A method and apparatus for modeling tropospheric wet information

Abstract

The application discloses a modeling method and device for tropospheric wet information, and the method comprises the following steps: obtaining tropospheric meteorological data of several height layers in a preset time range, and statistically obtaining a water vapor density fluctuation range of the several height layers in the preset time range according to the tropospheric meteorological data; fitting a layered height curve changing with time according to the water vapor density fluctuation range and a water vapor density threshold; and discretizing and modeling the wet information at the layered height according to the layered height curve and the tropospheric meteorological data, so as to obtain a tropospheric wet information model. According to the embodiment of the application, the water vapor density fluctuation range is obtained by statistically processing the tropospheric meteorological data of each height layer in the preset time range, the layered height curve is obtained by combining the water vapor density threshold and fitting, the height range under a certain water vapor density can be modeled, the calculation and modeling of the whole troposphere are avoided, and thus the calculation amount and complexity are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of meteorological modeling, and in particular to a modeling method and device for tropospheric wet information. BACKGROUND

[0002] When GNSS satellite signals pass through the troposphere, the troposphere has two effects on the signals, namely, propagation speed delay and propagation path bending delay. The path delay caused by the two effects is called tropospheric delay. In the process of GNSS data processing, the tropospheric delay of the signal propagation path is usually projected to the zenith direction and divided into zenith tropospheric hydrostatic delay and zenith tropospheric wet delay. The zenith tropospheric hydrostatic delay is related to atmospheric pressure and is relatively stable. The zenith tropospheric wet delay is related to water vapor pressure, and the water vapor pressure is related to the water vapor content in the air. Water vapor information plays an important role in weather forecasting and climate prediction. However, water vapor changes rapidly and is not uniformly distributed, for example, the water vapor content in coastal areas is significantly greater than that in inland areas in horizontal distribution, and the water vapor content is higher at lower altitudes in vertical distribution. When calculating or using tropospheric wet information by using sounding products, radio occultation products, ERA5 products, etc., the calculation amount and complexity are greatly increased if the entire troposphere is calculated or modeled because most of the tropospheric wet information exists at a certain height in the troposphere. SUMMARY

[0003] The present application provides a modeling method and device for tropospheric wet information to solve the technical problems of large calculation amount and high complexity in modeling tropospheric wet information in the prior art.

[0004] To solve the above technical problems, the present application provides a modeling method for tropospheric wet information, comprising:

[0005] Obtaining tropospheric meteorological data of a plurality of height layers in a preset time range, and according to the tropospheric meteorological data, obtaining a water vapor density fluctuation range of the plurality of height layers in the preset time range by statistics;

[0006] Fitting a layered height curve varying with time according to the water vapor density fluctuation range and a water vapor density threshold value;

[0007] Modeling the wet information at the layered height after discretization according to the layered height curve and the tropospheric meteorological data, to obtain a tropospheric wet information model.

[0008] The present application obtains the water vapor density fluctuation range by statistically processing the tropospheric meteorological data of each height layer in a preset time range, and obtains the layered height curve by fitting the water vapor density fluctuation range and the water vapor density threshold value.

[0009] Further, the tropospheric meteorological data of several height layers in a preset time range is obtained, and the water vapor density fluctuation range of several height layers in a preset time range is statistically obtained according to the tropospheric meteorological data, specifically:

[0010] The tropospheric meteorological data includes temperature and water vapor pressure.

[0011] The temperature of several height layers in a preset time range and the water vapor pressure of several height layers in a preset time range are obtained.

[0012] The water vapor density of several height layers in a preset time range is calculated according to the temperature and the water vapor pressure.

[0013] The water vapor density fluctuation range of several height layers in a preset time range is statistically obtained according to the water vapor density.

[0014] The present application calculates the water vapor density of each height layer in a preset time range by the temperature and the water vapor pressure of several height layers in a preset time range, and then statistically obtains the water vapor density fluctuation range, which can be used for subsequent modeling in a certain preset water vapor density range, thereby avoiding calculation and modeling of the entire troposphere, thereby reducing the amount of calculation and complexity.

[0015] Further, the layered height curve changing with time is fitted according to the water vapor density fluctuation range and the water vapor density threshold value, specifically:

[0016] The water vapor density threshold value includes a first threshold value.

[0017] The water vapor density mean value of each height layer is calculated according to the water vapor density fluctuation range.

[0018] The first height layer with a water vapor density mean value less than the first threshold value is selected according to the water vapor density mean value of each height layer and the first threshold value, and the layered height corresponding to the maximum water vapor density of the first height layer at different time is obtained.

[0019] The layered height curve changing with time is fitted according to the layered height at different time.

[0020] The application calculates the water vapor density average of each height layer according to the water vapor density fluctuation range of each height layer, and determines the corresponding stratification height of the maximum water vapor density of the height layer below the first threshold value by reasonably setting the first threshold value, and further obtains the stratification height curve changing with time, which can be used for modeling at the stratification height through the stratification height curve, thereby avoiding calculation and modeling of the entire troposphere, and reducing the calculation amount and complexity.

[0021] Further, the expression of the stratification height is:

[0022]

[0023] Wherein, ρ1 is the water vapor density value average of the first height layer, ρ2 is the water vapor density average of the height layer adjacent to the first height layer, and ρ1 < ρ max < ρ2, ρ max is the maximum water vapor density of the first height layer, h1 is the height corresponding to the water vapor density average ρ1, and h2 is the height corresponding to the water vapor density average ρ2.

[0024] Further, after the water vapor density average of each height layer is calculated according to the water vapor density fluctuation range, the method further comprises:

[0025] Wherein, the water vapor density threshold value comprises a second threshold value; the second threshold value is less than the first threshold value;

[0026] According to the water vapor density average of each height layer and the second threshold value, a second height layer with a water vapor density average less than the second threshold value is selected, and the boundary height corresponding to the maximum water vapor density of the second height layer at different times is obtained.

[0027] According to the boundary height at different times, a boundary height curve changing with time is fitted.

[0028] Further, after the stratification height curve changing with time is fitted according to the water vapor density fluctuation range and the water vapor density threshold value, the method further comprises:

[0029] According to the stratification height curve and the boundary height curve, the wet delay information between the stratification height and the boundary height is obtained using a meteorological product.

[0030] The application further calculates the boundary height curve of the region with smaller water vapor density through the water vapor density average and the second threshold value, and according to the boundary height curve, the wet delay information in the region with smaller water vapor density can be obtained through the meteorological product, thereby reducing the calculation amount and complexity.

[0031] Further, the wet information at the layer height is discretized and modeled according to the layer height curve and the tropospheric meteorological data to obtain a tropospheric wet information model, specifically:

[0032] The tropospheric meteorological data includes temperature and water vapor pressure.

[0033] The wet information is calculated according to the temperature and the water vapor pressure, and the wet information includes slant path wet delay and slant path water vapor content.

[0034] The wet information below the layer height is discretized according to the layer height curve, and a first wet information model is established.

[0035] The tropospheric meteorological data and GNSS data are time-synchronized to obtain updated tropospheric meteorological data.

[0036] The first wet information model is optimized according to the updated tropospheric meteorological data to obtain the tropospheric wet information model.

[0037] The first wet information model is established below the layer height, avoiding calculation and modeling of the entire troposphere, thereby reducing the calculation amount and complexity. In addition, the tropospheric meteorological data and GNSS data are time-synchronized, so that the tropospheric meteorological data and GNSS data are updated at the same time period, thereby reducing the calculation amount and complexity while improving the spatial and temporal resolution of the tropospheric information wet information model.

[0038] Further, the expression of the updated tropospheric meteorological data is:

[0039]

[0040]

[0041] Wherein, f i (t) is the updated tropospheric meteorological data, t is time, y i is the tropospheric meteorological data of the meteorological product.

[0042] Further, the expression of the tropospheric wet information model is:

[0043]

[0044] Wherein, X uFor the tropospheric wet information to be reconstructed, X0 is the wet information, A is a distance matrix after the satellite signal propagation route is discretized, B is a matrix corresponding to the wet information, W is a horizontal constraint matrix during discretized solving, V is a vertical constraint matrix during discretized solving, Δ1 is a first observation value noise matrix, and Δ2 is a second observation value noise matrix.

[0045] In another aspect, the embodiment of the present application also provides a modeling device for tropospheric wet information, comprising a data acquisition module, a height curve establishment module and a model establishment module.

[0046] The data acquisition module is configured to acquire tropospheric meteorological data of a plurality of height layers within a preset time range, and to statistically obtain a water vapor density fluctuation range of the plurality of height layers within the preset time range according to the tropospheric meteorological data.

[0047] The height curve establishment module is configured to fit a stratified height curve varying with time according to the water vapor density fluctuation range and a water vapor density threshold.

[0048] The model establishment module is configured to model the wet information at the stratified height after discretization according to the stratified height curve and the tropospheric meteorological data, to obtain a tropospheric wet information model.

[0049] The present application statistically obtains a water vapor density fluctuation range from tropospheric meteorological data of a plurality of height layers within a preset time range, fits a stratified height curve according to the water vapor density fluctuation range and a water vapor density threshold, and can model the height range at a certain water vapor density by reasonable selection of the water vapor density threshold, thereby avoiding calculation and modeling of the entire troposphere, and reducing the calculation amount and complexity. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 A flowchart of an embodiment of the high-temporal and high-spatial resolution tropospheric stratified modeling method provided by the present application;

[0051] Figure 2 A flowchart of another embodiment of the high-temporal and high-spatial resolution tropospheric stratified modeling method provided by the present application;

[0052] Figure 3 A flowchart of another embodiment of the high-temporal and high-spatial resolution tropospheric stratified modeling method provided by the present application;

[0053] Figure 4 A flowchart of another embodiment of the high-temporal and high-spatial resolution tropospheric stratified modeling method provided by the present application;

[0054] Figure 5A structural schematic diagram of one embodiment of the high-temporal and spatial resolution troposphere layered modeling device provided by the present application;

[0055] Figure 6 A modeling process schematic diagram provided by the present application. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0057] Embodiment one

[0058] Please refer to Figure 1 A flowchart of one embodiment of the high-temporal and spatial resolution troposphere layered modeling method provided by the present application mainly includes steps 101-103, and the details are as follows:

[0059] Step 101: Obtain troposphere meteorological data of a plurality of height layers in a preset time range, and according to the troposphere meteorological data, obtain a water vapor density fluctuation range of the plurality of height layers in the preset time range.

[0060] In this embodiment, the troposphere meteorological data can be obtained through meteorological products, such as wireless sounding products, wireless occultation products and ERA5 products. These meteorological products can provide high vertical resolution spatial distribution of atmospheric pressure, atmospheric water vapor pressure and atmospheric temperature, and the water vapor density in different height layers can be estimated through these data.

[0061] In this embodiment, the preset time range can be a time range of half a year, one year or even longer, and the number of the plurality of height layers can be set by the user as needed.

[0062] In this embodiment, the water vapor density fluctuation range can be expressed as: P(ρ min <ρ i <ρ max )=0.9;wherein, ρ i is the water vapor density of a height layer, ρ min is the minimum value of the water vapor density of the height layer, and ρ max is the maximum value of the water vapor density of the height layer; in addition, the value 0.9 of the water vapor density fluctuation range represents that the probability of the water vapor density ρ i of each layer being between ρ min and ρ max is 90%, and thus ρ iThe water vapor density fluctuation range can be set to other values according to actual needs, except for 0.9.

[0063] Step 102: fitting to obtain a stratification height curve changing with time according to the water vapor density fluctuation range and the water vapor density threshold.

[0064] In the embodiment, the height layer belonging to a certain water vapor density range and the height corresponding to the height layer can be screened out through the water vapor density fluctuation range of each height layer and the water vapor density threshold that can be set by the user, and the corresponding height of the height layer at different times can be obtained in combination with a preset time range, and then a stratification height curve changing with time can be obtained.

[0065] In the embodiment, the stratification height curve can be used to determine the height region to be considered for modeling, so as to avoid modeling the entire troposphere and reduce the calculation amount and complexity required for modeling.

[0066] Step 103: discretizing and modeling the wet information at the stratification height according to the stratification height curve and the tropospheric meteorological data, to obtain a tropospheric wet information model.

[0067] In the embodiment, the height region to be considered for modeling can be determined through the stratification height curve, and the wet information required for modeling can be provided by the tropospheric meteorological data, and then the wet information is discretized to establish a tropospheric wet information model. The wet information can be three-dimensional wet information, including wet refractive index, water vapor density, etc. In addition, the wet information required for modeling can be calculated from the tropospheric meteorological data, and this process can be automatically calculated in meteorological products such as ERA5 products.

[0068] Please refer to Figure 2 for another embodiment of the high-spatial and temporal resolution tropospheric stratification modeling method provided by the present application. Figure 2 The main difference between the present application and Figure 1 is that the present application is based on the stratification height curve changing with time. Figure 2 The present application comprises steps 201-203, which are as follows.

[0069] In the embodiment, step 201 specifically comprises steps 201 to 203.

[0070] In the embodiment, the tropospheric meteorological data includes temperature and water vapor pressure.

[0071] Step 201: obtaining temperature of a plurality of height layers in a preset time range and water vapor pressure of a plurality of height layers in a preset time range.

[0072] In the embodiment, the temperature and the water vapor pressure can be obtained by a meteorological product, the meteorological product collects the temperature and the water vapor pressure at different heights or different air pressures, and the temperature and the water vapor pressure in a preset time range are obtained by historical data.

[0073] Step 202: According to the temperature and the water vapor pressure, the water vapor density of several height layers in a preset time range is calculated.

[0074] In the embodiment, the expression of the water vapor density is:

[0075]

[0076] Wherein, T is the temperature of a certain height layer, and e is the water vapor pressure of a certain height layer.

[0077] Step 203: According to the water vapor density, the water vapor density fluctuation range of several height layers in a preset time range is counted.

[0078] In the embodiment, if ERA5 is used to collect the temperature and the water vapor pressure, the maximum time resolution is 1 hour, the spatial resolution is global, and the historical data provided by ERA5 can be used to count and calculate in a long time range, for example, 1 year, to obtain the water vapor density fluctuation range of each height layer in 1 year.

[0079] The present application calculates the water vapor density of each height layer in a preset time range by the temperature and the water vapor pressure of several height layers in the preset time range, and then counts the water vapor density fluctuation range, which can be used for subsequent modeling in a region with a preset water vapor density range, thereby avoiding calculation and modeling of the entire troposphere, and reducing the calculation amount and complexity.

[0080] Please refer to Figure 3 , the flowchart of another embodiment of the high-spatial and temporal resolution tropospheric layered modeling method provided by the present application. Figure 3 The main difference between Figure 1 Figure 3 The steps 301-303 are included, and the details are as follows:

[0081] In the embodiment, the step 102 specifically includes the steps 301 to 303.

[0082] In the embodiment, the water vapor density threshold includes a first threshold.

[0083] Step 301: According to the water vapor density fluctuation range, the water vapor density mean value of each height layer is calculated.

[0084] ​In the embodiment, the water vapor density of each height layer is averaged to obtain the water vapor density average of each layer in a preset time range; the preset time range includes but is not limited to 1 year.

[0085] In step 302, according to the water vapor density average of each height layer and the first threshold value, a first height layer with a water vapor density average less than the first threshold value is selected, and a layered height corresponding to a maximum water vapor density of the first height layer at different time is obtained.

[0086] In the embodiment, the value of the first threshold value includes but is not limited to 1 g / m 3 The water vapor density average of each height layer is used to determine the height layer with a water vapor density average less than the first threshold value, and the maximum water vapor density corresponding to the height layer is found, and the height of the maximum water vapor density is the layered height.

[0087] In the embodiment, the expression of the layered height is:

[0088]

[0089] Wherein, ρ1 is the water vapor density value average of the first height layer, ρ2 is the water vapor density average of the height layer adjacent to the first height layer, and ρ1<ρ max <ρ2, ρ max is the maximum water vapor density of the first height layer, h1 is the height corresponding to the water vapor density average ρ1, and h2 is the height corresponding to the water vapor density average ρ2.

[0090] Further, after the water vapor density average of each height layer is calculated according to the water vapor density fluctuation range, the following steps are further included:

[0091] Wherein, the water vapor density threshold value includes a second threshold value; the second threshold value is less than the first threshold value;

[0092] According to the water vapor density average of each height layer and the second threshold value, a second height layer with a water vapor density average less than the second threshold value is selected, and a boundary height corresponding to a maximum water vapor density of the second height layer at different time is obtained.

[0093] According to the boundary height at different time, a boundary height curve changing with time is fitted.

[0094] In the embodiment, the value of the second threshold value includes but is not limited to 0.001 g / m 3 The second threshold value can be used to screen out the boundary area by the water vapor density average.

[0095] In the embodiment, the expression of the layered height is:

[0096]

[0097] wherein p3 is the mean value of the water vapor density of the second height layer, p4 is the mean value of the water vapor density of the height layer adjacent to the second height layer, and p3 max1 < p4, p max1 is the maximum value of the water vapor density of the second height layer, h3 is the height corresponding to the mean value of the water vapor density p3, and h4 is the height corresponding to the mean value of the water vapor density p4.

[0098] Step 303: fitting the stratification height curve varying with time according to the stratification height at different times.

[0099] In the embodiment, after obtaining the stratification height at different times, the stratification height can be fitted into a height function varying with time, i.e., a stratification height curve, using a quartic function; wherein the expression of the stratification height curve is:

[0100] h layer (t) = at 4 + bt 3 + ct 2 + dt

[0101] wherein a, b, c, d, and e are fitting coefficients, and the fitting coefficients are related to the region corresponding to the stratification height.

[0102] In the embodiment, in the subsequent modeling process, only the stratification height h layer The following region is modeled, which can avoid modeling the entire troposphere.

[0103] In the embodiment, after fitting the stratification height curve varying with time according to the water vapor density fluctuation range and the water vapor density threshold, the method further comprises: using meteorological products to obtain the wet delay information between the stratification height and the boundary height according to the stratification height curve and the boundary height curve.

[0104] The application also calculates the boundary height curve of the region with smaller water vapor density through the mean value of the water vapor density and the second threshold value; according to the boundary height curve, the wet delay information in the region with smaller water vapor density can be obtained through meteorological products, and the calculation amount and complexity are reduced.

[0105] In the embodiment, the boundary of the troposphere is determined through the stratification height curve, the troposphere above the stratification height and below the boundary height does not use the modeling method to obtain the wet information, but directly obtains the wet delay information through ERA5 and other meteorological products, thereby avoiding discretization and modeling of the entire troposphere.

[0106] According to the water vapor density fluctuation range of each height layer, the water vapor density average of each height layer is calculated, the corresponding stratification height of the maximum water vapor density of the height layer below the first threshold value is determined by reasonably setting the first threshold value, and then the stratification height curve changing with time is obtained, which can be used for modeling at the stratification height through the stratification height curve, so as to avoid calculation and modeling of the whole troposphere, thereby reducing the calculation amount and complexity.

[0107] Please refer to Figure 4 The flowchart of another embodiment of the high-spatial and temporal resolution troposphere stratification modeling method provided by the application is shown. Figure 4 The main difference between the application and Figure 1 is that Figure 4 comprises steps 401-404, specifically as follows:

[0108] In this embodiment, step 103 specifically comprises steps 401 to 404.

[0109] In this embodiment, the troposphere meteorological data includes temperature and water vapor pressure.

[0110] Step 401: calculating the wet information according to the temperature and the water vapor pressure; wherein the wet information includes slant path wet delay and slant path water vapor content.

[0111] In this embodiment, the temperature and water vapor pressure of each height layer can be obtained through meteorological products, and the water vapor density and wet refractive index can be calculated through the temperature and water vapor pressure; wherein the expression of the wet refractive index is:

[0112]

[0113] Wherein T is the temperature of a certain height layer, and e is the water vapor pressure of a certain height layer.

[0114] In this embodiment, the slant path wet delay (SWD) and the slant path water vapor (SWV) are calculated according to the water vapor density and the wet refractive index.

[0115] In this embodiment, the expression of the slant path wet delay is:

[0116] SWD=∫N w ds;

[0117] Wherein N w is the wet refractive index.

[0118] In this embodiment, the expression of the slant path water vapor content is:

[0119] SWV=∫ρds;

[0120] wherein p is the water vapor density.

[0121] In the embodiment, the slant path wet delay and the slant path water vapor content can also be obtained through GNSS data; GNSS precise positioning is obtained by dividing the troposphere delay into dry delay and wet delay, and estimating the zenith wet delay as an unknown parameter. The zenith troposphere wet delay (ZWD) can only reflect the overall wet information in the vertical direction of the GNSS receiver, and cannot reflect the three-dimensional spatial distribution of the troposphere wet information, so the zenith troposphere wet delay is mapped through a mapping function M w The projection is the slant path wet delay: SWD = M w ZWD; in this way, the slant path wet delay simultaneously contains the vertical and horizontal distribution of the troposphere wet information, and the conversion factor Π can be used to convert SWD to the water vapor content in the slant path: SWV = Π · SWD.

[0122] Step 402: After discretizing the wet information below the layer height according to the layer height curve, a first wet information model is established.

[0123] When modeling the troposphere wet information, discretization is needed, and the entire troposphere usually needs to be discretized, but the height of the troposphere varies with latitude, and is about 17-18 km in low-latitude areas, 10-12 km in mid-latitude areas, and only 8-9 km in high-latitude areas. The boundary height is difficult to define, and the water vapor is often concentrated below 6 km. When the top of the troposphere is used as the maximum height for discretization, the places without water vapor content and with less water vapor content are also discretized, which increases the complexity of calculation and reduces the accuracy of the discretely reconstructed wet information. In the embodiment, the first threshold is reasonably selected to filter out the layer height in the corresponding height layer, and modeling the area below the layer height can avoid the problem of large amount of calculation caused by modeling the entire troposphere.

[0124] In the embodiment, the expression of the first wet information model is:

[0125]

[0126] wherein X is the troposphere wet information to be reconstructed and modeled, A is the distance matrix of the satellite signal propagation route after discretization, B is the matrix corresponding to the wet information, W is the horizontal constraint matrix during discretization and calculation, V is the vertical constraint matrix during discretization and calculation, and Δ is the third observation noise matrix.

[0127] Step 403: Time synchronization is performed on the troposphere meteorological data and the GNSS data to obtain updated troposphere meteorological data.

[0128] The time resolution of the meteorological data obtained from the meteorological product, for example, the meteorological data obtained from ERA5, can be different from the time resolution of the GNSS data, please refer to Figure 6 The modeling process provided by the present application is schematically shown in the figure, time synchronization is performed through an interpolation function, based on the time resolution of the atmospheric change characteristics and the meteorological data and the GNSS data, the time period required for synchronization, such as 30 minutes / group, is set, and the GNSS data in each time period is regarded as the same time point, and then the meteorological data is interpolated to obtain the data under the time period or time scale.

[0129] In the embodiment, the expression of the updated tropospheric meteorological data is:

[0130]

[0131]

[0132] Wherein, f i (t) is the updated tropospheric meteorological data, t is the time, y i is the tropospheric meteorological data of the meteorological product.

[0133] Step 404: optimizing the first wet information model according to the updated tropospheric meteorological data to obtain the tropospheric wet information model.

[0134] In the embodiment, the expression of the tropospheric wet information model is:

[0135]

[0136] Wherein, X u is the tropospheric wet information to be reconstructed, X0 is the wet information, A is the distance matrix after discretization of the satellite signal propagation route, B is the matrix corresponding to the wet information, W is the horizontal constraint matrix during discretization calculation, V is the vertical constraint matrix during discretization calculation, Δ1 is the first observation noise matrix, and Δ2 is the second observation noise matrix.

[0137] In the embodiment, the ERA5 product can provide meteorological data of 4 days ago at the fastest, therefore, the meteorological data of the current date is extrapolated by using the meteorological data of 4 days ago to 24 days ago. Combined with the real-time satellite coordinates and real-time zenith tropospheric wet delay provided by the real-time PPP, the wet information required for modeling can be obtained after time synchronization, and the real-time tropospheric layered modeling is realized.

[0138] The first wet information model is established below the layered height, calculation and modeling of the whole troposphere are avoided, and thus the calculation amount and complexity are reduced; in addition, the troposphere meteorological data and the GNSS data are time-synchronized, the troposphere meteorological data and the GNSS data are updated in the same time period, and thus the spatial and temporal resolution of the troposphere information wet information model is improved while the calculation amount and complexity are reduced.

[0139] Please refer to Figure 5 An embodiment of the layered modeling device for the troposphere with high spatial and temporal resolution provided by the application mainly comprises a data acquisition module 501, a height curve establishment module 502 and a model establishment module 503.

[0140] In the embodiment, the data acquisition module 501 is used to acquire troposphere meteorological data of several height layers in a preset time range, and the water vapor density fluctuation range of the several height layers in the preset time range is obtained by counting according to the troposphere meteorological data.

[0141] In the embodiment, the data acquisition module 501 comprises a data acquisition unit, a water vapor density calculation unit and a fluctuation range counting unit; the troposphere meteorological data comprises temperature and water vapor pressure; the data acquisition unit is used to acquire the temperature of several height layers in a preset time range and the water vapor pressure of several height layers in a preset time range; the water vapor density calculation unit is used to calculate the water vapor density of several height layers in a preset time range according to the temperature and the water vapor pressure; and the fluctuation range counting unit is used to obtain the water vapor density fluctuation range of several height layers in a preset time range according to the water vapor density.

[0142] The height curve establishment module 502 is used to fit the layered height curve changing with time according to the water vapor density fluctuation range and a water vapor density threshold.

[0143] In the embodiment, the height curve establishment module 502 comprises a mean value calculation unit, a first height calculation unit and a first curve calculation unit; the water vapor density threshold comprises a first threshold; the mean value calculation unit is used to calculate the water vapor density mean value of each height layer according to the water vapor density fluctuation range; the first height calculation unit is used to select a first height layer with a water vapor density mean value less than the first threshold according to the water vapor density mean value of each height layer and the first threshold, and acquire the layered height corresponding to the maximum water vapor density of the first height layer at different time; and the first curve calculation unit is used to fit the layered height curve changing with time according to the layered height at different time.

[0144] In the embodiment, the height curve establishing module 502 further comprises a second height calculating unit and a second curve calculating unit; the water vapor density threshold comprises a second threshold; the second threshold is smaller than the first threshold; the second height calculating unit is configured to select a second height layer with a mean water vapor density less than the second threshold according to the mean water vapor density of each height layer and the second threshold, and obtain a boundary height corresponding to a maximum water vapor density of the second height layer at different time points; and the second curve calculating unit is configured to fit a boundary height curve varying with time according to the boundary heights at different time points.

[0145] In the embodiment, the high spatiotemporal resolution troposphere layering modeling device further comprises a wet delay information acquisition module; the wet delay information acquisition module is configured to acquire wet delay information between the layering height and the boundary height using meteorological products according to the layering height curve and the boundary height curve after the second curve calculating unit fits the boundary height curve varying with time.

[0146] The model establishing module 503 is configured to model the wet information at the layering height after discretization according to the layering height curve and the troposphere meteorological data, and obtain a troposphere wet information model.

[0147] In the embodiment, the model establishing module 503 comprises a wet information calculating unit, a first model establishing unit, a time synchronizing unit and a second model establishing unit; the wet information calculating unit is configured to calculate the wet information according to the temperature and the water vapor pressure; the wet information comprises a slant path wet delay and a slant path water vapor content; the first model establishing unit is configured to establish a first wet information model after discretization of the wet information below the layering height according to the layering height curve; the time synchronizing unit is configured to time synchronize the troposphere meteorological data and GNSS data to obtain updated troposphere meteorological data; and the second model establishing unit is configured to optimize the first wet information model according to the updated troposphere meteorological data to obtain the troposphere wet information model.

[0148] The present application can model the height range at a certain water vapor density by reasonable selection of the water vapor density threshold, avoid calculation and modeling of the whole troposphere, and thus reduce the calculation amount and complexity.

[0149] The above-described specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above-described specific embodiments are merely examples of the present application and are not intended to limit the protection scope of the present application. It is particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for modeling tropospheric humidity information, characterized in that, include: Acquire tropospheric meteorological data at several altitudes within a preset time range, and statistically determine the water vapor density fluctuation range at several altitudes within the preset time range based on the tropospheric meteorological data. Based on the water vapor density fluctuation range and water vapor density threshold, a stratification height curve that changes over time is obtained by fitting. Based on the stratification height curve and the tropospheric meteorological data, the moisture information at the stratification height is discretized and then modeled to obtain the tropospheric moisture information model; The stratification height curve that varies with time is obtained by fitting the water vapor density fluctuation range and water vapor density threshold, specifically as follows: The water vapor density threshold includes a first threshold. Based on the water vapor density fluctuation range, the average water vapor density of each altitude layer is calculated; Based on the average water vapor density of each altitude layer and the first threshold, the first altitude layer with an average water vapor density less than the first threshold is selected, and the layer height corresponding to the maximum water vapor density of the first altitude layer at different times is obtained. Based on the layer height at different times, a layer height curve varying with time is obtained by fitting. After calculating the average water vapor density at each altitude layer based on the water vapor density fluctuation range, the method further includes: Wherein, the water vapor density threshold includes a second threshold; the second threshold is less than the first threshold; Based on the average water vapor density of each altitude layer and the second threshold, a second altitude layer with an average water vapor density less than the second threshold is selected, and the boundary height corresponding to the maximum water vapor density of the second altitude layer at different times is obtained. Based on the boundary height at different times, a boundary height curve varying with time is fitted. After fitting the stratification height curve over time based on the water vapor density fluctuation range and water vapor density threshold, the method further includes: Based on the stratification height curve and the boundary height curve, the wet delay information between the stratification height and the boundary height is obtained using meteorological products.

2. The method for modeling tropospheric humidity information as described in claim 1, characterized in that, The process of acquiring tropospheric meteorological data at several altitudes within a preset time range, and statistically determining the water vapor density fluctuation range at several altitudes within the preset time range based on the tropospheric meteorological data, specifically involves: The tropospheric meteorological data includes temperature and water vapor pressure; Obtain the temperature and water vapor pressure at several altitude levels within a preset time range; Based on the temperature and the water vapor pressure, the water vapor density at several altitudes within a preset time range is calculated. Based on the water vapor density, the fluctuation range of water vapor density at several altitude layers within a preset time range is statistically obtained.

3. The method for modeling tropospheric humidity information as described in claim 1, characterized in that, The expression for the layer height is: ； in, This represents the average water vapor density value in the first altitude layer. The average water vapor density of the layer adjacent to the first altitude layer, and , This represents the maximum water vapor density in the first altitude layer. Mean water vapor density Corresponding height, Mean water vapor density The corresponding height.

4. The method for modeling tropospheric humidity information as described in claim 1, characterized in that, The process involves discretizing the moisture information at different stratification levels based on the stratification height curve and the tropospheric meteorological data, and then modeling the resulting tropospheric moisture information model. Specifically: The tropospheric meteorological data includes temperature and water vapor pressure. The humidity information is calculated based on the temperature and the vapor pressure; wherein the humidity information includes: oblique path humidity delay and oblique path water vapor content; Based on the layer height curve, the moisture information below the layer height is discretized to establish a first moisture information model; The tropospheric meteorological data and GNSS data are synchronized in time to obtain updated tropospheric meteorological data; Based on the updated tropospheric meteorological data, the first wet information model is optimized to obtain the tropospheric wet information model.

5. The method for modeling tropospheric humidity information as described in any one of claims 1-4, characterized in that, The expression for the tropospheric wet information model is: ； in, For the tropospheric wet information to be reconstructed and modeled, For the aforementioned wet information, The distance matrix is ​​the discretized result of the satellite signal propagation path. The matrix corresponding to the wet information. This is the horizontal constraint matrix for discretization. This is the vertical constraint matrix used in discretization. The noise matrix for the first observation. This is the noise matrix for the second observation.

6. A modeling device for tropospheric humidity information, characterized in that, include: Data acquisition module, height curve creation module, and model creation module; The data acquisition module is used to acquire tropospheric meteorological data at several altitudes within a preset time range, and to statistically determine the water vapor density fluctuation range at several altitudes within the preset time range based on the tropospheric meteorological data. The height curve establishment module is used to fit a stratified height curve that changes over time based on the water vapor density fluctuation range and water vapor density threshold. The model building module is used to discretize the moisture information at the stratification height and model it based on the stratification height curve and the tropospheric meteorological data to obtain a tropospheric moisture information model; The height curve establishment module includes an average value calculation unit, a first height calculation unit, and a first curve calculation unit; wherein, the water vapor density threshold includes a first threshold; the average value calculation unit is used to calculate the average water vapor density of each height layer based on the water vapor density fluctuation range; the first height calculation unit is used to select a first height layer whose average water vapor density is less than the first threshold based on the average water vapor density of each height layer and the first threshold, and obtain the layer height corresponding to the maximum water vapor density of the first height layer at different times; the first curve calculation unit is used to fit a layer height curve that changes with time based on the layer height at different times; The altitude curve establishment module further includes a second altitude calculation unit and a second curve calculation unit; wherein, the water vapor density threshold includes a second threshold; the second threshold is less than the first threshold; the second altitude calculation unit is used to select a second altitude layer whose average water vapor density is less than the second threshold based on the average water vapor density of each altitude layer and the second threshold, and obtain the boundary altitude corresponding to the maximum water vapor density of the second altitude layer at different times; the second curve calculation unit is used to fit a boundary altitude curve that changes with time based on the boundary altitude at different times; The high spatiotemporal resolution tropospheric stratification modeling device also includes a wet delay information acquisition module; the wet delay information acquisition module is used to obtain the wet delay information between the stratification height and the boundary height using meteorological products after the boundary height curve is obtained by fitting the boundary height curve with time in the second curve calculation unit.

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