A wind speed vertical profile interpolation method and system based on atmospheric thermodynamic model

Abstract

The application discloses a wind speed vertical profile interpolation method and system based on an atmospheric thermodynamic model, belongs to the technical field of wind energy, and acquires native vertical level meteorological data and vertical coordinate definition parameters output by a climate model; the meteorological data comprises horizontal wind components, air temperatures, specific humidity and ground surface air pressures of each vertical level; air pressure values of each vertical level are calculated according to the vertical coordinate definition parameters and the ground surface air pressures; virtual temperatures of each vertical level are calculated according to the air temperatures and the specific humidity; based on hydrostatic equilibrium, the geometric heights of each vertical level are calculated by layer-by-layer upward integration from the ground surface according to the air pressure values and the virtual temperatures; and the horizontal wind components at the target height are obtained by linear interpolation of the horizontal wind components in the logarithmic height coordinate system after the vertical level interval where the target height is located is determined, so that the wind speed vertical distribution can be accurately calculated.

Description

Technical Field

[0001] This invention belongs to the field of wind energy technology, specifically relating to a method and system for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model. Background Technology

[0002] In wind energy resource assessments, especially long-term assessments that take into account climate change, it is typically necessary to use output data from Global Climate Models (GCMs) or Regional Climate Models (RCMs). However, the wind speed data output by these models usually correspond to standard heights (such as 10 meters above the ground) or are based on the model's inherent pressure / topography-following coordinate system, rather than the actual hub height of the wind turbine (typically 80-150 meters, and over 200 meters offshore).

[0003] The traditional approach is to use power-law or logarithmic-law formulas, based on a fixed wind shear index (α), to extrapolate low-level wind speeds (such as wind speeds at a height of 10 meters) to the hub height. However, this extrapolation method has the following drawbacks: (1) Ignoring key climate feedback. The wind shear index itself is affected by atmospheric stability (vertical temperature gradient) and surface roughness. In the context of climate change, changes in sea surface temperature and air temperature will alter atmospheric stability, thereby changing the shape of the wind profile. Traditional fixed index methods cannot capture this dynamic physical process, which can easily lead to deviations in the prediction of future wind energy resource changes, often exaggerating the magnitude of changes.

[0004] (2) Insufficient data utilization. Traditional methods only use the single variable of wind speed at a height of 10 meters output by the model, and cannot utilize the temperature, humidity and air pressure information provided by the model at the vertical level, which are key parameters for describing the state of atmospheric stratification.

[0005] Therefore, there is an urgent need for a new interpolation method that has a solid physical foundation, can make full use of climate model output information, and can more accurately calculate the vertical distribution of wind speed. Summary of the Invention

[0006] The purpose of this invention is to overcome the problem of how to accurately calculate the vertical distribution of wind speed, and to propose a method and system for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model, comprising the following steps: Step 1: Obtain the original vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure for each vertical level. Step 2: Calculate the air pressure value for each vertical layer based on the defined parameters of the vertical coordinates and the surface air pressure; calculate the virtual temperature for each vertical layer based on the air temperature and specific humidity. Step 3: Based on hydrostatic equilibrium, integrate layer by layer from the surface upwards, and calculate the geometric height of each vertical layer according to the air pressure and virtual temperature. Step 4: Determine the vertical layer interval of the target height, and perform linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

[0008] Furthermore, the vertical coordinate definition parameters include reference air pressure and coordinate coefficients for each vertical level; in step two, the air pressure values ​​for each vertical level are calculated based on the reference air pressure, coordinate coefficients, and surface air pressure.

[0009] Furthermore, in step three, the thickness of the air column between two adjacent vertical layers is calculated based on the air pressure value and the virtual temperature, as shown in the following formula: z_{k→k+1}=(R_d \bar{T}_{v,[k,k+1]} / g) ln(p_k / p_{k+1}) Where z_{k→k+1} is the geometric thickness of the air column between the k-th and k+1-th layers, R_d is the dry air gas constant, g is the gravitational acceleration, T_{v,[k,k+1]} is the arithmetic mean of the imaginary temperatures between the k-th and k+1-th layers, p_{k+1} is the air pressure of the k+1-th layer, and ln is the natural logarithm function; The thickness of the air column is accumulated layer by layer from the ground surface to obtain the geometric height of each vertical layer.

[0010] Furthermore, in step four, the interpolation weights are calculated based on the logarithmic values ​​of the target height and the geometric heights at both ends of the vertical layer interval, as shown in the following formula: weight=[ln(z_target)-ln(z_k)] / [ln(z_{k+1})-ln(z_k)] Where weight is the interpolation weight, z_target is the target wheel hub height, z_k is the geometric height of the k-th layer, z_{k+1} is the geometric height of the (k+1)-th layer, and ln is the natural logarithm function; Based on the interpolation weights, the horizontal wind components at both ends of the vertical layer interval are linearly interpolated to obtain the horizontal wind component at the target height, as shown in the following formula: u_target=u_k+weight (u_{k+1}-u_k) v_target = v_k + weight (v_{k+1}-v_k) Where u_target is the zonal wind speed component at the target altitude, v_target is the meridional wind speed component at the target altitude, u_k is the zonal wind speed component at the k-th layer, u_{k+1} is the zonal wind speed component at the (k+1)-th layer, v_k is the meridional wind speed component at the k-th layer, v_{k+1} is the meridional wind speed component at the (k+1)-th layer, and weight is the interpolation weight.

[0011] Furthermore, after step four, the horizontal wind speed and direction at the target height are obtained by synthesizing the horizontal wind components.

[0012] Furthermore, within the vertical layer range of the target altitude, the air pressure and virtual temperature are linearly interpolated in a logarithmic height coordinate system to obtain the air pressure and virtual temperature at the target altitude; the air density at the target altitude is calculated based on the air pressure and virtual temperature; and the wind power density at the target altitude is calculated based on the air density and the horizontal wind speed.

[0013] Furthermore, if the climate model directly outputs the air pressure values ​​for each vertical level, the air pressure values ​​are directly read in step two; if the climate model directly outputs the geometric height for each vertical level, the geometric height is directly read in step three.

[0014] Secondly, the present invention provides a wind speed vertical profile interpolation system based on an atmospheric thermodynamic model, comprising: The data acquisition module is used to acquire the native vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure at each vertical level. The virtual temperature calculation module is used to calculate the air pressure value of each vertical layer based on the vertical coordinate definition parameters and the surface air pressure; and to calculate the virtual temperature of each vertical layer based on the air temperature and specific humidity. The height calculation module is used to calculate the geometric height of each vertical level by integrating layer by layer from the ground surface based on hydrostatic equilibrium and according to air pressure and virtual temperature. The component interpolation module is used to determine the vertical layer interval where the target height is located. It performs linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

[0015] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model.

[0017] Compared with the prior art, the present invention has the following beneficial technical effects: This invention proposes a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model. This method reconstructs the geometric height of each vertical layer based on the principle of hydrostatic equilibrium, and incorporates virtual temperature calculated from temperature and humidity data into the height calculation process. The reconstructed height field is strictly consistent with the thermodynamic state of the climate model itself, avoiding the idealized assumptions of fixed wind shear indices in traditional methods. The interpolated wind speed results conform to the actual distribution law of the atmospheric boundary layer wind profile, exhibiting stronger physical consistency. This invention can dynamically adapt to the spatiotemporal changes in atmospheric stratification. During the calculation process, the vertical distribution characteristics of air pressure, temperature, and humidity participate in the height reconstruction and interpolation constraints throughout, inherently reflecting changes in atmospheric stability. In the long-term assessment of wind energy resources under the background of climate change, it can accurately capture the impact of changes in air temperature and sea surface temperature on the wind shear profile, restore the true evolution trend of wind energy resources, and avoid the misjudgment of the magnitude of resource changes by traditional fixed index methods. This invention fully utilizes multi-dimensional meteorological data from the native vertical layers of climate models, incorporating horizontal wind components, air temperature, specific humidity, and surface air pressure into the computational framework, rather than relying solely on single-layer near-surface wind speed data. This significantly improves the utilization efficiency of climate model output data, and the mutual constraints of multiple physical quantities further ensure the reliability of the interpolation results. This invention employs a linear interpolation method in a logarithmic height coordinate system, which aligns with the logarithmic distribution characteristics of near-surface wind speed with altitude. Combined with physically reconstructed precise geometric height coordinates, this effectively improves the calculation accuracy of wind speed at the target altitude, providing reliable wind speed data support for scenarios such as wind energy resource assessment and preliminary wind farm surveys. Attached Figure Description

[0018] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way. Furthermore, the shapes and proportions of the components in the drawings are merely schematic to aid in understanding the invention and do not specifically limit the shapes and proportions of the components. In the drawings: Figure 1 This is a flowchart of a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to the present invention.

[0019] Figure 2 This is a simplified structural diagram of a wind speed vertical profile interpolation system based on an atmospheric thermodynamic model according to the present invention.

[0020] Figure 3 This is an electronic device diagram of an air velocity vertical profile interpolation method based on an atmospheric thermodynamic model according to the present invention.

[0021] Figure 4 This is a simplified flowchart of a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model, as described in an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] GCMs (Global Climate Models). WRA (Wind Resource Assessment).

[0024] Example 1 See Figure 1 A method for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model includes the following steps: Step 1: Obtain the native vertical-layer meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure of each vertical layer; using the native vertical-layer multi-physical quantity data of the climate model as the calculation input, it breaks through the limitation of traditional methods that only use a single layer of near-surface wind speed, and provides complete thermodynamic and dynamic basic data for the subsequent physical interpolation process, ensuring the physical integrity of the calculation link.

[0025] Step 2: Calculate the air pressure values ​​for each vertical layer based on the vertical coordinate definition parameters and surface air pressure; calculate the virtual temperature for each vertical layer based on air temperature and specific humidity; the vertical coordinate definition parameters include the reference air pressure and the coordinate coefficients for each vertical layer; in Step 2, the air pressure values ​​for each vertical layer are calculated based on the reference air pressure, coordinate coefficients, and surface air pressure. The coordinate definition system based on the climate model reconstructs the air pressure field for each layer, while introducing virtual temperature calculations to correct the influence of water vapor on the thermodynamic properties of the air, providing accurate air pressure and thermodynamic fundamental parameters for subsequent geometric altitude reconstruction, ensuring the physical accuracy of the altitude calculation. The method of calculating layer air pressure using reference air pressure, coordinate coefficients, and surface air pressure is adapted to the climate model data format of hybrid sigma-pressure coordinates.

[0026] Step 3: Based on hydrostatic equilibrium, integrate layer by layer upwards from the Earth's surface, calculating the geometric height of each vertical layer according to the air pressure and virtual temperature. In Step 3, calculate the air column thickness between two adjacent vertical layers based on the air pressure and virtual temperature, and accumulate the air column thickness layer by layer from the Earth's surface to obtain the geometric height of each vertical layer. Using the hydrostatic equilibrium equation as the theoretical basis, by calculating the air column thickness between adjacent vertical layers layer by layer and accumulating it layer by layer, the transformation from the model's original coordinates to geometric height coordinates is completed. The reconstructed height field is strictly consistent with the model's temperature, pressure, and humidity conditions, replacing the traditional empirical height assumption method.

[0027] Step 4: Determine the vertical layer interval where the target height is located, and perform linear interpolation of the horizontal wind component in a logarithmic height coordinate system to obtain the horizontal wind component at the target height. In Step 4, the interpolation weight is calculated based on the logarithmic values ​​of the geometric heights at both ends of the vertical layer interval and the target height. The horizontal wind component at both ends of the vertical layer interval is then linearly interpolated based on the interpolation weight to obtain the horizontal wind component at the target height. The linear interpolation method using a logarithmic height coordinate system conforms to the logarithmic distribution of near-surface atmospheric wind speed with height. Combined with the accurately reconstructed height layer from physical measurements, the wind field interpolation is completed, ensuring that the wind profile interpolation results conform to the basic distribution characteristics of the atmospheric boundary layer. The method of calculating the interpolation weight using the logarithmic height value ensures the mathematical rigor of the interpolation process.

[0028] After step four, the horizontal wind speed and direction at the target height are synthesized based on the horizontal wind components. Through vector synthesis, the horizontal wind components in two orthogonal directions are converted into the wind speed amplitude and direction information required for wind energy assessment. The output results directly match the conventional data requirements for wind energy resource assessment.

[0029] Within the vertical layer range of the target altitude, linear interpolation of air pressure and virtual temperature is performed in a logarithmic height coordinate system to obtain the air pressure and virtual temperature at the target altitude. The air density at the target altitude is then calculated based on the air pressure and virtual temperature. Finally, the wind power density at the target altitude is calculated based on the air density and horizontal wind speed. Thermodynamic parameters at the target altitude are obtained using interpolation logic consistent with the wind field, and then air density and wind power density are calculated. This achieves integrated calculation of core wind energy resource assessment parameters, ensuring the consistency of all physical quantities under the same height coordinate system.

[0030] If the climate model directly outputs the air pressure values ​​for each vertical level, the air pressure values ​​are directly read in step two; if the climate model directly outputs the geometric altitude for each vertical level, the geometric altitude is directly read in step three. Adaptive branches are set up for climate models with different vertical coordinate systems. For models that directly output air pressure values ​​or geometric altitude, the corresponding parameters can be directly read without repeating the air pressure or altitude calculation steps. This improves the method's adaptability to multi-source climate model data and simplifies the calculation process in corresponding scenarios.

[0031] See Figure 4 A method for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model is described below, with the following specific steps: Step 1: Obtaining raw data: Obtain a multidimensional dataset of the target region from the output database of a climate model (such as CMIP6), arranged in time series (e.g., every 6 hours), for a specified time period. This dataset must include: 1.1 Zonal wind speed components (ua) and meridional wind speed components (va) at the original vertical level of the model.

[0032] 1.2. Air temperature (ta) and specific humidity (hus) at the same vertical level.

[0033] 1.3 Surface air pressure (ps).

[0034] 1.4 Define the parameters of the vertical coordinate of the model (e.g., for mixed sigma-pressure coordinates, coefficients a_k and b_k, as well as the reference pressure p0 are required).

[0035] Step 2: Calculation of air pressure and virtual temperature in the model layer: For each horizontal grid point and each output time step: 2.1 Calculate the air pressure of each model layer. If the model uses a mixed coordinate system, the air pressure p_k of the k-th layer is obtained using the formula p_k=a_k. p0+b_k The values ​​are calculated from ps. Here, p0 is the reference pressure, a_k and b_k are the sigma coefficients of the model at level k, and ps is the surface air pressure. These parameters and data are all from the 6hrLev table of CMIP6.

[0036] 2.2 Calculate the virtual temperature of each model layer. The virtual temperature T_{v,k} of the k-th layer is calculated using the formula T_{v,k}=ta_k (1+0.608 The virtual temperature (hus_k) is calculated, where 0.608 is a commonly used approximation of the ratio of water vapor to the gas constant of dry air (R_v / R_d-1). The virtual temperature is the "effective temperature" that takes into account the effect of humidity, used to accurately calculate air density and stratification. ta_k is the air temperature at layer k, and hus_k is the specific humidity at layer k.

[0037] Step 3: Calculation of model layer geometric height (thickness): Based on the hydrostatic equilibrium assumption, the geometric height z_k of the midpoint or interface of each model layer from the ground surface is calculated by integrating upwards from the ground surface.

[0038] 3.1 For two adjacent layers k and k+1, the thickness of the air column between them is determined by the pressure height formula: z_{k→k+1}=(R_d \bar{T}_{v,[k,k+1]} / g) ln(p_k / p_{k+1}) in: z_{k→k+1} is the geometric thickness of the air column between the k-th layer and the (k+1)-th layer; R_d is the gas constant for dry air (~287.058 J / kg / K).

[0039] g is the acceleration due to gravity (~9.80665 m / s²). 2 ).

[0040] \bar{T}_{v,[k,k+1]} is the arithmetic mean of the virtual temperatures between the k-th and k+1-th layers, i.e. (T_{v,k}+T_{v,k+1}) / 2.

[0041] p_{k+1} represents the air pressure at the (k+1)th layer.

[0042] ln is the natural logarithm function.

[0043] 3.2 Starting from the ground height z_0=0 meters and the air pressure p_0=ps, the height z corresponding to all model layers is obtained by accumulating Δz.

[0044] Step 4: Target Height Wind Field Interpolation: For a given target wheel hub height z_target (e.g., 100 meters, 150 meters): 4.1 Interpolating wind components in logarithmic height coordinates. To conform to the general shape of the atmospheric boundary layer wind speed profile, linear interpolation is performed in the (ln(z),u) and (ln(z),v) coordinate systems. Specifically: find the model hierarchy interval [z_k,z_{k+1}] where z_target is located, and calculate the interpolation weights: weight=[ln(z_target)-ln(z_k)] / [ln(z_{k+1})-ln(z_k)] Where weight is the interpolation weight; z_target is the target wheel hub height; z_k is the geometric height of the k-th layer; z_{k+1} is the geometric height of the (k+1)th layer; ln is the natural logarithm function.

[0045] Then calculate the zonal and meridional winds at the target altitude: u_target=u_k+weight (u_{k+1}-u_k) v_target = v_k + weight (v_{k+1}-v_k) Where u_target is the zonal wind speed component at the target altitude; v_target is the meridional wind speed component at the target altitude; u_k is the zonal wind speed component of the k-th layer; u_{k+1} represents the zonal wind speed component at the (k+1)th layer; v_k is the meridional wind speed component of the k-th layer; v_{k+1} is the meridional wind speed component of the (k+1)th layer; weight is the interpolation weight.

[0046] 4.2 Composite Wind Speed ​​and Direction. Calculate the horizontal wind speed at the target height: U_target = sqrt{(u_target)} 2 +(v_target) 2 The meteorological wind direction is calculated based on u_target and v_target.

[0047] Step 5: Calculation of air density and wind power density at target altitude: 5.1. Using the same interpolation method as in 4.1, obtain the air pressure p_target and virtual temperature T_{v,target} at the target altitude.

[0048] 5.2 Calculate the air density at the target altitude: ρ_target = p_target / (R_d) T_{v,target}).

[0049] 5.3 Calculate wind power density: P_target = 0.5 ρ_target (U_target) 3 .

[0050] The method described in this invention is applicable not only to models using hybrid sigma-pressure coordinates (requiring a_k, b_k coefficients), but also to models that directly output stratified pressure (pfull) or geometrical altitude (zhalf). For the latter, step 2.1 can be simplified to directly reading the pressure or altitude, and step 3 can be simplified or skipped accordingly.

[0051] This invention boasts high physical precision, based on hydrostatic and thermodynamic equations, directly utilizing temperature and humidity information to ensure strict self-consistency between the interpolation results and the model's own physical state, particularly accurately reflecting low-wind shear characteristics at sea. It exhibits strong dynamic adaptability; since the interpolation process relies on the vertical profiles of temperature and humidity varying with time and space, this invention automatically and intrinsically considers changes in atmospheric stability. In scenarios where climate warming leads to stability changes, this method provides more reliable wind speed change predictions than the fixed-index method. It reduces systematic bias, fundamentally avoiding the systematic overestimation caused by the use of inappropriate fixed indices in traditional power-law methods, providing more accurate input for wind farm power generation estimation and reducing investment risk. It fully utilizes data, maximizing the use of multivariate and multi-level information provided by climate models, incorporating the coordinated changes of wind, temperature, humidity, and pressure into the computational framework.

[0052] This invention, based on fundamental atmospheric thermodynamic equations, directly utilizes original vertical layer data from climate models for precise vertical interpolation of wind speed. Using pressure, temperature, and humidity data from the model layers, it calculates the height of each model layer by solving hydrostatic equations. Then, it performs logarithmic linear interpolation of the horizontal wind speed component at each height, ultimately obtaining wind speed and direction at a height of 100 meters above the ground (approximately the hub height of modern offshore wind turbines). By directly utilizing wind, temperature, humidity, and pressure data from the original vertical layers of the climate model, it accurately reconstructs the geometric height from the model coordinates according to physical equations, and performs linear interpolation of the wind component in the logarithmic height coordinates, obtaining hub-height wind field data that is consistent with the physical state of the model and dynamically reflects the influence of atmospheric stability. This invention, based on original layer data from climate models, uses hydrostatic equations for physical interpolation to obtain more accurate hub-height wind conditions. Compared to simple power-law extrapolation methods, it more accurately reflects boundary layer wind shear changes and considers possible changes in atmospheric stability. It has broad application value in future climate change scenario assessments. Because its interpolation results inherently depend on the vertical profiles of temperature and humidity that change with climate change, this invention can more accurately capture the potential impact of atmospheric stability changes caused by global warming on wind energy resources, thus solving the technical defect of systematic bias in the traditional fixed index method in this scenario.

[0053] Example 2 See Figure 2 A wind speed vertical profile interpolation system based on an atmospheric thermodynamic model, comprising: The data acquisition module is used to acquire the native vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure at each vertical level. The virtual temperature calculation module is used to calculate the air pressure value of each vertical layer based on the vertical coordinate definition parameters and the surface air pressure; and to calculate the virtual temperature of each vertical layer based on the air temperature and specific humidity. The height calculation module is used to calculate the geometric height of each vertical level by integrating layer by layer from the ground surface based on hydrostatic equilibrium and according to air pressure and virtual temperature. The component interpolation module is used to determine the vertical layer interval where the target height is located. It performs linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

[0054] Example 3 See Figure 3 An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model, comprising the following steps: Step 1: Obtain the original vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure for each vertical level. Step 2: Calculate the air pressure value for each vertical layer based on the defined parameters of the vertical coordinates and the surface air pressure; calculate the virtual temperature for each vertical layer based on the air temperature and specific humidity. Step 3: Based on hydrostatic equilibrium, integrate layer by layer from the surface upwards, and calculate the geometric height of each vertical layer according to the air pressure and virtual temperature. Step 4: Determine the vertical layer interval of the target height, and perform linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

[0055] Example 4 A computer-readable storage medium storing a computer program, which, when executed by a processor, implements a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model, comprising the following steps: Step 1: Obtain the original vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure for each vertical level. Step 2: Calculate the air pressure value for each vertical layer based on the defined parameters of the vertical coordinates and the surface air pressure; calculate the virtual temperature for each vertical layer based on the air temperature and specific humidity. Step 3: Based on hydrostatic equilibrium, integrate layer by layer from the surface upwards, and calculate the geometric height of each vertical layer according to the air pressure and virtual temperature. Step 4: Determine the vertical layer interval of the target height, and perform linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

[0056] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, read-only optical discs, optical storage, etc.) containing computer-usable program code.

[0057] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0058] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0059] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for interpolating the vertical profile of wind speed based on an atmospheric thermodynamic model, characterized in that, Includes the following steps: Step 1: Obtain the original vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure of each vertical level. Step 2: Calculate the air pressure value for each vertical layer based on the defined parameters of the vertical coordinates and the surface air pressure; calculate the virtual temperature for each vertical layer based on the air temperature and the specific humidity. Step 3: Based on hydrostatic equilibrium, integrate layer by layer from the ground surface upwards, and calculate the geometric height of each vertical layer according to the air pressure value and the virtual temperature; Step 4: Determine the vertical layer interval where the target height is located, and perform linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

2. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 1, characterized in that, The vertical coordinate definition parameters include reference air pressure and coordinate coefficients for each vertical level; In step two, the air pressure values ​​for each vertical level are calculated based on the reference air pressure, the coordinate coefficient, and the surface air pressure.

3. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 1, characterized in that, In step three, the thickness of the air column between two adjacent vertical layers is calculated based on the air pressure value and the virtual temperature, as shown in the following formula: z_{k→k+1}=(R_d \bar{T}_{v,[k,k+1]} / g) ln(p_k / p_{k+1}) Where z_{k→k+1} is the geometric thickness of the air column between the k-th and k+1-th layers, R_d is the dry air gas constant, g is the gravitational acceleration, T_{v,[k,k+1]} is the arithmetic mean of the imaginary temperatures between the k-th and k+1-th layers, p_{k+1} is the air pressure of the k+1-th layer, and ln is the natural logarithm function; The thickness of the air column is accumulated layer by layer from the ground surface to obtain the geometric height of each vertical layer.

4. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 1, characterized in that, In step four, the interpolation weight is calculated based on the logarithm of the target height and the geometric heights at both ends of the vertical layer interval, as shown in the following formula: weight=[ln(z_target)-ln(z_k)] / [ln(z_{k+1})-ln(z_k)] Where weight is the interpolation weight, z_target is the target wheel hub height, z_k is the geometric height of the k-th layer, z_{k+1} is the geometric height of the (k+1)-th layer, and ln is the natural logarithm function; Based on the interpolation weights, the horizontal wind components at both ends of the vertical layer interval are linearly interpolated to obtain the horizontal wind component at the target height, as shown in the following formula: u_target=u_k+weight (u_{k+1}-u_k) v_target=v_k+weight (v_{k+1}-v_k) Where u_target is the zonal wind speed component at the target altitude, v_target is the meridional wind speed component at the target altitude, u_k is the zonal wind speed component at the k-th layer, u_{k+1} is the zonal wind speed component at the (k+1)-th layer, v_k is the meridional wind speed component at the k-th layer, v_{k+1} is the meridional wind speed component at the (k+1)-th layer, and weight is the interpolation weight.

5. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 1, characterized in that, After step four, the horizontal wind speed and direction at the target height are synthesized based on the horizontal wind components.

6. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 5, characterized in that, Within the vertical layer range where the target altitude is located, the air pressure value and the virtual temperature are linearly interpolated in a logarithmic height coordinate system to obtain the air pressure value and virtual temperature at the target altitude; the air density at the target altitude is calculated based on the air pressure value and the virtual temperature at the target altitude; and the wind power density at the target altitude is calculated based on the air density and the horizontal wind speed.

7. The wind speed vertical profile interpolation method based on an atmospheric thermodynamic model according to claim 1, characterized in that, If the climate model directly outputs the air pressure values ​​for each vertical level, the air pressure values ​​are read directly in step two; if the climate model directly outputs the geometric heights for each vertical level, the geometric heights are read directly in step three.

8. A wind speed vertical profile interpolation system based on an atmospheric thermodynamic model, characterized in that, include: The data acquisition module is used to acquire the native vertical-level meteorological data and vertical coordinate definition parameters output by the climate model; the meteorological data includes the horizontal wind component, air temperature, specific humidity, and surface air pressure of each vertical level. The virtual temperature calculation module is used to calculate the air pressure value of each vertical layer based on the defined parameters of the vertical coordinates and the surface air pressure; and to calculate the virtual temperature of each vertical layer based on the air temperature and the specific humidity. The height calculation module is used to calculate the geometric height of each vertical layer by integrating from the ground surface upwards based on the hydrostatic equilibrium and according to the air pressure value and the virtual temperature. The component interpolation module is used to determine the vertical layer interval where the target height is located, and to perform linear interpolation on the horizontal wind component in the logarithmic height coordinate system to obtain the horizontal wind component at the target height.

9. An electronic device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the wind speed vertical profile interpolation method based on an atmospheric thermodynamic model as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements a wind speed vertical profile interpolation method based on an atmospheric thermodynamic model as described in any one of claims 1-7.

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