CN116304491A - Assimilation method and system for marine anomaly observation data - Google Patents

Assimilation method and system for marine anomaly observation data Download PDF

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CN116304491A
CN116304491A CN202310525860.6A CN202310525860A CN116304491A CN 116304491 A CN116304491 A CN 116304491A CN 202310525860 A CN202310525860 A CN 202310525860A CN 116304491 A CN116304491 A CN 116304491A
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杜梦蛟
文仁强
梁犁丽
易侃
张子良
张皓
王浩
陈圣哲
殷兆凯
杨恒
李梦杰
刘琨
李洲
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Beijing Gezhouba Electric Power Rest House
China Three Gorges Corp
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Abstract

The invention discloses an assimilation method and system of marine anomaly observation data, wherein the method comprises the following steps: acquiring abnormal marine surface observation data and long-term weather average data of the abnormal marine surface observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode; optimizing the basic theoretical equation of the set optimal interpolation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula; and assimilating the pretreated marine surface abnormal observation data according to the long-term weather average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface observation data to obtain an analysis field. The assimilation method and the assimilation system provided by the invention can be used for quickly and effectively adjusting the simulation error of the abnormal observation data of the ocean surface layer in the ocean numerical mode, greatly reducing the calculation process and the time of operation, and having certain economic value.

Description

Assimilation method and system for marine anomaly observation data
Technical Field
The invention relates to the technical field of ocean numerical simulation and offshore wind energy resource utilization, in particular to an assimilation method and an assimilation system of ocean anomaly observation data.
Background
In the ocean numerical mode, certain ocean observation data are assimilated, so that the simulation result of the ocean numerical mode can be improved better. However, due to the influence of the physical frame, lattice resolution, parameter selection, driving data and other factors of the ocean numerical mode, errors can be inevitably generated in the simulation of the ocean surface layer observation data, and the difference between the ocean surface layer observation data and the actual ocean surface layer observation data is caused, so that the overall performance of the mode simulation is influenced, and adverse effects are caused on subsequent research analysis, prediction and early warning.
Currently, when assimilating marine surface observations, the manner of assimilating data is generally divided into two methods, namely, directly assimilating full-field marine surface observations and assimilating marine surface anomaly observations, due to the differences in data types, although the assimilation algorithms employed differ (e.g., three-dimensional variation assimilation method, set optimal interpolation method, etc.). The method for assimilating the full-field ocean surface layer observation data is relatively simple and convenient, but the specific change condition of relevant parameters in an ocean mode cannot be effectively described, and the assimilation ocean surface layer abnormal observation can better reflect the characteristic that physical elements on the ocean upper layer change along with climate, but the assimilation method needs to process the abnormal observation data so as to accord with the reasonable numerical range of real ocean two-dimensional parameters, and compared with the direct assimilation of the abnormal observation data, the mode operation breakdown can be caused, the operation calculation process is more complicated, the occupied calculation amount is larger, and the calculation time is longer.
Disclosure of Invention
Therefore, the invention provides an assimilation method and system for the marine anomaly observation data, which can be used for quickly and effectively adjusting the simulation errors of the marine surface anomaly observation data in the marine numerical mode, so that the simulation and forecast capacity of the marine numerical mode on the upper marine physical elements and the climate change and disaster early warning thereof is improved, the calculation process and time of operation are greatly reduced, and the assimilation method and system have certain economic value, so as to solve the technical problems in the background.
In order to achieve the above purpose, the present invention provides the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for assimilating marine anomaly observation data, including:
acquiring abnormal marine surface observation data and long-term weather average data of the abnormal marine surface observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode;
optimizing the basic theoretical equation of the set optimal interpolation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula;
assimilating the pretreated marine surface abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface observation data to obtain an analysis field.
Preferably, the data processing requirement of the ocean numerical mode is that the grid point horizontal interpolation is carried out on the abnormal observation data of the ocean surface layer and the long-term weather average data of the observation data of the ocean surface layer based on a linear interpolation method.
Preferably, the process of obtaining the optimization formula includes:
optimizing a set optimal interpolation basic theory equation according to the physical characteristics of the abnormal marine surface observation data and the marine surface observation data, wherein the set optimal interpolation basic theory equation is as follows:
Figure SMS_1
wherein ,λrepresenting the state quantity of the mode, superscript
Figure SMS_2
、bAndorepresenting the analysis, origin and observation respectively,Brepresenting a pattern full-field error matrix,Crepresenting a dimensionless function for a model full field error matrixBThe simplification of the area is carried out and,Prepresenting an observation operator, which is used for adjusting the observation data according to the mode requirement format,Tthe symbols are transposed on behalf of the matrix,Rrepresenting the observed covariance matrix of the image,αrepresenting relative coefficients for adjusting the relative magnitude between the original error and the observed error of the mode, and determining according to the type of the marine surface layer observed data and the corresponding practical application thereof;
adjusting term for basic theoretical equation of set optimal interpolation
Figure SMS_3
Simplifying to obtain an optimization formula:
Figure SMS_4
wherein ,
Figure SMS_5
represents the adjustment value of the observation data of the ocean surface layer,Xrepresenting the observation data of ocean surface layer, superscriptoAndbrepresenting the original values of the observation and the mode, respectively, +.>
Figure SMS_6
、/>
Figure SMS_7
and />
Figure SMS_8
The two-dimensional full-field value of the ocean surface data, the abnormal value of the ocean surface data and the long-term climate average value of the ocean surface data are represented respectively.
Preferably, the process of assimilating the pretreated marine surface anomaly observation comprises: long-term climate average value of marine surface layer data in optimization formula based on long-term climate average data of marine surface layer observation data
Figure SMS_9
Performing deviation correction to enable +.>
Figure SMS_10
The term tends to 0, and the pretreated marine surface abnormal observation data is directly assimilated on the basis.
Preferably, the preset operation time of the marine numerical mode setting includes: the timing of assimilation or the period of assimilation.
Preferably, the types of marine surface observations include: altitude observations, salinity observations, temperature observations, and flow field observations.
Preferably, the marine numerical mode comprises: LICOM mode, HYCOM mode, and ROMS mode.
In a second aspect, an embodiment of the present invention provides an assimilation system for marine anomaly observation data, including:
the data acquisition and processing module is used for acquiring abnormal marine surface layer observation data and long-term weather average data of the marine surface layer observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode;
the set optimal interpolation optimization module is used for optimizing a set optimal interpolation basic theoretical equation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula;
the abnormal observation data assimilation module is used for assimilating the pretreated marine surface layer abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface layer observation data to obtain an analysis field.
In a third aspect, an embodiment of the present invention provides a computer apparatus, including: the marine anomaly observation data assimilation method comprises the steps of at least one processor and a memory in communication connection with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the marine anomaly observation data assimilation method according to the first aspect of the embodiment of the invention.
In a fourth aspect, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing a computer to execute the assimilation method of the marine anomaly observation material of the first aspect of the embodiments of the present invention.
The technical scheme of the invention has the following advantages:
the invention provides an assimilation method and system of marine anomaly observation data, wherein the assimilation method comprises the following steps: acquiring abnormal marine surface observation data and long-term weather average data of the abnormal marine surface observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode; optimizing the basic theoretical equation of the set optimal interpolation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula; assimilating the pretreated marine surface abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface observation data to obtain an analysis field. The assimilation method and the assimilation system provided by the invention can be used for quickly and effectively adjusting the simulation errors of the abnormal observation data of the ocean surface layer in the ocean numerical mode, so that the simulation and forecast capability of the ocean numerical mode on the upper ocean physical elements and the climate change and disaster early warning thereof is improved, the operation calculation process and time are greatly reduced, and the method and the system have certain economic value.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for assimilating marine anomaly observation data provided in an embodiment of the present invention;
FIG. 2 is a schematic diagram of assimilation results of marine surface height anomaly observations provided in an embodiment of the present invention;
FIG. 3 is a schematic diagram of assimilation results of abnormal observation of ocean surface temperature provided in the example of the present invention;
FIG. 4 is a schematic illustration of the results of assimilation of marine surface salinity anomaly observations provided in an embodiment of the present invention;
FIG. 5 is a schematic diagram of assimilation results of abnormal observations of a marine surface flow field provided in an embodiment of the present invention;
FIG. 6 is a block diagram of an assimilation system for marine anomaly observation provided in an embodiment of the present invention;
FIG. 7 is a block diagram of one specific example of a computer device provided in an embodiment of the present invention.
Detailed Description
In order to make the present invention better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments, but not intended to limit the scope of the present disclosure. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Example 1
The embodiment of the invention provides an assimilation method of marine anomaly observation data, which is shown in figure 1 and comprises the following steps:
step S1: acquiring abnormal marine surface observation data and long-term weather average data of the abnormal marine surface observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode.
In this embodiment, the types of marine surface observations include: altitude observations, salinity observations, temperature observations, and flow field observations. It should be noted that, in the embodiment of the present invention, the abnormal observation data of the ocean surface layer and the long-term weather average data of the observation data of the ocean surface layer are obtained through well-known data platforms in the field. Specifically, the observation data of the ocean surface layer height is downloaded and obtained based on AVISO (modeling, validation and Interpretation of Satellite Oceanographic) issued by the French weather agency; the observation data related to the salinity of the ocean surface layer is downloaded and obtained based on CCI (Climate Change Initiative) issued by ESA Climate Office; observations relating to ocean skin temperature were downloaded based on OISST (Optimum Interpolation Sea Surface Temperature) provided by the national ocean and atmosphere administration (National Oceanic and Atmospheric Administration, NOAA); observations related to the ocean surface flow field are obtained based on ENVISAT ASAR satellite observations, by way of example only, and not by way of limitation.
In this embodiment, the marine numerical mode includes: LICOM mode, HYCOM mode and ROMS mode are only used as examples, and are adapted according to actual application requirements. The ocean numerical mode is a model built for the ocean, and aims to provide a model capable of simulating large-scale wind-induced circulation, hot salt circulation and the like.
In this embodiment, the data processing requirement of the ocean numerical mode is that the grid point horizontal interpolation is performed on the ocean surface abnormal observation data and the long-term climate average data of the ocean surface observation data based on the linear interpolation method. Specifically, a bilinear method is adopted to perform horizontal interpolation, that is, for a certain selected interpolation lattice point, four lattice point data adjacent to the selected interpolation lattice point are respectively subjected to linear interpolation in the warp direction and the weft direction, which is only used as an illustration and not a limitation.
Step S2: and optimizing the basic theoretical equation of the set optimal interpolation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula.
In this embodiment, according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer, the set of optimal interpolation basic theoretical equations are optimized, and the set of optimal interpolation basic theoretical equations are:
Figure SMS_11
wherein ,λrepresenting the state quantity of the mode, superscript
Figure SMS_12
、bAndorepresenting the analysis, origin and observation respectively,Brepresenting a pattern full-field error matrix,Crepresenting a dimensionless function for a model full field error matrixBThe simplification of the area is carried out and,Prepresenting an observation operator, which is used for adjusting the observation data according to the mode requirement format,Tthe symbols are transposed on behalf of the matrix,Rrepresenting the observed covariance matrix of the image,αrepresenting relative coefficient for adjusting the relative magnitude between the original error and the observed error of the model, and determining according to the type of the marine surface layer observed data and the corresponding practical application. In particular, when the marine surface observations are altitude observationsαThe value is 0.4; when the marine surface layer observation is salinity observationαThe value is 0.5; when the marine surface layer observation data is temperature observation dataαThe value is 0.3; when the marine surface layer observation data is the flow field observation dataαThe value is 0.35, which is only used as an example and is adaptively adjusted according to the actual application requirements.
In the present embodiment, since
Figure SMS_13
The physical meaning of the term is the influence degree of the analysis field obtained after assimilation observation data on the original field, so the term for adjusting the basic theoretical equation of the optimal interpolation is +.>
Figure SMS_14
Simplifying to obtain an optimization formula:
Figure SMS_15
wherein ,
Figure SMS_16
represents the adjustment value of the observation data of the ocean surface layer,Xrepresenting the observation data of ocean surface layer, superscriptoAndbrepresenting the original values of the observation and the mode, respectively, +.>
Figure SMS_17
、/>
Figure SMS_18
and />
Figure SMS_19
The two-dimensional full-field value of the ocean surface data, the abnormal value of the ocean surface data and the long-term climate average value of the ocean surface data are represented respectively.
Step S3: assimilating the pretreated marine surface abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface observation data to obtain an analysis field.
In this embodiment, the preset operation time for setting the ocean numerical mode includes: the timing of assimilation or the period of assimilation. The assimilation process includes: long-term climate average value of marine surface layer data in optimization formula based on long-term climate average data of marine surface layer observation data
Figure SMS_20
Performing deviation correction to enable +.>
Figure SMS_21
The term tends to 0, and the pretreated marine surface abnormal observation data is directly assimilated on the basis.
In practical application, the analysis field obtained by assimilating the abnormal observation data of the ocean surface layer is also subjected to post-treatment, wherein the post-treatment comprises: and returning the analysis field obtained by assimilation to the ocean numerical mode for storage or other application of the mode, wherein the analysis field is not particularly limited and is determined according to actual application scenes.
In one embodiment, the ocean numerical mode selects LICOM mode, assimilates the altitude observations in the ocean surface observations, and the assimilation process comprises:
1. based on AVISO issued by French weather bureau, the observed data of sea surface height abnormality and the long-term weather average data of sea surface height are downloaded.
2. The observed data of the sea surface height abnormality and the long-term weather average data of the sea surface height are horizontally interpolated according to the grid points of the ocean numerical mode LICOM, the mode horizontal grid points are guaranteed to be in one-to-one correspondence, and the observed data and the long-term weather average data are stored in a server, so that the observed data and the long-term weather average data are convenient to read at any time.
3. According to the physical implications of the sea surface height and the abnormal sea surface height, an optimization formula is obtained:
Figure SMS_22
。
4. and (3) setting the preset running time of the ocean numerical mode LICOM as the assimilation time, reading long-term weather average data of the sea surface height to perform deviation correction on the sea surface height simulated by the ocean numerical mode LICOM, and directly assimilating the observation data of the abnormal sea surface height on the basis of the sea surface height without the deviation mode. Specifically, for the above-mentioned optimization formula, when the long-term weather average value of the sea surface height is infinitely close to the observed value, that is, the average power topography (Mean Dynamic Topography, MDT) adopted can be regarded as no deviation, the change of the sea level reference surface can be accurately depicted, which means that the result of the rightmost term of the optimization formula is close to 0. Thus, if the MDT is selected and the deviation corrected to reach the expected result, the two-dimensional full field value of the sea surface height and the abnormal value of the sea surface height can be obtained according to the optimization formula, and the generated abnormal value of the sea surface height is obtainedΔHAnd should be approximately equal. In theory, the effect of two-dimensional full-field value of the sea surface height can be obtained by assimilating the observation data of the sea surface height abnormality after the MDT generated by the sea numerical mode is subjected to sufficient deviation correction, so that the huge calculation amount for generating the MDT by combining the long-term simulation result of the sea numerical mode with a large amount of observation data is limited.
5. And returning the assimilated analysis field to the ocean numerical mode LICOM, and determining the application of the analysis field according to the ocean numerical mode. When the preset operating time of the ocean numerical mode LICOM is set as the assimilation period, the time of the next setting for assimilation is waited after the current assimilation is finished until the assimilation is finished.
The results after assimilation by the above-described procedure are shown in FIG. 2. It should be noted that, different gray values in fig. 2 represent different sea heights (units: m) of the tropical pacific ocean; the left graph in fig. 2 is the observed result, i.e., the observed field; FIG. 2 is a diagram showing the results of the present embodiment for assimilating sea surface height anomaly data, i.e., analytical fields; the right hand graph in fig. 2 is the sea surface altitude, i.e. the original field, originally simulated by the sea pattern.
From the graph, the more the image or the closer the image is to the observed field, namely the left image, namely the more real and reasonable the assimilation result is. The left graph clearly simulates the 97-98 year early Nino event, and the mode does not simulate the correct signal, namely the right graph (original field), but basically accords with the observation field after the abnormal observation (analysis field) is added. Therefore, the altitude observation data in the ocean surface observation data can be assimilated, the advantages of assimilating the sea surface altitude of the whole field and assimilating the sea surface altitude abnormality in the past can be combined, the ocean surface altitude simulation error in the ocean numerical mode can be quickly and effectively adjusted, the change condition of the sea surface altitude and the information of the change of the upper ocean on the climate scale can be more accurately marked, the simulation and prediction capability of the elnino phenomenon and other ocean climate abnormal events which take the physical change of the ocean upper ocean as the dominant and the disastrous weather generated in ocean power and thermal motion such as typhoons can be improved obviously.
In one embodiment, the ocean numerical mode selects LICOM mode, and assimilates the temperature observation in the ocean surface observation, the assimilation process is the same as the altitude observation, and the assimilation result is shown in FIG. 3. The original field is the observation result of the temperature of the ocean surface layer of the assimilation full field, and the analysis field is the observation result of the temperature abnormality of the ocean surface layer of the assimilation of the embodiment of the invention. The analysis of the temperature change trend of the original field and the analysis field shows that the change trend is consistent with the change trend of the original field and the analysis field, and the effectiveness of the assimilation method of the embodiment of the invention is demonstrated (the assimilation abnormal temperature data can obtain a result which is consistent with the original assimilation marine full-field temperature observation, namely, after correcting the long-term average climate deviation of the marine surface temperature, the assimilation marine surface temperature abnormal observation data can obtain the effect of assimilating the two-dimensional full-field value of the marine surface temperature, and meanwhile, the information on the upper marine physical structure and the climate change, which is reflected by the marine surface temperature abnormal data, is reserved); in addition, the method has smaller variation trend, which shows that the method has small oscillation, thus not only improving the simulation and forecast capability of the ocean numerical mode to the upper ocean physical element field and the climate change and disaster early warning thereof, but also greatly reducing the matrix transformation and operation of the prior assimilation ocean surface temperature anomaly observation data on a high-performance computer, saving the operation time and the economic cost of matching high calculation power, and having certain economic value.
In one embodiment, the ocean numerical mode selects LICOM mode, and assimilates salinity observations in ocean surface observations, the assimilation process is the same as the altitude observations, and the assimilation results are shown in FIG. 4. The black dotted line is an observation field of ocean salinity. By analyzing the change trend of the original field and the analysis field and the observation field, the analysis field change trend is closer to the observation field, so that the effectiveness of the assimilation method of the embodiment of the invention is illustrated, the simulation and forecast capability of the ocean numerical mode on the phenomena of ocean hydrologic environment, ecological conditions, offshore seawater corrosion and the like are improved, and the method has the advantages of low cost, simple calculation, short running time and the like.
In one embodiment, the ocean numerical mode selects LICOM mode, assimilates the flow field observations in the ocean surface observations, and the assimilation process is the same as the altitude observations, and the assimilation result is shown in FIG. 5. It should be noted that, in fig. 5, different gray values represent different sea heights (units: m) of the tropical pacific ocean, and arrows (units: m/s) represent directions of long-term average distribution of the horizontal flow field. From the graph, the variation trend of the analysis field (assimilation of the embodiment of the invention) is closer to the observation field (the graph shows a large value region which is more consistent with the observation field, and the flow field direction is more consistent with the observation field), which indicates the effectiveness of the assimilation method of the embodiment of the invention.
In conclusion, the assimilation method of the marine anomaly observation data provided by the embodiment of the invention can be used for quickly and effectively adjusting the simulation error of the marine surface anomaly observation data in the marine numerical mode, so that the calculation process and time of operation are greatly reduced, and the method has certain economic value.
Example 2
The embodiment of the invention provides an assimilation system for marine anomaly observation data, which is shown in fig. 6 and comprises:
the data acquisition and processing module is used for acquiring abnormal marine surface layer observation data and long-term weather average data of the marine surface layer observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode; this module performs the method described in step S1 in embodiment 1, and will not be described here again.
The set optimal interpolation optimization module is used for optimizing a set optimal interpolation basic theoretical equation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula; this module performs the method described in step S2 in embodiment 1, and will not be described here.
The abnormal observation data assimilation module is used for assimilating the pretreated marine surface layer abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface layer observation data to obtain an analysis field; this module performs the method described in step S3 in embodiment 1, and will not be described here.
The assimilation system of the marine anomaly observation data provided by the embodiment of the invention is based on the basic mathematical theory of the integrated data assimilation method in the marine numerical mode, and combines the marine field observation data which are widely applied at present, and has the premise of fully cognizing the simulation deviation of the marine numerical mode and the quality of the observation data; the method combines the advantages of assimilating full-field ocean surface layer observation data and assimilating ocean surface layer abnormal observation data in the past, can quickly and effectively regulate the simulation errors of the ocean surface layer abnormal observation data in an ocean numerical mode, can realize assimilation of the ocean surface layer abnormal observation data in the ocean numerical mode, improves the simulation and forecast capabilities of the mode on an upper ocean physical element field and climate change and disaster early warning thereof, greatly reduces the data quantity and calculated quantity required by the past calculation to generate reliable MDT, saves the operation time and the economic cost matched with high calculation power, and has certain economic value.
Example 3
An embodiment of the present invention provides a computer device, as shown in fig. 7, including: at least one processor 701, at least one communication interface 703, a memory 704, and at least one communication bus 702. The communication bus 702 is used to implement the connection communication between these components, and the communication interface 703 may include a display screen and a keyboard, and the optional communication interface 703 may further include a standard wired interface and a wireless interface. The memory 704 may be a high-speed volatile random access memory, a non-volatile memory, or at least one memory device located remotely from the processor 701. Wherein the processor 701 can execute the assimilation method of the marine anomaly observation material of embodiment 1. A set of program codes is stored in the memory 704, and the processor 701 calls the program codes stored in the memory 704 for executing the assimilation method of the marine anomaly observation material of embodiment 1.
The communication bus 702 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. Communication bus 702 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one line is shown in fig. 7, but not only one bus or one type of bus.
The Memory 704 may include a Volatile Memory (RAM) such as a random access Memory (Random Access Memory); the Memory may also include a nonvolatile Memory (Non-volatile Memory), such as a Flash Memory (Flash Memory), a Hard Disk (HDD) or a Solid State Drive (SSD); memory 704 may also include combinations of the above types of memory.
The processor 701 may be a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP) or a combination of CPU and NP.
The processor 701 may further include a hardware chip. The hardware chip may be an Application-specific integrated circuit (ASIC), a programmable logic device (Programmable Logic Device, PLD), or a combination thereof. The PLD may be a complex programmable logic device (Complex Programmable Logic Device, CPLD for short), a field programmable gate array (Field Programmable Gate Array, FPGA for short), general-purpose array logic (Generic Array Logic, GAL for short), or any combination thereof.
Optionally, the memory 704 is also used for storing program instructions. The processor 701 may call program instructions to implement the assimilation method of marine anomaly observation material in accordance with embodiment 1 of the present invention.
The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores computer executable instructions thereon, wherein the computer executable instructions can execute the assimilation method of the marine anomaly observation data in the embodiment 1. The storage medium may be a magnetic Disk, an optical disc, a Read Only Memory (ROM), a random access Memory (Random Access Memory RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), a solid state Disk (Solid State Drive SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. And obvious variations or modifications thereof are contemplated as falling within the scope of the present invention.

Claims (10)

1. A method for assimilating marine anomaly observation data, comprising:
acquiring abnormal marine surface observation data and long-term weather average data of the abnormal marine surface observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode;
optimizing the basic theoretical equation of the set optimal interpolation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula;
assimilating the pretreated marine surface abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface observation data to obtain an analysis field.
2. The method for assimilating marine anomaly observation according to claim 1, wherein the data processing requirement of the marine numerical model is that the marine surface anomaly observation and the long-term weather-averaging data of the marine surface observation are subjected to lattice point horizontal interpolation based on a linear interpolation method.
3. The method of assimilating marine anomaly observation according to claim 1, wherein the process of obtaining an optimization formula comprises:
optimizing a set optimal interpolation basic theoretical equation according to the physical characteristics of the abnormal marine surface observation data and the marine surface observation data, wherein the set optimal interpolation basic theoretical equation is as follows:
Figure QLYQS_1
wherein ,λrepresenting the state quantity of the mode, superscript
Figure QLYQS_2
、bAndorepresenting the analysis, origin and observation respectively,Brepresenting a pattern full-field error matrix,Crepresenting a dimensionless function for a model full field error matrixBThe simplification of the area is carried out and,Prepresenting an observation operator for formatting the observed data according to the mode requirementThe adjustment is carried out so that the adjustment is carried out,Tthe symbols are transposed on behalf of the matrix,Rrepresenting the observed covariance matrix of the image,αrepresenting relative coefficients for adjusting the relative magnitude between the original error and the observed error of the mode, and determining according to the type of the marine surface layer observed data and the corresponding practical application thereof;
adjusting terms of the set of optimal interpolation basic theoretical equations
Figure QLYQS_3
Simplifying to obtain an optimization formula:
Figure QLYQS_4
wherein ,
Figure QLYQS_5
represents the adjustment value of the observation data of the ocean surface layer,Xrepresenting the observation data of ocean surface layer, superscriptoAndbrepresenting the original values of the observation and the mode, respectively, +.>
Figure QLYQS_6
、/>
Figure QLYQS_7
and />
Figure QLYQS_8
The two-dimensional full-field value of the ocean surface data, the abnormal value of the ocean surface data and the long-term climate average value of the ocean surface data are represented respectively.
4. A method of assimilating marine anomaly observations according to claim 3 wherein the process of assimilating pretreated marine surface anomaly observations comprises: long-term climate average value of marine surface layer data in optimization formula based on long-term climate average data of marine surface layer observation data
Figure QLYQS_9
Performing deviation correction so that
Figure QLYQS_10
The term tends to 0, and the pretreated marine surface abnormal observation data is directly assimilated on the basis.
5. The method of assimilating marine anomaly observation according to claim 1, wherein the preset operation time for marine numerical mode setting comprises: the timing of assimilation or the period of assimilation.
6. A method of assimilating marine anomaly observations according to claim 3 wherein the marine surface observations are of the type comprising: altitude observations, salinity observations, temperature observations, and flow field observations.
7. The method of assimilating marine anomaly observation according to claim 1, wherein the marine numerical pattern comprises: LICOM mode, HYCOM mode, and ROMS mode.
8. An assimilation system for marine anomaly observation data, comprising:
the data acquisition and processing module is used for acquiring abnormal marine surface layer observation data and long-term weather average data of the marine surface layer observation data, and preprocessing the data based on the data processing requirement of a marine numerical mode;
the set optimal interpolation optimization module is used for optimizing a set optimal interpolation basic theoretical equation according to the abnormal observation data of the ocean surface layer and the physical characteristics of the observation data of the ocean surface layer to obtain an optimization formula;
the abnormal observation data assimilation module is used for assimilating the pretreated marine surface layer abnormal observation data according to the long-term climate average data, the optimization formula and the preset running time set by the marine numerical mode of the pretreated marine surface layer observation data to obtain an analysis field.
9. A computer device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of assimilating marine anomaly observation material of any one of claims 1-7.
10. A computer-readable storage medium storing computer instructions for causing the computer to execute the method of assimilating marine anomaly observation data according to any one of claims 1 to 7.
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Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102004856A (en) * 2010-11-27 2011-04-06 中国海洋大学 Rapid collective Kalman filtering assimilating method for real-time data of high-frequency observation data
CN105046046A (en) * 2015-06-09 2015-11-11 哈尔滨工程大学 Ensemble Kalman filter localization method
CN109426886A (en) * 2017-08-29 2019-03-05 北京思湃德信息技术有限公司 A kind of climatic prediction system
CN109783932A (en) * 2019-01-14 2019-05-21 哈尔滨工程大学 A kind of close coupling data assimilation method of the optimal observation time window of combination
CN112800603A (en) * 2021-01-26 2021-05-14 北京航空航天大学 Atmospheric environment data assimilation method based on set optimal interpolation algorithm
CN113051795A (en) * 2021-03-15 2021-06-29 哈尔滨工程大学 Three-dimensional temperature-salinity field analysis and prediction method for offshore platform guarantee
CN113407524A (en) * 2021-06-30 2021-09-17 国家气候中心 Climate system mode multi-circle layer coupling data assimilation system
CN114153832A (en) * 2021-12-06 2022-03-08 国网湖南省电力有限公司 Method and system for fusing electric microclimate observation data and meteorological industry traditional data
CN114265836A (en) * 2021-11-16 2022-04-01 南京信息工程大学 All-weather assimilation method and device of satellite microwave hygrothermograph based on cloud area temperature and humidity profile inversion
CN114492680A (en) * 2022-04-18 2022-05-13 国家海洋技术中心 Buoy data quality control method and device, computer equipment and storage medium
CN114483485A (en) * 2022-02-24 2022-05-13 兰州大学 Method for improving wind speed prediction of Nudging wind power plant observation data
CN115203942A (en) * 2022-07-14 2022-10-18 中国长江三峡集团有限公司 Ocean temperature correction method and device, electronic equipment and storage medium
CN115511192A (en) * 2022-09-30 2022-12-23 中国科学院西北生态环境资源研究院 Rainfall forecasting method and system based on lightning data assimilation
CN115526038A (en) * 2022-09-19 2022-12-27 国家海洋环境预报中心 Offshore ecological environment numerical forecasting method and system
US20230048788A1 (en) * 2021-08-06 2023-02-16 The Government Of The United States Of America, As Represented By The Secretary Of The Navy Method and System for Multi-scale Assimilation of Surface Water Ocean Topography (SWOT) Observations

Patent Citations (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102004856A (en) * 2010-11-27 2011-04-06 中国海洋大学 Rapid collective Kalman filtering assimilating method for real-time data of high-frequency observation data
CN105046046A (en) * 2015-06-09 2015-11-11 哈尔滨工程大学 Ensemble Kalman filter localization method
CN109426886A (en) * 2017-08-29 2019-03-05 北京思湃德信息技术有限公司 A kind of climatic prediction system
CN109783932A (en) * 2019-01-14 2019-05-21 哈尔滨工程大学 A kind of close coupling data assimilation method of the optimal observation time window of combination
CN112800603A (en) * 2021-01-26 2021-05-14 北京航空航天大学 Atmospheric environment data assimilation method based on set optimal interpolation algorithm
CN113051795A (en) * 2021-03-15 2021-06-29 哈尔滨工程大学 Three-dimensional temperature-salinity field analysis and prediction method for offshore platform guarantee
CN113407524A (en) * 2021-06-30 2021-09-17 国家气候中心 Climate system mode multi-circle layer coupling data assimilation system
US20230048788A1 (en) * 2021-08-06 2023-02-16 The Government Of The United States Of America, As Represented By The Secretary Of The Navy Method and System for Multi-scale Assimilation of Surface Water Ocean Topography (SWOT) Observations
CN114265836A (en) * 2021-11-16 2022-04-01 南京信息工程大学 All-weather assimilation method and device of satellite microwave hygrothermograph based on cloud area temperature and humidity profile inversion
CN114153832A (en) * 2021-12-06 2022-03-08 国网湖南省电力有限公司 Method and system for fusing electric microclimate observation data and meteorological industry traditional data
CN114483485A (en) * 2022-02-24 2022-05-13 兰州大学 Method for improving wind speed prediction of Nudging wind power plant observation data
CN114492680A (en) * 2022-04-18 2022-05-13 国家海洋技术中心 Buoy data quality control method and device, computer equipment and storage medium
CN115203942A (en) * 2022-07-14 2022-10-18 中国长江三峡集团有限公司 Ocean temperature correction method and device, electronic equipment and storage medium
CN115526038A (en) * 2022-09-19 2022-12-27 国家海洋环境预报中心 Offshore ecological environment numerical forecasting method and system
CN115511192A (en) * 2022-09-30 2022-12-23 中国科学院西北生态环境资源研究院 Rainfall forecasting method and system based on lightning data assimilation

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
张人禾等: "Argo大洋观测资料的同化及其在短期气候预测和海洋分析中的应用", 《大气科学》, vol. 37, no. 2, pages 411 - 424 *
杜梦蛟等: "同化Argo海洋廓线观测对CAS-ESM-C的上层海洋温度模拟的改进", 《成都信息工程大学学报》, vol. 32, no. 3, pages 289 - 296 *
杨海鹏等: "同化卫星高度计观测对CAS-ESM-C上层海洋温度模拟的改进", 《成都信息工程大学学报》, vol. 34, no. 6, pages 615 - 624 *

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