A joint inversion method of ground-atmosphere coupling factor and impedance

Abstract

The present invention provides a joint inversion method of ground-atmosphere coupling factor and impedance (including surface impedance and aerodynamic impedance), which relates to the technical field of ground-atmosphere interaction, including: obtaining global surface temperature remote sensing data and reanalysis meteorological data products; deconstructing the surface energy balance equation to obtain the corresponding physical model of each component; mathematically deriving according to the physical model to obtain a dynamic interaction model containing ground-atmosphere coupling factor and impedance; based on the model, using an iterative algorithm and global surface temperature remote sensing data and reanalysis meteorological data products to obtain an integrated inversion of the global ground-atmosphere coupling factor and impedance. The present invention is based on the dynamic interaction between impedance and coupling factor with surface evapotranspiration as the medium, based on its physical process mechanism, on the basis of inverting surface evapotranspiration, and simultaneously realizes the integrated inversion of impedance and ground-atmosphere coupling factor, which can provide a new idea for accurately and objectively quantifying impedance and ground-atmosphere coupling factor.

Description

Technical Field

[0001] The present invention relates to the technical field of ground-atmosphere interaction, and in particular to a joint inversion method of ground-atmosphere coupling factor and impedance. Background Art

[0002] The land-atmosphere coupling factor and impedance are key regulatory factors in the water and heat transfer between the land surface and the atmosphere (abbreviated as land-atmosphere). They directly affect the rate of surface evapotranspiration, and thus play a decisive role in the stability of the global water cycle and energy balance. Accurately quantifying the land-atmosphere coupling factor and impedance is of great significance for predicting and responding to extreme climate events caused by climate change, protecting ecosystems, and promoting sustainable development.

[0003] The existing estimation of impedance usually adopts simple empirical formulas such as constant value or linear temperature model, humidity feedback model and photosynthetically active model, ignoring its dynamic relationship with environmental factors such as vegetation physiological state, soil moisture, and air temperature, resulting in the inability to obtain accurate impedance information. At the same time, since the land-air system is a complex network, multiple processes (such as soil moisture, phenology, turbulent flux, air temperature, humidity, etc.) need to be considered as a whole, and although the land-air coupling factor is a basic element in the land-air system, there is almost no research on its objective quantification, which further affects the further understanding of key processes and mechanisms such as boundary layer mixing, convection, cloud cover, precipitation and surface evapotranspiration. Therefore, how to quantify impedance and coupling factors with high precision is still a difficult problem that has not been solved. Summary of the invention

[0004] In order to overcome the deficiencies of the prior art, the present invention aims to provide a joint inversion method of ground-atmosphere coupling factor and impedance.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A joint inversion method of ground-atmosphere coupling factor and impedance, comprising:

[0007] Obtain global surface temperature remote sensing data and reanalysis meteorological data products;

[0008] Deconstruct the surface energy balance equation to obtain the corresponding physical model of each component;

[0009] Mathematically deriving the physical model, a dynamic interaction model including ground-air coupling factor, ground surface impedance and aerodynamic impedance is obtained;

[0010] Based on the dynamic interaction model, an iterative algorithm and the global surface temperature remote sensing data and reanalysis meteorological data products are used to obtain the integrated inversion of the global ground-atmosphere coupling factor, surface impedance and aerodynamic impedance.

[0011] Preferably, the global surface temperature remote sensing data and reanalysis meteorological data products include: air temperature, atmospheric pressure, relative humidity, wind speed, surface net radiation flux data and soil heat flux data.

[0012] Preferably, the physical model includes:

[0013] LE=R n -HG;

[0014]

[0015] Where, LE is the latent heat flux; H is the sensible heat flux; R n is the net radiation of the surface; G is the soil heat flux; T s is the surface temperature; T a is the air temperature; ρ is the air density; C p is the specific heat of air; γ is the dry-bulb constant; e s is the surface vapor pressure; e a is the actual water vapor pressure; is the surface saturated vapor pressure; r s is the surface impedance; r ae is the aerodynamic impedance.

[0016] Preferably, mathematical deduction is performed based on the physical model to obtain a dynamic interaction model containing ground-air coupling factor, surface impedance and aerodynamic impedance, including:

[0017] An aerodynamic impedance estimation model is constructed according to the physical model; the formula of the aerodynamic impedance estimation model is:

[0018] A surface impedance estimation model is constructed according to the physical model; the formula of the surface impedance estimation model is:

[0019] Construct a surface vapor pressure estimation model; the formula of the surface vapor pressure estimation model is: Where Ω is the ground-atmosphere coupling factor; h s,max is the maximum relative humidity of the surface; the calculation formula of the ground-air coupling factor is: Where, Δ is the slope of the saturated water vapor pressure curve;

[0020] The dynamic interaction model is determined according to the aerodynamic impedance estimation model, the surface impedance estimation model and the surface vapor pressure estimation model. The dynamic interaction model is characterized by being a combination of the aerodynamic impedance estimation model, the surface impedance estimation model and the surface vapor pressure estimation model.

[0021] Preferably, the iterative algorithm is the Fletcher-Reeves algorithm.

[0022] Preferably, the steps of the iterative algorithm include:

[0023] Obtaining input data; the input data are global surface temperature remote sensing data and reanalysis meteorological data products;

[0024] Set initial values ​​of aerodynamic impedance, surface impedance, and surface vapor pressure based on historical data or empirical values;

[0025] An objective function is determined, and the aerodynamic impedance, surface impedance, and surface vapor pressure are calculated based on numerical minimization. The objective function has the form: in, f1, f2, and f3 represent the errors between the parameter values ​​of the current iteration step and the expected values ​​of the model. By continuously iteratively adjusting the parameters, these errors are minimized to find the optimal solution.

[0026] Calculate the gradient function of the objective function for the iterative process of the optimization algorithm; the gradient function is: in,

[0027] An iterative process is performed, and the iterative process is stopped when an iteration stopping condition is satisfied.

[0028] Preferably, the iteration stopping condition includes:

[0029] When the objective function When the value of is less than the preset threshold, the iteration stops; when the number of iterations reaches the maximum number of iterations, the iteration stops; when the change in the results of two adjacent iterations is less than the preset threshold, the iteration stops.

[0030] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0031] The present invention provides a joint inversion method of ground-atmosphere coupling factor and impedance, including: obtaining global surface temperature remote sensing data and reanalysis meteorological data products; deconstructing the surface energy balance equation to obtain the corresponding physical model of each component; mathematically deriving according to the physical model to obtain a dynamic interaction model containing ground-atmosphere coupling factor, surface impedance and aerodynamic impedance; based on the dynamic interaction model, using an iterative algorithm and the global surface temperature remote sensing data and reanalysis meteorological data products to obtain integrated inversion of the global ground-atmosphere coupling factor, surface impedance and aerodynamic impedance. The present invention is based on the dynamic interaction relationship between aerodynamic impedance, surface impedance and coupling factor with surface evapotranspiration as the medium, considering its potential physical process mechanism, and on the basis of inverting surface evapotranspiration, simultaneously realizes the integrated inversion of aerodynamic impedance, surface impedance and ground-atmosphere coupling factor, which can provide a new idea for accurately and objectively quantifying surface impedance and ground-atmosphere coupling factor. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0033] Figure 1 A flow chart of a method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides a joint inversion method of ground-air coupling factor and impedance, comprising:

[0037] Step 100: Obtain global surface temperature remote sensing data and reanalysis meteorological data products;

[0038] Step 200: Deconstruct the surface energy balance equation to obtain the corresponding physical model of each component;

[0039] Step 300: Perform mathematical deduction based on the physical model to obtain a dynamic interaction model including ground-air coupling factor, surface impedance and aerodynamic impedance;

[0040] Step 400: Based on the dynamic interaction model, an iterative algorithm and the global surface temperature remote sensing data and reanalysis meteorological data products are used to obtain an integrated inversion of the global ground-atmosphere coupling factor, surface impedance and aerodynamic impedance.

[0041] Specifically, this embodiment includes the following steps:

[0042] Step 1: Collect global surface temperature remote sensing data and reanalysis meteorological data products;

[0043] Step 2: Deconstruct the surface energy balance equation to obtain the corresponding physical model of each component;

[0044] Step 3: Based on the corresponding physical models of each component in the surface energy balance obtained in step 2, further mathematical deduction is performed to obtain a dynamic interaction model containing the ground-air coupling factor, surface impedance and aerodynamic impedance;

[0045] Step 4: Based on the dynamic interaction model of the ground-atmosphere coupling factor, surface impedance and aerodynamic impedance proposed in step 3, the iterative algorithm and the global reanalysis meteorological data collected in step 1 are used to obtain the integrated inversion of the global ground-atmosphere coupling factor, surface impedance and aerodynamic impedance.

[0046] Optionally, in step 1, the collected global high-precision reanalysis meteorological data includes air temperature, atmospheric pressure, relative humidity, wind speed, surface net radiation flux data and soil heat flux data, etc.

[0047] Furthermore, in step 2, the surface energy balance equation is deconstructed, and the corresponding physical models of each component are as follows: Formulas 1 to 4:

[0048] LE=R n -HG#(1)

[0049]

[0050]

[0051] Where LE is the latent heat flux (the energy expression of evaporation) (W / m 2 ); H is the sensible heat flux (W / m 2 );R n is the net radiation of the surface (W / m 2); G is soil heat flux (W / m 2 );T s is the surface temperature (℃); T a is the air temperature (℃); ρ is the air density (kg / m 3 );C p is the specific heat of air (J / (kg·℃); γ is the dry-bulb constant (Pa / ℃); e s is the surface vapor pressure (Pa); e a is the actual water vapor pressure (Pa); is the surface saturated vapor pressure (Pa); r s is the surface impedance (s / m); r ae is the aerodynamic impedance (s / m).

[0052] Furthermore, in step 3, based on the deconstruction of the corresponding physical models of each component of the surface energy balance equation, the aerodynamic impedance estimation model can be obtained by combining formula (1), (2), and (3) in formula 1: Formula 5:

[0053]

[0054] Furthermore, in step 3, based on the physical models of the components of the deconstructed surface energy balance equation, the surface impedance estimation model can be obtained by combining equations (3) and (4):

[0055]

[0056] Specifically, based on Formula 5 and Formula 6, in order to solve the aerodynamic impedance and surface impedance, the surface vapor pressure e is further introduced s The estimation method is as follows: Formula 7:

[0057]

[0058] Where Ω is the ground-atmosphere coupling factor; h s,max is the maximum relative humidity of the surface.

[0059] Furthermore, in step 3, the method for estimating the ground-atmosphere coupling factor is as follows:

[0060]

[0061] Where Δ is the slope of the saturated water vapor pressure curve (Pa / ℃).

[0062] Optionally, in step 4, the new method of the dynamic interaction model of the ground-atmosphere coupling factor and impedance described in formulas 5, 6, and 8 utilizes the meteorological data collected in step 1 and is further combined with an iterative algorithm to obtain the ground-atmosphere coupling factor and impedance values.

[0063] Furthermore, the iterative algorithm is a Fletcher-Reeves algorithm.

[0064] Furthermore, the Fletcher-Reeves iterative algorithm is specifically implemented as follows:

[0065] Data input: According to the new method for joint inversion of ground-atmosphere coupling factor and impedance as claimed in claim 1, in step 1, the input data includes air temperature, atmospheric pressure, relative humidity, wind speed, surface net radiation flux data and soil heat flux data.

[0066] Set the initial value. Set the aerodynamic impedance (r based on historical data or empirical values. ae ), surface impedance (r s ) and surface vapor pressure (e s ) has an important influence on the convergence and computational efficiency of the iterative process.

[0067] Determine the objective function. It is characterized by calculating the aerodynamic impedance (r ae ), surface impedance (r s ) and surface vapor pressure (e s ), the objective function is in the form of:

[0068]

[0069] in:

[0070]

[0071] Determine the gradient function. It is characterized by calculating the gradient of the objective function for use in the iterative process of the optimization algorithm. The gradient is defined as follows:

[0072]

[0073] It is characterized in that each partial derivative is expressed as:

[0074]

[0075] Iteration stop condition. It is characterized by that the iteration process will stop when any of the following conditions is met:

[0076] When the objective function When the value of is less than the preset threshold, the iteration stops.

[0077] When the number of iterations reaches the maximum number of iterations, the iteration stops.

[0078] When the difference between the results of two adjacent iterations is less than a preset threshold, the iteration stops.

[0079] The present invention is based on the dynamic interactive relationship among aerodynamic impedance, surface impedance and coupling factor with surface evapotranspiration as the medium, and takes into account the underlying physical process mechanism. On the basis of inverting surface evapotranspiration, the present invention simultaneously realizes the integrated inversion of aerodynamic impedance, surface impedance and ground-air coupling factor, which provides a new idea for accurately and objectively quantifying aerodynamic impedance, surface impedance and ground-air coupling factor.

[0080] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0081] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A joint inversion method of ground-atmosphere coupling factor and impedance, characterized in that: include: Obtain global surface temperature remote sensing data and reanalysis meteorological data products; Deconstruct the surface energy balance equation to obtain the corresponding physical model of each component; Mathematically deriving the physical model, a dynamic interaction model including ground-air coupling factor, ground surface impedance and aerodynamic impedance is obtained; Based on the dynamic interaction model, an iterative algorithm and the global surface temperature remote sensing data and reanalysis meteorological data products are used to obtain the integrated inversion of the global ground-atmosphere coupling factor, surface impedance and aerodynamic impedance; The physical model includes: THE R n -HG; Where, LE is the latent heat flux; H is the sensible heat flux; R n is the net radiation of the surface; G is the soil heat flux; T s is the surface temperature; T a is the air temperature; ρ is the air density; C p is the specific heat of air; γ is the dry-bulb constant; e s is the surface vapor pressure; e a is the actual water vapor pressure; is the surface saturated vapor pressure; r s is the surface impedance; r ae is the aerodynamic impedance; According to the physical model, mathematical deduction is performed to obtain a dynamic interaction model containing ground-air coupling factor, surface impedance and aerodynamic impedance, including: An aerodynamic impedance estimation model is constructed according to the physical model; the formula of the aerodynamic impedance estimation model is: A surface impedance estimation model is constructed according to the physical model; the formula of the surface impedance estimation model is: Construct a surface vapor pressure estimation model; the formula of the surface vapor pressure estimation model is: Where Ω is the ground-atmosphere coupling factor; h s,max is the maximum relative humidity of the surface; the calculation formula of the ground-air coupling factor is: Where, Δ is the slope of the saturated water vapor pressure curve; The dynamic interaction model is determined according to the aerodynamic impedance estimation model, the ground surface impedance estimation model and the ground surface vapor pressure estimation model.

2. The joint inversion method of ground-atmosphere coupling factor and impedance according to claim 1, characterized in that: The global surface temperature remote sensing data and reanalysis meteorological data products include: air temperature, atmospheric pressure, relative humidity, wind speed, surface net radiation flux data and soil heat flux data.

3. The joint inversion method of ground-atmosphere coupling factor and impedance according to claim 1, characterized in that: The iterative algorithm is the Fletcher-Reeves algorithm.

4. The joint inversion method of ground-atmosphere coupling factor and impedance according to claim 3 is characterized in that: The steps of the iterative algorithm include: Obtaining input data; the input data are global surface temperature remote sensing data and reanalysis meteorological data products; Set initial values ​​of aerodynamic impedance, surface impedance, and surface vapor pressure based on historical data or empirical values; An objective function is determined, and the aerodynamic impedance, surface impedance, and surface vapor pressure are calculated based on numerical minimization. The objective function has the form: in, f1, f2, and f3 all represent the error between the parameter value of the current iteration step and the expected value of the model; Calculate the gradient function of the objective function for the iterative process of the optimization algorithm; the gradient function is: in, An iterative process is performed, and the iterative process is stopped when an iteration stopping condition is satisfied.

5. The joint inversion method of ground-atmosphere coupling factor and impedance according to claim 4, characterized in that: The iteration stop condition includes: When the objective function When the value of is less than the preset threshold, the iteration stops; when the number of iterations reaches the maximum number of iterations, the iteration stops; when the change in the results of two adjacent iterations is less than the preset threshold, the iteration stops.

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