Method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data

Abstract

The invention discloses a method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data, and belongs to the technical field of ocean satellite remote sensing application, and the method comprises the following steps: step 1, based on a parameterization scheme of sub-mesoscale vertical buoyancy flux, deducing a sub-mesoscale vertical heat flux calculation formula; step 2, based on field observation and numerical simulation data, determining empirical coefficients in a sub-mesoscale vertical heat flux formula based on a parameterization scheme; and step 3, calculating the sub-mesoscale vertical heat flux by using the current vortex resolution satellite remote sensing data. According to the method, calculation of global or regional ocean sub-mesoscale vertical heat transport can be realized by utilizing current popular vortex resolution satellite remote sensing data, and the problem that sub-mesoscale dynamics calculation has high requirements on data spatial resolution and is difficult to realize is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of marine satellite remote sensing applications, and in particular relates to a method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data. Background Art

[0002] Ocean satellite remote sensing is an advanced means of earth observation. By installing different types of remote sensors, it can directly detect or indirectly invert ocean elements and ocean phenomena. It is also the only observation platform that can detect global ocean environmental information for a long time and quickly, providing humans with a data source that cannot be replaced by other observation methods for in-depth understanding and knowledge of the ocean. Since its rise in the late twentieth century, with the rapid development of ocean satellite remote sensing technology, the observation data resolution of most ocean dynamic environment satellites has reached the order of 10–25 kilometers (referred to as eddy resolution). At this resolution, only mesoscale processes can be partially resolved, and submesoscale processes cannot be resolved. However, submesoscale processes can break the constraints of geostrophic equilibrium, thereby generating strong vertical motion, which can lead to large-scale vertical transport of heat, nutrients and other tracers in the upper ocean. Through this transport, submesoscale processes significantly regulate the dynamics and biogeochemical processes in the upper ocean. Therefore, in order to obtain global submesoscale process vertical transport information, it is necessary to diagnose through parameterized formulas based on satellite remote sensing data.

[0003] Currently, there are few technologies that use parameterization schemes of submesoscale processes based on satellite remote sensing data to calculate their vertical heat fluxes. There is only one method for diagnosing vertical heat fluxes, which is a parameterization scheme of submesoscale vertical buoyancy flux based on the theory of mixed layer baroclinic instability (referred to as F08 scheme). However, this method has the following two limitations. First, the parameterization scheme used in this method assumes that the vertical buoyancy flux below the mixed layer is zero, so it can only diagnose the heat flux above the mixed layer. This is contrary to the results of field observations. In fact, the vertical heat flux caused by submesoscale processes can penetrate the mixed layer to a depth of several hundred meters below. Secondly, this method only considers the baroclinic instability mechanism of the mixed layer, while the main generation mechanism of submesoscale processes should also include the stretching-induced frontogenesis process. The incomplete consideration of the generation mechanism also leads to a large error between the submesoscale vertical heat flux calculated based on this method and the observation. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a new method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data. According to the parameterization scheme of sub-mesoscale vertical buoyancy flux under the mechanism of "mixing-transition layer instability under frontogenesis regulation" established by the research team through long-term observation and research on sub-mesoscale processes in the ocean, the parameterized calculation formula of sub-mesoscale vertical heat flux is theoretically derived; at the same time, the true value calculated by the definition formula of sub-mesoscale vertical heat flux and the parameterized diagnostic value calculated by the parameterization scheme are fitted by the least squares method to determine the empirical coefficients in the parameterized calculation formula of sub-mesoscale vertical heat flux; thereby realizing the calculation of sub-mesoscale vertical heat flux by eddy resolution satellite remote sensing data.

[0005] The technical solution of the present invention is as follows: A method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data comprises the following steps: Step 1: Based on the parameterization scheme of sub-mesoscale vertical buoyancy flux, derive the calculation formula of sub-mesoscale vertical heat flux; Step 2: Based on field observations and numerical simulation data, determine the empirical coefficients in the submesoscale vertical heat flux formula based on the parameterization scheme; Step 3: Calculate the submesoscale vertical heat flux using satellite remote sensing data with current eddy resolution.

[0006] Furthermore, the specific process of step 1 is as follows: Submesoscale vertical buoyancy flux The definition of is: (1); in, is the vertical velocity of the submesoscale process; It is a submesoscale buoyancy disturbance; is the submesoscale effective potential energy release rate; Based on the mechanism of “mixing-transition layer instability under frontogenesis regulation”, a submesoscale vertical buoyancy flux parameterization scheme is established, and its mathematical expression is: (2); (3); in, is the empirical coefficient; is the background stretching rate; is the zonal background velocity; is the meridional background velocity; is the latitudinal coordinate; is the meridian coordinate; is the depth of the mixed layer; is the Coriolis parameter; is the background buoyancy, , is the potential density, is the reference density, is the acceleration due to gravity; is the horizontal gradient; is the vertical structure function; for depth; is an exponential function with base e; Potential density from temperature and salinity Determine that the state equation of potential density satisfies: (4); in, is the coefficient of thermal expansion; is the salinity contraction coefficient; is the reference temperature; is the reference salinity; Considering the upper ocean where submesoscale processes are active, the potential density is determined by the temperature, and the equation of state is further simplified to: (5); in, is an approximate symbol; Substituting the simplified state equation into the definition of submesoscale vertical buoyancy flux in formula (1), we obtain: (6); in, It is a submesoscale temperature disturbance; is the submesoscale vertical temperature flux; Submesoscale vertical heat flux The definition of is: (7); in, is the heat capacity of seawater; Combining formula (6) and formula (7), the relationship between submesoscale vertical buoyancy flux and heat flux is expressed as: (8); Substituting the simplified state equation into the parameterization formula (2) of the submesoscale vertical buoyancy flux, the calculation formula of the submesoscale vertical heat flux based on the parameterization scheme is obtained: (9); in, is the background temperature.

[0007] Furthermore, the specific process of step 2 is as follows: Based on the field observation or numerical simulation data with sub-mesoscale resolution, the true value and parameterized diagnostic value of the sub-mesoscale vertical heat flux are calculated according to formula (7) and formula (9), respectively. The true value and parameterized diagnostic value are fitted by the least squares method to obtain the empirical coefficient : (10); in, and are the true value and parameterized diagnostic value of submesoscale vertical heat flux, respectively; and They are and The average value of is the number of sample points for calculation.

[0008] Furthermore, the specific process of step 3 is: based on the satellite remote sensing observation data of global sea surface temperature and horizontal flow velocity at the current eddy resolution, combined with the mixed layer depth data observed by global ocean drifting buoys or other instruments, it is substituted into formula (9) to realize the calculation of sub-mesoscale vertical heat flux.

[0009] The beneficial technical effects brought by the present invention are as follows: Based on the parameterization scheme of submesoscale vertical buoyancy flux under the mechanism of "mixing-transition layer instability under frontogenesis regulation" established by the research team through long-term observation and research on submesoscale processes in the ocean, the present invention can calculate submesoscale vertical heat flux at different depths, and the calculation results can naturally extend below the mixing layer, overcoming the defect that the existing technical methods can only diagnose the heat flux above the mixing layer; in addition, the vertical heat flux calculation formula of the present invention simultaneously considers the two major generation mechanisms of submesoscale processes, baroclinic instability and stretching-induced frontogenesis, and the calculation results are closer to the actual situation of the ocean than the existing technology. The present invention can use eddy resolution satellite data to calculate the global submesoscale vertical heat flux, forming a fixed data product of satellite inversion, which is used for the study of vertical transport of submesoscale processes, which is conducive to improving the understanding and prediction capabilities of key processes in Earth system science. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 The present invention is a flow chart of a method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data.

[0011] Figure 2 It is a fitting result diagram of the true value and parameterized diagnostic value of the sub-mesoscale vertical heat flux in an embodiment of the present invention.

[0012] Figure 3 This is a graph of sub-mesoscale vertical heat flux results averaged over 100 meters in different sea areas calculated based on eddy resolution satellite remote sensing data in an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments: like Figure 1 As shown, a method for calculating sub-mesoscale vertical heat flux based on satellite remote sensing data includes the following steps: Step 1: Based on the parameterization scheme of submesoscale vertical buoyancy flux, derive the calculation formula of submesoscale vertical heat flux. The specific process is: Submesoscale vertical buoyancy flux The definition of is: (1); in, is the vertical velocity of the submesoscale process; It is a submesoscale buoyancy disturbance; is the submesoscale effective potential energy release rate.

[0014] Based on the long-term research accumulation of sub-mesoscale processes, the research team established a sub-mesoscale generation mechanism - "mixing-transition layer instability under frontogenesis regulation", and derived a parameterization scheme for the sub-mesoscale vertical buoyancy flux based on this mechanism. The diagnostic verification based on the sub-mesoscale resolution ocean numerical model MITgcm llc4320 shows that compared with the F08 scheme that only considers the baroclinic instability of the mixed layer, the parameterization scheme used in the present invention is more realistic than the F08 scheme in terms of the three-dimensional structure of the sub-mesoscale vertical buoyancy flux. At present, the research team has proposed a new technology to integrate this parameterization scheme into the ocean numerical simulation, and proved that it can effectively improve the problem of deep mixed layer simulation, thereby improving the model's simulation ability of the upper ocean density distribution. The mathematical expression of the sub-mesoscale vertical buoyancy flux in the parameterization scheme is: (2); (3); in, is the empirical coefficient; is the background stretching rate; is the zonal background velocity; is the meridional background velocity; is the latitudinal coordinate; is the meridian coordinate; is the depth of the mixed layer; is the Coriolis parameter; is the background buoyancy, , is the potential density, is the reference density, is the acceleration due to gravity; is the horizontal gradient; is the vertical structure function; for depth; is an exponential function with base e; Furthermore, the potential density is given by the temperature and salinity Determine that the state equation of potential density satisfies: (4); in, is the coefficient of thermal expansion; is the salinity contraction coefficient; is the reference temperature; is the reference salinity; Considering that the upper ocean is active in submesoscale processes, the potential density is mainly determined by temperature, and the equation of state can be further simplified as: (5); in, is an approximate symbol; Substituting the simplified state equation into the definition of submesoscale vertical buoyancy flux in formula (1), we can obtain: (6); in, It is a submesoscale temperature disturbance; is the submesoscale vertical temperature flux; Submesoscale vertical heat flux The definition of is: (7); in, is the heat capacity of seawater; Combining formula (6) and formula (7), the relationship between submesoscale vertical buoyancy flux and heat flux can be expressed as: (8); The simplified state equation is further introduced into the parameterization formula (2) of the sub-mesoscale vertical buoyancy flux, and the calculation formula of the sub-mesoscale vertical heat flux based on the parameterization scheme is obtained: (9); in, is the background temperature.

[0015] Step 2: Based on field observations and numerical simulation data, determine the empirical coefficients in the submesoscale vertical heat flux formula. The specific process is: Before calculating the submesoscale vertical heat flux according to formula (9), it is necessary to determine the empirical coefficient .

[0016] Based on the field observation or numerical simulation data with sub-mesoscale resolution, the true value and parameterized diagnostic value of sub-mesoscale vertical heat flux can be calculated according to formula (7) and formula (9), respectively. The empirical coefficient can be obtained by fitting the true value and parameterized diagnostic value using the least squares method: ,Right now: (10); in, and are the true value and parameterized diagnostic value of the submesoscale vertical heat flux, Based on formula (7), Calculated based on formula (9); and They are and The average value of is the number of sample points for calculation.

[0017] The fitting results of the true value and parameterized diagnostic value of the submesoscale vertical heat flux obtained by formula (7) and formula (9) are as follows: Figure 2 As shown in the figure, the horizontal and vertical coordinates corresponding to the scattered points in the figure represent the calculation results of the true value and parameterized diagnostic value of the sub-mesoscale vertical heat flux, respectively. The straight line represents that the true value and the diagnostic value are completely equal. By fitting the two, the empirical coefficient is first determined. .also, Figure 2 It shows that the method of the present invention can better characterize the distribution characteristics of sub-mesoscale vertical heat flux in the ocean, and the Pearson correlation coefficient between the diagnostic value and the true value reaches 0.76.

[0018] Step 3: Calculate the sub-mesoscale vertical heat flux using satellite remote sensing data with current eddy resolution. The specific process is: Based on the satellite remote sensing observation data of global sea surface temperature and horizontal flow velocity with current eddy resolution, combined with the mixed layer depth data observed by global ocean drifting buoys or other instruments, the calculation of sub-mesoscale vertical heat flux can be realized by substituting them into formula (9).

[0019] In order to demonstrate the feasibility and superiority of the parameterization method of the present invention, the submesoscale vertical heat flux in the global ocean is calculated based on the sea surface temperature observed by infrared remote sensing, the sea surface velocity observed by altimeter, and the ocean mixed layer depth data integrated with observations such as ocean drifting buoys.

[0020] Figure 3The sub-mesoscale vertical heat flux of the western boundary current area of ​​the global ocean (including the Kuroshio extension area, the Gulf Stream area, the recirculation area, the Leven Current area, the East Australian Current area, and the Brazilian Current area), the North Pacific Subtropical Countercurrent area, and the Antarctic Circumpolar Current area (all hot spots where sub-mesoscale processes are active) diagnosed based on the present invention is demonstrated. It can be seen that the present invention can use the current mainstream eddy resolution satellite remote sensing data to realize the diagnosis of the sub-mesoscale vertical heat flux of the global ocean, overcoming the problem that sub-mesoscale dynamic calculations are difficult to achieve due to the high requirements for data spatial resolution. Through this technology, researchers can establish data products of sub-mesoscale vertical heat fluxes for use in research related to sub-mesoscale processes in the ocean, which is crucial to improving the understanding and prediction of the ocean material energy cycle and the sea-air interaction process.

[0021] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A method for calculating submesoscale vertical heat flux based on satellite remote sensing data, characterized in that: The steps include: Step 1: Based on the parameterization scheme of sub-mesoscale vertical buoyancy flux, derive the calculation formula of sub-mesoscale vertical heat flux; Step 2: Based on field observations and numerical simulation data, determine the empirical coefficients in the submesoscale vertical heat flux formula based on the parameterization scheme; Step 3: Calculate the submesoscale vertical heat flux using satellite remote sensing data with current eddy resolution.

2. The method for calculating submesoscale vertical heat flux based on satellite remote sensing data according to claim 1, characterized in that: The specific process of step 1 is as follows: Submesoscale vertical buoyancy flux The definition of is: (1)； in, is the vertical velocity of the submesoscale process; It is a submesoscale buoyancy disturbance; is the submesoscale effective potential energy release rate; Based on the mechanism of "mixing-transition layer instability under frontogenesis regulation", a submesoscale vertical buoyancy flux parameterization scheme is established, and its mathematical expression is: (2)； (3)； in, is the empirical coefficient; is the background stretching rate; is the zonal background velocity; is the meridional background velocity; is the latitudinal coordinate; is the meridian coordinate; is the depth of the mixed layer; is the Coriolis parameter; is the background buoyancy, , is the potential density, is the reference density, is the acceleration due to gravity; is the horizontal gradient; is the vertical structure function; for depth; is an exponential function with base e; Potential density from temperature and salinity Determine that the state equation of potential density satisfies: (4)； in, is the coefficient of thermal expansion; is the salinity contraction coefficient; is the reference temperature; is the reference salinity; Considering the upper ocean where submesoscale processes are active, the potential density is determined by the temperature, and the equation of state is further simplified to: (5)； in, is an approximate symbol; Substituting the simplified state equation into the definition of submesoscale vertical buoyancy flux in formula (1), we obtain: (6)； in, It is a submesoscale temperature disturbance; is the submesoscale vertical temperature flux; Submesoscale vertical heat flux The definition of is: (7)； in, is the heat capacity of seawater; Combining formula (6) and formula (7), the relationship between submesoscale vertical buoyancy flux and heat flux is expressed as: (8)； Substituting the simplified state equation into the parameterization formula (2) of the submesoscale vertical buoyancy flux, the calculation formula of the submesoscale vertical heat flux based on the parameterization scheme is obtained: (9)； in, is the background temperature.

3. The method for calculating submesoscale vertical heat flux based on satellite remote sensing data according to claim 2, characterized in that: The specific process of step 2 is: Based on the field observation or numerical simulation data with sub-mesoscale resolution, the true value and parameterized diagnostic value of the sub-mesoscale vertical heat flux are calculated according to formula (7) and formula (9), respectively. The true value and parameterized diagnostic value are fitted by the least squares method to obtain the empirical coefficient : (10)； in, and are the true value and parameterized diagnostic value of submesoscale vertical heat flux, respectively; and They are and The average value of is the number of sample points for calculation.

4. The method for calculating sub-mesoscale vertical heat flux using satellite remote sensing data according to claim 3, characterized in that: The specific process of step 3 is: based on the satellite remote sensing observation data of global sea surface temperature and horizontal flow velocity at the current eddy resolution, combined with the mixed layer depth data observed by global ocean drifting buoys or other instruments, it is substituted into formula (9) to realize the calculation of sub-mesoscale vertical heat flux.

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