Method and device for determining atmospheric precipitable water at target height, electronic equipment and storage medium

Abstract

The invention discloses a method and device for determining atmospheric precipitable water at a target height, electronic equipment and a storage medium, and belongs to the technical field of meteorology, and the method comprises the steps: obtaining the target height, the measurement time, the longitude, the latitude, the surface height and the atmospheric precipitable water at the surface height of a to-be-measured site; inputting the measurement time, the longitude and the latitude into a preset height correction parameter prediction model, so that the height correction parameter prediction model generates height correction parameters of the place to be measured according to the measurement time, the longitude and the latitude; according to the height correction parameters of the to-be-measured site, the target height, the surface height and the atmospheric precipitable water amount of the surface height, generating the atmospheric precipitable water amount of the target height of the to-be-measured site based on a preset water vapor layering model; by implementing the method and the device, the problem that the atmospheric precipitable water at the target height cannot be determined in the prior art can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of meteorology, and in particular to a method and device for determining atmospheric precipitable water at a target height, an electronic device and a storage medium. BACKGROUND

[0002] Atmospheric precipitable water (PWV) is a key physical quantity representing the water vapor content in the atmosphere, which has important indicative significance for the prediction and early warning of disastrous weather, especially sudden rainstorms. However, the development of different weather processes is closely related to the vertical distribution of water vapor. For example, the development of convective weather often depends on the water vapor transport and accumulation at a specific height layer (such as the boundary layer top or the free convection height). Therefore, only obtaining the total water vapor from the ground to the top of the atmosphere cannot meet the current needs of refined meteorological services. Accurate determination of atmospheric precipitable water at any target height is of great value to improve the accuracy of short-term weather prediction and deepen the understanding of the evolution mechanism of weather systems.

[0003] Currently, although some existing ground-based observation techniques can continuously measure the total water vapor of the entire atmosphere at a high frequency, they essentially provide a two-dimensional planar integral value and cannot directly give the atmospheric precipitable water at a target height. SUMMARY

[0004] The embodiments of the present application provide a method and device for determining atmospheric precipitable water at a target height, an electronic device and a storage medium, which can solve the problem that the atmospheric precipitable water at a target height cannot be determined in the prior art.

[0005] An embodiment of the present application provides a method for determining atmospheric precipitable water at a target height, comprising: obtaining a target height, a measurement time, a longitude, a latitude, a ground surface height and atmospheric precipitable water at the ground surface height of a to-be-measured location; inputting the measurement time, the longitude and the latitude into a preset height correction parameter prediction model, so that the height correction parameter prediction model generates a height correction parameter of the to-be-measured location according to the measurement time, the longitude and the latitude; wherein the height correction parameter prediction model is trained by a plurality of training samples; each training sample includes historical measurement time, historical longitude, historical latitude and corresponding labels of a typical observation point; the labels are the height correction parameters of the typical observation point; generating atmospheric precipitable water at the target height of the to-be-measured location based on a preset water vapor layering model according to the height correction parameter of the to-be-measured location, the target height, the ground surface height and the atmospheric precipitable water at the ground surface height; wherein the height correction parameter of the typical observation point is obtained by the following way: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

[0006] Furthermore, the height correction parameter prediction model is trained in the following manner: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

[0007] Furthermore, based on the historical atmospheric precipitable water, historical temperature profile, and historical pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate a corrected target historical specific humidity profile, including: Based on historical temperature profiles and historical pressure profiles, historical saturated specific humidity profiles for typical observation points are calculated and generated; wherein, the historical saturated specific humidity profile is composed of the saturated specific humidity value of each altitude layer and the height of each altitude layer. Repeat the specific humidity correction operation until each current first difference is less than the preset convergence threshold, and the specific humidity value of each height layer in the current corrected specific humidity profile is less than the saturated specific humidity value of each height layer in the historical saturated specific humidity profile, and generate the corrected target historical specific humidity profile. The specific humidity correction operation includes: The scaling factor is calculated based on the historical atmospheric precipitable water at the surface height of typical observation points and the current remotely sensed total water vapor. The initial remotely sensed total water vapor is calculated based on the historical specific humidity profile and the historical pressure profile. Based on the current scaling factor, the current specific humidity profile to be corrected is corrected to generate the current corrected specific humidity profile; wherein, the initial specific humidity profile to be corrected is the historical specific humidity profile. Based on the current corrected specific humidity profile, calculate and generate the current corrected atmospheric precipitable water at each altitude layer of typical observation points; For each altitude level, calculate the difference between the current corrected atmospheric precipitable water and the previous corrected atmospheric precipitable water, and generate the current first difference for each altitude level. Determine whether each current first difference is less than the preset convergence threshold, and whether the specific humidity value of each height layer in the current corrected specific humidity profile is less than the specific humidity value of each height layer in the historical saturated specific humidity profile; if so, then use the current corrected specific humidity profile as the corrected target historical specific humidity profile. If not, update the current remotely sensed total water vapor based on the current corrected specific humidity profile and historical pressure profile; update the current corrected specific humidity profile to the current specific humidity profile to be corrected.

[0008] Furthermore, the saturated specific humidity value for any altitude layer is calculated using the following formula: In the formula, For the first saturated specific humidity value of each altitude layer; The first in the historical temperature profile Temperature at each altitude level; The first in the historical pressure profile The air pressure at each altitude.

[0009] Furthermore, the scaling factor is calculated using the following formula: In the formula, This is the scaling factor; Historical atmospheric precipitation at the surface height of typical observation points; This is for remote sensing inversion of total water vapor content.

[0010] Furthermore, the water vapor stratification model is specifically as follows: In the formula, The atmospheric precipitable water content at the target altitude of the location to be measured; The atmospheric precipitable water content is at the surface height of the location to be measured. For height correction parameters; The target altitude of the location to be measured; The elevation is the ground level at the location to be measured.

[0011] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0012] One embodiment of the present invention provides a device for determining atmospheric precipitable water at a target altitude, comprising: a data acquisition module, an altitude correction parameter determination module, and an atmospheric precipitable water determination module; The data acquisition module is used to acquire the target altitude, measurement time, longitude, latitude, surface altitude, and atmospheric precipitable water at the surface altitude of the location to be measured. The altitude correction parameter determination module is used to input the measurement time, longitude, and latitude into a preset altitude correction parameter prediction model, so that the altitude correction parameter prediction model generates altitude correction parameters for the location to be measured based on the measurement time, longitude, and latitude; wherein, the altitude correction parameter prediction model is trained by several training samples; each training sample includes the historical measurement time, historical longitude, historical latitude, and corresponding label of a typical observation point; the label is the altitude correction parameter of the typical observation point; The atmospheric precipitable water determination module is used to generate the atmospheric precipitable water at the target altitude of the test location based on a preset water vapor stratification model, according to the altitude correction parameters of the test location, the target altitude, the surface altitude, and the atmospheric precipitable water at the surface altitude. The height correction parameters for typical observation points are obtained through the following methods: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

[0013] Furthermore, the device for determining the atmospheric precipitable water at the target altitude trains the altitude correction parameter prediction model in the following manner: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

[0014] Based on the above method embodiments, the present invention provides corresponding electronic device embodiments.

[0015] An embodiment of the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for determining the atmospheric precipitable water at a target altitude as described in any of the above-described method embodiments.

[0016] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments.

[0017] One embodiment of the present invention provides a storage medium storing a computer program thereon, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the method for determining the atmospheric precipitable water at the target altitude as described in any of the above-described method embodiments.

[0018] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method, apparatus, electronic device, and storage medium for determining atmospheric precipitable water at a target altitude. In the model training phase, the method uses historical surface atmospheric precipitable water to correct historical humidity profiles and fits them to generate altitude correction parameters that characterize the vertical distribution of water vapor. These parameters are then used as labels to train a prediction model. In the application phase, the measurement time and latitude / longitude are input into the altitude correction parameter prediction model to obtain the altitude correction parameters. Combined with surface atmospheric precipitable water, the atmospheric precipitable water at the target altitude can be quickly decomposed and calculated.

[0019] This invention utilizes a height correction parameter prediction model trained from training samples and a preset water vapor stratification model to generate the atmospheric precipitable water at a target altitude based on the obtained atmospheric precipitable water at the surface altitude of the location to be measured, the measurement time, longitude, and latitude. This method solves the technical problem of existing technologies that can only provide the total atmospheric precipitable water at the surface altitude, but cannot directly generate the atmospheric precipitable water at a specific target altitude. Attached Figure Description

[0020] Figure 1This is a flowchart illustrating a method for determining atmospheric precipitable water at a target altitude, provided by an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of a device for determining atmospheric precipitable water at a target altitude, provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figure 1 As shown, to address the problem in the prior art that the atmospheric precipitable water content at a target altitude cannot be determined, an embodiment of the present invention provides a method for determining the atmospheric precipitable water content at a target altitude, comprising at least the following steps: Step S1: Obtain the target altitude, measurement time, longitude, latitude, surface altitude, and atmospheric precipitation at the surface altitude of the location to be measured.

[0024] Specifically, in one embodiment of the present invention, it is first necessary to obtain all the initial parameters required for determining atmospheric precipitable water. These parameters include the geographical coordinates of the location to be measured, i.e., longitude and latitude; the specific target altitude for determining atmospheric precipitable water, the ground surface altitude for observation, and the measurement time for calculation. A key input data point is the total atmospheric precipitable water, representing the total amount of water vapor in the entire layer at that location, obtained by ground-based observation equipment at that ground surface altitude. The measurement time consists of the year, the number of days in the year, and the number of hours in the day. For example, a specific measurement time "August 2, 2025, 14:00" will be represented as year equal to 2025, number of days in the year equal to 214, and number of hours in the day equal to 14.

[0025] In practice, this ground-based observation equipment serves as a receiver station for the Global Navigation Satellite System (GNSS). In this scheme, GNSS not only provides the station's precise ellipsoidal altitude but also provides a high-precision atmospheric precipitation value based on the surface altitude by analyzing signal delay.

[0026] After acquiring all the above parameters, the measurement time, longitude, and latitude are used as spatiotemporal input factors and transmitted to a height correction parameter prediction model pre-trained with a large amount of historical data. Upon receiving the current spatiotemporal input factors, the prediction model immediately outputs a height correction parameter uniquely corresponding to the location and measurement time. Finally, this height correction parameter, along with the acquired real-time total precipitable water vapor, surface height, and target height, are substituted into a pre-set water vapor stratification model that characterizes the decreasing trend of water vapor with elevation exponential, to determine the precipitable water vapor at the target height at the location to be measured. This method efficiently resolves the total water vapor information from ground-based observations to a specified vertical height, enabling rapid determination of the vertical structure of water vapor.

[0027] Step S2: Input the measurement time, longitude, and latitude into a preset height correction parameter prediction model, so that the height correction parameter prediction model generates height correction parameters for the location to be measured based on the measurement time, longitude, and latitude; wherein, the height correction parameter prediction model is trained by several training samples; each training sample includes the historical measurement time, historical longitude, historical latitude, and corresponding label of a typical observation point; the label is the height correction parameter of the typical observation point.

[0028] In a preferred embodiment, the height correction parameters for a typical observation point are obtained in the following manner: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

[0029] It should be noted that the historical total atmospheric precipitable water at surface altitude was acquired via GNSS. Historical temperature, pressure, and specific humidity profiles, used to characterize the conditions at each altitude level, were acquired using the Geographic Infrared Hyperspectral Observatory (GIIRS) onboard a meteorological satellite. After acquiring these two types of data, a crucial spatiotemporal matching step must be performed: spatially, each ground-based station is mapped to its nearest satellite data grid point, and temporally, high-frequency ground-based observations are aligned with the closest satellite observation times, thus forming the final usable paired dataset.

[0030] Furthermore, because GNSS and GIIRS use different height references—GNSS provides ellipsoidal height based on a reference ellipsoid, while GIIRS provides geopotential height based on gravitational potential energy—height correction is necessary for both. The purpose of this correction is to unify the two different elevation systems into an orthographic height system based on the geoid. Specifically, for the ellipsoidal height provided by GNSS, the geoid difference value at its location can be obtained by consulting global gravity field models such as EGM 2008, and then its orthographic height can be calculated. Similarly, the geopotential heights at various height levels provided by GIIRS also need to be converted to orthographic height using appropriate physical conversion formulas, thus ensuring that all data are fitted and calculated under the same height reference.

[0031] For example, the ellipsoidal height provided by GNSS can be converted to orthographic height using the following formula: in, Elevation under the positive elevation system; Ellipsoidal height provided for GNSS; The geoid height is provided by EGM 2008.

[0032] For example, the geopotential height provided by GIRS can be converted to a positive height using the following formula: in, Elevation under the positive elevation system; The potential provided for GIRS is high.

[0033] In a preferred embodiment, the historical specific humidity profile is corrected based on the historical atmospheric precipitable water, historical temperature profile, and historical air pressure profile at the surface height of typical observation points to generate a corrected target historical specific humidity profile, including: Based on historical temperature profiles and historical pressure profiles, historical saturated specific humidity profiles for typical observation points are calculated and generated; wherein, the historical saturated specific humidity profile is composed of the saturated specific humidity value of each altitude layer and the height of each altitude layer. Repeat the specific humidity correction operation until each current first difference is less than the preset convergence threshold, and the specific humidity value of each height layer in the current corrected specific humidity profile is less than the saturated specific humidity value of each height layer in the historical saturated specific humidity profile, and generate the corrected target historical specific humidity profile. The specific humidity correction operation includes: The scaling factor is calculated based on the historical atmospheric precipitable water at the surface height of typical observation points and the current remotely sensed total water vapor. The initial remotely sensed total water vapor is calculated based on the historical specific humidity profile and the historical pressure profile. Based on the current scaling factor, the current specific humidity profile to be corrected is corrected to generate the current corrected specific humidity profile; wherein, the initial specific humidity profile to be corrected is the historical specific humidity profile. Based on the current corrected specific humidity profile, calculate and generate the current corrected atmospheric precipitable water at each altitude layer of typical observation points; For each altitude level, calculate the difference between the current corrected atmospheric precipitable water and the previous corrected atmospheric precipitable water, and generate the current first difference for each altitude level. Determine whether each current first difference is less than the preset convergence threshold, and whether the specific humidity value of each height layer in the current corrected specific humidity profile is less than the specific humidity value of each height layer in the historical saturated specific humidity profile; if so, then use the current corrected specific humidity profile as the corrected target historical specific humidity profile. If not, update the current remotely sensed total water vapor based on the current corrected specific humidity profile and historical pressure profile; update the current corrected specific humidity profile to the current specific humidity profile to be corrected.

[0034] In a preferred embodiment, the saturated specific humidity value for any altitude layer is calculated using the following formula: In the formula, For the first saturated specific humidity value of each altitude layer; The first in the historical temperature profile Temperature at each altitude level; The first in the historical pressure profile The air pressure at each altitude.

[0035] In a preferred embodiment, the scaling factor is calculated using the following formula: In the formula, This is the scaling factor; Historical atmospheric precipitation at the surface height of typical observation points; This is for remote sensing inversion of total water vapor content.

[0036] In a preferred embodiment, the height correction parameter prediction model is trained in the following manner: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

[0037] Specifically, in one embodiment of the present invention, a method for determining atmospheric precipitable water at a target altitude is provided. The core of this method lies in pre-constructing and training an altitude correction parameter prediction model, and then using this model for rapid calculation in real-time applications. The construction and training process of this model first requires preparing a high-precision historical training dataset. Specifically, it requires acquiring historical data from typical observation points, including total atmospheric precipitable water at the surface, as well as historical temperature profiles, historical humidity profiles, and historical air pressure profiles. To improve the accuracy of the original historical humidity profile, it is necessary to use the total atmospheric precipitable water at the surface as a benchmark, and combine it with the physical constraints provided by the historical temperature and air pressure profiles to iteratively correct the historical humidity profile, thereby generating a high-precision, corrected target historical specific humidity profile.

[0038] In a preferred embodiment, the correction process includes first calculating a historical saturated specific humidity profile as a physical upper limit based on historical temperature and pressure profiles. Specifically, the saturated specific humidity value for each altitude layer is calculated using a preset empirical physical formula based on the temperature and pressure of that altitude layer. Subsequently, the specific humidity correction operation is repeated using the original historical specific humidity profile as the initial specific humidity profile to be corrected. This operation includes: first, calculating an initial remote sensing inversion total water vapor based on the historical specific humidity and historical pressure profiles; then, calculating the ratio of historical atmospheric precipitable water at the surface height to the current remote sensing inversion total water vapor, and using this ratio as the current scaling factor; next, using this scaling factor to scale the current specific humidity profile to be corrected proportionally to generate a corrected specific humidity profile, and constraining the corrected specific humidity profile to ensure that the specific humidity value at each altitude layer is not greater than the saturated specific humidity value of the corresponding altitude layer in the historical saturated specific humidity profile. Subsequently, based on the current corrected specific humidity profile and historical pressure profile, the current remotely sensed total water vapor is updated, and the current corrected specific humidity profile is used as the specific humidity profile to be corrected in the next iteration. This iterative process is repeated until the difference in atmospheric precipitable water at the same altitude level calculated in two consecutive iterations is less than the preset convergence threshold. The finally converged profile is the corrected target historical specific humidity profile.

[0039] For example, the total water vapor content retrieved by remote sensing can be calculated using the following formula: In the formula, To remotely invert the total amount of water vapor; For the first Specific humidity values ​​for each altitude layer; For the first Specific humidity values ​​for each altitude layer; This represents the total number of floors by height. The first in the historical pressure profile The air pressure at each altitude level; The first in the historical pressure profile The air pressure at each altitude level; This is the acceleration due to gravity.

[0040] After obtaining the corrected historical specific humidity profile of the target, the historical atmospheric precipitable water content of the multiple altitude layers included in the profile is calculated. Then, using the historical atmospheric precipitable water content at the surface altitude as the baseline value, and based on the historical atmospheric precipitable water content of each altitude layer and the corresponding altitude difference, a unique altitude correction parameter describing the overall decay trend of the profile is derived by fitting an exponential decay model.

[0041] Specifically, the height correction parameters are generated by fitting in the following way: First, the total precipitable atmospheric water at the Earth's surface is used as the starting point of a decay curve. The historical precipitable atmospheric water at each altitude level and its corresponding altitude difference are considered as a series of data points describing the vertical decline path of water vapor. Then, through a mathematical optimization process, various decay rates are tried to generate multiple exponential decay curves starting from this starting point, and the overall fit of each curve to all actual data points is evaluated. This process aims to find an "optimal" curve that passes through all data points with minimal overall deviation. Finally, the unique decay rate value corresponding to this optimally fitted curve is determined, and this value is defined as the altitude correction parameter that represents the water vapor distribution characteristics of the entire vertical profile.

[0042] For example, using a water vapor stratification model, assume the total atmospheric precipitable water at an observation point is 50 mm, while the actual atmospheric precipitable water at altitudes of 2 km, 4 km, and 6 km relative to the surface is 18.4 mm, 6.8 mm, and 2.5 mm, respectively. During the fitting process, the mathematical optimization program tries different attenuation rate values ​​to find the optimal curve. If a lower attenuation rate is tried, such as 0.4, the model calculates values ​​of 22.5 mm and 10.1 mm at altitudes of 2 km and 4 km, respectively, which deviates significantly from the actual measurements. However, when the program tries an attenuation rate of 0.5, the calculated values ​​at altitudes of 2 km, 4 km, and 6 km are approximately 18.4 mm, 6.8 mm, and 2.5 mm, respectively, which closely match all actual data points. Therefore, through mathematical methods such as least squares fitting, the optimization process ultimately determines 0.5 as the unique attenuation rate value corresponding to this best-fit curve; this 0.5 is then determined as the altitude correction parameter that can represent this set of data.

[0043] Each height correction parameter obtained in this way will serve as a predicted label, and together with its corresponding historical measurement time, historical longitude, and historical latitude (as input features), they will constitute a training sample. After obtaining several training samples, they will be sequentially input into the height correction parameter prediction model for training. During each training iteration, the model will output a predicted height correction parameter based on the input features, and update the model parameters based on the loss function value between the predicted value and the true label, until the preset number of training iterations is reached, thus completing the model training process.

[0044] Once the model training is complete, it can enter the real-time application phase. First, the target altitude, current measurement time, longitude, latitude, surface altitude, and real-time total precipitable water vapor at the location to be measured are obtained. The current measurement time, longitude, and latitude are input into the trained altitude correction parameter prediction model, which will instantly generate a real-time altitude correction parameter suitable for the current conditions. Finally, combining this real-time altitude correction parameter, the real-time total precipitable water vapor at the surface, the target altitude, and the surface altitude, and based on a preset water vapor stratification model, the precipitable water vapor at the target altitude at the location to be measured can be calculated. This method efficiently resolves the total water vapor information from ground-based observations to a specified vertical altitude, enabling rapid determination of the vertical structure of water vapor.

[0045] Step S3: Based on the height correction parameters of the location to be measured, the target height, the surface height, and the atmospheric precipitable water at the surface height, generate the atmospheric precipitable water at the target height of the location to be measured based on the preset water vapor stratification model.

[0046] In a preferred embodiment, the water vapor stratification model is specifically: In the formula, The atmospheric precipitable water content at the target altitude of the location to be measured; The atmospheric precipitable water content is at the surface height of the location to be measured. For height correction parameters; The target altitude of the location to be measured; The elevation is the ground level at the location to be measured.

[0047] In a specific implementation of this invention, once the real-time height correction parameters of the location to be measured are obtained, the final calculation step for determining the atmospheric precipitable water at the target height can proceed. This step incorporates several key input parameters, including: the total atmospheric precipitable water at the ground surface measured in real-time by ground-based equipment, which serves as the calculation benchmark; the real-time height correction parameters generated by the prediction model for the current measurement time and geographical location; the target height to be solved by the user; and the ground surface height of the observation point serving as the reference benchmark.

[0048] This calculation process is based on a pre-defined water vapor stratification model that characterizes the general law of water vapor content variation with altitude. The core physical law of this model is that water vapor content decreases exponentially with increasing altitude. Specifically, the calculation first determines the height difference between the target height and the surface height. Then, combining the real-time height correction parameter with this height difference, the attenuation ratio of water vapor from the surface to the target height is calculated. Finally, multiplying the total precipitable atmospheric water at the surface (as a baseline) by this attenuation ratio determines the remaining precipitable atmospheric water at the target height of the measured location. In a preferred embodiment, the water vapor stratification model can be specifically characterized by a mathematical relationship, where the precipitable atmospheric water at the target height of the measured location is determined by the precipitable atmospheric water at the surface height of the measured location, the height correction parameter, the target height of the measured location, and the surface height of the measured location. Through this calculation step, the present invention can accurately resolve a macroscopic, whole-layer ground observation value into a microscopic, specific-height-layer physical quantity, achieving refined determination of vertical water vapor information.

[0049] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0050] like Figure 2 As shown, an embodiment of the present invention provides a device for determining atmospheric precipitable water at a target altitude, comprising: a data acquisition module, an altitude correction parameter determination module, and an atmospheric precipitable water determination module; The data acquisition module is used to acquire the target altitude, measurement time, longitude, latitude, surface altitude, and atmospheric precipitable water at the surface altitude of the location to be measured. The altitude correction parameter determination module is used to input the measurement time, longitude, and latitude into a preset altitude correction parameter prediction model, so that the altitude correction parameter prediction model generates altitude correction parameters for the location to be measured based on the measurement time, longitude, and latitude; wherein, the altitude correction parameter prediction model is trained by several training samples; each training sample includes the historical measurement time, historical longitude, historical latitude, and corresponding label of a typical observation point; the label is the altitude correction parameter of the typical observation point; The atmospheric precipitable water determination module is used to generate the atmospheric precipitable water at the target altitude of the test location based on a preset water vapor stratification model, according to the altitude correction parameters of the test location, the target altitude, the surface altitude, and the atmospheric precipitable water at the surface altitude. The height correction parameters for typical observation points are obtained through the following methods: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

[0051] In a preferred embodiment, the height correction parameter prediction model is trained in the following manner: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

[0052] It should be noted that the embodiments of the device described above correspond to the embodiments of the present invention described above, and can realize the method for determining atmospheric precipitable water at the target altitude as described in any one of the above embodiments of the present invention. Furthermore, the embodiments of the device described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without creative effort.

[0053] Based on the above-described method embodiments of the present invention, a corresponding embodiment of an electronic device is provided.

[0054] An embodiment of the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for determining atmospheric precipitable water at a target altitude as described in any one of the present invention, or, when the processor executes the computer program, it implements the functions of each module in the above-described device embodiments.

[0055] For example, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device.

[0056] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0057] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0058] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0059] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments; Another embodiment of the present invention provides a storage medium including a stored computer program, wherein, when the computer program is executed, the device where the storage medium is located executes the method for determining atmospheric precipitable water at any of the target altitudes described above.

[0060] The aforementioned storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0061] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0062] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for determining atmospheric precipitable water at a target altitude, characterized in that, include: Obtain the target altitude, measurement time, longitude, latitude, surface altitude, and atmospheric precipitable water at the surface altitude of the location to be measured; The measurement time, longitude, and latitude are input into a preset altitude correction parameter prediction model, so that the altitude correction parameter prediction model generates altitude correction parameters for the location to be measured based on the measurement time, longitude, and latitude. The altitude correction parameter prediction model is trained using several training samples. Each training sample includes the historical measurement time, historical longitude, historical latitude, and corresponding label for a typical observation point. The label represents the altitude correction parameters for the typical observation point. Based on the height correction parameters of the location to be measured, the target height, the surface height, and the atmospheric precipitable water at the surface height, the atmospheric precipitable water at the target height of the location to be measured is generated based on the preset water vapor stratification model. The height correction parameters for typical observation points are obtained through the following methods: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

2. The method for determining atmospheric precipitable water at a target altitude as described in claim 1, characterized in that, The height correction parameter prediction model is trained using the following method: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

3. The method for determining atmospheric precipitable water at a target altitude as described in claim 2, characterized in that, Based on the historical atmospheric precipitable water, historical temperature profile, and historical air pressure profile at typical observation points, the historical specific humidity profile is corrected to generate a corrected target historical specific humidity profile, including: Based on historical temperature profiles and historical pressure profiles, historical saturated specific humidity profiles for typical observation points are calculated and generated; wherein, the historical saturated specific humidity profile is composed of the saturated specific humidity value of each altitude layer and the height of each altitude layer. Repeat the specific humidity correction operation until each current first difference is less than the preset convergence threshold, and the specific humidity value of each height layer in the current corrected specific humidity profile is less than the saturated specific humidity value of each height layer in the historical saturated specific humidity profile, and generate the corrected target historical specific humidity profile. The specific humidity correction operation includes: The scaling factor is calculated based on the historical atmospheric precipitable water at the surface height of typical observation points and the current remotely sensed total water vapor. The initial remotely sensed total water vapor is calculated based on the historical specific humidity profile and the historical pressure profile. Based on the current scaling factor, the current specific humidity profile to be corrected is corrected to generate the current corrected specific humidity profile; wherein, the initial specific humidity profile to be corrected is the historical specific humidity profile. Based on the current corrected specific humidity profile, calculate and generate the current corrected atmospheric precipitable water at each altitude layer of typical observation points; For each altitude level, calculate the difference between the current corrected atmospheric precipitable water and the previous corrected atmospheric precipitable water, and generate the current first difference for each altitude level. Determine whether each current first difference is less than the preset convergence threshold, and whether the specific humidity value of each height layer in the current corrected specific humidity profile is less than the specific humidity value of each height layer in the historical saturated specific humidity profile; if so, then use the current corrected specific humidity profile as the corrected target historical specific humidity profile. If not, update the current remotely sensed total water vapor based on the current corrected specific humidity profile and historical pressure profile; update the current corrected specific humidity profile to the current specific humidity profile to be corrected.

4. The method for determining atmospheric precipitable water at a target altitude as described in claim 3, characterized in that, The saturated specific humidity value for any altitude layer is calculated using the following formula: In the formula, For the first saturated specific humidity value of each altitude layer; The first in the historical temperature profile Temperature at each altitude level; The first in the historical pressure profile The air pressure at each altitude.

5. The method for determining atmospheric precipitable water at a target altitude as described in claim 4, characterized in that, The scaling factor is calculated using the following formula: In the formula, This is the scaling factor; Historical atmospheric precipitation at the surface height of typical observation points; This is for remote sensing inversion of total water vapor content.

6. The method for determining atmospheric precipitable water at a target altitude as described in claim 5, characterized in that, The water vapor stratification model is specifically as follows: In the formula, The atmospheric precipitable water content at the target altitude of the location to be measured; The atmospheric precipitable water content is at the surface height of the location to be measured. For height correction parameters; The target altitude of the location to be measured; The elevation is the ground surface elevation at the location to be measured.

7. A device for determining precipitable atmospheric water at a target altitude, characterized in that, include: Data acquisition module, altitude correction parameter determination module, and atmospheric precipitable water determination module; The data acquisition module is used to acquire the target altitude, measurement time, longitude, latitude, surface altitude, and atmospheric precipitable water at the surface altitude of the location to be measured. The altitude correction parameter determination module is used to input the measurement time, longitude, and latitude into a preset altitude correction parameter prediction model, so that the altitude correction parameter prediction model generates altitude correction parameters for the location to be measured based on the measurement time, longitude, and latitude; wherein, the altitude correction parameter prediction model is trained by several training samples; each training sample includes the historical measurement time, historical longitude, historical latitude, and corresponding label of a typical observation point; the label is the altitude correction parameter of the typical observation point; The atmospheric precipitable water determination module is used to generate the atmospheric precipitable water at the target altitude of the test location based on a preset water vapor stratification model, according to the altitude correction parameters of the test location, the target altitude, the surface altitude, and the atmospheric precipitable water at the surface altitude. The height correction parameters for typical observation points are obtained through the following methods: The historical atmospheric precipitable water at the surface height of typical observation points, the historical temperature profile for each altitude layer of typical observation points, the historical pressure profile for each altitude layer of typical observation points, and the historical specific humidity profile for each altitude layer of typical observation points are obtained. Based on the historical atmospheric precipitable water, historical temperature profile and historical air pressure profile at the surface height of typical observation points, the historical specific humidity profile is corrected to generate the corrected target historical specific humidity profile. Based on the target historical relative humidity profile, calculate and generate the historical atmospheric precipitable water at each altitude layer of typical observation points; Using the historical atmospheric precipitable water at the surface height of a typical observation point as the baseline value, height correction parameters are generated by fitting the historical atmospheric precipitable water at each height layer of the typical observation point and the height difference between each height layer of the typical observation point and the surface height.

8. The apparatus for determining precipitable atmospheric water at a target altitude as described in claim 7, characterized in that, The height correction parameter prediction model is trained using the following method: Obtain several training samples; Each training sample is sequentially input into the height correction parameter prediction model to train the model until a preset number of training iterations are reached. The height correction parameter prediction model outputs the predicted height correction parameter corresponding to each training sample received. A loss function value is calculated based on the height correction parameter and its corresponding label. The height correction parameter prediction model is then updated based on the loss function value.

9. An electronic device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the method for determining atmospheric precipitable water at a target altitude as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the storage medium to perform the method for determining atmospheric precipitable water at a target altitude as described in any one of claims 1 to 6.

Images