budget in the satellite altimetry era after inversion by adjustment in the embodiment one of the present application.

[0035] Figure 5 Figure 7 is a diagram showing the mean sea level budget in a certain region in the satellite altimetry era in the prior art.

[0036] Figure 6 Figure 8 is a diagram showing the mean sea level budget in a certain region in the satellite altimetry era after inversion by adjustment in the embodiment one of the present application. DETAILED DESCRIPTION

[0037] It should be noted that the following detailed description is merely exemplary in nature and is intended to provide further description of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0038] It is to be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application.

[0039] In the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0040] Overall idea: Considering that there is a large closing error between the sum of each component observed based on independent technical means and the sea level rise rate observed by satellite altimetry in the satellite altimetry era, the present application provides a sea level budget closing calculation method based on spherical harmonic domain adjustment inversion, a sea level budget closing model based on spherical harmonic domain adjustment inversion to reduce the sea level budget closing error and further accurately invert the proportion of each component of sea level rise, i.e., first, obtaining independent observations of each component of sea level rise based on various independent observations; then, converting all components and the total sea level rise rate observed by satellite altimetry into the spherical harmonic domain, constructing an error equation using all spherical harmonic coefficients and performing adjustment calculation; finally, correcting each component using the correction coefficient calculated by the error equation to obtain the sea level budget result after adjustment.

[0041] Embodiment one

[0042] The present embodiment discloses a sea level budget closing calculation method based on spherical harmonic domain adjustment inversion.

[0043] As Figure 1 shown in the figure, the sea level budget closure calculation method based on spherical harmonic domain adjustment inversion includes:

[0044] Obtaining independent observation sea level data of each multi-component in sea level rise;

[0045] Converting each independent observation sea level data of the multi-component together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain the corresponding spherical harmonic coefficients;

[0046] Based on the obtained spherical harmonic coefficients, an error equation is constructed, and the error equation is solved based on the indirect adjustment theory to obtain the correction coefficients corresponding to each multi-component;

[0047] The observation values of each multi-component are corrected using the obtained correction coefficients and converted back to the spatial domain to determine the budget results of each multi-component of the corrected sea level, and the sea level budget closure calculation is realized.

[0048] Based on the above process, the established indirect adjustment framework can be used to obtain more accurate proportions of each multi-component in the sea level rise process, thereby providing theoretical support for related research on sea level rise. In order to facilitate the understanding of the technical scheme of the present application, the specific implementation method in the technical scheme of the present application will be further explained and described below.

[0049] Step S1, obtaining independent observation sea level data of each multi-component in sea level rise.

[0050] In this embodiment, the satellite altimetry data is obtained from the website data provided by AVISO organization, the dynamic sea level data is obtained from the website data provided by SODA and IAP organizations, the south and north polar ice cap data is obtained from the website data provided by IMBIE organization, the mountain glacier data is obtained from the website data provided by Malles & Marzeion and GlaMBIE Team, and the land hydrology data is obtained from the website data provided by Humphrey & Gudmundsson.

[0051] Step S2, converting each independent observation sea level data of the multi-component together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain the corresponding spherical harmonic coefficients.

[0052] Firstly, the sea level change data set in the spatial domain is converted to the spherical harmonic domain, and all spherical harmonic coefficients are used for adjustment inversion. The expression form of SHF (spherical harmonic function) in the sea level rise research is:

[0053] (1)

[0054] Wherein, SLRepresents sea level observations; N It is the maximum expansion order of the spherical harmonic function SHF. In this embodiment, N The value was set to 120; and This indicates the spherical harmonic coefficients that need to be calculated; express n Step m The accompanying Legendre polynomial of degree 1; Indicates latitude, Indicates longitude. m Indicates the number of times.

[0055] With variables x of n Step m The associated Legendre polynomial of degree 1 can be expressed as:

[0056] (2)

[0057] in, Indicates having variables x of n Step m The accompanying Legendre polynomial of degree 1; Indicates having variables x of n The order-wise adjoint Legendre polynomial is expressed as:

[0058] (3)

[0059] For ease of understanding, the following will use second-order ( n =2) Taking the expansion of the truncated equation (1) as an example:

[0060] (4)

[0061] This invention utilizes indirect adjustment to solve for the spherical harmonic coefficients in equation (4). The expression for indirect adjustment is:

[0062] (5)

[0063] In this example, L Representative observation, that is SL ; V Represents measurement error. Coefficient matrix. A and spherical harmonic coefficients X It can be represented as follows:

[0064] (6)

[0065] (7)

[0066] in,A which can be calculated according to the longitude and latitude of the grid point; X represent the spherical harmonic coefficients corresponding to the second-order spherical harmonic function, the data on each grid point corresponds to an error equation, all grid points form a plurality of error equations, and the spherical harmonic coefficient matrix can be calculated through the least square principle X :

[0067] (8)

[0068] wherein, P represents a unit weight matrix.

[0069] X After the solution is completed, the spherical harmonic function expression shown in formula (1) is substituted, and the sea level value of any longitude and latitude can be obtained.

[0070] Step S3, based on step S2, each component and satellite altimetry observation overall sea level rate are all converted into corresponding spherical harmonic coefficients, and error equations are further constructed based on the obtained spherical harmonic coefficients; the error equations are solved through indirect adjustment to obtain the correction coefficients corresponding to each multivariate component; the observation values of each multivariate component are modified and converted back to the spatial domain using the obtained correction coefficients, so that the balance results of the modified sea level each multivariate component can be determined, and the sea level balance closed calculation is realized.

[0071] The present application utilizes indirect adjustment equations to adjust and inverse each component of the sea level rise, and distributes the closed difference of the sea level balance to each component. Specifically, the error equation of indirect adjustment can be expressed in the form of formula (5).

[0072] In this embodiment, the quantities in the error equation of formula (5) are redefined, that is, the observation value is represented by L The present application uses satellite altimetry sea level height data provided by AVISO; the coefficient matrix is represented by A , which contains the sea level height data of each component; and the correction coefficient of each component is represented by X . They can be represented as follows:

[0073] (9)

[0074] (10)

[0075] Due to the ill-conditioned problem of the coefficient matrix A , the adjustment result may lose statistical significance. Therefore, the regularization parameter is introduced into the error equation, which is specifically shown as follows:

[0076] (11)

[0077] wherein, kdenotes a regularization parameter, I denotes an identity matrix.

[0078] To further prove the significant effect of the present application, the following experiments were performed in the present embodiment:

[0079] 1) Selection of the regularization parameter.

[0080] As shown in Figure 2 , the correction coefficient X varies with the regularization parameter k . The results show that when the regularization parameter k is set to 0, the correction coefficient X is too large and lacks statistical significance, which is caused by the ill-conditioned problem of the coefficient matrix A . With the increase of the regularization parameter k , the correction coefficient X tends to 1 and gradually stabilizes, and meanwhile shows a relatively significant statistical significance. Therefore, the selected regularization parameter K value of the present application is about 14000.

[0081] 2) Comparison of the global and specific regional sea level budget results before and after adjustment.

[0082] As shown in Figure 3 , Figure 4 , the global average SLB (sea level budget) schematic diagrams before and after adjustment in the satellite altimetry era are shown respectively. Among them, AVISO represents the satellite altimetry observed sea level height data, SUM represents the sum of all components of sea level rise, and the difference between the two is the closure error. From the comparison results of Figure 4 and Figure 3 , it can be seen that after adjustment, the global sea level budget closure error is reduced from 0.32 mm / yr to 0.14 mm / yr.

[0083] ​The global adjustment inversion result of the present application reveals that: the global sea level rise is mainly dominated by the SDSL (dynamic sea level) component, with a rate of about 1.47 mm / yr, accounting for about 44% of the global sea level rise; the remaining about 56% contribution is attributed to the ocean mass increase, which is mainly contributed by the Glacier (mountain glacier) component, with a rate of 0.92 mm / yr, accounting for about 28%. The rates of GrIS (Greenland ice sheet) component and AIS (Antarctic ice sheet) component are 0.56 mm / yr and 0.13 mm / yr, respectively, accounting for 17.1% and 3.9%, respectively. The time series of GrIS, AIS and Glacier all show obvious acceleration trend, which is also a strong evidence of global warming intensification. The time series of TWS (terrestrial hydrology) has no obvious trend, and its contribution in the whole period of 1993-2022 is the lowest, with a rate of about 0.08 mm / yr.

[0084] As shown in Figure 5 and Figure 6 respectively, the sea level budget before and after adjustment of a certain regional coastal area in satellite altimetry era is shown. By Figure 6 and Figure 5 comparison, it can be seen that after adjustment, the sea level budget closure difference of a certain regional coastal area decreases from 0.36 mm / yr to 0.07 mm / yr. The result after adjustment inversion shows that among the sea level rise of a certain regional coastal area, the contributions of SDSL (dynamic sea level) component and Glacier (mountain glacier) component are the largest, which is similar to the global sea level budget result.

[0085] 3) The adjustment inversion result of the present application is compared with the prior art.

[0086] In order to verify the reliability of the inverted results of each component, the satellite altimetry era global sea level budget result obtained by adjustment inversion in the present embodiment is compared with the prior art, as shown in Table 1.

[0087] Table 1 Comparison of adjustment results

[0088]

[0089] Table 1 shows the difference between the adjustment inversion results of the present application and the prior art in the same time period. Among them, all the comparisons show that the closure error of the results obtained by the present application is smaller in the same time period, and the time period covered by the present application is the longest. The SDSL component and the Glacier component are slightly larger than the prior art, the TWS component is slightly smaller than the prior art, and the rest of the components have little difference from the prior art, which also proves the reliability of the results obtained by the present application. It should be particularly pointed out that the SDSL component used in the present study includes ocean density changes and ocean circulation changes driven by surface pressure (such as wind, sea level pressure, and density difference), while most of the prior art only analyzes spatial ocean changes caused by seawater specific volume changes.

[0090] In the adjustment inversion results of the present application, the SDSL and Glacier components are considered to be the main driving factors of sea level rise, and it is believed that these two components show stronger sensitivity to global warming acceleration. This is also supported by the fact that more than 90% of the heat captured by greenhouse gases is absorbed by the ocean, which drives ocean thermal expansion; mountain glaciers are mainly distributed in low and middle latitudes, and are more sensitive to global warming, which leads to the dominant contribution of mountain glacier ablation to sea level rise.

[0091] By comparing with the results of previous studies, it is proved that the results obtained by the adjustment inversion framework established in the present application have strong reliability. The indirect adjustment method can be well applied to reducing the sea level budget closure error and accurately inverting the proportion of each component of sea level rise. From the above comparative analysis, it can be seen that the adjustment inversion framework established in the present application has good effect on reducing the sea level budget closure error in the global and specific regional coastal areas, that is, the present application can obtain more accurate proportion of each multi-component in the process of sea level rise through indirect adjustment, thereby providing theoretical support for the related research of sea level rise.

[0092] Embodiment Two

[0093] The embodiment discloses a sea level budget closure calculation system based on spherical harmonic domain adjustment inversion.

[0094] The sea level budget closure calculation system based on spherical harmonic domain adjustment inversion comprises:

[0095] The data acquisition module is configured to acquire independent observation sea level data of each multi-component in sea level rise;

[0096] The spherical harmonic domain conversion module is configured to convert each independent observation sea level data of the multi-component together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain to obtain the corresponding spherical harmonic coefficients;

[0097] The adjustment inversion module is configured to construct an error equation based on the obtained spherical harmonic coefficients, and perform adjustment solving on the error equation based on an indirect adjustment theory to obtain correction coefficients corresponding to each multivariate component;

[0098] The sea level balance calculation module is configured to correct the observation values of each multivariate component and convert them back to the spatial domain by using the obtained correction coefficients, determine the balance results of each multivariate component of the sea level after correction, and realize sea level balance calculation.

[0099] Embodiment three

[0100] An objective of this embodiment is to provide a computer-readable storage medium.

[0101] A computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the steps in the sea level balance calculation method based on spherical harmonic domain adjustment inversion as described in Embodiment One of the present disclosure.

[0102] Embodiment four

[0103] An objective of this embodiment is to provide an electronic device.

[0104] An electronic device, comprising a memory, a processor, and a program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps in the sea level balance calculation method based on spherical harmonic domain adjustment inversion as described in Embodiment One of the present disclosure.

[0105] The steps and methods involved in the above embodiments two, three and four correspond to Embodiment One, and the specific implementation can be referred to the relevant description part of Embodiment One. The term "computer-readable storage medium" should be understood as including a single medium or multiple media of one or more instruction sets; and should also be understood as including any medium capable of storing, encoding or carrying instruction sets for execution by a processor and causing the processor to perform any method in the present disclosure.

[0106] Those skilled in the art should understand that each module or step of the present disclosure described above can be implemented by a general computer device, and alternatively, they can be implemented by program codes executable by a computing device, so that they can be stored in a storage device for execution by a computing device, or they can be respectively manufactured into individual integrated circuit modules, or a plurality of modules or steps among them can be manufactured into a single integrated circuit module. The present disclosure is not limited to any specific combination of hardware and software.

[0107] The above describes the specific embodiments of the present application in combination with the drawings, but is not a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications or variations made by those skilled in the art on the basis of the technical solutions of the present application without creative labor are still within the protection scope of the present application.

Claims

1. A method for calculating sea level budget closure based on spherical harmonic domain adjustment inversion, characterized in that, The method comprises the following steps: obtaining independent observation sea level data of each multi-component in sea level rise; the multi-component comprises an Antarctic ice sheet, a Greenland ice sheet, a mountain glacier, land hydrology and a dynamic sea level; converting each independent observation sea level data of the multi-component together with an overall sea level rise rate obtained by satellite altimetry observation from a spatial domain to a spherical harmonic domain to obtain corresponding spherical harmonic coefficients; constructing an error equation based on the obtained spherical harmonic coefficients, and solving the error equation based on an indirect adjustment theory to obtain correction coefficients corresponding to each multi-component; the error equation is an indirect adjustment model, specifically, observation values of the indirect adjustment model are constituted by satellite altimetry data, and a coefficient matrix of the indirect adjustment model is constituted by sea level height data of each multi-component; wherein solving the correction coefficients corresponding to each multi-component based on the indirect adjustment theory comprises: forming an error equation by data of each grid point in an adjustment inversion process, making all marine grid points jointly constitute an equation set, and solving an adjustment solution by using a least square adjustment method; correcting the observation values of each multi-component by using the obtained correction coefficients and converting them back to the spatial domain to determine a balance result of each multi-component of the corrected sea level, and realizing closed calculation of sea level balance.

2. The method for sea level mass balance closure computation based on spherical harmonic domain adjustment inversion according to claim 1, wherein, Converting from the spatial domain to the spherical harmonic domain comprises: setting a maximum expansion order, and adopting a spherical harmonic function expansion method to convert each independent observation sea level data of the multi-component together with the overall sea level rise rate obtained by satellite altimetry observation from the spatial domain to the spherical harmonic domain.

3. The method of claim 1, wherein, When solving the error equation based on the indirect adjustment theory, a regularization parameter is introduced to perform regularization processing on the error equation.

4. The method of claim 3, wherein, The value of the regularization parameter is determined by a cross-validation method.

5. A system for computing sea level budget closure based on spherical harmonic domain adjustment inversion, characterized in that, The method comprises the following steps: a data acquisition module configured to obtain independent observation sea level data of each multi-component in sea level rise; the multi-component comprises an Antarctic ice sheet, a Greenland ice sheet, a mountain glacier, land hydrology and a dynamic sea level; a spherical harmonic domain conversion module configured to convert each independent observation sea level data of the multi-component together with an overall sea level rise rate obtained by satellite altimetry observation from a spatial domain to a spherical harmonic domain to obtain corresponding spherical harmonic coefficients; an adjustment inversion module configured to construct an error equation based on the obtained spherical harmonic coefficients, and solve the error equation based on an indirect adjustment theory to obtain correction coefficients corresponding to each multi-component; the error equation is an indirect adjustment model, specifically, observation values of the indirect adjustment model are constituted by satellite altimetry data, and a coefficient matrix of the indirect adjustment model is constituted by sea level height data of each multi-component; wherein solving the correction coefficients corresponding to each multi-component based on the indirect adjustment theory comprises: forming an error equation by data of each grid point in an adjustment inversion process, making all marine grid points jointly constitute an equation set, and solving an adjustment solution by using a least square adjustment method; a sea level balance closed calculation module configured to correct the observation values of each multi-component by using the obtained correction coefficients and convert them back to the spatial domain to determine a balance result of each multi-component of the corrected sea level, and realizing closed calculation of sea level balance.

6. A computer-readable storage medium having stored thereon a program, characterized in that, The program, when executed by the processor, implements the steps in the sea level budget closure calculation method based on spherical harmonic domain adjustment inversion according to any one of claims 1-4.

7. An electronic device comprising a memory, a processor, and a program stored in the memory and capable of running on the processor, characterized by The processor implements the steps in the sea level budget closure calculation method based on spherical harmonic domain adjustment inversion according to any one of claims 1-4 when executing the program.

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