Real-time monitoring method for rainfall of sea troposphere atmosphere based on GNSS (Global Navigation Satellite System)

Abstract

The invention relates to the field of marine meteorological monitoring, and discloses a GNSS-based marine troposphere atmosphere rainfall real-time monitoring method, which comprises the following steps: estimating total troposphere zenith delay of an observation station position by using GNSS precise point positioning, and calculating troposphere zenith dry delay by using meteorological elements so as to obtain troposphere zenith wet delay; obtaining ERA5 reanalysis data, and constructing an atmospheric weighted average temperature model; calculating an atmospheric weighted average temperature and a water vapor conversion coefficient by using an atmospheric weighted average temperature model and combining with meteorological elements of the observation station position; and calculating atmospheric rainfall of the troposphere by using the troposphere zenith wet delay and the water-vapor conversion coefficient at the observation station position. According to the method disclosed by the invention, the GNSS signal which is high in space-time coverage and passively received is taken as a signal source, real-time precise single-point positioning is carried out, zenith troposphere wet delay is extracted, and atmospheric rainfall can be monitored in real time in a high-precision manner under the condition of lacking historical sounding data.

Description

Technical Field

[0001] The present invention relates to the field of marine meteorological monitoring, and in particular to a method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS. Background Art

[0002] The troposphere is the lowest layer of the atmosphere and the most closely related to human activities in the near-Earth space environment. Water vapor is an important component of the troposphere. Although water vapor accounts for a very small proportion of the troposphere, it directly affects weather changes and climate evolution. It has a profound impact on the earth's environment and human activities by participating in atmospheric energy transfer, regulating climate change, affecting the global water cycle, and driving extreme weather. Studying water vapor is not only the key to improving the accuracy of weather and climate forecasts, but also has important significance for practical applications such as water resources management, agricultural production, disaster prevention and mitigation, and public health.

[0003] As the impact of global climate change on the water cycle system intensifies, water vapor research will become increasingly important. Through the continuous development of observation technology and improvement of models, water vapor research will provide strong support for responding to environmental challenges and promoting sustainable development. The ocean is the main place for water and vapor exchange. Most of the water vapor in the atmosphere is provided by the ocean. Therefore, the ocean is the main source of atmospheric water vapor. Continuous, real-time, and high-precision monitoring of the water vapor content in the marine troposphere and its temporal and spatial changes play an important role in the forecasting of extreme weather such as heavy rain, air quality monitoring, hydrology, oceanography and other application fields. Strengthening the research on the monitoring methods and applications of marine tropospheric water vapor will also help to respond to global climate change and prevent marine disasters.

[0004] There are many traditional methods for water vapor detection, including radiosondes, microwave radiometers, and lidar, but each has its own drawbacks. Radiosondes is a technology that uses meteorological detection instruments to carry balloons to the upper atmosphere to detect water vapor in the atmosphere in real time. This method has the advantages of high accuracy, high vertical resolution, and little influence from the weather environment. However, the construction cost is high, the temporal and spatial resolution is low, the sounding stations are sparsely distributed, and each station launches two sounding balloons every day. Microwave radiometers can measure water vapor in the atmosphere by detecting microwave radiation signals in the atmosphere. They have the advantages of high accuracy and high temporal resolution. However, their vertical resolution is limited, and the detection process is greatly affected by the tropospheric atmospheric environment. Lidar is a remote sensing technology that uses laser pulses to detect water vapor in the atmosphere. It has significant advantages in water vapor detection, especially in providing high-precision and high-resolution vertical profiles of atmospheric water vapor. However, its equipment maintenance cost is high, and it is difficult to achieve dense stationing and real-time observation. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a real-time monitoring method for atmospheric precipitable water in the marine troposphere based on GNSS, so as to achieve the purpose of high-precision real-time monitoring of atmospheric precipitable water in the absence of historical sounding data.

[0006] To achieve the above object, the technical solution of the present invention is as follows: A method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS comprises the following steps: Step 1: use GNSS precise single point positioning to estimate the total tropospheric zenith delay of the measuring station, use meteorological element sensors to measure the meteorological elements of the measuring station to calculate the tropospheric zenith dry delay, and use the tropospheric zenith total delay and tropospheric zenith dry delay to calculate the tropospheric zenith wet delay of the measuring station; Step 2: Obtain ERA5 reanalysis data and construct an atmospheric weighted mean temperature model related to surface meteorological parameters through regression analysis; Step 3, using the atmospheric weighted average temperature model and combining the meteorological elements at the measuring station location, calculate the atmospheric weighted average temperature and water vapor conversion coefficient; Step 4: Calculate the tropospheric atmospheric precipitable water using the tropospheric zenith wet delay and water vapor conversion coefficient at the station location.

[0007] In the above scheme, in step 1, the method for obtaining the actual observed values ​​of the zenith total delay, dry delay and wet delay is as follows: (1) Using GNSS receivers to obtain dual-frequency raw observations, combined with the Beidou satellite-based broadcast PPP-B2b corrections, the ionospheric delay error is eliminated through ionosphere-free combination, and the actual observation value of the tropospheric zenith total delay (ZTD) is extracted; (2) Calculate the tropospheric zenith dry delay ZHD using meteorological elements: ; in, is the geographical latitude of the site, is the site air pressure, is the station elevation; (3) Calculate the zenith wet delay ZWD using the zenith total delay and zenith dry delay: ZWD=ZTD-ZHD; Among them, ZWD is the tropospheric zenith wet delay, ZTD is the tropospheric zenith total delay, and ZHD is the tropospheric zenith dry delay.

[0008] In the above scheme, in step 2, the weighted average temperature of the atmosphere T m The ERA5 reanalysis dataset is used to construct the weighted average temperature T of the atmosphere at sea. m The model specifically includes the following steps: (1) Obtain ERA5 reanalysis data of the four grid points closest to the observation station in terms of spatial distribution from the European Centre for Medium-Range Weather Forecasts, including surface meteorological data and upper-air meteorological data; the surface meteorological data include surface temperature, surface dew point temperature and surface air pressure, and the upper-air meteorological data include the potential, temperature and relative humidity of each pressure altitude layer; (2) Calculate the surface water vapor pressure at each grid point using the ground dew point temperature at each grid point, calculate the height of each pressure layer at each grid point using the potential of each pressure layer at each grid point, and calculate the water vapor pressure of each pressure layer at each grid point using the relative humidity of each pressure layer at each grid point; (3) Perform inverse distance weighted horizontal interpolation on the surface temperature, surface air pressure, surface water vapor pressure of each grid point, as well as the height, temperature, and water vapor pressure of each pressure altitude layer at each grid point, to obtain the surface temperature, surface air pressure, surface water vapor pressure corresponding to the measuring station location, as well as the height, temperature, and water vapor pressure of each pressure altitude layer above the measuring station location; (4) Use the numerical integration method to integrate the temperature and water vapor pressure of each pressure layer above the measuring station along the zenith direction, and calculate the weighted average temperature of the atmosphere at the measuring station at the jth moment: ; (5) The least squares regression method is used to construct the atmospheric weighted average temperature model, namely T m The combined relationship between the ground temperature, ground water vapor pressure and ground air pressure at the measuring station location: ; Among them, T m is the weighted average temperature of the atmosphere at the station location, is the ground temperature at the measuring station, is the surface water vapor pressure at the station location, is the surface air pressure at the station location, , , , is the regression coefficient to be estimated, is the residual; The regression coefficients are estimated by the least squares method to minimize the residual sum of squares: ; in, is the ground temperature at the measuring station at the jth moment, is the surface water vapor pressure at the measuring station at the jth moment, is the surface air pressure at the jth moment of the measuring station; j is the time sequence number in the downloaded data set, j=1,2,…,M, M is the total number of time series in the data set; After least squares regression, we can get Model: .

[0009] In a further technical solution, in step (2), the ground dew point temperature of each grid point is used to calculate the ground water vapor pressure of each grid point according to the following formula: ; in, represents the ground water vapor pressure at the i-th grid point at the j-th moment, Represents the ground dew point temperature at the i-th grid point at the j-th moment.

[0010] In a further technical solution, in step (2), the formula for calculating the height of each pressure altitude layer at each grid point using the potential of each pressure altitude layer at each grid point is as follows: ; in, represents the height of the kth layer at the jth moment at the i-th grid point, is the gravitational acceleration value corresponding to the latitude grid, is the radius of the Earth, is the potential of the kth layer at the jth moment at the i-th grid point, is the potential height of the kth layer at the jth moment at the i-th grid point.

[0011] In a further technical solution, in step (2), the formula for calculating the water vapor pressure of each pressure layer at each grid point using the relative humidity of each pressure layer at each grid point is as follows: ; in, represents the water vapor pressure of the kth layer at the jth time at the i-th grid point, is the relative humidity at the i-th grid point at the j-th moment, is the temperature of the kth layer at the jth moment at the i-th grid point, and the constant The value is 6.1121, constant The value is 17.502, constant The value is 240.97.

[0012] In a further technical solution, in step (3), the method of inverse distance weighted horizontal interpolation is as follows: Assume that the latitude and longitude of the station are and , the longitude and latitude of the four adjacent grid points around the station are expressed as and , i=1,2,3,4; , , , They represent the ground temperature at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the surface water vapor pressure at the jth moment at the four neighboring grid points around the station; , , , They represent the surface air pressure at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the height of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the temperature of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the water vapor pressure of the kth layer at the jth moment at the four neighboring grid points around the station; The ground temperature at the measuring station at the jth moment is , surface pressure and surface water pressure , and the height of the kth layer at the jth moment of the station position ,temperature , Vapor Pressure It is expressed as: ; in, is the weight, expressed as: ; in, is the distance from the station to the four neighboring grid points. is the radius of the Earth, Calculate as follows: .

[0013] In a further technical solution, in step (4), the weighted average temperature of the atmosphere is calculated The formula is as follows: ; in, It is expressed as the weighted average temperature of the atmosphere at the jth time station location, is the height difference between two adjacent floors; is the water vapor pressure of the kth layer at the jth moment at the measuring station, is the temperature of the kth layer at the jth moment at the measuring station.

[0014] In the above scheme, in step 3, the measured ground temperature, ground water vapor pressure and ground air pressure are used to calculate the atmospheric weighted average temperature model. ,Will Substitute the numerical value into the water vapor conversion coefficient formula and calculate the water vapor conversion coefficient: ; In the formula, is the water vapor conversion coefficient, and are the density of liquid water and the gas constant of water vapor, respectively. and , and are constants, and their values ​​are and .

[0015] In the above scheme, in step 4, the tropospheric atmospheric precipitable water is calculated by combining the tropospheric zenith wet delay and the water vapor conversion coefficient:

[0016] Where PWV is the atmospheric precipitable water in the troposphere, ZWD is the zenith wet delay in the troposphere, is the water vapor conversion coefficient.

[0017] Through the above technical solution, the real-time monitoring method of atmospheric precipitable water in the marine troposphere based on GNSS provided by the present invention has the following beneficial effects: 1. The present invention uses GNSS signals and meteorological sensors to coordinate observations, combines Beidou satellite-based broadcasting of PPP-B2b corrections and dual-frequency ionospheric error elimination technology, and obtains high-precision tropospheric zenith wet delay in real time; 2. Based on ERA5 reanalysis data, the present invention uses the least squares method to construct an atmospheric weighted average temperature model. Compared with the traditional atmospheric weighted average temperature model that relies on historical sounding data, the present invention gets rid of the dependence on local sounding observation data and breaks through the modeling limitations of areas with scarce sounding data such as oceans and plateaus. 3. The present invention uses the atmospheric weighted average temperature model and the meteorological elements at the measuring station location to calculate the atmospheric weighted average temperature and water vapor conversion coefficient. The tropospheric atmospheric precipitable water is calculated using the tropospheric zenith wet delay and water vapor conversion coefficient at the measuring station location; In summary, the method provided by the present invention uses high temporal and spatial coverage, passively received GNSS signals as signal sources, performs real-time precise single-point positioning at sea, extracts zenith tropospheric wet delay, and can monitor atmospheric precipitable water in real time with high precision in the absence of historical sounding data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0019] Figure 1 A schematic diagram of hardware used in a method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS disclosed in an embodiment of the present invention; Figure 2 A schematic flow chart of a method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS disclosed in an embodiment of the present invention; Figure 3 A comparison chart of ZWD obtained by real-time precise point positioning disclosed in an embodiment of the present invention and reference data; Figure 4 This is a comparison chart of atmospheric precipitable water monitored in real time by GNSS disclosed in an embodiment of the present invention and benchmark data. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0021] Take the real-time monitoring of atmospheric precipitable water by GNSS on a pontoon platform as an example. Figure 1 As shown in the figure, the hardware design mainly includes three parts: GNSS antenna, integrated weather station and equipment host. The equipment host includes: power module, signal processing module and data processing module. The GNSS antenna is connected to the equipment host through a feeder, and the signal processing module in the equipment host completes GNSS signal demodulation, decodes GNSS original signals and extracts GNSS original messages. The GNSS antenna and the integrated weather station are installed on the fence of the fourth deck of the pontoon. The installation height is consistent and both are installed vertically upward to avoid tilting or lying on the side. There is no other equipment near the installation position of the GNSS antenna to block the GNSS signal. The equipment host is installed in the pontoon laboratory. The integrated weather station is used to collect the station meteorological parameters of the GNSS antenna position, assist in positioning and tropospheric delay extraction. The power module supplies power to the integrated weather station and other modules; the signal processing module completes GNSS signal demodulation and decoding, and is connected to the data processing module through a network cable; the data processing module collects the data of the integrated weather station and the signal processing module to complete real-time precise single-point positioning and tropospheric delay extraction.

[0022] Based on the above hardware equipment, the present invention provides a real-time monitoring method for atmospheric precipitable water in the marine troposphere based on GNSS, such as Figure 2 As shown, the following steps are included: Step 1: use GNSS precise single point positioning to estimate the total tropospheric zenith delay of the measuring station, use meteorological element sensors to measure the meteorological elements of the measuring station to calculate the tropospheric zenith dry delay, and use the tropospheric zenith total delay and tropospheric zenith dry delay to calculate the tropospheric zenith wet delay of the measuring station; The specific method is as follows: (1) Using GNSS receivers to obtain dual-frequency raw observations, combined with the Beidou satellite-based broadcast PPP-B2b corrections, the ionospheric delay error is eliminated through ionosphere-free combination, and the actual observation value of the tropospheric zenith total delay (ZTD) is extracted; (2) Calculate the tropospheric zenith dry delay ZHD using meteorological elements: ; in, is the geographical latitude of the site, is the site air pressure, is the station elevation; (3) Calculate the zenith wet delay ZWD using the zenith total delay and zenith dry delay: ZWD=ZTD-ZHD; Among them, ZWD is the tropospheric zenith wet delay, ZTD is the tropospheric zenith total delay, and ZHD is the tropospheric zenith dry delay.

[0023] Step 2: Obtain ERA5 reanalysis data and construct an atmospheric weighted mean temperature model related to surface meteorological parameters through regression analysis; In the study of using GNSS to invert water vapor, the atmospheric weighted average temperature is an important parameter that will directly affect the inversion accuracy of water vapor. The atmospheric weighted average temperature is the weighted average of the atmospheric temperature at different altitudes, which is closely related to ground meteorological parameters (such as temperature, water vapor pressure, air pressure, etc.). Therefore, through the comprehensive analysis of these ground meteorological data, the atmospheric weighted average temperature can be estimated. Since there are mostly no sounding stations at sea, the ERA5 reanalysis data is used to analyze the relationship between the atmospheric weighted average temperature and ground meteorological parameters, and the least squares method is used to establish the atmospheric weighted average temperature model in the offshore area, which includes the following steps: (1) ERA5 reanalysis data of the four grid points closest to the observation station in terms of spatial distribution were obtained from the European Centre for Medium-Range Weather Forecasts, including surface meteorological data and upper-air meteorological data; the surface meteorological data included surface temperature, surface dew point temperature and surface air pressure, and the upper-air meteorological data included the potential, temperature and relative humidity of each pressure altitude layer; (2) Calculate the surface water vapor pressure at each grid point using the ground dew point temperature at each grid point, calculate the height of each pressure layer at each grid point using the potential of each pressure layer at each grid point, and calculate the water vapor pressure of each pressure layer at each grid point using the relative humidity of each pressure layer at each grid point; Specifically, the ground water vapor pressure formula for each grid point is calculated using the ground dew point temperature of each grid point as follows: ; in, represents the ground water vapor pressure at the i-th grid point at the j-th moment, Represents the ground dew point temperature at the i-th grid point at the j-th moment.

[0024] The formula for calculating the height of each pressure altitude layer at each grid point using the potential of each pressure altitude layer at each grid point is as follows: ; in, represents the height of the kth layer at the jth moment at the i-th grid point, is the gravitational acceleration value corresponding to the latitude grid, is the radius of the Earth, is the potential of the kth layer at the jth moment at the i-th grid point, is the potential height of the kth layer at the jth moment at the i-th grid point.

[0025] The formula for calculating the water vapor pressure at each pressure level at each grid point using the relative humidity at each pressure level at each grid point is as follows: ; in, represents the water vapor pressure of the kth layer at the jth time at the i-th grid point, is the relative humidity at the i-th grid point at the j-th moment, is the temperature of the kth layer at the jth moment at the i-th grid point, and the constant The value is 6.1121, constant The value is 17.502, constant The value is 240.97.

[0026] (3) Perform inverse distance weighted horizontal interpolation on the surface temperature, surface air pressure, surface water vapor pressure of each grid point, as well as the height, temperature, and water vapor pressure of each pressure altitude layer at each grid point, to obtain the surface temperature, surface air pressure, surface water vapor pressure corresponding to the measuring station location, as well as the height, temperature, and water vapor pressure of each pressure altitude layer above the measuring station location; Specifically, the method of inverse distance weighted horizontal interpolation is as follows: Assume that the latitude and longitude of the station are and , the longitude and latitude of the four adjacent grid points around the station are expressed as and , i=1,2,3,4; , , , They represent the ground temperature at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the surface water vapor pressure at the jth moment at the four neighboring grid points around the station; , , , They represent the surface air pressure at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the height of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the temperature of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the water vapor pressure of the kth layer at the jth moment at the four neighboring grid points around the station; The ground temperature at the measuring station at the jth moment is , surface pressure and surface water pressure , and the height of the kth layer at the jth moment of the station position ,temperature , Vapor Pressure It is expressed as: ; in, is the weight, expressed as: ; in, is the distance from the station to the four neighboring grid points. is the radius of the Earth, Calculate as follows: .

[0027] (4) Use the numerical integration method to integrate the temperature and water vapor pressure of each pressure layer above the measuring station along the zenith direction, and calculate the weighted average temperature of the atmosphere at the measuring station at the jth moment: ; Calculate the atmospheric weighted mean temperature The formula is as follows: ; in, It is expressed as the weighted average temperature of the atmosphere at the jth time station location, is the height difference between two adjacent floors; is the water vapor pressure of the kth layer at the jth moment at the measuring station, is the temperature of the kth layer at the jth moment at the measuring station.

[0028] (5) The least squares regression method is used to construct the atmospheric weighted average temperature model, namely T m The combined relationship between the ground temperature, ground water vapor pressure and ground air pressure at the measuring station location: ; Among them, T m is the weighted average temperature of the atmosphere at the station location, is the ground temperature at the measuring station, is the surface water vapor pressure at the station location, is the surface air pressure at the station location, , , , is the regression coefficient to be estimated, is the residual; The regression coefficients are estimated by the least squares method to minimize the residual sum of squares: ; in, is the ground temperature at the measuring station at the jth moment, is the surface water vapor pressure at the measuring station at the jth moment, is the surface air pressure at the jth moment of the measuring station; j is the time sequence number in the downloaded data set, j=1,2,…,M, M is the total number of time series in the data set; After least squares regression, we can get the value used to calculate T m Model: .

[0029] Step 3, using the atmospheric weighted average temperature model and combining the meteorological elements at the measuring station location, calculate the atmospheric weighted average temperature and water vapor conversion coefficient; T is calculated using the atmospheric weighted average temperature model using the measured ground temperature, ground water vapor pressure and ground air pressure. m , T m Substitute the numerical value into the water vapor conversion coefficient formula to calculate the water vapor conversion coefficient: ; In the formula, is the water vapor conversion coefficient, and are the density of liquid water and the gas constant of water vapor, respectively. and , and are constants, and their values ​​are and .

[0030] Step 4: Calculate the tropospheric atmospheric precipitable water using the tropospheric zenith wet delay and water vapor conversion coefficient at the station location.

[0031] The tropospheric atmospheric precipitable water is calculated by combining the tropospheric zenith wet delay and the water vapor conversion coefficient: ; Where PWV is the atmospheric precipitable water in the troposphere, ZWD is the zenith wet delay in the troposphere, is the water vapor conversion coefficient.

[0032] In order to evaluate the accuracy of the method of the present invention, the ZWD result obtained by post-processing the online solution platform of the Canadian Spatial Reference System Precision Point Positioning (CSRS-PPP) is used as a benchmark to evaluate the accuracy of ZWD obtained by real-time precise point positioning, and the atmospheric precipitable water calculated by the sounding data of the offshore sounding station is used as a benchmark to evaluate the accuracy of GNSS real-time inversion of atmospheric precipitable water. Figure 3 As shown in FIG. 1 , CSRS-ZWD represents the reference ZWD obtained by post-processing, and PPP-ZWD represents the ZWD obtained by real-time precise point positioning of the present invention. The root mean square error between the ZWD obtained by real-time precise point positioning and the reference data is 10.06 mm. Figure 4 As shown in the figure, RS-PWV represents the atmospheric precipitable water benchmark calculated by sounding data, and GNSS-PWV represents the atmospheric precipitable water inverted by GNSS in real time in the present invention. The root mean square error between the atmospheric precipitable water inverted by GNSS in real time and the benchmark data is 1.51 mm. The test results show that the real-time monitoring method of atmospheric precipitable water in the marine troposphere based on GNSS provided by the present invention is effective. In the figure, DOY is the annual accumulated day, that is, January 1 of each year is the first day of the year, and the right side is accumulated to 365 in sequence.

[0033] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS, characterized in that: The steps include: Step 1: use GNSS precise single point positioning to estimate the total tropospheric zenith delay of the measuring station, use meteorological element sensors to measure the meteorological elements of the measuring station to calculate the tropospheric zenith dry delay, and use the tropospheric zenith total delay and tropospheric zenith dry delay to calculate the tropospheric zenith wet delay of the measuring station; Step 2: Obtain ERA5 reanalysis data and construct an atmospheric weighted mean temperature model related to surface meteorological parameters through regression analysis; Step 3, using the atmospheric weighted average temperature model and combining the meteorological elements at the measuring station location, calculate the atmospheric weighted average temperature and water vapor conversion coefficient; Step 4: Calculate the tropospheric atmospheric precipitable water using the tropospheric zenith wet delay and water vapor conversion coefficient at the station location.

2. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 1, characterized in that: In step 1, the method for obtaining the actual observed values ​​of the zenith total delay, dry delay, and wet delay is as follows: (1) Using GNSS receivers to obtain dual-frequency raw observations, combined with the Beidou satellite-based broadcast PPP-B2b corrections, the ionospheric delay error is eliminated through ionosphere-free combination, and the actual observation value of the tropospheric zenith total delay (ZTD) is extracted; (2) Calculate the tropospheric zenith dry delay ZHD using meteorological elements: ； in, is the geographical latitude of the site, is the site air pressure, is the station elevation; (3) Calculate the zenith wet delay ZWD using the zenith total delay and zenith dry delay: ZWD=ZTD-ZHD; Among them, ZWD is the tropospheric zenith wet delay, ZTD is the tropospheric zenith total delay, and ZHD is the tropospheric zenith dry delay.

3. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 1, characterized in that: In step 2, the weighted average temperature of the atmosphere T m The ERA5 reanalysis dataset is used to construct the weighted average temperature T of the atmosphere at sea. m The model specifically includes the following steps: (1) Obtain ERA5 reanalysis data of the four grid points closest to the observation station in terms of spatial distribution from the European Centre for Medium-Range Weather Forecasts, including surface meteorological data and upper-air meteorological data; the surface meteorological data include surface temperature, surface dew point temperature and surface air pressure, and the upper-air meteorological data include the potential, temperature and relative humidity of each pressure altitude layer; (2) Calculate the surface water vapor pressure at each grid point using the ground dew point temperature at each grid point, calculate the height of each pressure layer at each grid point using the potential of each pressure layer at each grid point, and calculate the water vapor pressure of each pressure layer at each grid point using the relative humidity of each pressure layer at each grid point; (3) Perform inverse distance weighted horizontal interpolation on the surface temperature, surface air pressure, surface water vapor pressure of each grid point, as well as the height, temperature, and water vapor pressure of each pressure altitude layer at each grid point, to obtain the surface temperature, surface air pressure, surface water vapor pressure corresponding to the measuring station location, as well as the height, temperature, and water vapor pressure of each pressure altitude layer above the measuring station location; (4) Use the numerical integration method to integrate the temperature and water vapor pressure of each pressure layer above the measuring station along the zenith direction, and calculate the weighted average temperature of the atmosphere at the measuring station at the jth moment: ; (5) The least squares regression method is used to construct the atmospheric weighted average temperature model, namely T m The combined relationship between the ground temperature, ground water vapor pressure and ground air pressure at the measuring station location: ； Among them, T m is the weighted average temperature of the atmosphere at the station location, is the ground temperature at the measuring station, is the surface water vapor pressure at the station location, is the surface air pressure at the station location, , , , is the regression coefficient to be estimated, is the residual; The regression coefficients are estimated by the least squares method to minimize the residual sum of squares: ； in, is the ground temperature at the measuring station at the jth moment, is the surface water vapor pressure at the measuring station at the jth moment, is the surface air pressure at the jth moment of the measuring station; j is the time sequence number in the downloaded data set, j=1,2,…,M, M is the total number of time series in the data set; After least squares regression, we can get Model: 。 4. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 3, characterized in that: In step (2), the ground dew point temperature of each grid point is used to calculate the ground water vapor pressure of each grid point as follows: ； in, represents the ground water vapor pressure at the i-th grid point at the j-th moment, Represents the ground dew point temperature at the i-th grid point at the j-th moment.

5. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 3, characterized in that: In step (2), the formula for calculating the height of each pressure altitude layer at each grid point using the potential of each pressure altitude layer at each grid point is as follows: ； in, represents the height of the kth layer at the jth moment at the i-th grid point, is the gravitational acceleration value corresponding to the latitude grid, is the radius of the Earth, is the potential of the kth layer at the jth moment at the i-th grid point, is the potential height of the kth layer at the jth moment at the i-th grid point.

6. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 3, characterized in that: In step (2), the formula for calculating the water vapor pressure of each pressure layer at each grid point using the relative humidity of each pressure layer at each grid point is as follows: ； in, represents the water vapor pressure of the kth layer at the jth time at the i-th grid point, is the relative humidity at the i-th grid point at the j-th moment, is the temperature of the kth layer at the jth moment at the i-th grid point, and the constant The value is 6.1121, constant The value is 17.502, constant The value is 240.

97.

7. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 3, characterized in that: In step (3), the method of inverse distance weighted horizontal interpolation is as follows: Assume that the latitude and longitude of the station are and , the longitude and latitude of the four adjacent grid points around the station are expressed as and , i=1,2,3,4; , , , They represent the ground temperature at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the surface water vapor pressure at the jth moment at the four neighboring grid points around the station; , , , They represent the surface air pressure at the jth moment at the four adjacent grid points around the measuring station; , , , They represent the height of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the temperature of the kth layer at the jth moment at the four neighboring grid points around the measuring station; , , , They represent the water vapor pressure of the kth layer at the jth moment at the four neighboring grid points around the station; The ground temperature at the measuring station at the jth moment is , surface pressure and surface water pressure , and the height of the kth layer at the jth moment of the station position ,temperature , water vapor pressure It is expressed as: ； in, is the weight, expressed as: ； in, is the distance from the station to the four neighboring grid points. is the radius of the Earth, Calculate as follows: 。 8. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 7, characterized in that: In step (4), calculate the weighted average temperature of the atmosphere The formula is as follows: ； in, It is expressed as the weighted average temperature of the atmosphere at the jth time station location, is the height difference between two adjacent floors; is the water vapor pressure of the kth layer at the jth moment at the measuring station, is the temperature of the kth layer at the jth moment at the measuring station.

9. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 1, characterized in that: In step 3, the measured ground temperature, ground water vapor pressure and ground air pressure are used to calculate the atmospheric weighted average temperature model. ,Will Substitute the numerical value into the water vapor conversion coefficient formula to calculate the water vapor conversion coefficient: ； In the formula, is the water vapor conversion coefficient, and are the density of liquid water and the gas constant of water vapor, respectively. and , and are constants, and their values ​​are and .

10. The method for real-time monitoring of atmospheric precipitable water in the marine troposphere based on GNSS according to claim 1, characterized in that: In step 4, the tropospheric atmospheric precipitable water is calculated by combining the tropospheric zenith wet delay and the water vapor conversion coefficient: ； Where PWV is the atmospheric precipitable water in the troposphere, ZWD is the zenith wet delay in the troposphere, is the water vapor conversion coefficient.

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