A method and system for evaluating the layout of a meteorological observation station network

Abstract

The present invention discloses a method and system for evaluating the layout of a meteorological observation station network. The method includes: determining a regression equation for a structure function that varies with the distance between stations; combining the regression equation to calculate error functions for interpolating standard errors of a target meteorological element in multiple preset standard observation station network layouts as they vary with the distance between stations; for each preset standard observation station network layout of the target meteorological element, combining the error functions corresponding to the preset standard observation station network layouts to calculate the maximum allowable error of the target meteorological element in each preset standard observation station network layout; determining the optimal station layout among the multiple preset standard observation station network layouts based on the maximum allowable error and the maximum allowable distance; and comparing the optimal station layout with the current station layout in the target area to perform layout evaluation on the target area. The present invention solves the problem that the prior art cannot accurately evaluate the meteorological observation capability of the existing meteorological observation station network layout.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological observation station network layout evaluation, and in particular to a meteorological observation station network layout evaluation method and system. Background Art

[0002] The assessment of the layout of the meteorological observation station network is a key task carried out by the Meteorological Administration, aimed at improving the monitoring capabilities for severe weather and meeting the needs of economic and social development. With the rapid development of the economy and society and the continuous expansion of economic aggregate, the losses caused by meteorological disasters are also increasing. There is an urgent need to significantly enhance public meteorological services and meteorological disaster prevention and mitigation capabilities, which puts new and higher demands on comprehensive meteorological observation.

[0003] The evaluation and design of the layout of the meteorological observation station network involves multiple aspects to ensure the accuracy and continuity of observation data, thereby improving the accuracy and efficiency of meteorological services. At present, with the requirement of comprehensively promoting high-quality development of meteorology, there are still blind spots in comprehensive meteorological observation. The layout and observation capabilities are still far from the overall requirements of "precise observation, accurate forecast, and refined service", and there is still a big gap between the monitoring and early warning of meteorological disasters, applied meteorological observation services, ecological meteorological observation systems covering multiple fields, and multi-sphere meteorological observation capabilities for the Earth system. Therefore, the existing meteorological observation capabilities are evaluated, and the design and optimization of the layout of the meteorological observation station network are carried out from three aspects: filling in the gaps, strengthening the weak points, and improving the quality. A meteorological observation station network layout design with distinct regional characteristics is formed, laying a solid foundation for the high-quality development of the meteorological observation system. Summary of the Invention

[0004] The present invention provides a method and system for evaluating the layout of a meteorological observation station network, which solves the problem that the prior art cannot accurately evaluate the meteorological observation capability of the existing meteorological observation station network layout.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for evaluating the layout of a meteorological observation station network, the method comprising:

[0007] Based on the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element is determined, and the regression equation of the structure function changing with the distance between stations is determined; the structure function is used to reflect the degree of dispersion of the target meteorological element between multiple stations;

[0008] Combined with the regression equation, the error functions of the interpolation standard errors of the target meteorological elements as a function of the distance between stations are calculated for multiple preset standard observation station network layouts; the preset standard observation station network layouts include line segment interpolation layout, equilateral triangle interpolation layout, and square interpolation layout.

[0009] For each preset standard observation station network layout mode of the target meteorological element, combined with the error function corresponding to the preset standard observation station network layout mode, when the inter-station distance satisfies the interpolation standard error less than the preset observation standard error, the maximum allowable error of the target meteorological element in each preset standard observation station network layout mode is calculated, and the inter-station distance corresponding to the maximum allowable error is used as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout mode;

[0010] Determining an optimal station layout among multiple preset standard observation station network layouts based on a maximum allowable error and a maximum allowable distance; the optimal station layout includes an optimal layout method and an optimal layout distance, the optimal layout distance being the maximum value of the maximum allowable distance, and the optimal layout method being the preset standard observation station network layout method corresponding to the optimal layout distance;

[0011] The optimal layout is compared with the current layout of the target area to evaluate the layout of the target area.

[0012] In a possible implementation, the optimal site layout is compared with the current site layout of the target area to perform a layout evaluation on the target area, specifically including:

[0013] Calculate the optimal number of stations required for the target meteorological element in the optimal station layout in the target area at the optimal layout distance, and record it as the first data group;

[0014] Obtain the number of stations in the target area with the target meteorological element at the current station spacing in the current station layout, and record it as the second data group;

[0015] The first data set and the second data set are compared to evaluate the density of the site layout in the target area at different station spacings.

[0016] In one possible implementation, based on historical meteorological data of a target meteorological element at multiple stations within a target area, a structure function of the target meteorological element is determined, and a regression equation for how the structure function varies with the distance between stations is determined, specifically including:

[0017] Combined with the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element between any two stations is calculated as the average of the squares of the differences in the anomaly values ​​of the two stations to obtain the structure function of the target meteorological element;

[0018] The structure function of the target meteorological element is fitted using a linear, quadratic polynomial, cubic polynomial or exponential function to obtain the regression equation of the structure function changing with the distance between stations.

[0019] In one possible implementation, any two sites are site A and site B;

[0020] The specific structure function is:

[0021]

[0022] Among them, b f (A, B) represents the structure function, f′(A) and f′(B) represent the anomaly values ​​of the target meteorological element f at station A and station B, respectively.

[0023] In one possible implementation, the regression equation for the structure function changing with the distance between sites is:

[0024]

[0025] in, l is the distance between site A and site B, ρ is the radius of the earth, is the latitude of the current site, and λ is the longitude of the current site;

[0026] b′ f (l) represents the actual structure function, i.e., the regression equation, b f (l) represents the structure function;

[0027] is the random standard error of observations between site A and site B, and

[0028] In a possible implementation, when the preset standard observation station network layout is a line segment interpolation layout, the error function is specifically:

[0029]

[0030] When the preset standard observation station network layout is the equilateral triangle interpolation layout, the error function is specifically:

[0031]

[0032] When the preset standard observation station network layout is a square interpolation layout, the error function is specifically:

[0033]

[0034] Where E represents the error function.

[0035] In one possible implementation, when calculating the maximum allowable error of the target meteorological element in each preset standard observation station network layout, the calculation function of the maximum allowable error is specifically:

[0036]

[0037] Among them, Emax Indicates the maximum allowable error.

[0038] In a second aspect, the present invention provides a meteorological observation station network layout evaluation system, the device comprising:

[0039] The first processing module is used to determine the structure function of the target meteorological element based on the historical meteorological data of the target meteorological element at multiple stations obtained in the target area, and to determine the regression equation of the structure function as the distance between the stations changes; the structure function is used to reflect the degree of dispersion of the target meteorological element between the multiple stations;

[0040] The second processing module is used to calculate the error function of the interpolation standard error of the target meteorological element in a plurality of preset standard observation station network layouts as a function of the distance between stations, in combination with the regression equation; the preset standard observation station network layouts include line segment interpolation layout, equilateral triangle interpolation layout, and square interpolation layout;

[0041] A third processing module is configured to calculate, for each preset standard observation station network layout mode of the target meteorological element, a maximum allowable error of the target meteorological element in each preset standard observation station network layout mode in combination with an error function corresponding to the preset standard observation station network layout mode, when the inter-station distance satisfies the interpolation standard error less than the preset observation standard error, and use the inter-station distance corresponding to the maximum allowable error as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout mode;

[0042] a fourth processing module, configured to determine an optimal station layout among a plurality of preset standard observation station network layouts based on a maximum allowable error and a maximum allowable distance; the optimal station layout includes an optimal layout method and an optimal layout distance, the optimal layout distance being a maximum value of the maximum allowable distance, and the optimal layout method being a preset standard observation station network layout method corresponding to the optimal layout distance;

[0043] The fifth processing module is used to compare the optimal layout with the acquired current layout of the target area to perform layout evaluation on the target area.

[0044] In a possible implementation, the fifth processing module is specifically configured to execute:

[0045] Calculate the optimal number of stations required for the target meteorological element in the optimal station layout in the target area at the optimal layout distance, and record it as the first data group;

[0046] Obtain the number of stations in the target area with the target meteorological element at the current station spacing in the current station layout, and record it as the second data group;

[0047] The first data set and the second data set are compared to evaluate the density of the site layout in the target area at different station spacings.

[0048] In a possible implementation, the first processing module is specifically configured to execute:

[0049] Combined with the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element between any two stations is calculated as the average of the squares of the differences in the anomaly values ​​of the two stations to obtain the structure function of the target meteorological element;

[0050] The structure function of the target meteorological element is fitted using a linear, quadratic polynomial, cubic polynomial or exponential function to obtain the regression equation of the structure function changing with the distance between stations.

[0051] In one possible implementation, in the process of obtaining the structure function of the target meteorological element by combining the acquired historical meteorological data of the target meteorological element at multiple stations within the target area, and according to the structure function of the target meteorological element between any two stations being the average of the square of the difference between the deviation values ​​of the any two stations, when any two stations in the first processing module are station A and station B, the structure function in the first processing module is specifically configured as follows:

[0052]

[0053] Among them, b f (A, B) represents the structure function, f′(A) and f′(B) represent the anomaly values ​​of the target meteorological element f at station A and station B, respectively.

[0054] In a possible implementation, the regression equation of the structure function changing with the distance between sites in the first processing module is specifically configured as follows:

[0055]

[0056] in, l is the distance between site A and site B, ρ is the radius of the earth, is the latitude of the current site, and λ is the longitude of the current site;

[0057] b′ f (l) represents the actual structure function, i.e., the regression equation, b f (l) represents the structure function;

[0058] is the random standard error of observations between site A and site B, and

[0059] In a possible implementation, when the preset standard observation station network layout is a line segment interpolation layout, the error function in the second processing module is specifically configured as follows:

[0060]

[0061] When the preset standard observation station network layout is the equilateral triangle interpolation layout, the error function in the second processing module is specifically configured as follows:

[0062]

[0063] When the preset standard observation station network layout is a square interpolation layout, the error function in the second processing module is specifically configured as follows:

[0064]

[0065] Where E represents the error function.

[0066] In one possible implementation, when calculating the maximum allowable error of the target meteorological element in each preset standard observation station network layout, the calculation function of the maximum allowable error in the third processing module is specifically configured as follows:

[0067]

[0068] Among them, E max Indicates the maximum allowable error.

[0069] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement any one of the above-mentioned meteorological observation station network layout evaluation methods.

[0070] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, the at least one program, the code set or instruction set is loaded and executed by a processor to implement the meteorological observation station network layout evaluation method described in any one of the above items.

[0071] The meteorological observation station network layout evaluation method provided by the embodiment of the present invention is based on the spatial structure function. According to the principle that the interpolation standard error is less than the preset observation standard error, the optimal station layout of multiple target meteorological elements in the target area is studied. The layout of the target area is evaluated by comparing the optimal station layout with the current station layout of the target area, thereby achieving an accurate evaluation of the meteorological observation capability of the existing meteorological observation station network layout, and providing a scientific basis for the layout optimization of the meteorological observation station network in the target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1A flowchart of a method for evaluating the layout of a meteorological observation station network provided by an embodiment of the present invention;

[0073] Figure 2 (a) is the structure function of the daily average temperature in the plains and mountainous hills of Province A from 1992 to 2021 as a function of the distance between stations; (b) is the structure function of the daily average relative humidity in the plains and mountainous hills of Province A from 1992 to 2021 as a function of the distance between stations; (c) is the structure function of the daily precipitation in the plains and mountainous hills of Province A from 1992 to 2021 as a function of the distance between stations; (d) is the structure function of the daily average air pressure in the plains and mountainous hills of Province A from 1992 to 2021 as a function of the distance between stations;

[0074] Figure 3 (a) is a graph showing the relationship between the interpolation standard error of the daily average temperature in the plains and mountainous hills of Province A from 1992 to 2021 under three interpolation methods and the distance between stations; (b) is a graph showing the relationship between the interpolation standard error of the daily average relative humidity in the plains and mountainous hills of Province A from 1992 to 2021 under three interpolation methods and the distance between stations; (c) is a graph showing the relationship between the interpolation standard error of the daily precipitation in the plains and mountainous hills of Province A from 1992 to 2021 under three interpolation methods and the distance between stations; (d) is a graph showing the relationship between the interpolation standard error of the daily average air pressure in the plains and mountainous hills of Province A from 1992 to 2021 under three interpolation methods and the distance between stations;

[0075] Figure 4 This is a structural block diagram of a meteorological observation station network layout evaluation system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0076] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0077] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, the use of "based on" or "according to" means openness and inclusiveness, because the process, steps, calculations or other actions "based on" or "according to" one or more of the conditions or values ​​may be based on additional conditions or values ​​beyond the stated in practice.

[0078] In order to solve the problem that the existing technology cannot accurately evaluate the meteorological observation capability of the existing meteorological observation station network layout, an embodiment of the present invention provides a meteorological observation station network layout evaluation method and system.

[0079] like Figure 1 As shown, in a first aspect, an embodiment of the present invention further provides a method for evaluating the layout of a meteorological observation station network, the method comprising:

[0080] Step 101: Determine the structure function of the target meteorological element based on historical meteorological data of the target meteorological element at multiple sites acquired within the target area, and determine a regression equation for how the structure function changes with the distance between sites.

[0081] Among them, the structure function is used to reflect the degree of dispersion of the target meteorological elements among multiple stations.

[0082] The target area is the geographical area to be studied; multiple stations include national benchmark, basic and conventional meteorological observation stations, national meteorological observation stations, regional meteorological observation stations, agricultural microclimate observation stations and facility agriculture observation stations, and the agricultural microclimate observation stations and facility agriculture observation stations are merged together and referred to as applied meteorological observation stations; target meteorological elements include temperature, relative humidity, precipitation, air pressure and other meteorological elements.

[0083] In an embodiment of the present invention, the target area is Province A, and a total of 119 national benchmark, basic and conventional meteorological observation stations in Province A are selected for research. Combined with the topographic map and altitude of Province A, the selected 119 stations are divided into 64 plain stations and 55 mountainous and hilly stations. The daily average temperature, daily average relative humidity, daily precipitation and daily average air pressure data of each station from 1992 to 2021 are selected as the historical meteorological data to be studied, and the structural functions corresponding to each target meteorological element in the plain area and mountainous and hilly area of ​​Province A are determined respectively.

[0084] For each target meteorological element, all inter-station distances are divided into different distance intervals according to preset intervals. At the same time, the average value of the structure function in each distance interval is obtained, and a curve between the inter-station distance and the structure function is drawn to obtain the curve of the structure function changing with the inter-station distance, and the regression equation of the structure function changing with the inter-station distance is determined.

[0085] Step 102: Combined with the regression equation, calculate the error function of the interpolation standard error of the target meteorological element in multiple preset standard observation station network layouts as the distance between stations changes.

[0086] Among them, the preset standard observation station network layout methods include three interpolation methods: line segment interpolation layout method, equilateral triangle interpolation layout method and square interpolation layout method.

[0087] Specifically, since the midpoint error between two points of meteorological element interpolation is the largest, based on the regression equation of each observation element, the interpolation standard error corresponding to the line segment interpolation layout method, the equilateral triangle interpolation layout method, and the square interpolation layout method of the target meteorological element at different inter-station distances can be calculated respectively, thereby determining the error function of the interpolation standard error of each interpolation method as the inter-station distance changes.

[0088] Step 103: For each preset standard observation station network layout mode of the target meteorological element, combined with the error function corresponding to the preset standard observation station network layout mode, when the inter-station distance satisfies the interpolation standard error less than the preset observation standard error, calculate the maximum allowable error of the target meteorological element in each preset standard observation station network layout mode, and use the inter-station distance corresponding to the maximum allowable error as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout mode.

[0089] Specifically, for most meteorological elements, the standard error of point value interpolation should not exceed the preset observation standard error.

[0090] That is, the maximum allowable error is the maximum value of the interpolation standard error, and the maximum allowable distance is the maximum inter-station distance corresponding to the maximum allowable error.

[0091] Step 104: Determine the optimal station layout among multiple preset standard observation station network layouts based on the maximum allowable error and the maximum allowable distance.

[0092] Among them, the optimal station layout includes the optimal layout method and the optimal layout distance.

[0093] The optimal layout distance is the maximum value of the maximum allowable distance among the three interpolation methods, and the optimal layout method is the preset standard observation station network layout method corresponding to the optimal layout distance.

[0094] Step 105: Compare the optimal site layout with the acquired current site layout of the target area to perform layout evaluation on the target area.

[0095] Specifically, the optimal station layout in the target area is compared with the number of stations arranged at different distances between stations in the current station layout to obtain a layout evaluation result.

[0096] For example, at the same distance between sites, the number of sites in the current layout is less than the number of sites in the optimal layout, which means that the number of sites in the current layout is too small and the number of sites needs to be increased.

[0097] Furthermore, based on the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element is determined, and the regression equation of the structure function varying with the distance between stations is determined, specifically including:

[0098] Combined with the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element between any two stations is calculated as the average of the squares of the differences in the anomaly values ​​of the two stations to obtain the structure function of the target meteorological element;

[0099] The structure function of the target meteorological element is fitted using a linear, quadratic polynomial, cubic polynomial or exponential function to obtain the regression equation of the structure function changing with the distance between stations.

[0100] Furthermore, any two sites are site A and site B;

[0101] The specific structure function is:

[0102]

[0103] Among them, b f (A, B) represents the structure function, f′(A) and f′(B) represent the anomaly values ​​of the target meteorological element f at station A and station B, respectively.

[0104] Since the observation error of meteorological elements consists of two parts: systematic error and random error, the systematic error has been eliminated when the structure function is calculated using formula (1). It is assumed that the random standard error of the observation of the target meteorological element at a certain station in the target area is independent of the random standard error of the observation at other stations, and the random standard error of the observation at each station is equal.

[0105] Furthermore, the regression equation of the structure function changing with the distance between sites can be expressed as:

[0106]

[0107] in,

[0108] l is the distance between site A and site B, ρ is the radius of the earth, is the latitude of the current site, and λ is the longitude of the current site;

[0109] b′ f (l) represents the actual structure function, i.e., the regression equation, b f (l) represents the structure function;

[0110] is the random standard error of observation between sites A and B. When sites A and B coincide, i.e., when l = 0, b f (0) = 0, so:

[0111]

[0112] The structure function is extrapolated to zero distance, and the preset observation random standard error in the present invention can be calculated according to formula (4).

[0113] Furthermore, when the preset standard observation station network layout is the line segment interpolation layout, the error function of the midpoint of any two stations can be expressed as:

[0114]

[0115] By combining formula (2) and formula (4) to process formula (5), we can obtain that when the preset standard observation station network layout is the line segment interpolation layout, the error function is specifically:

[0116]

[0117] Among them, b f ′(0) is obtained by extrapolating the curve corresponding to the regression equation of the structure function and the distance between sites to zero distance.

[0118] Similarly, when the preset standard observation station network layout is the equilateral triangle interpolation layout, the error function is specifically:

[0119]

[0120] When the preset standard observation station network layout is a square interpolation layout, the error function is specifically:

[0121]

[0122] Where E represents the error function.

[0123] Furthermore, the maximum allowable error can be determined by ensuring that the calculated values ​​of the first two terms of the error function in formula (5) do not exceed the preset observation standard error, that is:

[0124]

[0125] That is to say, when calculating the maximum allowable error of the target meteorological element in each preset standard observation station network layout, the calculation function of the maximum allowable error is specifically:

[0126]

[0127] Among them, E max Indicates the maximum allowable error.

[0128] Specifically, the maximum allowable error can be used as a basis for the reasonable layout of station networks.

[0129] Specifically, for each target meteorological element, taking 64 plain stations as an example, with any two plain stations as a group, the structure function and inter-station distance corresponding to the 64 plain stations are calculated using formula (1) and formula (3) respectively, and m(m-1) / 2 pairs of structure function and inter-station distance are obtained, where m is the total number of plain stations.

[0130] The distances between all stations are divided into different distance intervals at intervals of 20 km. At the same time, the average value of the structure function corresponding to the target meteorological element in each distance interval is obtained. The curve of the structure function changing with the distance between stations is drawn. The curve is extrapolated to zero distance to obtain the actual structure function b. f '(0).

[0131] Afterwards, the interpolation standard error values ​​of the line segment interpolation layout mode, the equilateral triangle interpolation layout mode, and the square interpolation layout mode under different inter-station distances are obtained according to formulas (6), (7), and (8), and a curve graph of the interpolation standard error corresponding to different interpolation methods versus inter-station distance is drawn;

[0132] Then, the maximum allowable error of the target meteorological element is calculated according to formula (10), and the inter-station spacing corresponding to the maximum allowable error is the maximum allowable distance of the target meteorological element.

[0133] like Figure 2 As shown in FIG. 1 , in the embodiment of the present invention, the structure functions of the four target meteorological elements, namely, daily average temperature, daily average relative humidity, daily precipitation and daily average air pressure, are shown as the distance between stations changes in the plain area and the mountainous and hilly area of ​​Province A. Figure 2As shown in Figures (a)-(d), the structure functions of each target meteorological element in both the plains and hilly regions increase with increasing inter-station distance. The structure functions in the plains exhibit a smoother, more linear trend with inter-station distance, while the structure functions in the hilly region exhibit a more pronounced change with distance. The structure functions in the hilly region exhibit higher values ​​at different inter-station distances than those in the plains. This fully reflects the differences in the spatial gradients of each target meteorological element across different terrains. Specifically, the dispersion of the sequence differences of target meteorological elements increases with increasing terrain height and altitude. Because the structure function represents the dispersion of the sequence differences of target meteorological elements across different points in space, the structure functions of target meteorological elements in hilly regions exhibit different characteristics from those in plains, reflecting the differences in the dispersion of structure functions across different terrains.

[0134] In order to obtain the regression equation of the structure function of the four target meteorological elements (daily average temperature, daily average relative humidity, daily precipitation, and daily average air pressure) in the plain area and mountainous and hilly area of ​​Province A, which varies with the distance between stations, this embodiment uses four functions: linear, quadratic polynomial, cubic polynomial, and exponential to fit the structure function of each target meteorological element. By studying the fitting results of the four functions, it is concluded that the quadratic polynomial and cubic polynomial functions have better fitting effects, and the fitting correlation coefficients and fit degrees of these two functions differ slightly. In order to meet the high fitting accuracy of the structure function and make the fitting function as simple as possible, when the fitting correlation coefficients of the quadratic polynomial and cubic polynomial functions differ slightly, the fitting function with a low polynomial order is selected as the final regression function.

[0135] Specifically, the regression equations of the structure functions of daily average temperature, daily average relative humidity, daily precipitation, and daily average air pressure in the plain and hilly areas of Province A and the distance between stations from 1992 to 2021 are shown in Table 1:

[0136] Table 1 Regression equations of the structure functions of daily average temperature, daily average relative humidity, daily precipitation, and daily average air pressure and the distance between stations from 1992 to 2021

[0137]

[0138] Substituting the regression equations corresponding to the target meteorological factors in Table 1 into formula (6), formula (7), and formula (8), we can obtain the error functions of the interpolation standard error as the distance between stations changes under the line segment interpolation layout mode, the equilateral triangle interpolation layout mode, and the square interpolation layout mode in the plain area and the mountainous and hilly area. The calculation results are shown in Table 2:

[0139] Table 2 Error functions of the interpolation standard errors of daily average temperature, daily average relative humidity, daily precipitation, and daily average air pressure under three interpolation methods as a function of the distance between stations from 1992 to 2021

[0140]

[0141]

[0142] According to the regression function in Table 2, the relationship curves between the interpolation standard error of the daily average temperature, daily average relative humidity, daily precipitation and daily average air pressure and the distance between stations in the plain area and mountainous and hilly area of ​​Province A are drawn respectively. The relationship curves are shown in the figure below. Figure 3 As shown in (a)-(d) in the figure.

[0143] Depend on Figure 3 As shown in Figures (a)-(d), the interpolation standard errors for daily mean temperature, daily mean relative humidity, daily precipitation, and daily mean pressure in the plains and hilly regions of Province A under the three interpolation methods increase with increasing distance between stations. Furthermore, the interpolation standard errors for each target meteorological element are higher in the hilly regions than in the plains.

[0144] For daily mean temperature, daily mean relative humidity, daily precipitation, and daily mean air pressure in plain and hilly areas, the square interpolation layout achieves the highest interpolation accuracy, while the line segment interpolation layout achieves the lowest interpolation accuracy when the inter-station distance decreases. When the inter-station distance exceeds a certain critical distance threshold, the equilateral triangle interpolation layout achieves the highest interpolation accuracy, while the square interpolation layout achieves the lowest interpolation accuracy. The critical distance threshold varies for different target meteorological elements. For the four target meteorological elements, daily mean temperature, daily mean relative humidity, daily precipitation, and daily mean air pressure, the interpolation standard error for daily precipitation is the largest at the same inter-station distance. This conclusion is consistent with the characteristic that the structure function value corresponding to daily precipitation is the largest. In practice, due to the uneven distribution and large variability of daily precipitation in time and space, the interpolation standard error for daily precipitation is the largest at the same inter-station distance.

[0145] According to formula (10), the interpolation standard errors of the four target meteorological elements, namely daily average temperature, daily average relative humidity, daily precipitation and daily average air pressure, are calculated. The maximum allowable distances of the interpolation standard errors under the three interpolation layout methods, namely line segment interpolation layout, equilateral triangle interpolation layout and square interpolation layout, are determined. The calculation results are shown in Table 3:

[0146] Table 3 shows the maximum allowable distances of the four target meteorological elements of temperature, relative humidity, precipitation and air pressure under three interpolation layout methods: line segment interpolation layout method, equilateral triangle interpolation layout method and square interpolation layout method.

[0147] Table 3 Maximum allowable interpolation standard error and maximum allowable distance of 4 target meteorological elements under three layout modes

[0148]

[0149] Table 3 shows that the maximum allowable interpolation errors for temperature, relative humidity, and pressure in the plains are smaller than those in the hilly region, and the maximum allowable distances for all three interpolation methods are greater in the plains than in the hilly region. Regarding precipitation, the maximum allowable interpolation error in the plains is greater than that in the hilly region, and the maximum allowable distances for all three interpolation methods are also greater in the hilly region.

[0150] The maximum allowable interpolation error of each target meteorological element is determined by the maximum allowable error and the interpolation accuracy. That is, each target meteorological element is affected by the temporal variation amplitude, spatial gradient and the preset observation random standard error. Because the temporal variation amplitude and spatial gradient of each target meteorological element in mountainous and hilly areas are significantly different from those in plain areas due to the influence of local climate, combined with Figure 3 It can be seen that the interpolation accuracy of each target meteorological element in the mountainous and hilly areas is lower than that in the plain area. These factors together lead to the difference in the maximum allowable distance of the target meteorological elements in the plain area and the mountainous and hilly areas.

[0151] Depend on Figure 3 As can be seen from Table 3, for plain areas and mountainous and hilly areas, when the interpolation standard error of the distance between stations is less than the preset observation standard error, the four target meteorological elements of temperature, relative humidity, precipitation, and air pressure all show that the interpolation accuracy of the equilateral triangle interpolation layout method is the highest, and the maximum allowable distance of the equilateral triangle interpolation layout method is the largest. Therefore, for the four target meteorological elements of temperature, relative humidity, precipitation and air pressure in the plain area and mountainous and hilly areas of Province A, the optimal station layout method is the equilateral triangle interpolation layout method. Among them, the optimal layout distances of temperature factors in the plain area and mountainous and hilly areas are ≤36.4km and ≤29.4km respectively; the optimal layout distances of relative humidity factors in the plain area and mountainous and hilly areas are ≤90.9km and ≤73.3km respectively; the optimal layout distances of precipitation factors in the plain area and mountainous and hilly areas are ≤81.9km and ≤52.3km respectively; the optimal layout distances of air pressure factors in the plain area and mountainous and hilly areas are ≤44.8km and ≤31.2km respectively.

[0152] Because each national benchmark, basic, and conventional meteorological observation station in Province A is simultaneously configured with temperature, relative humidity, precipitation, and air pressure, rather than with a single element, the optimal layout for these stations in both the plain and hilly regions of Province A is equilateral triangle interpolation. The optimal layout distance in the plain region is no more than 36.4 km, and in the hilly region no more than 29.4 km.

[0153] Furthermore, the optimal layout is compared with the current layout of the target area to evaluate the layout of the target area, including:

[0154] Calculate the optimal number of stations required for the target meteorological element in the optimal station layout in the target area at the optimal layout distance, and record it as the first data group;

[0155] Obtain the number of stations in the target area with the target meteorological element at the current station spacing in the current station layout, and record it as the second data group;

[0156] The first data set and the second data set are compared to evaluate the density of the site layout in the target area at different station spacings.

[0157] Specifically, the existing horizontal station spacing of each observation element of the national benchmark, basic and conventional meteorological observation stations in multiple regions of Province A was calculated according to the horizontal resolution formula of the observation station network. At the same time, the maximum allowable distance in the optimal layout was used as the optimal layout distance, and the optimal number of stations required in the plain area and mountainous and hilly area at the optimal layout distance was calculated.

[0158] The formula for the horizontal resolution of the observation station network is as follows:

[0159]

[0160] Among them, C represents the average station spacing, that is, the horizontal resolution, in kilometers; S represents the area, in ten thousand square kilometers; Ni represents the number of observation stations of the i-th instrument; and m represents the number of instrument types observing the target elements.

[0161] The station spacing and number of existing national benchmark, basic and conventional meteorological observation stations in Province A are compared with the optimal layout to evaluate the density of station layout in the target area at different station spacings.

[0162] In the embodiment of the present invention, the existing station spacing and number of national benchmark, basic and conventional meteorological observation stations in 16 regions of Province A and the optimal station spacing and number of stations for the optimal layout determined by the present invention are shown in Table 4:

[0163] Table 4 Comparison of the existing spacing and number of national benchmark, basic and conventional meteorological observation stations in 16 regions of Province A with the optimal spacing and number of stations for the optimal layout determined by the present invention

[0164]

[0165]

[0166] In Table 4, “ / ” indicates that the terrain of the city is not considered to be plain or mountainous or hilly.

[0167] As shown in Table 4, under the same station spacing, the number of stations in the current layout and the optimal layout of each prefecture-level city are compared to evaluate the density of stations in the current layout.

[0168] For example, the number of existing sites in region E is 3 more than the number of sites in the optimal layout, indicating that the site density of the existing layout is greater than that of the optimal layout. The site layout in region E is slightly denser, and the number of sites can be adaptively reduced.

[0169] The number of existing sites in Region I is 5 less than the number of sites in the optimal layout, which is a large difference. This shows that the site density of the existing layout is lower than that of the optimal layout. The site layout in Region I is obviously too small, and it is necessary to adaptively increase sites.

[0170] The number of existing sites in area B is equal to the number of sites in the optimal layout, which means that the site density of the existing layout is the same as that of the optimal layout. The existing layout is reasonable and no site adjustment is required.

[0171] The meteorological observation station network layout evaluation method provided by the embodiment of the present invention is based on the spatial structure function. According to the principle that the interpolation standard error is less than the preset observation standard error, the optimal station layout of multiple target meteorological elements in the target area is studied. The layout of the target area is evaluated by comparing the optimal station layout with the current station layout of the target area, thereby achieving an accurate evaluation of the meteorological observation capability of the existing meteorological observation station network layout, and providing a scientific basis for the layout optimization of the meteorological observation station network in the target area.

[0172] like Figure 4 As shown, in a second aspect, an embodiment of the present invention further provides a meteorological observation station network layout evaluation system, the device comprising:

[0173] The first processing module 201 is configured to determine a structure function of the target meteorological element based on historical meteorological data of the target meteorological element at multiple sites acquired within the target area, and to determine a regression equation for how the structure function varies with the distance between sites. The structure function is configured to reflect the degree of dispersion of the target meteorological element between the multiple sites.

[0174] The second processing module 202 is configured to calculate, using the regression equation, an error function of the interpolation standard error of the target meteorological element as a function of the distance between stations in a plurality of preset standard observation station network layouts; the preset standard observation station network layouts include a line segment interpolation layout, an equilateral triangle interpolation layout, and a square interpolation layout;

[0175] The third processing module 203 is configured to calculate, for each preset standard observation station network layout of the target meteorological element, a maximum allowable error of the target meteorological element in each preset standard observation station network layout, in combination with the error function corresponding to the preset standard observation station network layout, when the inter-station distance satisfies that the interpolation standard error is less than the preset observation standard error, and use the inter-station distance corresponding to the maximum allowable error as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout;

[0176] The fourth processing module 204 is configured to determine an optimal station layout among a plurality of preset standard observation station network layouts based on the maximum allowable error and the maximum allowable distance; the optimal station layout includes an optimal layout method and an optimal layout distance, the optimal layout distance being the maximum value of the maximum allowable distance, and the optimal layout method being the preset standard observation station network layout method corresponding to the optimal layout distance;

[0177] The fifth processing module 205 is configured to compare the optimal layout with the acquired current layout of the target area to perform layout evaluation on the target area.

[0178] Furthermore, the fifth processing module 205 is specifically configured to execute:

[0179] Calculate the optimal number of stations required for the target meteorological element in the optimal station layout in the target area at the optimal layout distance, and record it as the first data group;

[0180] Obtain the number of stations in the target area with the target meteorological element at the current station spacing in the current station layout, and record it as the second data group;

[0181] The first data set and the second data set are compared to evaluate the density of the site layout in the target area at different station spacings.

[0182] Furthermore, the first processing module 201 is specifically configured to execute:

[0183] Combined with the historical meteorological data of the target meteorological element at multiple stations in the target area, the structure function of the target meteorological element between any two stations is calculated as the average of the squares of the differences in the anomaly values ​​of the two stations to obtain the structure function of the target meteorological element;

[0184] The structure function of the target meteorological element is fitted using a linear, quadratic polynomial, cubic polynomial or exponential function to obtain the regression equation of the structure function changing with the distance between stations.

[0185] Furthermore, in the process of obtaining the structure function of the target meteorological element by combining the acquired historical meteorological data of the target meteorological element at multiple stations within the target area, and according to the structure function of the target meteorological element between any two stations being the average of the square of the difference between the deviation values ​​of any two stations, when any two stations in the first processing module 201 are station A and station B, the structure function in the first processing module 201 is specifically configured as follows:

[0186]

[0187] Among them, b f (A, B) represents the structure function, f′(A) and f′(B) represent the anomaly values ​​of the target meteorological element f at station A and station B, respectively.

[0188] Furthermore, the regression equation of the structure function changing with the distance between sites in the first processing module 201 is specifically configured as follows:

[0189]

[0190] in, l is the distance between site A and site B, ρ is the radius of the earth, is the latitude of the current site, and λ is the longitude of the current site;

[0191] b′ f (l) represents the actual structure function, i.e., the regression equation, b f (l) represents the structure function;

[0192] is the random standard error of observations between site A and site B, and

[0193] Furthermore, when the preset standard observation station network layout is a line segment interpolation layout, the error function in the second processing module 202 is specifically configured as follows:

[0194]

[0195] When the preset standard observation station network layout is the equilateral triangle interpolation layout, the error function in the second processing module 202 is specifically configured as follows:

[0196]

[0197] When the preset standard observation station network layout is a square interpolation layout, the error function in the second processing module 202 is specifically configured as follows:

[0198]

[0199] Where E represents the error function.

[0200] Furthermore, when calculating the maximum allowable error of the target meteorological element in each preset standard observation station network layout, the calculation function of the maximum allowable error in the third processing module 203 is specifically configured as follows:

[0201]

[0202] Among them, E max Indicates the maximum allowable error.

[0203] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0204] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the meteorological observation station network layout evaluation method in an embodiment of the present invention.

[0205] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, in which at least one instruction, at least one program, code set or instruction set is stored, and at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the meteorological observation station network layout evaluation method in an embodiment of the present invention.

[0206] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0207] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed by the present invention shall be covered by the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for evaluating the layout of a meteorological observation station network, characterized in that: include: Determining a structure function of the target meteorological element between different terrains based on historical meteorological data of the target meteorological element at multiple sites within the target area, and determining a regression equation for how the structure function varies with distance between sites; The structure function is used to reflect the degree of dispersion of the target meteorological element among the multiple sites; In combination with the regression equation, error functions of interpolation standard errors of the target meteorological element as a function of inter-station distances are calculated in a plurality of preset standard observation station network layouts; the preset standard observation station network layouts include a line segment interpolation layout, an equilateral triangle interpolation layout, and a square interpolation layout; For each preset standard observation station network layout mode of the target meteorological element, in combination with the error function corresponding to the preset standard observation station network layout mode, when the inter-station distance satisfies the interpolation standard error less than the preset observation standard error, calculate the maximum allowable error of the target meteorological element in each preset standard observation station network layout mode, and use the inter-station distance corresponding to the maximum allowable error as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout mode; Determining an optimal station layout among the plurality of preset standard observation station network layout modes according to the maximum allowable error and the maximum allowable distance; the optimal station layout includes an optimal layout mode and an optimal layout distance, the optimal layout distance being the maximum value of the maximum allowable distance, and the optimal layout mode being the preset standard observation station network layout mode corresponding to the optimal layout distance; Comparing the optimal station layout with the acquired current station layout of the target area, the target area is evaluated for layout; and an accurate evaluation of the meteorological observation capability of the meteorological observation station network layout is achieved.

2. The meteorological observation station network layout evaluation method according to claim 1, characterized in that: Comparing the optimal layout with the acquired current layout of the target area to perform layout evaluation on the target area specifically includes: Calculating the optimal number of stations required for the target meteorological element in the target area at the optimal layout distance in the optimal station layout, and recording it as a first data group; Obtaining the number of stations for the target meteorological element in the target area in the current station layout at the current station spacing, and recording this as a second data group; The first data set and the second data set are compared to evaluate the density of the site layout in the target area at different site spacings.

3. The method for evaluating the layout of a meteorological observation station network according to claim 1, wherein: Based on historical meteorological data of a target meteorological element at multiple sites obtained within a target area, a structure function of the target meteorological element is determined, and a regression equation for how the structure function varies with the distance between sites is determined, specifically including: Combining the acquired historical meteorological data of the target meteorological element at multiple stations in the target area, and obtaining the structure function of the target meteorological element according to the structure function of the target meteorological element between any two stations being the average of the squares of the differences between the anomalies of the two stations; The structure function of the target meteorological element is fitted using a linear, quadratic polynomial, cubic polynomial or exponential function to obtain a regression equation of the structure function varying with the distance between sites.

4. The method for evaluating the layout of a meteorological observation station network according to claim 3, wherein: The arbitrary two sites are site A and site B; The structure function is specifically: ； in, represents the structure function, and Represents target meteorological elements Anomalies at Site A and Site B.

5. The method for evaluating the layout of a meteorological observation station network according to claim 4, wherein: The regression equation of the structure function changing with the distance between sites is specifically: ； in, ; is the inter-site distance between site A and site B, is the radius of the Earth, is the latitude of the current site, is the longitude of the current station; represents the actual structure function, i.e. the regression equation, represents the structure function; is the random standard error of observations between sites A and B, and .

6. The method for evaluating the layout of a meteorological observation station network according to claim 5, wherein: When the preset standard observation station network layout is a line segment interpolation layout, the error function is specifically: ； When the preset standard observation station network layout is an equilateral triangle interpolation layout, the error function is specifically: ； When the preset standard observation station network layout is a square interpolation layout, the error function is specifically: ； in, represents the error function.

7. The method for evaluating the layout of a meteorological observation station network according to claim 6, wherein: When calculating the maximum allowable error of the target meteorological element in each of the preset standard observation station network layout modes, the calculation function of the maximum allowable error is specifically: ； in, Indicates the maximum allowable error.

8. A meteorological observation station network layout evaluation system, characterized in that: include: A first processing module is configured to determine a structure function of a target meteorological element between different terrains based on historical meteorological data of the target meteorological element at multiple sites acquired within a target area, and to determine a regression equation for how the structure function varies with distance between sites; The structure function is used to reflect the degree of dispersion of the target meteorological element among the multiple sites; A second processing module is configured to calculate, in combination with the regression equation, error functions of interpolation standard errors of the target meteorological element as a function of inter-station distance in a plurality of preset standard observation station network layouts; the preset standard observation station network layouts include a line segment interpolation layout, an equilateral triangle interpolation layout, and a square interpolation layout; A third processing module is configured to calculate, for each preset standard observation station network layout mode of the target meteorological element, a maximum allowable error of the target meteorological element in each preset standard observation station network layout mode in combination with an error function corresponding to the preset standard observation station network layout mode, when the inter-station distance satisfies that the interpolation standard error is less than the preset observation standard error, and use the inter-station distance corresponding to the maximum allowable error as the maximum allowable distance of the target meteorological element in the preset standard observation station network layout mode; a fourth processing module, configured to determine an optimal station layout among the plurality of preset standard observation station network layouts based on the maximum allowable error and the maximum allowable distance; the optimal station layout including an optimal layout method and an optimal layout distance, the optimal layout distance being a maximum value of the maximum allowable distance, and the optimal layout method being a preset standard observation station network layout method corresponding to the optimal layout distance; The fifth processing module is used to compare the optimal station layout with the acquired current station layout of the target area to evaluate the layout of the target area; and to achieve an accurate evaluation of the meteorological observation capability of the meteorological observation station network layout.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the meteorological observation station network layout evaluation method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the meteorological observation station network layout evaluation method according to any one of claims 1 to 7.

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