Atmospheric precipitation estimation method and device, computer equipment and storage medium

Abstract

The application relates to an atmospheric precipitable water estimation method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring observation data of a plurality of global navigation satellite system stations, first atmospheric precipitable water of a plurality of European Centre for Medium-Range Weather Forecasts grid positions, sounding atmospheric precipitable water and position information of a to-be-measured position in a to-be-measured area; according to the observation data of the plurality of stations, second atmospheric precipitable water and precipitation uncertainty of the corresponding stations are solved; based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty and fitting parameters, a target function is determined, and the fitting parameters corresponding to the function value convergence of the target function are taken as target fitting parameters; and based on the target fitting parameters and the position information of the to-be-measured position, the atmospheric precipitable water at the to-be-measured position is determined. The method can improve the atmospheric precipitable water estimation result acquisition efficiency.

Description

Technical Field

[0001] This application relates to the field of water vapor measurement technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for estimating atmospheric precipitable water. Background Technology

[0002] With the in-depth development of Global Navigation Satellite Systems (GNSS), water vapor retrieval technology, which boasts advantages such as high spatiotemporal resolution, high accuracy, and low operating costs, has seen increasing applications in recent years. However, due to the sparse and uneven distribution of GNSS stations and the discontinuity of observations, it is difficult to obtain accurate spatial distributions of PWV (Precipitable Water Vapor) based on GNSS observations. The ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis dataset assimilates multiple observational data, and its provided water vapor grid data has advantages such as uniform recording, global coverage, and spatial integrity. However, reliable data is difficult to obtain in areas lacking assimilated data.

[0003] Existing methods for estimating atmospheric precipitable water often construct a regional water vapor field by fusing water vapor data obtained from GNSS data processing and water vapor data provided by ECMWF. However, the constructed models are relatively complex, and training the models is time-consuming and laborious, resulting in low efficiency in obtaining atmospheric precipitable water estimation results. Summary of the Invention

[0004] Therefore, it is necessary to address the problem of low efficiency in obtaining atmospheric precipitable water estimation results in traditional methods, and to provide an atmospheric precipitable water estimation method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve the efficiency of obtaining atmospheric precipitable water estimation results.

[0005] Firstly, this application provides a method for estimating atmospheric precipitable water. The method includes:

[0006] The observation data from multiple Global Navigation Satellite System stations, the first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, the radiosonde atmospheric precipitable water content, and the location information of the location to be measured are obtained in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0007] Based on observation data from multiple global navigation satellite system stations, the second atmospheric precipitable water content and precipitation uncertainty of the corresponding stations were calculated.

[0008] Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, the objective function is determined, and the fitting parameters corresponding to the convergence of the objective function value are taken as the target fitting parameters.

[0009] Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined.

[0010] In one embodiment, based on observation data from multiple Global Navigation Satellite System (GNSS) stations, the second atmospheric precipitable water content for each station is calculated, including:

[0011] For each of the multiple Global Navigation Satellite System (GNSS) sites, obtain the current site's atmospheric pressure, latitude, and elevation;

[0012] Based on the observation data of the current station, determine the total zenith tropospheric delay of the current station;

[0013] Based on the atmospheric pressure, latitude, and elevation of the current station, the zenith dry delay component of the current station is obtained through the tropospheric delay correction model.

[0014] The wet zenith delay component of the current station is determined based on the total zenith tropospheric delay and the dry zenith delay component of the current station.

[0015] The zenith wet delay component of the current station is converted based on a preset conversion coefficient to obtain the second atmospheric precipitable water content of the current station.

[0016] In one embodiment, based on the first atmospheric precipitable water content, the sounding atmospheric precipitable water content, the second atmospheric precipitable water content, the precipitation uncertainty, and the fitting parameters, the objective function is determined, including:

[0017] Based on the fitting parameters, the first difference between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitting data at the corresponding grid locations is determined.

[0018] Based on the fitting parameters, the second difference between the second atmospheric precipitable water at multiple Global Navigation Satellite System stations and the fitting data of the corresponding stations is determined;

[0019] Interpolate the first atmospheric precipitable at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations to obtain the interpolated atmospheric precipitable; determine the third difference between the interpolated atmospheric precipitable and the sounding atmospheric precipitable.

[0020] The objective function is determined based on the first difference, the second difference, the third difference, and the uncertainty of precipitation.

[0021] In one embodiment, an objective function is determined based on a first difference, a second difference, a third difference, and precipitation uncertainty, including:

[0022] Determine the difference matrix based on the first and second differences;

[0023] The variance matrix is ​​determined based on the third difference and the uncertainty of precipitation;

[0024] The objective function is determined based on the difference matrix and the variance matrix.

[0025] In one embodiment, based on fitting parameters, a first difference is determined between the first atmospheric precipitable water at a grid location of a plurality of European Centre for Medium-Range Weather Forecasts (ECMWF) locations and the fitted data at the corresponding grid locations, including:

[0026] Obtain grid location information for multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, including grid longitude, grid latitude, and grid elevation;

[0027] Based on the fitting parameters, determine the fitting model;

[0028] Based on the location information and fitting models of multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, the fitting data for the corresponding grid locations are determined.

[0029] The first difference between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitted data for the corresponding grid locations is determined; the fitted model is as follows: PWV fit = a0 + a1x + a2y + a3h, where a0, a1, a2, and a3 represent the fitting parameters, x represents the grid latitude, y represents the grid longitude, and h represents the grid elevation. PWV fit This represents the first atmospheric precipitable water content at the corresponding grid location.

[0030] In one embodiment, determining the atmospheric precipitable water at the location to be measured, based on the target fitting parameters and the location information of the location to be measured, includes:

[0031] Based on the target fitting parameters and the fitting model, determine the target fitting model;

[0032] The location information of the location to be measured is input into the target fitting model to obtain the atmospheric precipitation at the location to be measured.

[0033] Secondly, this application also provides a device for estimating atmospheric precipitable water. The device includes:

[0034] The data acquisition module is used to acquire observation data from multiple Global Navigation Satellite System stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, radiosonde atmospheric precipitable water content, and location information of the location to be measured in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0035] The calculation module is used to calculate the second atmospheric precipitable water and the precipitation uncertainty of the corresponding station based on the observation data of multiple global navigation satellite system stations.

[0036] The target fitting parameter determination module is used to determine the objective function based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters. The fitting parameters corresponding to the convergence of the objective function value are used as the target fitting parameters.

[0037] The precipitable water determination module is used to determine the atmospheric precipitable water at the location to be measured based on the target fitting parameters and the location information of the location to be measured.

[0038] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0039] The observation data from multiple Global Navigation Satellite System stations, the first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, the radiosonde atmospheric precipitable water content, and the location information of the location to be measured are obtained in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0040] Based on observation data from multiple global navigation satellite system stations, the second atmospheric precipitable water content and precipitation uncertainty of the corresponding stations were calculated.

[0041] Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, the objective function is determined, and the fitting parameters corresponding to the convergence of the objective function value are taken as the target fitting parameters.

[0042] Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined.

[0043] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0044] The observation data from multiple Global Navigation Satellite System stations, the first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, the radiosonde atmospheric precipitable water content, and the location information of the location to be measured are obtained in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0045] Based on observation data from multiple global navigation satellite system stations, the second atmospheric precipitable water content and precipitation uncertainty of the corresponding stations were calculated.

[0046] Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, the objective function is determined, and the fitting parameters corresponding to the convergence of the objective function value are taken as the target fitting parameters.

[0047] Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined.

[0048] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0049] The observation data from multiple Global Navigation Satellite System stations, the first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, the radiosonde atmospheric precipitable water content, and the location information of the location to be measured are obtained in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0050] Based on observation data from multiple global navigation satellite system stations, the second atmospheric precipitable water content and precipitation uncertainty of the corresponding stations were calculated.

[0051] Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, the objective function is determined, and the fitting parameters corresponding to the convergence of the objective function value are taken as the target fitting parameters.

[0052] Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined.

[0053] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for estimating atmospheric precipitable water acquires observation data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water, radiosonde atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, and location information of the location to be measured in the area to be measured. Based on the observation data from multiple GNSS stations, the second atmospheric precipitable water and precipitation uncertainty of the corresponding stations are calculated. Based on the first atmospheric precipitable water, radiosonde atmospheric precipitable water, second atmospheric precipitable water, precipitation uncertainty, and fitting parameters, an objective function is determined. The fitting parameters corresponding to the convergence of the objective function's value are used as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined. This method, which uses observation data from GNSS stations, first atmospheric precipitable water, radiosonde atmospheric precipitable water at ECMWF grid locations, and location information of the location to be measured, can quickly determine the objective function and target fitting parameters, thus improving the efficiency of determining the atmospheric precipitable water estimation results at the location to be measured. Attached Figure Description

[0054] Figure 1 This is an application environment diagram of a method for estimating atmospheric precipitable water in one embodiment;

[0055] Figure 2 This is a flowchart illustrating a method for estimating atmospheric precipitable water in one embodiment;

[0056] Figure 3 This is a schematic diagram of a sub-process of S204 in one embodiment;

[0057] Figure 4 This is a schematic diagram of a sub-process of S206 in one embodiment;

[0058] Figure 5 This is a schematic diagram of a sub-process of S408 in one embodiment;

[0059] Figure 6 This is a schematic diagram of various stations in the area to be tested in one embodiment;

[0060] Figure 7 This is a schematic diagram of the overall process of estimating atmospheric precipitable water in one embodiment;

[0061] Figure 8 This is a schematic diagram of the fitting effect in one embodiment;

[0062] Figure 9 This is a structural block diagram of a device for estimating atmospheric precipitable water content in one embodiment;

[0063] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0065] The method for estimating atmospheric precipitable water provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on another network server. The method for estimating atmospheric precipitable water provided in this application embodiment can be executed by terminal 102 or server 104 alone, or by terminal 102 and server 104 in collaboration. Taking the execution by terminal 102 alone as an example: In the area to be measured, observation data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water, sounding atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, and location information of the location to be measured are acquired. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured. Based on the observation data from multiple GNSS stations, the second atmospheric precipitable water and the precipitation uncertainty of the corresponding stations are calculated. Based on the first atmospheric precipitable water, sounding atmospheric precipitable water, second atmospheric precipitable water, precipitation uncertainty, and fitting parameters, an objective function is determined. The fitting parameters corresponding to the convergence of the objective function's value are used as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0066] In one embodiment, such as Figure 2 As shown, a method for estimating atmospheric precipitable water is provided, and this method is applied to a computer device (which can be...) Figure 1 Taking terminal 102 or server 104 as an example, the following steps are included:

[0067] S202 acquires observation data from multiple Global Navigation Satellite System stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, sounding atmospheric precipitable water content, and location information of the location to be measured in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0068] The first atmospheric precipitable water content is derived from the fifth-generation atmospheric reanalysis dataset ERA5 of the European Centre for Medium-Range Weather Forecasts (ECMWF) for global climate. ERA5, produced by the Copernicus Climate Change Service of ECMWF, provides hourly estimates of numerous atmospheric, terrestrial, and oceanic climate variables. The measured area includes multiple ECMWF grid locations. The first atmospheric precipitable water content refers to the atmospheric precipitable water content at multiple ECMWF grid locations within the measured area. Computer equipment acquires observational data from multiple Global Navigation Satellite System (GNSS) stations within the measured area. Radiosonde atmospheric precipitable water content refers to the atmospheric precipitable water content observed by radiosonde stations within the measured area. A radiosonde station is a station that uses electronic methods to observe upper-air pressure, temperature, and humidity. The measured location is any location within the measured area. The location information for the measured location includes its longitude, latitude, and elevation.

[0069] S204, based on observation data from multiple global navigation satellite system stations, calculates the second atmospheric precipitable water content and the precipitation uncertainty for the corresponding stations.

[0070] The second atmospheric precipitable water refers to observational data from Global Navigation Satellite System (GNSS) stations. Computer equipment processes the observational data from multiple GNSS stations to obtain the second atmospheric precipitable water for each station. Precipitation uncertainty is an indicator used to measure the accuracy of the second atmospheric precipitable water. In some embodiments, the calculation method used can be the PPP (Precise Point Positioning) data processing method. The computer equipment uses the PPP data processing method to process the observational data from multiple GNSS stations to obtain the second atmospheric precipitable water and the corresponding precipitation uncertainty for each station.

[0071] S206. Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, the objective function is determined, and the fitting parameters corresponding to the convergence of the objective function value are taken as the target fitting parameters.

[0072] Here, the objective function refers to the data function used for estimating atmospheric precipitable water. Optionally, the objective function can be a three-parameter linear function or a three-parameter quadratic function. The fitting parameters refer to the parameters in the objective function. Different measurement regions correspond to different fitting parameters. The fitting function is determined by the fitting parameters and the objective function, thus determining the fitting function corresponding to different measurement regions. Different measurement regions can use the same objective function. The computer equipment inputs the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, and the precipitation uncertainty into the objective function, continuously adjusting the fitting parameters until the function value of the objective function converges. The fitting parameters corresponding to the minimum value of the objective function are taken as the target fitting parameters.

[0073] S208, based on the target fitting parameters and the location information of the location to be measured, determines the atmospheric precipitable water at the location to be measured.

[0074] In this process, the computer equipment determines a fitting function for the area to be measured based on the established target fitting parameters. This fitting function is used to estimate the precipitable atmospheric water at various locations within the area. The location information of the location to be measured is used to determine the precipitable atmospheric water at that location within the fitting function.

[0075] The aforementioned method for estimating atmospheric precipitable water involves acquiring observational data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water values ​​from multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured in the area to be measured. Based on the observational data from multiple GNSS stations, the second atmospheric precipitable water value and precipitation uncertainty of the corresponding stations are calculated. Based on the first atmospheric precipitable water value, sounding atmospheric precipitable water value, second atmospheric precipitable water value, precipitation uncertainty, and fitting parameters, an objective function is determined. The fitting parameters corresponding to the convergence of the objective function's value are used as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water value at the location to be measured is determined. This method, utilizing observational data from GNSS stations, first atmospheric precipitable water values ​​from multiple ECMWF grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured, can quickly determine the objective function and target fitting parameters, thus improving the efficiency of determining the atmospheric precipitable water value estimation results at the location to be measured.

[0076] In one embodiment, such as Figure 3 As shown, based on observation data from multiple Global Navigation Satellite System (GNSS) stations, the second atmospheric precipitable water content for each station was calculated, including:

[0077] S302 obtains the atmospheric pressure, latitude, and elevation of each of the multiple Global Navigation Satellite System (GNSS) stations.

[0078] Here, station atmospheric pressure, station latitude, and station elevation refer to the atmospheric pressure, latitude, and elevation of the Global Navigation Satellite System (GNSS) station location, respectively. For example, station elevation can be obtained from digital elevation model (DEM) data. The computer equipment acquires the station atmospheric pressure, station latitude, and station elevation for each of the multiple GNSS stations.

[0079] S304. Based on the observation data of the current station, determine the total zenith tropospheric delay of the current station; based on the station's atmospheric pressure, latitude, and elevation, obtain the zenith dry delay component of the current station through the tropospheric delay correction model.

[0080] In the GNSS field, tropospheric delay is one of the sources of positioning error. Tropospheric delay in global navigation and positioning typically refers to the signal delay caused by electromagnetic waves passing through the unionized neutral atmosphere below 50 km altitude. Computer equipment uses high-precision GNSS data processing software to calculate the total zenith tropospheric delay from the observed data.

[0081] Existing tropospheric delay correction models include the Hopfield model, the Saastamoinen model, the UNB series models, and the EGNOS (European Geostationary Navigation Overlay Service) model. Computer equipment uses these tropospheric delay correction models to incorporate the current station's atmospheric pressure, latitude, and elevation into the zenith dry delay component calculation method, obtaining the zenith dry delay component (ZHD) for the current station. For example, the calculation method for the ZHD is as follows: Among them, P s This represents the atmospheric pressure at the GNSS station, expressed in hPa. H represents the latitude of the GNSS station in degrees, and H represents the elevation of the GNSS station in meters.

[0082] S306. Determine the wet zenith delay component of the current station based on the total zenith tropospheric delay and the dry zenith delay component of the current station.

[0083] The total zenith tropospheric delay includes a zenith dry delay component and a zenith wet delay component. The computer equipment subtracts the zenith dry delay component from the total zenith tropospheric delay of the current site to obtain the zenith wet delay component of the current site.

[0084] S308, based on a preset conversion coefficient, converts the zenith wet delay component of the current station to obtain the second atmospheric precipitable water of the current station.

[0085] The preset conversion factor is calculated based on historical experimental data. The computer equipment multiplies the zenith wet delay component of the current station by the preset conversion factor, and the result is used as the second atmospheric precipitable water content for the current station. The second atmospheric precipitable water content for each of the multiple Global Navigation Satellite System (GNSS) stations can be obtained by calculating using the above method.

[0086] In this embodiment, for each of multiple Global Navigation Satellite System (GNSS) stations, the atmospheric pressure, latitude, and elevation of the current station are obtained. Using a tropospheric delay correction model, the zenith dry delay component of the current station is obtained. Based on the observation data of the current station, the total zenith tropospheric delay of the current station is determined. Based on the total zenith tropospheric delay and the zenith dry delay component of the current station, the zenith wet delay component of the current station is determined. Then, based on a preset conversion coefficient, the second precipitable atmospheric water content of the current station is obtained. This method, which determines the accurate second precipitable atmospheric water content of each station using the tropospheric delay correction model based on the atmospheric pressure, latitude, and elevation of each station, is beneficial for improving the efficiency of obtaining atmospheric precipitable water content estimation results.

[0087] In one embodiment, such as Figure 4 As shown, based on the first atmospheric precipitable water content, sounding atmospheric precipitable water content, second atmospheric precipitable water content, precipitation uncertainty, and fitting parameters, the objective function is determined, including:

[0088] S402, based on the fitting parameters, determines the first difference between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitted data at the corresponding grid locations.

[0089] Here, the fitted data refers to the fitting result obtained by substituting the location information into the objective function. Since the fitting parameters in the objective function are unknown, the fitting result is a function of the fitting parameters. The fitted data for multiple grid locations of the European Centre for Medium-Range Weather Forecasts (ECMWF) in the area under test refers to the fitting result obtained by substituting the location information of the corresponding grid location into the objective function. The computer equipment calculates the difference between the first atmospheric precipitable water at each grid location and the fitted data for the corresponding grid location to obtain the first difference value for each grid location.

[0090] S404, based on fitting parameters, determines the second difference between the second atmospheric precipitable water at multiple Global Navigation Satellite System (GNSS) stations and the fitting data for the corresponding stations.

[0091] The fitted data from multiple Global Navigation Satellite System (GNSS) stations refers to the fitting results obtained by substituting the location information of the corresponding stations into the objective function. The computer equipment then calculates the difference between the second atmospheric precipitable water value corresponding to each station and the fitted data for that station, obtaining the second difference value for each station's location.

[0092] S406 interpolates the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations to obtain the interpolated atmospheric precipitable water; and determines the third difference between the interpolated atmospheric precipitable water and the sounding atmospheric precipitable water.

[0093] The computer equipment interpolates the first atmospheric precipitable water values ​​from multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations to the radiosonde station locations, obtaining the interpolated atmospheric precipitable water values. Optionally, a bilinear interpolation algorithm can be used. The computer equipment then subtracts the interpolated atmospheric precipitable water values ​​from the radiosonde atmospheric precipitable water values ​​to obtain a third difference value.

[0094] S408. Based on the first difference, the second difference, the third difference, and the uncertainty of precipitation, the objective function is determined.

[0095] The computer equipment determines the objective function based on the first difference, the second difference, the third difference, and the uncertainty of precipitation. Since the first difference and the second difference are functions of the fitting parameters, the objective function is a function of the fitting parameters.

[0096] In this embodiment, by fitting parameters, the first difference between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitted data at the corresponding grid locations, the second difference between the second atmospheric precipitable water at multiple Global Navigation Satellite System (GNSS) stations and the fitted data at the corresponding stations, and the third difference between the interpolated atmospheric precipitable water and the radiosonde atmospheric precipitable water are determined. This determines the objective function. Since the first and second differences are functions of the fitting parameters, the objective function is a function of the fitting parameters. The determination of the objective function is based on the first atmospheric precipitable water, the second atmospheric precipitable water, the radiosonde atmospheric precipitable water, and the precipitation uncertainty, ensuring the accuracy of the atmospheric precipitable water estimated by the objective function for the measured area. Furthermore, the method for determining the objective function is simple, which is beneficial for improving the acquisition of atmospheric precipitable water estimation results for the measured area.

[0097] In one embodiment, such as Figure 5 As shown, based on the first difference, the second difference, the third difference, and the uncertainty of precipitation, the objective function is determined, including:

[0098] S502, determine the difference matrix based on the first difference and the second difference.

[0099] The computer equipment adds the first difference corresponding to the grid locations of each European Centre for Medium-Range Weather Forecasts (ECMWF) as an element to the difference matrix, and adds the second difference corresponding to the locations of each Global Navigation Satellite System (GNSS) station as an element to the difference matrix, thereby determining the difference matrix. For example, the difference matrix V is shown below:

[0100]

[0101] Where k represents the number of European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations within the area to be measured, and n represents the number of Global Navigation Satellite System (GNSS) stations within the area to be measured. This represents the first atmospheric precipitable water content at the corresponding grid location. This represents the second atmospheric precipitable water content at the corresponding station location. This represents the fitted data corresponding to the grid position. This represents the fitted data corresponding to the station location. This represents the first difference corresponding to each grid position. V represents the second difference corresponding to the location of each station. 1～k+n This represents the elements of the difference matrix V.

[0102] S504. Determine the variance matrix based on the third difference and the uncertainty of precipitation.

[0103] The computer device adds the square of the third difference and the square of the precipitation uncertainty to the variance matrix as elements of the variance matrix, thereby determining the variance matrix. For example, the variance matrix Q is shown below:

[0104]

[0105] in, PWV represents the interpolated atmospheric precipitable water. TK This indicates the amount of precipitable water in the atmosphere obtained through sounding. This represents the third difference. Q represents the uncertainty of precipitation at each station. 1～k+n This represents the elements of the variance matrix Q.

[0106] S506. Determine the objective function based on the difference matrix and the variance matrix.

[0107] The computer device inverts Q to obtain the weight matrix P. The difference matrix V is then transposed to obtain V0. T The objective function is expressed as V T PV.

[0108] In this embodiment, a difference matrix is ​​determined using the first and second differences, and a variance matrix is ​​determined based on the third difference and the precipitation uncertainty, thereby determining the objective function. The objective function is based on the first atmospheric precipitable water content, the second precipitable water content, the radiosonde atmospheric precipitable water content, and the precipitation uncertainty, ensuring the accuracy of the atmospheric precipitable water content estimated for the measured area. Furthermore, the method for determining the objective function is simple, which is beneficial for improving the acquisition of atmospheric precipitable water content estimation results for the measured area.

[0109] In one embodiment, determining the first difference between the first atmospheric precipitable water at multiple European Medium-Range Weather Forecasting (ECMWF) grid locations and the fitted data for the corresponding grid locations, based on fitting parameters, includes: acquiring grid location information for multiple ECMWF grid locations, including grid longitude, grid latitude, and grid elevation; determining a fitting model based on the fitting parameters; determining the fitted data for the corresponding grid locations based on the location information and fitting model of the multiple ECMWF grid locations; and determining the first difference between the first atmospheric precipitable water at multiple ECMWF grid locations and the fitted data for the corresponding grid locations; wherein the fitting model is as follows: PWV fit = a0 + a1x + a2y + a3h, where a0, a1, a2, and a3 represent the fitting parameters, x represents the grid latitude, y represents the grid longitude, and h represents the grid elevation. PWV fit This represents the first atmospheric precipitable water content at the corresponding grid location.

[0110] The computer equipment acquires grid location information of multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations within the area to be measured. The grid location information includes grid longitude, grid latitude, and grid elevation.

[0111] A fitting model refers to an objective function whose parameters are the fitting parameters. A computer device substitutes the fitting parameters into the objective function to obtain the fitting model. In some embodiments, the fitting model is a three-parameter linear model, which can be represented as: PWV fit = a0 + a1x + a2y + a3h, where a0, a1, a2, and a3 represent the fitting parameters, x represents the grid latitude, y represents the grid longitude, h represents the grid elevation, and PWV fit This represents the first atmospheric precipitable water content at the corresponding grid location.

[0112] The computer equipment inputs the location information of multiple grid locations of the European Centre for Medium-Range Weather Forecasts into the fitting model to obtain the fitting data corresponding to each grid location.

[0113] The computer equipment calculates the difference between the first atmospheric precipitation at multiple grid locations of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the fitted data at the corresponding grid locations to obtain the first difference value for each grid location.

[0114] Similarly, using the fitting model determined by the above method, the second difference corresponding to multiple Global Navigation Satellite System (GNSS) stations can be obtained. Specifically, the station location information of multiple GNSS stations is obtained, including station longitude, station latitude, and station elevation; based on the fitting parameters, a fitting model is determined; according to the location information of multiple GNSS stations and the fitting model, the fitting data for the corresponding station locations is determined; and the second difference between the second atmospheric precipitable water of multiple GNSS stations and the fitting data for the corresponding station locations is determined.

[0115] In this embodiment, grid location information from multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations is acquired. Based on fitting parameters, a fitting model is determined. Then, based on the location information of multiple grid locations and the fitting model, fitting data for the corresponding grid locations is determined, thereby determining the first difference between the first atmospheric precipitable water amount and the fitted data. The fitting data is determined based on the location information of each grid location and the fitting model, which helps improve the efficiency of obtaining atmospheric precipitable water amounts within the measured area.

[0116] In one embodiment, determining the atmospheric precipitable water at the location to be measured based on the target fitting parameters and the location information of the location to be measured includes: determining the target fitting model according to the target fitting parameters and the fitting model; and inputting the location information of the location to be measured into the target fitting model to obtain the atmospheric precipitable water at the location to be measured.

[0117] In this process, the computer equipment inputs the target fitting parameters into the fitting model to obtain the target fitting model, which is used to estimate the atmospheric precipitable water content within the measurement area. Alternatively, the computer equipment inputs the location information of the measurement location into the target fitting model to obtain the atmospheric precipitable water content at that location.

[0118] In this embodiment, a target fitting model is determined by using target fitting parameters and a fitting model. The location information of the location to be measured is input into the target fitting model to obtain the atmospheric precipitable water at the location to be measured. This method of estimating atmospheric precipitable water using a target fitting model has a simple model construction method and improves the efficiency of obtaining atmospheric precipitable water estimation results.

[0119] To illustrate in detail the estimation method and effectiveness of atmospheric precipitable water in this scheme, a detailed implementation example is provided below:

[0120] Computer equipment acquires observational data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, radiosonde atmospheric precipitable water content, and location information of the location to be measured in the area to be measured. The location information includes the longitude, latitude, and elevation of the location. In some embodiments, the GNSS system used is a Continuously Operating Reference Stations (CORS) system. Figure 6 The diagram shows the continuously operating reference station sites, European Centre for Medium-Range Weather Forecasts grid points, and radiosonde stations in the area to be measured.

[0121] The computer equipment calculates the second atmospheric precipitable water and the precipitation uncertainty for each corresponding station based on observation data from multiple Global Navigation Satellite System (GNSS) stations. Specifically, for each of the GNSS stations, the station's atmospheric pressure, latitude, and elevation are obtained. Based on the observation data of the current station, the total zenith tropospheric delay is determined. Using the station's atmospheric pressure, latitude, and elevation, the zenith dry delay component is obtained through a tropospheric delay correction model. Based on the total zenith tropospheric delay and the dry delay component, the wet delay component is determined. The wet delay component is then converted using a preset conversion factor to obtain the second atmospheric precipitable water for the current station. Figure 7 The diagram shows the overall process flow of the method for estimating atmospheric precipitable water.

[0122] The computer equipment determines the objective function based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, precipitation uncertainty, and fitting parameters. Specifically, based on the fitting parameters, a first difference is determined between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitted data at the corresponding grid locations; based on the fitting parameters, a second difference is determined between the second atmospheric precipitable water at multiple Global Navigation Satellite System (GNSS) stations and the fitted data at the corresponding stations; the first atmospheric precipitable water at multiple ECMWF grid locations is interpolated to obtain the interpolated atmospheric precipitable water, and a third difference is determined between the interpolated atmospheric precipitable water and the sounding atmospheric precipitable water. Based on the first and second differences, a difference matrix is ​​determined; based on the third difference and precipitation uncertainty, a variance matrix is ​​determined; and based on the difference matrix and variance matrix, the objective function is determined. For example, the difference matrix V is shown below:

[0123]

[0124] Where k represents the number of European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations within the area to be measured, and n represents the number of Global Navigation Satellite System (GNSS) stations within the area to be measured. This represents the first atmospheric precipitable water content at the corresponding grid location. This represents the second atmospheric precipitable water content at the corresponding station location. This represents the fitted data corresponding to the grid position. This represents the fitted data corresponding to the station location. This represents the first difference corresponding to each grid position. V represents the second difference corresponding to the location of each station. 1～k+n This represents the elements of the difference matrix V.

[0125] The variance matrix Q is shown below:

[0126]

[0127] in, PWV represents the interpolated atmospheric precipitable water. TK This indicates the amount of precipitable water in the atmosphere obtained through sounding. This represents the third difference. Q represents the uncertainty of precipitation at each station. 1～k+n This represents the elements of the variance matrix Q.

[0128] The computer device inverts Q to obtain the weight matrix P. It then transposes the difference matrix V to obtain V0. T The objective function is expressed as V T PV.

[0129] The computer device uses the fitting parameters corresponding to the convergence of the objective function's value as the target fitting parameters. For example, the convergence of the objective function can be represented as V... T PV = min. The least squares fitting method can be used to determine the target fitting parameters.

[0130] The computer equipment, based on fitting parameters, determines the first difference between the first atmospheric precipitable water at multiple European Medium-Range Weather Forecasting (ECMWF) grid locations and the corresponding fitted data. Specifically, the computer equipment acquires grid location information for multiple ECMWF grid locations, including grid longitude, grid latitude, and grid elevation. Based on the fitting parameters, a fitting model is determined. According to the location information and fitting model of the multiple ECMWF grid locations, the fitted data for the corresponding grid locations are determined, and the first difference between the first atmospheric precipitable water at multiple ECMWF grid locations and the corresponding fitted data is determined. The fitting model is as follows: PWV fit = a0 + a1x + a2y + a3h, where a0, a1, a2, and a3 represent the fitting parameters, x represents the grid latitude, y represents the grid longitude, and h represents the grid elevation. PWV fitThis represents the first atmospheric precipitable water content at the corresponding grid location.

[0131] Furthermore, by validating the fitting model in the test area, the root mean square error of the atmospheric precipitable water at the test location obtained using the fitting model decreased from 5.91 mm to 3.91 mm compared to the first atmospheric precipitable water obtained using the Global Navigation Satellite System (GNSS) station data. This indicates that the accuracy of the atmospheric precipitable water obtained by the fitting model is effectively improved. Two three-parameter quadratic models were used as the fitting model, and compared with a three-parameter linear model. The resulting fitting effect is illustrated in the diagram below. Figure 8 As shown. The objective function of the three-parameter linear model is: PWV fit =a0+a1x+a2y+a3h, the objective function of the three-parameter quadratic model 1 is: PWV fit = a0 + a1x + a2y + a3h + a4x 2 +a5y 2 +a6h 2 The objective function of the three-parameter quadratic model 2 is: PWV fit = a0 + a1x + a2y + a3h + a4x 2 +a5y 2 +a6h 2 +a7xy+a8xh+a9yh. The three sets of fitting curves in the figure, from top to bottom, represent the fitting curves of the three-parameter linear model, the three-parameter quadratic model 1, and the three-parameter quadratic model 2, respectively. As can be seen from the schematic diagram of the fitting curves, the fitting effect of using the three-parameter linear model is better than that of the two three-parameter quadratic models.

[0132] The computer equipment determines the target fitting model based on the target fitting parameters and the fitting model, inputs the location information of the location to be measured into the target fitting model, and obtains the atmospheric precipitable water at the location to be measured.

[0133] The aforementioned method for estimating atmospheric precipitable water involves acquiring observational data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water values ​​from multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured in the area to be measured. Based on the observational data from multiple GNSS stations, the second atmospheric precipitable water value and precipitation uncertainty for each station are calculated. Based on the first atmospheric precipitable water value, sounding atmospheric precipitable water value, second atmospheric precipitable water value, precipitation uncertainty, and fitting parameters, an objective function is determined. The fitting parameters corresponding to the convergence of the objective function's value are used as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water value at the location to be measured is determined. This method, utilizing observational data from GNSS stations, first atmospheric precipitable water values ​​from multiple ECMWF grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured, can quickly determine the objective function and target fitting parameters, thus improving the efficiency of determining the atmospheric precipitable water value estimation results at the location to be measured.

[0134] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0135] Based on the same inventive concept, this application also provides an atmospheric precipitable water estimation device for implementing the above-mentioned method for estimating atmospheric precipitable water. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more embodiments of the atmospheric precipitable water estimation device provided below can be found in the limitations of the atmospheric precipitable water estimation method described above, and will not be repeated here.

[0136] In one embodiment, such as Figure 9 As shown, a device 100 for estimating atmospheric precipitable water is provided, comprising: a data acquisition module 120, a calculation module 140, a target fitting parameter determination module 160, and a precipitable water determination module 180, wherein:

[0137] The data acquisition module 120 is used to acquire observation data from multiple global navigation satellite system stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts grid locations, radiosonde atmospheric precipitable water content, and location information of the location to be measured in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured.

[0138] The calculation module 140 is used to calculate the second atmospheric precipitable water and the precipitation uncertainty of the corresponding station based on the observation data of multiple global navigation satellite system stations.

[0139] The target fitting parameter determination module 160 is used to determine the objective function based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, and to use the fitting parameters corresponding to the convergence of the objective function value as the target fitting parameters.

[0140] The precipitable water determination module 180 is used to determine the atmospheric precipitable water at the location to be measured based on the target fitting parameters and the location information of the location to be measured.

[0141] The aforementioned device for estimating atmospheric precipitable water acquires observation data from multiple Global Navigation Satellite System (GNSS) stations, first atmospheric precipitable water values ​​from multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured in the area to be measured. Based on the observation data from multiple GNSS stations, it calculates the second atmospheric precipitable water value and the precipitation uncertainty for the corresponding station. Based on the first atmospheric precipitable water value, sounding atmospheric precipitable water value, second atmospheric precipitable water value, precipitation uncertainty, and fitting parameters, it determines an objective function. The fitting parameters corresponding to the convergence of the objective function's value are used as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water value at the location to be measured is determined. This method, which utilizes observation data from GNSS stations, first atmospheric precipitable water values ​​from multiple ECMWF grid locations, sounding atmospheric precipitable water values, and location information of the location to be measured, can quickly determine the objective function and target fitting parameters, thus improving the efficiency of determining the atmospheric precipitable water value estimation results at the location to be measured.

[0142] In one embodiment, in calculating the second precipitable atmospheric water content of a corresponding station based on observation data from multiple Global Navigation Satellite System (GNSS) stations, the calculation module 140 is further configured to: for each of the multiple GNSS stations, obtain the station's atmospheric pressure, latitude, and elevation; determine the total zenith tropospheric delay of the current station based on the observation data of the current station; obtain the zenith dry delay component of the current station using a tropospheric delay correction model based on the station's atmospheric pressure, latitude, and elevation; determine the zenith wet delay component of the current station based on the total zenith tropospheric delay and the zenith dry delay component; and convert the zenith wet delay component of the current station based on a preset conversion coefficient to obtain the second precipitable atmospheric water content of the current station.

[0143] In one embodiment, regarding the determination of the objective function based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, precipitation uncertainty, and fitting parameters, the objective fitting parameter determination module 160 is further configured to: determine a first difference between the first atmospheric precipitable water at multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitted data at the corresponding grid locations, based on the fitting parameters; determine a second difference between the second atmospheric precipitable water at multiple Global Navigation Satellite System (GNSS) stations and the fitted data at the corresponding stations, based on the fitting parameters; interpolate the first atmospheric precipitable water at multiple ECMWF grid locations to obtain the interpolated atmospheric precipitable water; determine a third difference between the interpolated atmospheric precipitable water and the sounding atmospheric precipitable water; and determine the objective function based on the first difference, the second difference, the third difference, and the precipitation uncertainty.

[0144] In one embodiment, in determining the objective function based on the first difference, the second difference, the third difference, and the precipitation uncertainty, the objective fitting parameter determination module 160 is further configured to: determine a difference matrix based on the first difference and the second difference; determine a variance matrix based on the third difference and the precipitation uncertainty; and determine the objective function based on the difference matrix and the variance matrix.

[0145] In one embodiment, in determining the first difference between the first atmospheric precipitable water at multiple European Medium-Range Weather Forecasting Center (ECMWF) grid locations and the fitted data for the corresponding grid locations based on fitting parameters, the target fitting parameter determination module 160 is further configured to: acquire grid location information of multiple ECMWF grid locations, including grid longitude, grid latitude, and grid elevation; determine a fitting model based on the fitting parameters; determine the fitted data for the corresponding grid locations based on the location information and fitting model of the multiple ECMWF grid locations; and determine the first difference between the first atmospheric precipitable water at multiple ECMWF grid locations and the fitted data for the corresponding grid locations; wherein the fitting model is as follows: PWV fit = a0 + a1x + a2y + a3h, where a0, a1, a2, and a3 represent the fitting parameters, x represents the grid latitude, y represents the grid longitude, and h represents the grid elevation. PWV fit This represents the first atmospheric precipitable water content at the corresponding grid location.

[0146] In one embodiment, in determining the atmospheric precipitable water at a location based on the target fitting parameters and the location information of the location to be measured, the precipitable water determination module 180 is further configured to: determine the target fitting model according to the target fitting parameters and the fitting model; input the location information of the location to be measured into the target fitting model to obtain the atmospheric precipitable water at the location to be measured.

[0147] Each module in the aforementioned atmospheric precipitable water estimation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0148] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for estimating atmospheric precipitable water.

[0149] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0150] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0151] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0152] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0153] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0154] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0155] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0156] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for estimating atmospheric precipitable water, characterized in that, The method includes: In the area to be measured, observation data from multiple Global Navigation Satellite System stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts grid locations, radiosonde atmospheric precipitable water content, and location information of the location to be measured are acquired. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured. Based on the observation data from the multiple global navigation satellite system stations, the second atmospheric precipitable water content and the precipitation uncertainty of the corresponding stations are calculated. Based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, an objective function is determined, and the fitting parameters corresponding to the convergence of the function value of the objective function are taken as the target fitting parameters. Based on the target fitting parameters and the location information of the location to be measured, the atmospheric precipitable water at the location to be measured is determined; The objective function is determined based on the first atmospheric precipitable water content, the radiosonde atmospheric precipitable water content, the second atmospheric precipitable water content, the precipitation uncertainty, and fitting parameters, including: Based on the fitting parameters, the first difference between the first atmospheric precipitable water at the grid location of the multiple European Centre for Medium-Range Weather Forecasts (ECMWF) and the fitting data at the corresponding grid location is determined. Based on the fitting parameters, a second difference between the second atmospheric precipitable water at the multiple global navigation satellite system stations and the fitting data of the corresponding stations is determined; Interpolate the first atmospheric precipitable water at the grid locations of the multiple European Centre for Medium-Range Weather Forecasts (ECMWF) to obtain the interpolated atmospheric precipitable water; determine the third difference between the interpolated atmospheric precipitable water and the sounding atmospheric precipitable water. The objective function is determined based on the first difference, the second difference, the third difference, and the uncertainty of precipitation.

2. The method according to claim 1, characterized in that, The calculation of the second atmospheric precipitable water at the corresponding station based on the observation data from the multiple global navigation satellite system stations includes: For each of the multiple global navigation satellite system sites, obtain the current site's atmospheric pressure, latitude, and elevation; Based on the observation data of the current station, determine the total zenith tropospheric delay of the current station; Based on the atmospheric pressure, latitude, and elevation of the current station, the zenith dry delay component of the current station is obtained using a tropospheric delay correction model. The zenith wet delay component of the current station is determined based on the total zenith tropospheric delay of the current station and the zenith dry delay component of the current station. The zenith wet delay component of the current station is converted based on a preset conversion coefficient to obtain the second atmospheric precipitable water content of the current station.

3. The method according to claim 1, characterized in that, The step of determining the objective function based on the first difference, the second difference, the third difference, and the precipitation uncertainty includes: Determine the difference matrix based on the first difference and the second difference; The variance matrix is ​​determined based on the third difference and the precipitation uncertainty. The objective function is determined based on the difference matrix and variance matrix.

4. The method according to claim 1, characterized in that, The determination of the first difference between the first atmospheric precipitable water at the grid location of the multiple European Centre for Medium-Range Weather Forecasts (ECMWF) and the fitted data at the corresponding grid location, based on the fitting parameters, includes: Obtain grid location information for the multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations, including grid longitude, grid latitude, and grid elevation; Based on the fitting parameters, determine the fitting model; Based on the location information of the multiple European Centre for Medium-Range Weather Forecasts (ECMWF) grid locations and the fitting model, the fitting data for the corresponding grid locations is determined; Determine the first difference between the first atmospheric precipitable water at the first grid location of the plurality of European Centre for Medium-Range Weather Forecasts (ECMWF) and the fitted data at the corresponding grid location; wherein the fitted model is as follows: The fitting parameters are: x represents the grid latitude, y represents the grid longitude, h represents the grid elevation, and PWV. fit This represents the first atmospheric precipitable water content at the corresponding grid location.

5. The method according to claim 4, characterized in that, The step of determining the atmospheric precipitable water at the location to be measured based on the target fitting parameters and the location information of the location to be measured includes: Based on the target fitting parameters and the fitting model, determine the target fitting model; The location information of the location to be measured is input into the target fitting model to obtain the atmospheric precipitation at the location to be measured.

6. A device for estimating atmospheric precipitable water, characterized in that, The device includes: The data acquisition module is used to acquire observation data from multiple Global Navigation Satellite System stations, first atmospheric precipitable water content at multiple European Centre for Medium-Range Weather Forecasts grid locations, radiosonde atmospheric precipitable water content, and location information of the location to be measured in the area to be measured. The location information of the location to be measured includes the longitude, latitude, and elevation of the location to be measured. The calculation module is used to calculate the second atmospheric precipitable water and the precipitation uncertainty of the corresponding station based on the observation data of the multiple global navigation satellite system stations. The target fitting parameter determination module is used to determine the target function based on the first atmospheric precipitable water, the sounding atmospheric precipitable water, the second atmospheric precipitable water, the precipitation uncertainty, and the fitting parameters, and to take the fitting parameters corresponding to the convergence of the function value of the target function as the target fitting parameters. The precipitable water determination module is used to determine the atmospheric precipitable water at the location to be measured based on the target fitting parameters and the location information of the location to be measured. The target fitting parameter determination module is further configured to: determine a first difference between the first atmospheric precipitable amount at the grid locations of the plurality of European Centre for Medium-Range Weather Forecasts (ECMWF) and the fitted data at the corresponding grid locations, based on the fitting parameters; determine a second difference between the second atmospheric precipitable amount at the grid locations of the plurality of Global Navigation Satellite System (GNSS) stations and the fitted data at the corresponding stations, based on the fitting parameters; interpolate the first atmospheric precipitable amount at the grid locations of the plurality of ECMWF to obtain the interpolated atmospheric precipitable amount; determine a third difference between the interpolated atmospheric precipitable amount and the radiosonde atmospheric precipitable amount; and determine an objective function based on the first difference, the second difference, the third difference, and the precipitation uncertainty.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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