Method for constructing dusting or dusting parameterization scheme based on earth surface albedo

Abstract

The invention provides an earth surface albedo-based sand or dust parameterization scheme construction method, and belongs to the field of sand and dust numerical simulation, and the method comprises the steps: carrying out the stress measurement and illumination radiation measurement of a research region based on a wind tunnel experiment, and constructing a friction wind speed calculation model; performing grid division on the research area, obtaining the earth surface albedo of each grid by obtaining the satellite remote sensing data of each grid, and performing calculation by using the friction wind speed calculation model to obtain the friction wind speed of each grid; constructing a sand and dust emission formula, substituting the friction resistance wind speed of each grid into the sand and dust emission formula, calculating to obtain a sand and dust emission list of each grid, and completing construction of a sand raising or dust raising parameterization scheme; according to the method, the problems that the simulation result and the actual measurement result of the existing dusting or dusting parameterization scheme are uncertain, limited by real-time performance and limited by space singleness are solved.

Description

Technical Field

[0001] The present invention belongs to the field of numerical simulation of sand and dust, and particularly relates to a method for constructing a sand or dust emission parameterization scheme based on surface albedo. Background Technique

[0002] Sand and dust play an important role in the Earth system. It not only changes the atmospheric radiation properties and causes direct impacts, but also affects the Earth's radiation balance and water cycle, resulting in indirect impacts. Sand and dust pollution can lead to the onset of diseases in the human respiratory and cardiovascular systems and even cause death. The probability of residents suffering from desert pneumoconiosis is greatly increased for those who live in areas with frequent sand and dust weather for a long time. In arid and semi-arid regions of China, the frequency of sand and dust weather is high. Sand and dust are transported near the ground surface, increasing the concentration of particulate matter, causing air pollution, reducing visibility. When sand and dust are lifted to a certain height, it is easy to be transported over long distances, thus affecting the air quality in the transmission channel areas.

[0003] At present, with the support of field observations, wind tunnel experiments, and aeolian physics, many sand / dust emission parameterization schemes have been formed. Most of these parameterization schemes are based on the side shadow coverage of the windward side of the land. Through a large number of on-site measurements and land surveys, different land types are identified, and the friction velocity of different land types is obtained. However, the above parameterization schemes can only simulate fixed surface types, which are fixed in space, static in time, and the surface conditions are single. Therefore, there is a certain degree of uncertainty between the simulation results and the measured results. Summary of the Invention

[0004] Aiming at the above deficiencies in the prior art, the present invention provides a method for constructing a sand or dust emission parameterization scheme based on surface albedo, which solves the problems that the simulation results of the existing sand or dust emission parameterization schemes have uncertainty, are restricted by real-time performance, and are restricted by spatial singularity.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows: On the one hand, the present invention provides a method for constructing a sand or dust emission parameterization scheme based on surface albedo, including the following steps: S1. Based on wind tunnel experiments and light radiation experiments, stress measurement and light radiation measurement are carried out on the research area to construct a friction velocity calculation model; S2. The research area is divided into grids. By obtaining the satellite remote sensing data of each grid, the surface albedo of each grid is obtained, and the friction velocity calculation model is used for calculation to obtain the friction velocity of each grid; S3. A sand and dust emission formula is constructed, and the friction velocity of each grid is substituted into the sand and dust emission formula to calculate the sand and dust emission inventory of each grid, and the construction of the sand or dust emission parameterization scheme is completed.

[0006] The beneficial effects of the present invention are as follows: Based on wind tunnel experiments for stress measurement and light radiation experiments for light radiation measurement, the response relationship between surface albedo and friction velocity is constructed. By using the high spatio-temporal resolution surface albedo provided by satellite remote sensing data, a sand or dust emission parameterization scheme based on surface albedo is realized, improving the accuracy of the simulation results of the parameterization scheme compared with the measured results, and reducing the influence of real-time limitations and spatial singularity limitations on the sand or dust emission parameterization scheme.

[0007] Further, S1 includes the following steps: S101. Based on wind tunnel experiments, measure the shear stress of the surface and the lateral stress of each roughness element to obtain the experimental friction velocity. S102. Based on light radiation experiments, conduct light radiation measurement on the study area to obtain the experimental surface albedo. S103. Based on the parameterization scheme of shadow cover, use the surface albedo to replace the shadow cover, and construct a friction velocity calculation model according to the experimental friction velocity and the experimental surface albedo.

[0008] Still further, S103 includes the following steps: S1031. Based on the parameterization scheme of shadow cover, extract the fixed non-linear relationship between friction velocity and shadow cover. S1032. Normalize and invert the experimental surface albedo to obtain the processed surface albedo. S1033. Construct a friction velocity calculation model according to the experimental friction velocity, the processed surface albedo, and the fixed non-linear relationship between friction velocity and shadow cover.

[0009] Still further, the expression of the friction velocity calculation model is as follows: ; Wherein, represents the friction velocity, represents the free wind velocity at high altitude, represents the normalized surface albedo, A , B , C , D all represent model parameters.

[0010] The beneficial effects of the above further scheme are as follows: By replacing the shadow cover with the surface albedo, the present invention constructs the relationship between the surface albedo and the friction velocity, providing a basis for directly calculating the friction velocity using the surface albedo in the future; and simplifies the acquisition of the friction velocity, improving the accuracy and real-time performance of the friction velocity.

[0011] Still further, S2 includes the following steps: S201. Stitch, integrate, and interpolate the satellite tile data occupied by the research area to obtain satellite remote sensing data covering the entire research area; S202. Divide the research area into grids and obtain the surface albedo of each grid; S203. Calculate the friction velocity of each grid using the friction velocity calculation model based on the surface albedo of each grid.

[0012] The beneficial effects of the above further solution are as follows: By dividing the research area into grids, processing the satellite remote sensing data, and then calculating the friction velocity of each grid, the present invention realizes the construction of a sand or dust parameterization scheme for a large geographical area, reduces the difficulty of data acquisition, and improves the accuracy, real-time performance, and universality of the sand and dust parameterization scheme construction.

[0013] Furthermore, the S3 includes the following steps: S301. Obtain the critical friction velocity based on the soil particle size in each grid of the research area; S302. Construct a sand and dust emission formula based on the critical friction velocity, air density, gravitational acceleration, proportion of frozen soil, snow coverage, proportion of specific particle size sand and dust emitted into the air, and proportion of clay in each grid of the research area; S303. Substitute the friction velocity of each grid into the sand and dust emission formula to calculate the sand and dust emission inventory of each grid, and complete the construction of the sand or dust parameterization scheme.

[0014] Furthermore, the expression of the sand and dust emission formula is as follows: ; ; Where, represents the vertical emission amount of sand and dust, represents a constant, represents the air density in each grid of the research area, represents the gravitational acceleration, represents the critical friction velocity, represents the soil particle size in each grid of the research area, represents the soil water content, represents the horizontal emission amount of sand and dust, represents the proportion of frozen soil, represents the snow coverage, represents the proportion of sand and dust with a specific particle size emitted into the air, represents the proportion of clay.

[0015] To achieve the above object, according to the second aspect of the present invention, there is provided a computer device, comprising a memory for storing a computer program; a processor for implementing the steps of the method for constructing a sand or dust emission parameterization scheme based on surface albedo as described above when executing the computer program.

[0016] To achieve the above object, according to the third aspect of the present invention, there is provided a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for constructing a sand or dust emission parameterization scheme based on surface albedo as described above are implemented.

[0017] The beneficial effect of the above further scheme is that the present invention constructs a sand and dust emission formula, and obtains a sand and dust emission inventory based on surface albedo through the friction velocity of each grid; compared with the previous emission inventory based on side shadow coverage, the present invention improves the accuracy and reliability of the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0019] The following describes the specific embodiments of the present invention to facilitate those skilled in the art of the present technology to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions created using the concept of the present invention are within the scope of protection.

[0020] Embodiment 1 As Figure 1 shown, the present invention provides a method for constructing a sand or dust emission parameterization scheme based on surface albedo, and the implementation method is as follows: S1. Based on wind tunnel experiments and light radiation experiments, stress measurement and light radiation measurement are carried out on the research area, and a friction velocity calculation model is constructed. The specific steps are as follows: S101. Based on wind tunnel experiments, measure the shear stress of the ground surface and the side stress of each roughness element to obtain the experimental friction velocity; S102. Based on light radiation experiments, carry out light radiation measurement on the research area to obtain the experimental surface albedo; S103. Based on the parameterization scheme of side shadow coverage, use surface albedo to replace side shadow coverage, and construct a friction velocity calculation model according to the experimental friction velocity and the experimental surface albedo. The specific steps are as follows: S1031. Based on the parameterization scheme of the silhouette coverage, extract the fixed non-linear relationship between the friction velocity and the silhouette coverage; S1032. Normalize and invert the experimental surface albedo to obtain the processed surface albedo; S1033. According to the experimental friction velocity, the processed surface albedo, and the fixed non-linear relationship between the friction velocity and the silhouette coverage, construct a friction velocity calculation model.

[0021] In this embodiment, experiments are carried out in a wind tunnel. By measuring the stress on the ground surface, which includes the shear stress of the ground surface and the side stress of each rough element, the experimental friction velocity is obtained. And for different surface environments in the study area, the experimental surface albedo is obtained through light radiation measurement; Based on the parameterization scheme of the silhouette coverage, extract the fixed non-linear relationship between the friction velocity and the silhouette coverage; the expression of the parameterization scheme of the silhouette coverage is as follows: ; ; Wherein, represents the magnitude of the surface shear stress, , , and all represent constants, represents the air density, represents the friction velocity, represents the free wind speed at high altitude, represents the silhouette coverage, that is, when the light is incident at an angle of , the proportion of the projection of the surface obstacles on the ground surface to the entire surface area. It can be seen from the above formula that there is a fixed non-linear relationship between the friction velocity and the silhouette coverage , and the fixed non-linear relationship between the friction velocity and the silhouette coverage is extracted; Normalize and invert the experimental surface albedo to obtain the processed surface albedo; the inversion process means obtaining the part where the ground surface does not reflect. By using the experimentally processed surface albedo (black sky surface albedo), process the fixed non-linear relationship between the friction velocity and the silhouette coverage, and construct a friction velocity calculation model according to the experimental friction velocity; The expression of the friction velocity calculation model is as follows: ; Wherein, represents the silhouette coverage. Use the normalized surface albedo to replace the silhouette coverage , and organize the original expression to obtain the following formula: ; Among them, represents the normalized surface albedo, A , B , C , D all represent model parameters, which are obtained after parameter estimation from experimental data; in this embodiment, the values are respectively: , , , .

[0022] S2. Divide the study area into grids, obtain the surface albedo of each grid by acquiring satellite remote sensing data of each grid, and calculate the friction velocity of each grid using the friction velocity calculation model. The specific steps are as follows: S201. Stitch, integrate, and interpolate multiple satellite tile data occupied by the study area to obtain satellite remote sensing data covering the entire study area; S202. Divide the study area into grids and obtain the surface reflectance of each grid; S203. Calculate the friction velocity of each grid according to the surface albedo of each grid using the friction velocity calculation model.

[0023] In this embodiment, multiple satellite tile data occupied by the study area are stitched, integrated, and interpolated to obtain satellite remote sensing data covering the entire study area. The study area is divided into grids, the satellite remote sensing data of each grid is selected to obtain the surface albedo of each grid, and the friction velocity of each grid is calculated using the friction velocity calculation model; Since the surface albedo can be directly obtained from satellite remote sensing data, the method of the present invention is simpler to implement and has real-time and universality.

[0024] S3. Construct a sand dust emission formula, substitute the friction velocity of each grid into the sand dust emission formula, calculate the sand dust emission inventory of each grid, and complete the construction of the sand or dust parameterization scheme. The specific steps are as follows: S301. Obtain the critical friction velocity according to the soil particle size in each grid of the study area; S302. Construct a sand dust emission formula according to the critical friction velocity, air density, gravitational acceleration, proportion of frozen soil, snow coverage, proportion of sand dust with a specific particle size emitted into the air, and proportion of clay in each grid of the study area; S303. Substitute the friction velocity of each grid into the sand dust emission formula, calculate the sand dust emission inventory of each grid, and complete the construction of the sand or dust parameterization scheme.

[0025] In this embodiment, the critical friction velocity is obtained according to the soil particle size in each grid of the study area, and 10 is taken when studying PM10. , based on the MB (Marticorena-Bergametti) sand emission scheme, a sand dust emission formula is constructed according to the critical friction velocity, the air density in each grid of the study area, and the acceleration due to gravity. The specific expression of the sand dust emission formula is as follows: ; ; Among them, represents the vertical emission amount of sand dust, represents a constant, represents the air density in each grid of the study area, represents the acceleration due to gravity, represents the critical friction velocity, represents the soil particle size in each grid of the study area, represents the soil water content, represents the horizontal emission amount of sand dust (unit ), represents the proportion of frozen soil, represents the snow coverage rate, represents the proportion of sand dust with a specific particle size emitted into the air, represents the proportion of clay; Substitute the friction velocity of each grid into the sand dust emission formula to calculate the vertical emission amount and horizontal emission amount of sand dust in each grid, and obtain the sand dust emission inventory.

[0026] The present invention intends to use the surface albedo to replace the side shadow coverage to improve the accuracy of the friction velocity. Through wind tunnel experiments and light radiation experiments, the response relationship between the surface albedo and the friction velocity is constructed. Using the high spatio-temporal resolution surface albedo provided by satellite remote sensing data, a spatially heterogeneous and temporally dynamic friction velocity data set is established to complete the construction of a sand emission or dust generation parameterization scheme based on the surface albedo.

[0027] Example 2 In this embodiment, the friction velocity is obtained based on the surface albedo, and the atmospheric particulate matter concentration is further simulated.

[0028] Using the method of the present invention, the PM10 concentration in Tianjin area for each month of the whole year of 2023 was simulated, and the comparison between the predicted results and the measured values is shown in Table 1; Table 1

[0029] According to the data in Table 1, through practice, the maximum error of the method of the present invention does not exceed 30%, which is accurate and reliable. Moreover, due to the simple implementation method and the need for a large amount of on-site measurement work, under the condition of sufficient computing power, the prediction of the concentration of atmospheric particulate matter can be realized in real time.

[0030] Embodiment 3 In this embodiment, a computer device is provided, which is characterized by including a memory for storing a computer program; a processor for implementing the steps of the sand or dust generation parameterization scheme construction method based on surface albedo as described in Embodiment 1 when executing the computer program.

[0031] In this embodiment, a computer-readable storage medium is further provided, which is characterized in that a computer program is stored on the computer-readable storage medium, and the computer program implements the steps of the sand or dust generation parameterization scheme construction method based on surface albedo as described in Embodiment 1 when executed by a processor.

Claims

1. A method for constructing a parameterization scheme for sand or dust emission based on surface albedo, characterized in that, It includes the following steps: S1. Based on wind tunnel experiments and light radiation experiments, conduct stress measurement and light radiation measurement on the research area, and construct a friction velocity calculation model; S2. Divide the research area into grids, obtain the surface albedo of each grid by acquiring satellite remote sensing data of each grid, and use the friction velocity calculation model to calculate the friction velocity of each grid; S3. Construct a dust emission formula, substitute the friction velocity of each grid into the dust emission formula, calculate the dust emission inventory of each grid, and complete the construction of the sand or dust emission parameterization scheme.

2. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 1, wherein The S1 includes the following steps: S101. Based on wind tunnel experiments, measure the shear stress of the surface and the lateral stress of each roughness element to obtain the experimental friction velocity; S102. Based on light radiation experiments, conduct light radiation measurement on the research area to obtain the experimental surface albedo; S103. Based on the parameterization scheme of the silhouette coverage, use the surface albedo to replace the silhouette coverage, and construct a friction velocity calculation model according to the experimental friction velocity and the experimental surface albedo.

3. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 2, wherein The S103 includes the following steps: S1031. Based on the parameterization scheme of the silhouette coverage, extract the fixed non-linear relationship between the friction velocity and the silhouette coverage; S1032. Conduct normalization processing and inversion processing on the experimental surface albedo to obtain the processed surface albedo; S1033. Construct a friction velocity calculation model according to the experimental friction velocity, the processed surface albedo, and the fixed non-linear relationship between the friction velocity and the silhouette coverage.

4. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 3, characterized in that, The expression of the friction velocity calculation model is as follows: Among them, represents the friction velocity, represents the free wind speed at high altitude, represents the normalized surface albedo, A , B , C , D all represent model parameters.

5. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 1, wherein The S2 includes the following steps: S201. Stitch, integrate, and interpolate the multiple satellite tile data occupied by the research area to obtain the satellite remote sensing data including the entire research area; S202. Divide the research area into grids and obtain the surface reflectivity of each grid; S203. According to the surface albedo of each grid, use the friction velocity calculation model to calculate the friction velocity of each grid.

6. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 1, wherein The S3 includes the following steps: S301. Obtain the critical friction velocity according to the soil particle size in each grid of the research area; S302. Construct a dust emission formula according to the critical friction velocity, the air density, the gravitational acceleration, the proportion of frozen soil, the snow coverage rate, the proportion of specific particle size dust emitted into the air, and the proportion of clay in each grid of the research area; S303. Substitute the friction velocity of each grid into the dust emission formula, calculate the dust emission inventory of each grid, and complete the construction of the sand or dust emission parameterization scheme.

7. The method for constructing a sand or dust emission parameterization scheme based on surface albedo according to claim 6, wherein The expression of the dust emission formula is as follows: Among them, represents the vertical emission of dust, represents a constant, represents the air density in each grid of the study area, represents the acceleration due to gravity, represents the critical friction velocity of wind, represents the soil particle size in each grid of the study area, represents the soil water content, represents the horizontal emission of dust, represents the proportion of frozen soil, represents the snow coverage rate, represents the proportion of dust emissions of a specific particle size into the air, represents the proportion of clay.

8. A computer device, characterized in that, It includes a memory for storing computer programs; A processor, when executing the computer program, implements the steps of the method for constructing a sand or dust emission parameterization scheme based on surface albedo according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by the processor, it implements the steps of the method for constructing a sand or dust emission parameterization scheme based on surface albedo according to any one of claims 1 to 7.

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