CN115728842A - Method, system and device for acquiring atmospheric degradable water and storage medium - Google Patents
Method, system and device for acquiring atmospheric degradable water and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a system, a device and a storage medium for acquiring atmospheric degradable water, which belong to the technical field of meteorological application research and comprise the following steps: acquiring longitude, latitude, air pressure and time of a target point; inputting longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, searching grid point coefficients of a plurality of grid points of which the distances from the target point meet preset requirements according to input parameters by the empirical grid model, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water amount; according to the invention, the PWV acquisition efficiency is improved through the pre-constructed empirical grid model, and the PWV with higher precision is obtained.
Description
Technical Field
The invention relates to an atmospheric degradable water yield acquisition method, system, device and storage medium, belonging to the technical field of meteorological application research.
Background
Atmospheric water vapor is mainly stored in the troposphere, and although the storage amount is small, the atmospheric water vapor plays a dominant role in atmospheric changes such as weather system evolution, earth water circulation and atmospheric circulation. The amount of atmospheric Water reducible (PWV) is commonly used to characterize the atmospheric Water Vapor content, and is a key parameter in climate research and extreme weather early warning.
The existing PWV detection means mainly comprises radio sounding, satellite remote sensing, GNSS (Global Navigation Satellite System) water vapor inversion and reanalysis data acquired by using a numerical assimilation technology. The radio sounding utilizes the sounding balloon to actually observe and obtain the PWV, which is one of the water vapor detection modes with the highest precision, but the radio sounding has large workload, high cost and low space-time resolution. The satellite remote sensing inverses the PWV according to the radiation observation data of the satellite water vapor sensitive channel, can make up the discontinuity of the sounding site in space, but is greatly influenced by cloud layers, precipitation and the like, and the detection PWV has low precision. The GNSS inversion water vapor has the advantages of all weather, high space-time resolution, low cost and the like, but GNSS sites are sparsely distributed, and the acquired PWV is in discrete distribution in space. The numerical assimilation technology can acquire PWV with high precision and high space-time resolution by fusing earth surface station observation data, satellite remote sensing data and other data, but the product precision is unreliable in a region with less or lacking assimilation data, and the PWV difference is overlarge due to the influence of the height difference between a product grid point and a target point. In order to obtain PWV with large range and high precision, a scholars proposes to combine multi-source data to construct a water-vapor fusion model and construct a PWV vertical correction model, but the models depend on specific reanalysis data when in use, so that the efficiency of obtaining PWV by a user is low.
Disclosure of Invention
The invention aims to provide a method, a system, a device and a storage medium for acquiring atmospheric degradable water, which solve the problems of low efficiency and low acquisition precision in acquiring PWV in the prior art.
In order to realize the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the present invention provides a method for obtaining an amount of atmospheric degradable water, comprising:
acquiring longitude, latitude, air pressure and time of a target point;
inputting the longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, searching grid point coefficients of a plurality of grid points of which the distances from the target point meet preset requirements according to input parameters by the empirical grid model, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water amount.
With reference to the first aspect, further, the empirical grid model is constructed by:
acquiring a re-analysis product obtained based on sounding data in a certain area for a plurality of years;
establishing a primary expression of an empirical grid model by using an Askne model and a water-steam conversion coefficient model according to data in the reanalysis product;
expressing the input parameters in the preliminary expression by using a year period model and a half year period model, solving model coefficients of each lattice point in the reanalysis product in the year period model and the half year period model by using specific humidity corresponding to the bottommost air pressure value of the reanalysis product and a water vapor decrement factor obtained by back calculation of the preliminary expression by using a least square method, and substituting the model coefficients into the year period model and the half year period model to obtain the input parameters;
correcting the PWV deviation in the preliminary expression by using the spherical harmonic function to obtain a second expression;
and vertically correcting the second expression to obtain a final expression of the empirical grid model.
With reference to the first aspect, further, establishing a preliminary expression of the empirical grid model by using the Askne model and the water-steam conversion coefficient model, includes:
and (3) calculating the zenith wet delay by using the Askne model, wherein the zenith wet delay is calculated according to the following formula:
wherein, ZWD tableZenith Wet retardation, k' 2 And k 3 Denotes a first and a second atmospheric refractive index, k' 2 ＝22.1±2.2K/hPa，k 3 ＝3.739×105±0.012×105K2/hPa，T m Represents the atmospheric weighted average temperature, λ represents the water vapor decrement factor, g m Denotes the mean gravitational acceleration, R d Denotes the molar gas constant, R d ＝8.3143J/K/mol，e s Represents the vapor pressure;
the calculation formula of the water vapor pressure is as follows:
wherein q represents specific humidity, and P represents air pressure;
the expression of the water-vapor conversion coefficient model is as follows:
wherein II represents a water-vapor conversion coefficient, R v Represents the gas constant of water vapor;
multiplying the zenith wet retardation by the water-vapor conversion coefficient to obtain an initial expression as follows:
with reference to the first aspect, further, the expression of the year cycle and half year cycle model is as follows:
wherein A represents the input parameter in the preliminary expression, A 0 Represents a constant term, A 1 And A 2 Representing a first and a second annual cycle coefficient, A 3 And A 4 Representing a first and a second half-year-cycle coefficient, JD represents the julian day.
With reference to the first aspect, further, the correcting the PWV deviation in the preliminary expression by using the spherical harmonic function includes:
calculating initial PWV (weighted average) of each grid point in the reanalysis product for several years by using a primary expression, marking as PWV1, calculating PWV of each grid point in the reanalysis product for several years by using a first calculation formula, marking as PWV2, calculating PWV deviation of the PWV1 and the PWV2, fitting the PWV deviation by using a spherical harmonic function, solving a coefficient to be estimated in the spherical harmonic function by using a least square method, and finishing correction;
the first calculation formula is as follows:
wherein I represents the number of barometric pressure layers of the reanalyzed product, P i 、P i-1 Respectively, the air pressures of the i-th and i-1-th layers of the re-analyzed product, q i 、q i-1 The specific wettabilities of the i-th and i-1-th layers of the re-analyzed product are shown, respectively.
With reference to the first aspect, further, the expression of the spherical harmonic function is:
where dPWV represents a PWV deviation, N and M represent a maximum number of times and a maximum order of the spherical harmonics, respectively, N and M represent a number of times and an order of the spherical harmonics, respectively, A nm And B nm The first coefficient to be estimated and the second coefficient to be estimated respectively represent spherical harmonic functions, and are calculated by the following formula:
wherein, γ and
respectively representing the longitude and latitude, P, of a grid point nm (t) represents the Legendre function, the expression being as follows:
wherein k represents from 0 to
| is a whole number of! Representing a factorial.
With reference to the first aspect, further, performing vertical correction on the second expression to obtain a final expression of the empirical grid model, including:
obtaining PWV conversion formulas of two different air pressure height surfaces according to the power function nonlinear change relation of PWV and air pressure;
calculating the PWV of each air pressure height surface of the reanalysis product and the corresponding air pressure through a first calculation formula, substituting the PWV into the PWV conversion formula, and solving the PWV decreasing coefficient of each grid point;
expressing the PWV decreasing coefficient by using a year period and half year period model, solving the model coefficient of each grid point in the year period and half year period model by adopting a least square method to obtain a final expression;
the power function nonlinear change relationship between the PWV and the air pressure is as follows:
PWV＝a·P b
where a represents a non-linear coefficient, P represents air pressure, and b represents a PWV decrement coefficient.
In a second aspect, the present invention also provides an atmospheric degradable water yield acquiring system, comprising:
an input data acquisition module: the device is used for acquiring longitude, latitude, air pressure and time of a target point;
the atmospheric water-degradable amount acquisition module: the method is used for inputting longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, the empirical grid model searches grid point coefficients of a plurality of grid points closest to the target point according to input parameters, initial PWV of each grid point is calculated according to the grid point coefficients, the initial PWV is corrected, vertically corrected and subjected to bilinear interpolation to obtain the PWV of the target point and output, and the atmospheric degradable water yield acquisition is completed.
In a third aspect, the invention further provides an atmospheric degradable water yield obtaining device, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of the first aspect.
In a fourth aspect, the invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any one of the first aspect.
Compared with the prior art, the invention has the following beneficial effects:
according to the method, the system, the device and the storage medium for acquiring the atmospheric degradable water yield, the PWV can be acquired only by inputting the longitude, the latitude, the air pressure and the time of the target point into the constructed empirical grid model, and the acquisition efficiency of the PWV can be improved; according to the invention, the PWV is corrected by using the spherical harmonic function when the empirical grid model is constructed, and meanwhile, the PWV is vertically corrected according to the input target point air pressure value, so that the acquisition precision of the PWV can be improved.
Drawings
Fig. 1 is a flowchart of an atmospheric degradable water content obtaining method according to an embodiment of the present invention.
Detailed Description
The present invention is further described with reference to the accompanying drawings, and the following examples are only for clearly illustrating the technical solutions of the present invention, and should not be taken as limiting the scope of the present invention.
Example 1
As shown in fig. 1, an atmospheric reducible water obtaining method provided by an embodiment of the present invention includes the following steps:
s1, acquiring longitude, latitude, air pressure and time of a target point.
S2, inputting longitude, latitude, air pressure and time of a target point into the constructed empirical grid model, searching grid point coefficients of a plurality of grid points of which the distances from the target point accord with preset requirements according to the input parameters by the empirical grid model, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, outputting the PWV, and finishing the acquisition of the atmospheric degradable water quantity.
Prior to performing the steps of the present invention, an empirical grid model is pre-constructed, the steps of constructing including:
(1) And acquiring a re-analysis product obtained based on the sounding data in a plurality of years in a certain area.
(2) And establishing a primary expression of the empirical grid model by utilizing an Askne model and a water-vapor conversion coefficient model according to the data in the reanalyzed product.
The Askne model was used to calculate Zenith Wet Delay (ZWD), as shown in equation (1).
In the formula (1), k' 2 、k 3 Denotes a first atmospheric refractive index and a second atmospheric refractive index, k' 2 ＝22.1±2.2K/hPa，k 3 ＝3.739×10 5 ±0.012×10 5 K 2 /hPa，T m Denotes the atmospheric weighted mean temperature (K), λ denotes the water vapour decreasing factor (dimensionless), g m Represents the average gravitational acceleration (m/s) 2 )，R d According to R d ＝R/M d Calculated, R represents the molar gas constant (8.3143J/K/mol), M d Represents the molar mass of dry air (28.965 g/mol), e s Which represents the vapor pressure (hPa) can be calculated from equation (2).
In the formula (2), q represents specific humidity (kg/kg), and P represents air pressure (hPa).
And multiplying the ZWD by a water-vapor conversion coefficient II to obtain the PWV, wherein the formula (3) shows the water-vapor conversion coefficient model, and the formula (4) shows the water-vapor conversion coefficient model.
PWV＝ZWD×II (3)
In the formula (3), R v Representing the gas constant of water vapor.
Substituting the formula (1), the formula (2) and the formula (4) into the formula (3) and simplifying to obtain a preliminary expression of the empirical grid model, wherein the formula (5) is shown as the formula, input parameters in the formula (5) are q and lambda, and P is the lowest layer air pressure value of the product to be analyzed.
(3) And expressing the input parameters in the preliminary expression by using a year period model and a half year period model, solving model coefficients of each lattice point in the reanalysis product in the year period model and the half year period model by using the specific humidity corresponding to the bottommost air pressure value of the reanalysis product and a water vapor decrement factor obtained by back calculation of the preliminary expression by using a least square method, and substituting the model coefficients into the year period model and the half year period model to obtain the input parameters.
And (3) calculating the PWV at the lowest air pressure value P of the re-analysis product by using the re-analysis product for several years according to a first calculation formula, namely formula (6), taking the specific humidity at the position P as q, and performing inverse calculation by using formula (5) to obtain lambda.
In the formula (6), I represents the number of atmospheric layers of the product to be reanalyzed, P i 、P i-1 Respectively representThe product was analyzed again for gas pressure, q, of the i-1 th layer i 、q i-1 The specific wettabilities of the i-th and i-1-th layers of the re-analyzed product are shown, respectively.
And expressing q and lambda by using a year period model and a half year period model, wherein the year period model and the half year period model are shown as a formula (7).
In the formula (7), A represents q and lambda, A 0 Represents a constant term, A 1 、A 2 Representing a first and a second annual cycle coefficient, A 3 、A 4 Representing the first and second half-year-cycle coefficients, JD representing julian days.
And (3) solving the model coefficient of each lattice point in the reanalyzed product in the formula (7) by using q corresponding to the bottommost air pressure value of the reanalyzed product for several years and lambda obtained by inverse calculation of the formula (5).
(4) And correcting the PWV deviation in the preliminary expression by using the spherical harmonic function to obtain a second expression.
Firstly, obtaining initial PWV (marked as PWV 1) of each grid point of the reanalysis product for several years by using a primary expression, then calculating PWV (marked as PWV 2) according to a reanalysis product passing formula (6), and finally calculating the deviation (marked as dPWV) of PWV1 and PWV 2.
And fitting dPWV by using a spherical harmonic function, wherein the functional expression of the dPWV is shown as a formula (8), and solving a coefficient to be estimated in the spherical harmonic function model by using a least square method.
In the formula (8), N and M respectively represent the maximum degree and the maximum order of the spherical harmonic function, and N =9, M =9, A is taken nm 、B nm A first coefficient to be estimated and a second coefficient to be estimated which represent a spherical harmonic model, a nm And b nm Can be calculated by the equations (9) and (10).
In the formulae (9) and (10), gamma,
Respectively representing the longitude and latitude, P, of grid points nm (t) represents a Legendre function, whose expression is shown in equation (11):
(5) And vertically correcting the second expression to obtain a final expression of the empirical grid model.
PWV has a significant power function nonlinear variation relation with the air pressure, and the variation relation is shown as a formula (12):
PWV＝a·P b (12)
in the formula (12), a represents a formula coefficient, and b represents a PWV decrement coefficient.
Assuming two different pressure altitude planes P 1 And P 2 (P 2 >P 1 ) From formula (12):
formula (13) can be converted to:
in the formulae (13) and (14),
are respectively notSame air pressure altitude plane P 1 And P 2 The PWV of (a).
The method comprises the steps of calculating the PWV of each air pressure height surface of a re-analysis product and the corresponding air pressure of the re-analysis product through a formula (6) by utilizing the re-analysis product for several years, substituting the PWV of each air pressure height surface of the re-analysis product and the corresponding air pressure of the re-analysis product into an equation (14) to solve a PWV decreasing coefficient b of each lattice point, expressing the b by using a formula (7), wherein A in the formula (7) represents the PWV decreasing coefficient b, and solving a model coefficient of each lattice point in the formula (7) by adopting a least square method.
Thus, the establishment of the empirical grid model for obtaining the amount of atmospheric water reducible by the atmosphere is completed, and a user only needs to input the longitude, the latitude, the time and the air pressure of a target point to obtain the PWV when using the model, and the specific operation process of the model is as follows:
the empirical grid model searches grid point coefficients of a plurality of grid points (4 in this embodiment) whose distances from the target point meet preset requirements according to the input parameters;
and calculating the initial PWV of each grid point according to the grid point coefficient, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water volume.
Example 2
The method for obtaining the atmospheric degradable water provided by the embodiment of the invention takes an ERA5 reanalysis product of 2015-2019 as an example.
ERA5 is the fifth generation of analysis data issued by the European middle-range Weather forecasting center (ECMWF), and can provide global atmospheric, sea and land parameters since 1950, and the delay time of the product is only 5 days. The ERA5 reanalyzed product used in this example was atmospheric stratified meteorological data (37 layers by barometric pressure from 1000hPa to 1 hPa), with a spatial resolution of 0.25 ° × 0.25 °, a temporal resolution of 12h (00 h and 12 h), ranging from 75 ° E to 105 ° E, 25 ° N to 40 ° N, totaling 7381 grid points.
An experience grid model for acquiring the atmospheric degradable water volume is constructed in advance, and the experience grid model comprises the following steps:
(1) ERA5 was obtained from the Qinghai-Tibet plateau (75 ° E to 105 ° E, 25 ° N to 40 ° N) 2015-2019 and the product was reanalyzed.
(2) And establishing a model primary expression by using an Askne model and a water-vapor conversion coefficient model.
The Askne model was used to calculate Zenith Wet Delay (ZWD), as shown in equation (1).
K 'in the formula (1)' 2 、k 3 Denotes a first and a second atmospheric refractive index, k' 2 ＝22.1±2.2K/hPa，k 3 ＝3.739×10 5 ±0.012×10 5 K 2 /hPa，T m Denotes the atmospheric weighted mean temperature (K), λ denotes the water vapour decreasing factor (dimensionless), g m Represents the average gravitational acceleration (m/s) 2 )，R d According to R d ＝R/M d Calculated, R represents the molar gas constant (8.3143J/K/mol), M d Represents the molar mass of dry air (28.965 g/mol), e s Which represents the vapor pressure (hPa) can be calculated from equation (2).
In the formula (2), q represents specific humidity (kg/kg), and P represents air pressure (hPa).
And multiplying the ZWD by a water-vapor conversion coefficient II to obtain PWV, wherein the formula (3) shows, and the water-vapor conversion coefficient model is shown as the formula (4):
PWV＝ZWD×II (3)
in the formula (3), R v Representing the gas constant of water vapor.
Substituting the formula (1), the formula (2) and the formula (4) into the formula (3) and simplifying to obtain a preliminary expression of the model, wherein the input parameters in the formula (5) are q and lambda, and P is the lowest air pressure value of the reanalyzed product:
(3) And expressing the input parameters in the model primary expression by using the annual cycle and half-annual cycle models.
And (3) calculating PWV at the bottommost air pressure value P of the reanalysis product according to an equation (6) by utilizing ERA5 atmospheric stratification meteorological data in 2015-2019, taking the specific humidity at the P as q, and performing inverse calculation through an equation (5) to obtain lambda.
In the formula (6), I represents the number of atmospheric layers of the reanalyzed product, P i 、P i-1 Respectively, the air pressures of the i-th and i-1-th layers of the re-analyzed product, q i 、q i-1 The specific wettabilities of the i-th and i-1-th layers of the re-analyzed product are shown, respectively.
Expressing q and lambda by using a year period and half year period model, wherein the year period and half year period model is shown as a formula (7):
in the formula (7), A represents q and lambda, A 0 Represents a constant term, A 1 、A 2 Representing a first and a second annual cycle coefficient, A 3 、A 4 Representing the first and second half-year-cycle coefficients, JD representing julian days.
And solving the model coefficient of each lattice point in the reanalyzed product in the formula (7) by using q corresponding to the bottom air pressure value P of the reanalyzed product in 2015-2019 and lambda obtained by inverse calculation of the formula (5) by adopting a least square method.
(4) Correcting PWV deviation using spherical harmonics
The method comprises the steps of firstly obtaining initial PWV (recorded as PWV 1) of reanalysis products in grids 2015-2019 by using a preliminary expression, then calculating PWV (recorded as PWV 2) according to reanalysis products through formula (6), and finally calculating the deviation (recorded as dPWV) of the PWV1 and the PWV 2.
And fitting dPWV by using a spherical harmonic function, wherein the functional expression of the dPWV is shown as a formula (8), and solving a coefficient to be estimated in the spherical harmonic function model by using a least square method.
In the formula (8), N and M respectively represent the maximum degree and the maximum order of the spherical harmonic function, and N =9, M =9, A is taken nm 、B nm Coefficient to be estimated, a, representing a spherical harmonic model nm And b nm Can be calculated by the following equations (9) and (10):
in the formulae (9) and (10), gamma,
Respectively representing the longitude and latitude, P, of a grid point nm (t) represents a Legendre function, the expression of which is shown in equation (11):
(5) The model is corrected vertically.
PWV has a significant power function nonlinear variation relation with the air pressure P, and the variation relation is shown as a formula (12):
PWV＝a·P b (12)
in equation (12), a represents an equation coefficient, and b represents a PWV decrement coefficient.
Assuming two different pressure altitude planes P 1 And P 2 (P 2 >P 1 ) From formula (12):
formula (13) can be converted to:
in the formulae (13) and (14),
respectively being different air pressure altitude planes P 1 And P 2 The PWV value of (a).
Calculating the PWV of each air pressure height surface of the re-analysis product and the corresponding air pressure thereof by using the re-analysis product of 2015-2019 through an expression (6), substituting the PWV of each air pressure height surface of the re-analysis product and the corresponding air pressure thereof into an expression (14) to obtain a PWV decreasing coefficient b of each lattice point, expressing the b by using an expression (7), wherein A in the expression (7) represents the PWV decreasing coefficient b, and obtaining a model coefficient of each lattice point in the expression (7) by using a least square method.
Thus, the establishment of the empirical grid model for obtaining the amount of atmospheric water reducible by the atmosphere is completed, and a user only needs to input the longitude, the latitude, the time and the air pressure of a target point to obtain the PWV when using the model, and the specific operation process of the model is as follows:
the empirical grid model searches grid point coefficients of a plurality of grid points (4 in this embodiment) whose distances from the target point meet preset requirements according to the input parameters;
calculating the initial PWV of each grid point after being modified by the spherical harmonic function according to the grid point coefficient;
and calculating the PWV of each grid point at the target point according to the air pressure of the target point, performing bilinear interpolation processing on the PWV of each grid point at the target point to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water volume.
In order to verify the accuracy of the method, the PWV calculated by the data of the sounding site in 2020, which does not participate in modeling, is taken as a true value, and the PWV calculated by the C-PWVC2 model is introduced as comparison, so that an empirical grid model for acquiring the atmospheric water reducible quantity is represented as ASV-PWV. Wherein, 19 sounding sites are uniformly distributed in the Tibet plateau area, and the data of the sounding sites is used for calculating PWV by formula (6); the C-PWVC2 model is a newer PWV vertical correction model, PWV on 4 ERA5 grid points nearest to the sounding site is vertically corrected to the height of the sounding site by the model, and then PWV at the sounding site is obtained through bilinear interpolation. Expressions of the C-PWVC2 model are shown as formulas (15) and (16).
PWV h1 ＝PWV h2 ·exp(β(h 1 -h 2 )) (16)
In the formulas (15) and (16), β represents a decreasing coefficient of PWV, DOY represents the day of year, and PWV h1 And PWV h2 Respectively indicate being located at different heights h 1 And h 2 The PWV of (a).
The final calculation results are shown in the PWV comparison table (table 1). Table 1 shows that the PWV obtained by obtaining the empirical grid model of the atmospheric water reducible volume is closer to the PWV calculated by the sounding data than the C-PWVC2 model, and the C-PWVC2 model needs to obtain a specific reanalysis data product when in use, so the model provided by the present invention can improve the PWV obtaining efficiency and obtain the PWV with higher accuracy, and therefore the atmospheric water reducible volume obtaining method provided by the present invention can improve the PWV obtaining efficiency and obtain the PWV with higher accuracy.
TABLE 1 PWV COMPARATIVE TABLE
Example 3
The embodiment of the invention provides an atmospheric degradable water yield acquisition system, which comprises:
an input data acquisition module: the device is used for acquiring longitude, latitude, air pressure and time of a target point;
the atmospheric water-degradable amount acquisition module: the method is used for inputting longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, the empirical grid model searches grid point coefficients of a plurality of grid points nearest to the target point according to input parameters, an initial PWV of each grid point is calculated according to the grid point coefficients, the initial PWV is corrected, vertically corrected and subjected to bilinear interpolation to obtain a PWV of the target point and output, and atmospheric degradable water yield obtaining is completed.
Example 4
The embodiment of the invention provides an atmospheric degradable water yield acquisition device, which comprises a processor and a storage medium, wherein the processor is used for processing atmospheric degradable water yield;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method of:
acquiring longitude, latitude, air pressure and time of a target point;
inputting longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, searching grid point coefficients of a plurality of grid points closest to the target point by the empirical grid model according to input parameters, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water quantity.
Example 5
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the following method:
acquiring longitude, latitude, air pressure and time of a target point;
inputting the longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, searching grid point coefficients of a plurality of grid points nearest to the target point according to input parameters by the empirical grid model, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water amount.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. An atmospheric degradable water yield acquisition method is characterized by comprising the following steps:
acquiring longitude, latitude, air pressure and time of a target point;
inputting the longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, searching grid point coefficients of a plurality of grid points of which the distances from the target point meet preset requirements according to input parameters by the empirical grid model, calculating initial PWV of each grid point according to the grid point coefficients, correcting, vertically correcting and carrying out bilinear interpolation processing on the initial PWV to obtain the PWV of the target point, and outputting the PWV to finish the acquisition of the atmospheric degradable water amount.
2. The method for acquiring the amount of atmospheric water-reducing according to claim 1, wherein the empirical grid model is constructed by the following method:
acquiring a re-analysis product obtained based on sounding data in a certain area for a plurality of years;
establishing a primary expression of an empirical grid model by utilizing an Askne model and a water-vapor conversion coefficient model according to data in the reanalyzed product;
expressing the input parameters in the preliminary expression by using a year period model and a half year period model, solving model coefficients of each lattice point in the reanalysis product in the year period model and the half year period model by using specific humidity corresponding to the bottommost air pressure value of the reanalysis product and a water vapor decrement factor obtained by back calculation of the preliminary expression by using a least square method, and substituting the model coefficients into the year period model and the half year period model to obtain the input parameters;
correcting the PWV deviation in the preliminary expression by using the spherical harmonic function to obtain a second expression;
and vertically correcting the second expression to obtain a final expression of the empirical grid model.
3. The method for acquiring the amount of atmospheric water-degradable according to claim 2, wherein the step of establishing a preliminary expression of an empirical grid model by using an Askne model and a water-steam conversion coefficient model comprises the following steps:
and (3) calculating the zenith wet delay by using an Askne model, wherein the calculation formula of the zenith wet delay is as follows:
wherein ZWD represents zenith wet retardation, k' 2 And k 3 Denotes a first and a second atmospheric refractive index, k' 2 ＝22.1±2.2K/hPa，k 3 ＝3.739×105±0.012×105K2/hPa，T m Represents the atmospheric weighted average temperature, λ represents the water vapor decrement factor, g m Denotes the mean gravitational acceleration, R d Denotes the molar gas constant, R d ＝8.3143J/K/mol，e s Represents the water vapor pressure;
the calculation formula of the water vapor pressure is as follows:
wherein q represents specific humidity, and P represents air pressure;
the expression of the water-vapor conversion coefficient model is as follows:
wherein II represents a water-vapor conversion coefficient, R v Represents the gas constant of water vapor;
multiplying the zenith wet retardation by the water-vapor conversion coefficient to obtain an initial expression as follows:
4. the method for acquiring the amount of atmospheric water-degradable according to claim 2, wherein the expression of the year period and half year period model is as follows:
wherein A represents the input parameter in the preliminary expression, A 0 Represents a constant term, A 1 And A 2 Representing a first and a second annual cycle coefficient, A 3 And A 4 Representing the first and second half-year cycle coefficients, JD representing julian days.
5. The method for obtaining the amount of atmospheric water emission according to claim 2, wherein the correcting the PWV deviation in the preliminary expression by using the spherical harmonic function comprises:
calculating initial PWV (weighted average) of each grid point in the reanalysis product for several years by using a primary expression, marking as PWV1, calculating PWV of each grid point in the reanalysis product for several years by using a first calculation formula, marking as PWV2, calculating PWV deviation of the PWV1 and the PWV2, fitting the PWV deviation by using a spherical harmonic function, solving a coefficient to be estimated in the spherical harmonic function by using a least square method, and finishing correction;
the first calculation formula is as follows:
wherein I represents the number of barometric pressure layers of the reanalyzed product, P i 、P i-1 Respectively, the gas pressures of the i-th and i-1-th layers of the re-analyzed product, q i 、q i-1 The specific wettabilities of the i-th and i-1-th layers of the re-analyzed product are shown, respectively.
6. The method for obtaining the amount of atmospheric water reduction according to claim 5, wherein the spherical harmonic function is expressed as:
where dPWV represents a PWV deviation, N and M represent a maximum number of times and a maximum order of the spherical harmonics, respectively, N and M represent a number of times and an order of the spherical harmonics, respectively, A nm And B nm The first coefficient to be estimated and the second coefficient to be estimated respectively represent spherical harmonic functions, and are calculated by the following formula:
wherein, γ and
respectively representing the longitude and latitude, P, of a grid point nm (t) represents the Legendre function, the expression is as follows:
wherein k represents from 0 to
| is a whole number of! Indicating a factorial.
7. The method for obtaining the amount of atmospheric water reduction according to claim 5, wherein the vertical correction of the second expression to obtain the final expression of the empirical grid model comprises:
obtaining PWV conversion formulas of two different air pressure height surfaces according to the power function nonlinear change relation of PWV and air pressure;
calculating and analyzing the PWV of each air pressure altitude surface of the product and the corresponding air pressure through a first calculation formula, and substituting the PWV conversion formula to solve the PWV decreasing coefficient of each grid point;
expressing the PWV decreasing coefficient by using a year period and half year period model, solving the model coefficient of each grid point in the year period and half year period model by adopting a least square method to obtain a final expression;
the power function nonlinear change relationship between the PWV and the air pressure is as follows:
PWV＝a·P b
wherein a represents a nonlinear coefficient, P represents air pressure, and b represents a PWV decrement coefficient.
8. An atmospheric water reducible quantity acquisition system, comprising:
an input data acquisition module: the device is used for acquiring longitude, latitude, air pressure and time of a target point;
the atmospheric water degradable amount acquisition module: the method is used for inputting longitude, latitude, air pressure and time of a target point into a constructed empirical grid model, the empirical grid model searches grid point coefficients of a plurality of grid points nearest to the target point according to input parameters, an initial PWV of each grid point is calculated according to the grid point coefficients, the initial PWV is corrected, vertically corrected and subjected to bilinear interpolation to obtain a PWV of the target point and output, and atmospheric degradable water yield obtaining is completed.
9. An atmospheric degradable water yield acquisition device is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 7.
10. Computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN115993668A (en) * | 2023-03-22 | 2023-04-21 | 成都云智北斗科技有限公司 | Polynomial correction and neural network-based PWV reconstruction method and system |
| CN118091798A (en) * | 2024-04-19 | 2024-05-28 | 山东大学 | Typhoon response-based shipborne GNSS water vapor analysis method and system |
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| CN115993668A (en) * | 2023-03-22 | 2023-04-21 | 成都云智北斗科技有限公司 | Polynomial correction and neural network-based PWV reconstruction method and system |
| CN115993668B (en) * | 2023-03-22 | 2023-05-30 | 成都云智北斗科技有限公司 | Polynomial correction and neural network-based PWV reconstruction method and system |
| CN118091798A (en) * | 2024-04-19 | 2024-05-28 | 山东大学 | Typhoon response-based shipborne GNSS water vapor analysis method and system |
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