Refined evaluation method for atmospheric water substance delivery amount and change thereof in Tibet region

Abstract

The invention discloses a Tibet region atmosphere water substance conveying amount and change fine evaluation method, and relates to the technical field of atmosphere diagnosis. The invention relates to a Tibet region atmospheric water substance conveying amount and change refined evaluation method. The method comprises the following steps of boundary lattice point screening, a boundary lattice point conveying method, regional atmospheric water substance conveying amount, regional conveying change trend and result verification. The method aims at improving the precision and applicability of estimation of the regional atmospheric water substance conveying amount, and particularly has remarkable advantages for complex terrain regions such as Tibet. Performing cross validation in combination with high-resolution reanalysis data and rainfall grid point data, and proving the reliability of the method in the aspects of time sequence change trend and spatial distribution characteristics; standardized processing and linear tendency rate analysis can clearly reveal the long-term change rule of water vapor, cloud liquid water, cloud ice water and the like, and a scientific basis is provided for regional aerial water resource management and climate evolution research.

Description

Technical Field

[0001] This invention relates to the field of atmospheric diagnostic technology, specifically to a refined assessment method for atmospheric water substance transport and its changes in the Tibet region. Background Technology

[0002] The Qinghai-Tibet Plateau, hailed as the Earth's "Third Pole" and the "Water Tower of Asia," has seen profound scientific revelations from the Second Comprehensive Scientific Expedition to the Qinghai-Tibet Plateau, revealing fundamental scientific facts about the imbalance and warming / humidification trend of this "Water Tower." Tibet, occupying the main body of the Qinghai-Tibet Plateau, is a "sensitive area" and "amplifier" of climate and ecological changes. It is also a crucial ecological security barrier and strategic resource reserve base for my country, playing a vital role in maintaining climate system stability, water resource supply, and biodiversity conservation. Furthermore, the Qinghai-Tibet Plateau is the source of major Asian rivers, such as the Yangtze, Yellow, Indus, and Lancang (Mekong) Rivers. Studying the characteristics and trends of atmospheric water transport in Tibet is essential for understanding changes in the plateau's water cycle and is of great significance for building Tibet into an ecological security barrier and a high ground for ecological civilization. Summary of the Invention

[0003] The purpose of this invention is to provide a refined assessment method for atmospheric water substance transport and its changes in the Tibet region, which is used to provide a method for measuring atmospheric water substance transport.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A refined assessment method for atmospheric water substance transport and its changes in the Tibet region includes the following steps: boundary grid point screening, boundary grid point transport method, regional atmospheric water substance transport, regional transport change trend, and result verification. S1 Boundary Grid Point Filtering: Divide the administrative region of Tibet into an irregular polygon composed of multiple grid points, and filter boundary grid points near the administrative boundary line in order to process each grid point and calculate the input and output on the boundary. S2 Boundary Grid Transport Method: The physical flux of reanalyzed data is divided into eastern and northern components, with eastward and northward transport as positive directions and vice versa. Based on the location of each boundary grid point, all directions of atmospheric material input and output for each grid point are listed in both longitudinal and latitudinal directions. Considering the continuity of atmospheric motion, the transport relationship between boundary grid points at the same latitude or longitude is not included in the regional atmospheric water material balance. The annual and monthly transport volume of atmospheric water material in the Tibet region is calculated by accumulating the total annual and monthly transport volume of atmospheric water material through all boundary grid points in the Tibet region. The total annual and monthly input and output of atmospheric water material through all boundary grid points in the Tibet region are calculated, and then averaged over time to obtain the regional annual and monthly average total input and output. The difference between the two is the net input. Net input = total input – total output. Net input > 0 is called net input, and vice versa. Atmospheric water substance transport in the S3 region: Based on the annual average transport, the annual input of water vapor (WV), liquid water (LW), frozen water (FW), and total water substance (W) is compared with the annual output of water vapor, liquid water, frozen water, and total water substance to determine the net input value and the characteristics of atmospheric water substance transport in the region. S4 Region Transport Trends: The time series data of total monthly and annual inputs, total outputs, and net inputs of each component of atmospheric water matter (WV, LW, FW, and W) in the Tibet region were standardized using the following formulas: , In the formula: x This is the original data. μ The mean, σ The formula transforms the original data into a new series with a mean of 0 and a standard deviation of 1. After standardization, the linear trend of each component's time series is analyzed to obtain its respective linear tendency rate. Then, the correlation coefficient between the original series and time is calculated, and the linear tendency rate is... a， The correlation coefficient is ρ The calculation results are used to confirm the regional transport trend. S5 Results Verification: Based on the latest 0.5°×0.5° horizontal resolution precipitation grid data generated by the China Land Digital Elevation Model (DEM) produced by the National Meteorological Information Center using surface precipitation data from national-level stations across the country and GTOP30 data through resampling, and compared with the data, the feasibility of using high-resolution reanalysis data and the boundary grid transport method to assess atmospheric water transport in the Tibet region was verified.

[0005] Furthermore, in the S1 boundary grid point screening, the center point of the grid point is referenced based on the latitude and longitude of the reanalysis data. Select the grid point whose center point is closest to the administrative boundary line as the boundary grid point, so that the boundary grid point fits the administrative boundary line; Apart from other boundary grid points, no overlapping or obstructing grid points should appear in front of the four directions of atmospheric water material transport; that is, no redundant grid points should appear in front of the transport.

[0006] Furthermore, in the S2 boundary grid point transport method, a positive value for the north component of the flux at the grid point indicates northward transport, while a negative value indicates southward transport; a positive value for the east component of the flux at the grid point indicates eastward transport, while a negative value indicates westward transport; the transport direction between boundary grid points cannot be included in the input or output directions, and the selected atmospheric water material transport directions for all boundary grid points in the Tibet region are 1 to 3.

[0007] The beneficial effects of this invention are as follows: This application aims to improve the accuracy and applicability of regional atmospheric water transport estimation, especially for complex terrain regions such as Tibet, where it has significant advantages; by finely screening boundary grid points and standardizing the principles for determining transport direction, it effectively avoids the problem of repeated flux calculations caused by grid point redundancy or misjudgment of direction in traditional methods; by combining high-resolution reanalysis data with precipitation grid data for cross-validation, it further proves the reliability of this method in terms of time series variation trends and spatial distribution characteristics; the standardized processing and linear trend rate analysis adopted can clearly reveal the long-term variation patterns of components such as water vapor, cloud liquid water, and cloud ice water, providing a scientific basis for regional water resource management and climate evolution research.

[0008] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0009] Figure 1 To fit the administrative boundary of Tibet to the data for further analysis, a boundary grid map was selected.

[0010] Figure 2 A graph showing the boundary grid points and atmospheric water transport directions selected for the Tibet region.

[0011] Figure 3 This is a map showing the monthly average atmospheric water transport volume in the Tibet region from 1980 to 2024.

[0012] Figure 4 This is a map showing the number of boundary grid points for net atmospheric water input and net output in the Tibet region from 1980 to 2024.

[0013] Figure 5 This is a map showing the monthly average net input of atmospheric water substances at the north-south and east-west boundaries of the Tibet region from 1980 to 2024.

[0014] Figure 6 This is a map showing the net input and spatial distribution of the Tibetan border grid from 1980 to 2024.

[0015] Figure 7 A chart showing the number of grid points for each threshold value of net atmospheric water input in the Tibet region from 1980 to 2024.

[0016] Figure 8 Linear trend rate of monthly net input of atmospheric water substances in Tibet from 1980 to 2024. a and correlation coefficient ρ Data charts.

[0017] Figure 9This is a linear trend distribution map of atmospheric water transport at grid points along the Tibetan border from 1980 to 2024. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0020] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0022] Please see Figure 1 The refined assessment method for atmospheric water substance transport and its changes in the Tibet region presented in this application includes the following steps: boundary grid point screening, boundary grid point transport method, regional atmospheric water substance transport, regional transport change trend, and result verification. S1 Boundary Grid Point Filtering: Divide the administrative region of Tibet into an irregular polygon composed of multiple grid points, and filter boundary grid points near the administrative boundary line in order to process each grid point and calculate the input and output on the boundary. S2 Boundary Grid Transport Method: The physical flux of reanalyzed data is divided into eastern and northern components, with eastward and northward transport as positive directions and vice versa. Based on the location of each boundary grid point, all directions of atmospheric material input and output for each grid point are listed in both longitudinal and latitudinal directions. Considering the continuity of atmospheric motion, the transport relationship between boundary grid points at the same latitude or longitude is not included in the regional atmospheric water material balance. The annual and monthly transport volume of atmospheric water material in the Tibet region is calculated by accumulating the total annual and monthly transport volume of atmospheric water material through all boundary grid points in the Tibet region. The total annual and monthly input and output of atmospheric water material through all boundary grid points in the Tibet region are calculated, and then averaged over time to obtain the regional annual and monthly average total input and output. The difference between the two is the net input. Net input = total input – total output. Net input > 0 is called net input, and vice versa. S3 regional atmospheric water substance transport: Based on the annual average transport, the annual input of water vapor (WV), cloud liquid water (LW), cloud ice water (FW) and total water substance (W) is compared with the annual output of water vapor, cloud liquid water, cloud ice water and total water substance to determine the net input value and regional atmospheric water substance transport characteristics. S4 Region Transport Trends: The time series data of total monthly and annual inputs, total outputs, and net inputs of each component of atmospheric water matter (WV, LW, FW, and W) in the Tibet region were standardized using the following formulas: , In the formula: x This is the original data. μ The mean, σ The formula transforms the original data into a new series with a mean of 0 and a standard deviation of 1. After standardization, the linear trend of each component's time series is analyzed to obtain its respective linear tendency rate. Then, the correlation coefficient between the original series and time is calculated, and the linear tendency rate is... a， The correlation coefficient is ρ The calculation results are used to confirm the regional transport trend. S5 Results Verification: Based on the latest 0.5°×0.5° horizontal resolution precipitation grid data generated by the China Land Digital Elevation Model (DEM) produced by the National Meteorological Information Center using surface precipitation data from national-level stations across the country and GTOP30 data through resampling, and compared with the data, the feasibility of using high-resolution reanalysis data and the boundary grid transport method to assess atmospheric water transport in the Tibet region was verified.

[0023] In the S1 boundary grid point selection, the center point of the grid point is referenced based on the latitude and longitude of the reanalysis data. Select the grid point whose center point is closest to the administrative boundary line as the boundary grid point, so that the boundary grid point fits the administrative boundary line; Apart from other boundary grid points, no overlapping or obstructing grid points should appear in front of the four directions of atmospheric water material transport; that is, no redundant grid points should appear in front of the transport.

[0024] Figure 2 In the S2 boundary grid transport method, a positive value for the north component of the flux at a grid point indicates northward transport, while a negative value indicates southward transport; a positive value for the east component of the flux at a grid point indicates eastward transport, while a negative value indicates westward transport; the transport direction between boundary grid points cannot be included as input or output direction, and the selected boundary grid points in the Tibet region correspond to 1 to 3 transport directions for atmospheric water substances.

[0025] The total amount of atmospheric water substance input and output passing through all boundary grid points of the Tibet region is calculated year by year and month by month. Then, the average is calculated over time to obtain the region's annual and monthly average total input and output. The difference between these two values ​​is the net input. That is: Net Input = Total Input – Total Output. When net input > 0, it is called net input; conversely, when net input < 0, it is called net output.

[0026] Figure 3 This visually illustrates the monthly and annual average transport of atmospheric water substances in the Tibet region from 1980 to 2024. The monthly average water vapor transport ( Figure 3 a) It can be seen that from January to October, the total input exceeds the total output, resulting in a net water vapor input. In November and December, the total output exceeds the total input, resulting in a net water vapor output. Among these months, June has the largest total input and output, with a total input of 3129.7 × 10⁻⁶. 8 t, total output 2358.6×10 8 However, the largest net input occurred in July, reaching 1173.6 × 10⁻⁶. 8 t; December has the smallest total input and output, with a total input of 884.3 × 10. 8 t, total output 897.9 × 10 8 t, net input is –13.6 × 10 8 t. From the average monthly transport volume of cloud liquid water ( Figure 3 (b) From this perspective, the total input for all 12 months of the year exceeded the total output, indicating that cloud liquid water was a net input in every month of the year. The largest monthly transport volume also occurred in June, with a total input of 26.7 × 10⁻⁶. 8 t, total output 11.9 × 10 8 t, net input 14.8×10 8 t; November saw the lowest transport volume, with a total input of 7.5 × 10 8 t, total output 3.8 × 10 8 t, net input is only 3.7×10 8t. From the average monthly transport volume of cloud ice water ( Figure 3 c) From this perspective, the total monthly input is higher in winter and spring, and relatively lower in summer and autumn, with the highest total input being 25.7 × 10 in February. 8 t, the minimum is 6.9 × 10 in August. 8 The maximum total output for t is 27.6 × 10 in May. 8 t, the minimum is 9.9 × 10 in December. 8 t; Net monthly input is from January to March and December, and net output is from April to November. Total average monthly transport of water materials ( Figure 3 The monthly distribution of d) is similar to that of water vapor. From January to October, the total input exceeds the total output, resulting in a net input of total water matter. In November and December, the total output exceeds the total input, resulting in a net output of total water matter, but the net output is relatively small. The largest total input and output occurs in June, with a total input of 3168.4 × 10⁻⁶. 8 t, total output 2395.5×10 8 However, the largest net input occurred in July, reaching 1177.1 × 10⁻⁶. 8 t; December has the smallest total input and output, with a total input of 906.3 × 10. 8 t, total output 911.7×10 8 t, net input is –5.3 × 10 8 t.

[0027] In terms of average annual transport, the total annual input of water vapor, cloud liquid water, cloud ice water, and total water matter is 21841.4 × 10⁻⁶. 8 t, 191.9×10 8 t, 184.6×10 8 t and 22217.9×10 8 The first three components accounted for 98.3%, 0.9%, and 0.8% of the total water input, respectively. The annual output of water vapor, cloud liquid water, cloud ice water, and total water matter was 17407.0 × 10⁻⁶. 8 t, 85.7×10 8 t, 223.6×10 8 t and 17716.4×10 8 The first three components account for 98.2%, 0.5%, and 1.3% of the total annual water mass output, respectively. The annual net input of water vapor, cloud liquid water, cloud ice water, and total water mass is 4434.4 × 10⁻⁶. 8 t, 106.2×10 8 t、–39.0×10 8 t and 4501.6×10 8The first three components (water vapor, cloud water vapor, and cloud ice water) account for 98.5%, 2.4%, and -0.9% of the total net input of water substances, respectively. This shows that water vapor accounts for over 98% of the total annual water substance transport, while the transport of cloud liquid water and cloud ice water is relatively small, less than 2%. The annual output of cloud ice water exceeds the annual input, indicating a net output of solid cloud ice water in the Tibetan region. This is likely because the high altitude of the Tibetan Plateau facilitates the condensation of water vapor or cloud liquid water into solid cloud ice water, which is then exported from the Tibetan region, resulting in a net export of cloud ice water.

[0028] Boundary grid points where the net input for a given month and year is greater than 0 are called net input grid points, and vice versa, they are called net output grid points. The average number of boundary grid points for each component of atmospheric water matter and the net input and net output of total water matter in the Tibetan region for each month and year is counted.

[0029] from Figure 4 It can be seen that the number of grid points for net input and net output of various components of atmospheric water in the Tibetan region varies over time. Looking at the average number of grid points per month, the number of net input grid points is 1–33 more than the number of net output grid points from March to September, showing significant variation. Conversely, from January to February and from October to December, the number of net output grid points is 3–11 more than the number of net input grid points. Figure 4 a); Except for April and October, when the number of net input grid points exceeded the number of net output grid points by 1 and 5 respectively, the number of net output grid points exceeded the number of net input grid points in other months. Figure 4 b); The number of net output grid points for cloud ice water was higher than the number of net input grid points in each month of the year, with 77 and 65 more in July and August, respectively. Figure 4 c); The distribution of total water matter grid points is similar to that of water vapor. From March to September, the number of net input grid points is 1 to 31 more than the number of net output grid points, and the number varies considerably. From January to February and from October to December, the opposite is true, with the number of net output grid points being 5 to 13 more than the number of net input grid points. Figure 4 d). In terms of annual average quantity, the number of net output grid points for each component of atmospheric water matter is 5 to 9 more than the number of net input grid points.

[0030] Comparison Figure 2 Although the number of net output grid points for the annual total atmospheric water matter exceeds the number of net input grid points, the annual total water vapor, cloud liquid water, and total water matter are still net inputs. This indicates that the total input of the net input grid points for these three categories is greater than the total output of the net output grid points, meaning that the transport efficiency of the net input grid points is higher than that of the net output grid points. The number of net output grid points for cloud ice water is greater than the number of net input grid points in each month, but January to March and December show net inputs, indicating that the total input of the net input grid points for cloud ice water is greater than the total output of the net output grid points during these four months.

[0031] Figure 5To understand the atmospheric water transport at different locations along the Tibetan border, the geometric center of the rectangle with the largest latitude and longitude range (78.5°E~99.0°E, 27.0°N~36.5°N) of the Tibetan border was used as a reference point. Two sets of "bisections" were applied to the regional boundary: the central latitude line (31.75°N) divided the Tibetan border into north and south parts, and the central longitude line (88.75°E) divided it into east and west parts. The annual and monthly average net input of atmospheric water was calculated for both the north-south and east-west border grid points. Statistical results show that the southern border has a net input for all months and the annual total, with the summer half-year (May-October) accounting for 77.5% of the annual net input. The northern border has a net output for all months and the annual total, with the most significant net output in September and June, followed by October and May. Figure 5 a). The western border experiences net input in all months and annually, with relatively large net inputs from June to September, while net inputs in other months remain relatively stable. The eastern border experiences net inputs in July and August, while net outputs are present in all other months and annually, with relatively significant net outputs from October to December. Figure 5 b).

[0032] Calculate the average annual net input for each boundary grid point in Tibet; a positive value indicates net input, and a negative value indicates net output. Grid points with net input are marked in green, and those with net output are marked in brown, with the color intensity indicating the magnitude of the grid point's input. Figure 6 It can be seen that the boundary grid points with net input are mainly distributed along the boundaries of Nyingchi City, Shannan City, and Shigatse City, as well as the southern and western boundaries of Ngari Prefecture. Among them, some boundary grid points in Nyingchi City and Shannan City have relatively large net inputs. The boundary grid points with net output are mainly distributed along the northern and eastern boundaries, with the boundary grid points in Chamdo City and Nagqu City having relatively large net outputs.

[0033] Figure 7 The number of grid points for each threshold value of the average annual net input to the Tibetan border is listed. It can be seen that the number of net output grid points is 101, which is more than the number of net input grid points (96). The net input threshold is 100 × 10⁻⁶. 8 t~200×10 8 The maximum number of grid points for t is 37, followed by the threshold of 50 × 10. 8 t~100×10 8 The number of grid points in t is 22, with a minimum of 350 × 10⁻⁶. 8 t~500×10 8 There are only 6 t values. Net output threshold: 0–50 × 10⁻⁶ 8 The maximum number of t-grid points is 43, followed by the threshold of 200×10. 8 t~350×10 8 The number of t grid points is 25, with a minimum of ≥500×10. 8 There is only one t.

[0034] from Figure 8 It can be seen that the monthly net input of all components of atmospheric water matter showed a decreasing trend in March and April. Specifically, the decreasing trends of monthly net input of water vapor, cloud liquid water, and total water matter in March all passed the reliability test of over 98%, while the decreasing trends of monthly net input of water vapor, cloud liquid water, and total water matter in April all passed the reliability test of 90%. From May to August, the monthly net input of all components showed an increasing trend. Specifically, the increasing trends of monthly net input of water vapor, cloud liquid water, and total water matter in May passed the reliability test of over 98%, while the increasing trend of monthly net input of cloud liquid water in June passed the reliability test of 95%. In September, only the monthly net input of cloud ice water showed an increasing trend, passing the reliability test of 99%. The decreasing trend of monthly net input of cloud ice water in December passed the reliability test of 98%. The increases and decreases of other components, other months, and the annual total were not significant.

[0035] To accurately understand the changes in atmospheric water and material transport along the Tibetan border, the linear trend rate of the annual total atmospheric water and material transport sequence for each grid point along the Tibetan border was calculated. Grid points along the border were marked in green when the linear trend rate was positive and in brown when it was negative. Figure 9 The significance of the results, represented by color intensity, passed different levels of reliability testing. Figure 9 It can be seen that boundary grid points with positive linear propensity rates are mainly distributed along the southern and western boundaries of Ngari Prefecture, most of the boundaries of Shigatse City, and the western boundary of Shannan City. Among these, the net input along the southern boundary of Ngari Prefecture, most of the boundaries of Shigatse City, and the western boundary of Shannan City shows a significant increasing trend with a confidence level of over 95%. Boundary grid points with negative linear propensity rates are mainly distributed along the northern boundary of Ngari Prefecture, the northern boundary of Nagqu City, the southern boundary of Shannan City, and the southern boundary of Nyingchi City. Among these, the net input along the northern boundary of Ngari Prefecture, the northern boundary of Nagqu City, the southern boundary of Shannan City, and parts of Nyingchi City shows a significant decreasing trend. This indicates that atmospheric water content along the boundaries of the central and western Himalayas shows a significant increasing trend, while the southeastern part of the boundaries shows a significant decreasing trend.

[0036] Based on the latest 0.5°×0.5° horizontal resolution precipitation grid data generated by the National Meteorological Information Center using surface precipitation data from national-level stations (basic, benchmark, and general stations) and GTOP30 data through resampling, the average annual precipitation in the Tibet Autonomous Region from 1980 to 2024 was 396.1 mm. The National Bureau of Statistics' "2023 China Statistical Yearbook" clearly states that the area of ​​the Tibet Autonomous Region is 120.28 × 10⁻⁶ mm. 4 km 2 Therefore, the average annual precipitation in the Tibet region can be calculated to be 4764.3 × 10⁻⁶. 8 t, according to this study, the annual average net inflow of atmospheric water substances in the Tibet region is 4501.6 × 10⁻⁶.8 The fact that t is relatively close indicates that it is feasible to assess atmospheric water material transport in the Tibetan region using high-resolution reanalysis data and the boundary grid transport method.

[0037] In summary, this invention provides a method for refined assessment of atmospheric water transport and its changes in the Tibet region. This method aims to improve the accuracy and applicability of regional atmospheric water transport estimation, and has significant advantages, especially for complex terrain regions such as Tibet. By finely screening boundary grid points and standardizing the principles for determining transport direction, it effectively avoids the problem of flux duplication caused by grid redundancy or misjudgment of direction in traditional methods. Cross-validation with high-resolution reanalysis data and precipitation grid data further proves the reliability of this method in terms of time series variation trends and spatial distribution characteristics. The standardization processing and linear trend rate analysis used can clearly reveal the long-term variation patterns of components such as water vapor, cloud liquid water, and cloud ice water, providing a scientific basis for regional water resource management and climate evolution research.

[0038] This invention relates to the monitoring and assessment of atmospheric water cycle and the study of extreme precipitation mechanisms in the Tibetan Plateau.

[0039] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0040] The embodiments described above are merely illustrative of implementation methods of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for evaluating the amount of atmospheric water substance transported in the Tibet region and its change in detail, characterized by, It includes the following steps: boundary grid screening, boundary grid transport method, regional atmospheric water substance transport, regional transport trend, result verification, S1 boundary grid screening: the administrative region of Tibet is divided into an irregular polygon composed of multiple grid points, and the boundary grid points are selected from the vicinity of the administrative boundary line to facilitate the processing of each grid point and the calculation of input and output on the boundary; S2 boundary grid transport method: the physical quantity flux of the reanalysis data is divided into east and north components, and the transport to the east and north is positive, and vice versa; according to the position of each boundary grid point, all directions of the input and output of atmospheric substances of each grid point are listed in the meridian and latitude directions respectively, the continuity of atmospheric motion is considered, and the transport relationship between boundary grid points with the same latitude or longitude is not counted in the regional atmospheric water substance balance; the annual and monthly transport amounts of atmospheric water substance in the Tibet region are calculated, which is realized by accumulating the annual and monthly transport amounts of atmospheric water substance of all boundary grid points in the Tibet region; the total input and output amounts of atmospheric water substance through all boundary grid points in the Tibet region are calculated, and the average of the time dimension is obtained, that is, the annual and monthly average input and output amounts, and the difference between the two is the net input amount; net input amount = input total amount - output total amount, net input amount > 0 is called net input, otherwise, net input amount < 0 is called net output; S3 regional atmospheric water substance transport: the annual average transport amount is calculated, and the water vapor WV, cloud liquid water LW, cloud ice water FW and total water substance W in the annual input total amount are compared with the water vapor, cloud liquid water, cloud ice water and total water substance in the annual output total amount to determine the value of net input and the characteristics of regional atmospheric water substance transport; S4 regional transport trend: the time series of the annual and monthly input total amount, output total amount and net input amount of each component WV, LW, FW and W of the atmospheric water substance in the Tibet region are standardized respectively, and the standardization formula is: ， In the formula: x is the original data, S5 result verification: according to the latest China ground horizontal resolution 0.5°*0.5° precipitation grid data statistics generated by the national meteorological information center based on the ground precipitation data of national stations and GTOP30 data resampled production China land digital elevation model DEM, and compared with it, it is verified that the high resolution reanalysis data and the boundary grid transport method to evaluate the atmospheric water substance transport in the Tibet region is feasible. is the mean, In the S1 boundary grid screening, the central point of the reanalysis data grid is referenced according to the longitude and latitude; is the standard deviation, the formula converts the original data into a new sequence with a mean of 0 and a standard deviation of 1, after standardization, the linear trend of each component time series is analyzed, the linear trend rate of each component is obtained, and the test correlation coefficient of the original sequence and time is calculated, the linear trend rate is a， the correlation coefficient is The grid point closest to the administrative boundary line is selected as the boundary grid point, so that the boundary grid point fits the administrative boundary line; , and the change trend of the region is confirmed according to the calculation result; In addition to other boundary grid points, the boundary grid point cannot appear overlapping or blocking grid points in the front of the four directions of atmospheric water substance transport, that is, there cannot be extra grid points in the front of the transport.

2. The method of claim 1, wherein the method is characterized by: In the S2 boundary grid transport method, the north component value of the flux of the grid point is positive, indicating northward transport, and negative indicating southward transport; the east component value of the flux of the grid point is positive, indicating eastward transport, and negative indicating westward transport; the transport direction between boundary grid points cannot be included in the input or output direction, and the atmospheric water substance of all boundary grid points in the Tibet region selected corresponds to 1~3 transport directions. ​ ​ 3.The method of claim 1, wherein the method is characterized by, ​

Images