CN111881581B - Method and system for establishing three-dimensional water vapor grid model - Google Patents
Method and system for establishing three-dimensional water vapor grid model Download PDFInfo
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Abstract
According to the method and the system for establishing the three-dimensional water vapor grid model, the ZWD is inverted by using GNSS data, so that PWV is calculated, PWV is calculated by using data of a sounding station, and the two are subjected to data fusion by using least square difference estimation. And acquiring an atmospheric profile by using the occultation data and the sounding data, extracting meteorological factors in the atmospheric profile, determining time and space references of depth fusion on the basis of GNSS/sounding/occultation inversion vapor, and establishing a grid vapor model based on multi-source data. The technical scheme provided by the invention breaks through the limitation of taking the whole troposphere as a research object, and the built layered water vapor model can carry out fine extraction on water vapor data, thereby providing a theoretical basis for fine weather forecast and having a certain practical significance.
Description
Technical Field
The invention relates to the field of GNSS meteorology, in particular to a method and a system for establishing a three-dimensional water vapor grid model.
Background
Temperature and moisture are two important indicators of global change monitoring. Global warming is a prominent manifestation of global changes, and under the global climate background taking the global warming as a main characteristic, extreme weather and climate events are frequent, and are extremely easy to cause storm disaster weather, so that flood disasters and serious water and soil loss are caused, and casualties and great economic losses are caused. The accuracy of the water vapor monitoring technology is improved, and the method has certain social and economic values.
The global navigation satellite system (GlobalNavigation Satellite System, GNSS) inverts a water vapor deepening GNSS technology application mode, promotes discipline cross fusion and accords with the long-term development planning in national satellite navigation. The Beidou satellite navigation system (Bei DouNavigation Satellite System, BDS) is a satellite navigation positioning technology which is greatly developed in China and becomes an important component of GNSS. The final completion of the system can provide high-precision and high-reliability navigation positioning service, and can be applied to various fields such as weather and environment monitoring. In 2013, the national seal "long-term development planning in national satellite navigation industry", the GNSS theory and the application research thereof accord with the national long-term planning, and the Beidou satellite navigation system and compatible products thereof are widely applied in important national economy industry and key fields, and are gradually popularized in mass consumption markets. The key development direction comprises innovation industry application, expansion of mass application modes and the like. The GNSS dynamic monitoring water vapor belongs to two major development key points of industrial innovation application and mass application mode expansion, and has great application value.
The water vapor and atmospheric profile calculation by using sounding data is the most accurate technology at present, the distance between sounding stations is more than 200-300km, the sounding stations are observed once at intervals of 12 hours, and the spatial and temporal distribution is sparse, so that the global water vapor field and water vapor energy circulation are not thoroughly known. In addition, due to the strong noise background signal, the satellite radiometer is difficult to provide useful ground information, and the requirements of monitoring and forecasting medium-small scale disastrous weather can not be met, so that the satellite radiometer becomes one of important reasons for the disastrous weather miss report.
Foundation GNSS makes use of continuous measurements of dense ground station networks, which has unique advantages in monitoring severe weather such as densely populated areas and airports, while occultation observations provide convenience for studying climate change related to the early-ocean, deep-sea events. By using a foundation GNSS network with denser measuring stations, three-dimensional distribution of water vapor can be obtained through GNSS/sounding/occultation data fusion, a high-precision water vapor field is provided for a numerical weather forecast mode, and continuous atmospheric precipitation (Precipitable Water Vapor, PWV) data are obtained, so that the acquisition of the water vapor field becomes abnormal and precious.
However, no model capable of extracting refined water vapor information is available in the prior art to provide a theoretical basis for refined weather forecast.
Disclosure of Invention
The invention aims to provide a method and a system for establishing a three-dimensional water vapor grid model, so that water vapor information can be extracted in a refined mode, and a theoretical basis is provided for refined weather forecast.
In order to achieve the above object, the present invention provides the following solutions:
a method of creating a three-dimensional water vapor mesh model comprising:
acquiring GNSS observation data and sounding station layering data; the sounding station hierarchy data includes: liquid water density, vapor density in the atmosphere, overall troposphere height, vapor pressure and absolute temperature;
adopting GNSS data processing and analysis software to determine delay caused when satellite signals longitudinally pass through a troposphere to reach the ground according to the GNSS observation data;
determining the total delay of the troposphere of the station measurement receiver in the zenith direction according to the delay inversion;
separating according to the total delay to obtain zenith wet delay;
determining a first atmospheric precipitation amount according to the zenith wet delay;
determining the atmospheric precipitation amount of the air above the measuring station by adopting the layering data of the sounding station to obtain a second atmospheric precipitation amount;
constructing a GNSS/sounding water vapor model according to the first atmospheric precipitation amount and the second atmospheric precipitation amount; the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation;
determining occultation data and sounding data according to the GNSS/sounding water vapor model;
determining an atmospheric profile according to the occultation data and the sounding data;
acquiring preset same starting time and preset space interval;
determining unified time and space references according to the preset same starting time and the preset space interval;
extracting meteorological factors in the atmospheric profile according to the unified time and space references;
determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors;
and constructing a three-dimensional water vapor grid model according to the atmospheric precipitation.
Preferably, the separating to obtain zenith wet delay according to the total delay specifically includes:
acquiring latitude of a measuring station, ground height and air pressure of a position where the measuring station is located;
determining zenith dry delay from the latitude, the geodetic altitude and the barometric pressure; the zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure;
determining zenith wet delay from the zenith dry delay and the total delay; the zenith wet delay is:
ZWD＝ZTD-ZHD；
where ZWD is zenith wet delay and ZTD is total delay.
Preferably, the determining the first atmospheric precipitation amount according to the zenith wet delay specifically includes:
using the formula PWV 1 Pi·zwd, determining a first atmospheric precipitation PWV from the zenith wet delay 1 ；
Wherein ZWD is zenith wet delay, and pi is dimensionless scale factor.
Preferably, the determining the atmospheric precipitation amount of the air above the measuring station by adopting the layer data of the sounding station to obtain the second atmospheric precipitation amount specifically includes:
using the formulaDetermining the second atmospheric precipitation PWV from the probe station stratification data 2 ；
Wherein ρ is water Is the liquid water density ρ w R is the density of water vapor in the atmosphere v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapor pressure, T is the absolute temperature.
Preferably, the extracting weather factors in the atmospheric profile according to the unified time and space reference specifically includes:
layering the atmospheric profile according to a preset height;
the average temperature, air pressure and water vapor pressure of each layer are taken as dependent variables, and a formula is adopted
Determining weather layering factors of each layer;
determining the meteorological factors according to the meteorological layering factors;
wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value.
Preferably, the determining the atmospheric precipitation amount in the whole troposphere according to the extracted meteorological factors specifically includes:
determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors by adopting a formula PWV (i) =qx (i) ×pwv;
wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
A system for building a three-dimensional water vapor mesh model, comprising:
the first acquisition module is used for acquiring GNSS observation data and sounding station layering data; the sounding station hierarchy data includes: liquid water density, vapor density in the atmosphere, overall troposphere height, vapor pressure and absolute temperature;
the delay amount determining module is used for determining the delay amount caused when the satellite signal longitudinally passes through the troposphere to reach the ground according to the GNSS observation data by adopting GNSS data processing and analyzing software;
the total delay determining module is used for determining the total delay of the troposphere of the station measurement receiver in the zenith direction according to the delay inversion;
the zenith wet delay determining module is used for separating to obtain zenith wet delay according to the total delay;
the first atmospheric precipitation determining module is used for determining the first atmospheric precipitation according to the zenith wet delay;
the second atmospheric precipitation determining module is used for determining the atmospheric precipitation above the measuring station by adopting the sounding station layering data to obtain the second atmospheric precipitation;
the GNSS/sounding water vapor model construction module is used for constructing a GNSS/sounding water vapor model according to the first atmospheric precipitation and the second atmospheric precipitation; the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation;
the occultation data determining module is used for determining occultation data and sounding data according to the GNSS/sounding water vapor model;
the atmosphere profile determining module is used for determining an atmosphere profile according to the occultation data and the sounding data;
the second acquisition module is used for acquiring preset same starting time and preset space interval;
the time and space reference determining module is used for determining unified time and space references according to the preset same starting time and the preset space interval;
the meteorological factor extraction module is used for extracting meteorological factors in the atmospheric profile according to the unified time and space references;
the atmospheric precipitation determining module is used for determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors;
and the three-dimensional water vapor grid model construction module is used for constructing a three-dimensional water vapor grid model according to the atmospheric precipitation.
Preferably, the zenith wet delay determining module specifically includes:
the acquisition unit is used for acquiring the latitude of the measuring station, the ground height of the position and the air pressure;
a zenith dry delay determining unit configured to determine a zenith dry delay according to the latitude, the ground altitude, and the air pressure; the zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure;
a zenith wet delay determination unit configured to determine a zenith wet delay from the zenith dry delay and the total delay; the zenith wet delay is:
ZWD＝ZTD-ZHD；
where ZWD is zenith wet delay and ZTD is total delay.
Preferably, the first atmospheric precipitation amount determining module specifically includes:
a first atmospheric precipitation amount determination unit for applying the formula PWV 1 Pi·zwd, determining a first atmospheric precipitation PWV from the zenith wet delay 1 ；
Wherein ZWD is zenith wet delay, and pi is a dimensionless scale factor;
the second atmospheric precipitation amount determining module specifically includes:
a second atmospheric precipitation amount determination unit for applying the formulaDetermining the second atmospheric precipitation PWV from the probe station stratification data 2 ；
Wherein ρ is water Is the liquid water density ρ w R is the density of water vapor in the atmosphere v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapor pressure, T is the absolute temperature.
Preferably, the meteorological factor extraction module specifically includes:
the layering unit is used for layering the atmospheric profile according to a preset height;
a weather layering factor determining unit for using average temperature, air pressure and water vapor pressure of each layer as dependent variables and adopting formulaDetermining weather layering factors of each layer;
the weather factor determining unit is used for determining the weather factor according to the weather layering factor;
wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value.
The atmospheric precipitation amount determination module specifically includes:
an atmospheric precipitation amount determination unit configured to determine an atmospheric precipitation amount in the entire troposphere using a formula PWV (i) =qx (i) ×pwv, based on the extracted meteorological factors;
wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the method and the system for establishing the three-dimensional water vapor grid model, provided by the invention, the atmospheric profile is determined by using the sounding/occultation data, the time and space references of depth fusion are determined, the grid water vapor model based on multi-source data is established, the limitation that the whole troposphere is taken as a research object in the traditional technology is broken through, the fine extraction of water vapor information is realized, and a theoretical basis is provided for fine weather forecast.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for establishing a three-dimensional water vapor grid model provided by the invention;
FIG. 2 is a general block diagram of a method for creating a three-dimensional water vapor mesh model provided in an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a system for creating a three-dimensional water vapor grid model according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method and a system for establishing a three-dimensional water vapor grid model, so that water vapor information can be extracted in a refined mode, and a theoretical basis is provided for refined weather forecast.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Fig. 1 is a flowchart of a method for establishing a three-dimensional water vapor grid model according to the present invention, as shown in fig. 1, a method for establishing a three-dimensional water vapor grid model includes:
step 100: GNSS observation data and sounding station hierarchy data are acquired. The sounding station hierarchy data includes: liquid water density, atmospheric water vapor density, overall tropospheric height, vapor pressure and absolute temperature.
Step 101: and determining the delay caused by the satellite signal when the satellite signal longitudinally passes through the troposphere to reach the ground according to the GNSS observation data by adopting GNSS data processing and analyzing software.
Step 102: and determining the total delay of the troposphere of the station measurement receiver in the zenith direction according to the delay inversion.
Step 103: and separating according to the total delay to obtain zenith wet delay. The step 103 specifically includes:
step 1031: the latitude of the measuring station, the ground height of the position and the air pressure are obtained.
Step 1032: and determining zenith dry delay according to the latitude, the ground altitude and the air pressure. The zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure.
Step 1033: and determining zenith wet delay according to the zenith dry delay and the total delay. The zenith wet delay is:
ZWD＝ZTD-ZHD。
where ZWD is zenith wet delay and ZTD is total delay.
By linking the ZWD to the weather parameters, precipitation information important in climate research and weather forecast is obtained.
Step 104: and determining the first atmospheric precipitation amount according to the zenith wet delay. The method specifically comprises the following steps:
using the formula PWV 1 Pi·zwd, determining a first atmospheric precipitation PWV from the zenith wet delay 1 。
Wherein ZWD is zenith wet delay, pi is a dimensionless scale factor, and the relational expression is:
wherein R is v Is the constant of water vapor and is usually takenk' 2 、k 3 Is the atmospheric refraction factor, T m For the atmosphere weighted average temperature, the surface temperature T is established by using a Bevis model s And an atmospheric weighted average temperature T m Linear relation of (c):
T m ＝a+b*T s ,a＝70.2,b＝0.72。
step 105: and determining the atmospheric precipitation amount of the air above the measuring station by adopting the layering data of the sounding station to obtain the second atmospheric precipitation amount. The process comprises the following steps:
using the formulaDetermining the second atmospheric precipitation PWV from the probe station stratification data 2 。
Wherein ρ is water Is of liquid water density (10) 3 kg/m 3 )，ρ w Is the density (g/m) of water vapor in the atmosphere 3 )，R v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapour pressure (hpa), T is the absolute temperature (K).
Step 106: and constructing a GNSS/sounding water vapor model according to the first atmospheric precipitation amount and the second atmospheric precipitation amount. And the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation.
Step 107: and determining occultation data and sounding data according to the GNSS/sounding water vapor model.
Step 108: and determining an atmospheric profile according to the occultation data and the sounding data.
Step 109: and acquiring preset same starting time and preset space interval.
Step 110: and determining unified time and space references according to the preset same starting time and the preset space interval.
Step 111: and extracting meteorological factors in the atmosphere profile according to the unified time and space references. The method specifically comprises the following steps:
step 1111: layering the atmospheric profile according to a preset height.
Step 1112: the average temperature, air pressure and water vapor pressure of each layer are taken as dependent variables, and a formula is adoptedThe weather stratification factor for each layer is determined.
Step 1113: and determining the meteorological factors according to the meteorological layering factors.
Wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value.
Step 112: and determining the atmospheric precipitation amount in the whole troposphere according to the extracted meteorological factors. The method comprises the following steps:
the atmospheric precipitation in the whole troposphere is determined according to the extracted meteorological factors using the formula PWV (i) =qx (i) ×pwv.
Wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
Step 113: and constructing a three-dimensional water vapor grid model according to the atmospheric precipitation.
The sounding observation records the temperature, air pressure, humidity and other information in the atmosphere at different heights through the sensor on the sounding balloon. The radio satellite-occultation technology obtains the information of water vapor and other physical parameters of the earth atmosphere by observing the bending degree of a GNSS radio signal from the earth atmosphere, after the system works normally, the COSIC satellite performs about 2500 observations at the place which is almost uniformly distributed worldwide every 24 hours, after each observation is processed, the wet atmospheric profile directly gives out the atmospheric temperature, pressure and humidity profile with 100m as interval in the 0-40km altitude interval, and the high-vertical resolution observation data greatly make up the shortages of the conventional sounding data, especially for the areas lacking sounding observation such as plateau, desert, two poles and ocean.
In order to further improve the fineness of the extracted water vapor information, in the method for establishing the three-dimensional water vapor grid model, the atmospheric profile is preferably obtained by using the occultation data and the sounding data, and the atmospheric profile is layered along the vertical direction according to different heights. And (3) realizing optimal weighting of two data by adopting an MINQUE variance component estimation method, and establishing a unified water vapor model. The MINQUE model is proposed based on the mathematical statistics theory and can be used for directly estimating the variance-covariance matrix of the observed value. Assume that the variance-covariance matrix can be written as:
where m=n (n-1)/2 represents the number of variance components, [ θ ] 1 ,θ 2 ,L,θ m ]Each variance component in the upper triangular matrix, which is the variance-covariance matrix, [ T ] 1 ,T 2 ,…,T m ]Is the corresponding companion matrix. Constructing arbitrary linear function of variance component Ω=g 1 θ 1 +g 2 θ 2 +…+g m θ m And selecting a quadratic form l of the observation vector l under the Gaussian-Markov model T Ml, and requires invariance, unbiasedness, and minimum norm conditions. Let M be the minimum trace problem by solving the following matrix:
wherein A is a model coefficient arrayM is a quadratic positive definite matrix, namely a substitution matrix, alpha= (g) 1 g 2 ··· g m ) T Is a known m-dimensional vector, (θ) 1 θ 2 ··· θ m ) A solution l obtained by solving the linear equation set (8) as a unit weight variance component T Ml, the quadratic form is a minimum norm quadratic unbiased estimate of Ω. Accordingly, the variance component estimate is obtained as:
in the formula, the (i, j) th element S of the matrix S i,j ＝tr(RT i RT j ) The i-th element q of the vector q i ＝l T RT i Rl，R=c -1 [E-A(A T C -1 A) -1 A T C -1 ]E is an identity matrix, so->In the calculation process, theta is solved by iteration, namely, theta is given as an initial value theta 0 The jth iteration value is +.>When the variance component difference before and after the iteration is smaller than a certain tiny amount, the iteration is terminated. At this time, a variance-covariance matrix of the MINQUE model is obtained, so that an optimal weighting scheme of two heterogeneous data is determined, and an atmospheric profile model is built by optimal fusion.
The general block diagram for realizing the method for establishing the three-dimensional water vapor grid model provided by the invention is shown in figure 2.
In addition, for the method for establishing a three-dimensional water vapor grid model provided in the invention, the invention correspondingly provides a system for establishing a three-dimensional water vapor grid model, as shown in fig. 3, the system comprises: the system comprises a first acquisition module 1, a delay amount determination module 2, a total delay determination module 3, a zenith wet delay determination module 4, a first atmospheric precipitation amount determination module 5, a second atmospheric precipitation amount determination module 6, a GNSS/sounding water vapor model construction module 7, a occultation sounding data determination module 8, an atmospheric profile determination module 9, a second acquisition module 10, a time and space reference determination module 11, a meteorological factor extraction module 12, an atmospheric precipitation amount determination module 13 and a three-dimensional water vapor grid model construction module 14.
The first acquisition module 1 is used for acquiring GNSS observation data and sounding station layering data. The sounding station hierarchy data includes: liquid water density, atmospheric water vapor density, overall tropospheric height, vapor pressure and absolute temperature.
The delay amount determining module 2 is configured to determine, using GNSS data processing and analysis software, an amount of delay caused when the satellite signal passes longitudinally through the troposphere to reach the ground based on the GNSS observations.
The total delay determining module 3 is used for determining the total delay of the troposphere of the station-measuring receiver in the zenith direction according to the delay amount inversion.
The zenith wet delay determination module 4 is used for separating to obtain zenith wet delay according to the total delay.
The first atmospheric precipitation level determination module 5 is configured to determine a first atmospheric precipitation level based on the zenith wet delay.
The second atmospheric precipitation amount determining module 6 is used for determining the atmospheric precipitation amount of the air above the measuring station by adopting the layer data of the sounding station to obtain the second atmospheric precipitation amount.
The GNSS/sounding water vapor model construction module 7 is configured to construct a GNSS/sounding water vapor model from the first atmospheric precipitation and the second atmospheric precipitation. And the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation.
The occultation data determining module 8 is configured to determine occultation data and sounding data according to the GNSS/sounding water vapor model.
The atmospheric profile determination module 9 is configured to determine an atmospheric profile from the occultation data and the sounding data.
The second acquiring module 10 is configured to acquire a preset same starting time and a preset space interval.
The time and space reference determining module 11 is configured to determine a unified time and space reference according to the preset same starting time and the preset space interval.
The weather factor extraction module 12 is configured to extract weather factors in the atmospheric profile based on the unified temporal and spatial references.
The atmospheric precipitation determination module 13 is configured to determine the amount of atmospheric precipitation in the entire troposphere based on the meteorological factors extracted.
The three-dimensional water vapor mesh model construction module 14 is configured to construct a three-dimensional water vapor mesh model from the atmospheric precipitation.
As a preferred embodiment of the present invention, the zenith wet delay determining module 4 specifically includes: the device comprises an acquisition unit, a zenith dry delay determination unit and a zenith wet delay determination unit.
The acquisition unit is used for acquiring the latitude of the measuring station, the ground height of the position and the air pressure.
The zenith dry delay determining unit is used for determining zenith dry delay according to the latitude, the ground altitude and the air pressure. The zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure.
The zenith wet delay determination unit is used for determining the zenith wet delay according to the zenith dry delay and the total delay. The zenith wet delay is:
ZWD＝ZTD-ZHD。
where ZWD is zenith wet delay and ZTD is total delay.
As another preferred embodiment of the present invention, the first atmospheric precipitation amount determination module 5 specifically includes: a first atmospheric precipitation amount determination unit.
Wherein the first atmospheric precipitation amount determination unit is configured to employ the formula PWV 1 Pi·zwd, determining a first atmospheric precipitation PWV from the zenith wet delay 1 。
Wherein ZWD is zenith wet delay, and pi is dimensionless scale factor.
The second atmospheric precipitation amount determination module 6 specifically includes: a second atmosphere precipitation amount determination unit.
Wherein the second atmospheric precipitation amount determination unit is configured to employ a formula
Determining the second atmospheric precipitation PWV from the probe station stratification data 2 。
Wherein ρ is water Is the liquid water density ρ w R is the density of water vapor in the atmosphere v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapor pressure, T is the absolute temperature.
As another preferred embodiment of the present invention, the weather factor extraction module 12 specifically includes: the system comprises a layering unit, a meteorological layering factor determining unit and an meteorological factor determining unit.
The layering unit is used for layering the atmospheric profile according to a preset height.
The weather layering factor determining unit is used for taking the average temperature, the air pressure and the water vapor pressure of each layer as dependent variables and adopting a formulaThe weather stratification factor for each layer is determined.
The weather factor determining unit is used for determining the weather factor according to the weather layering factor.
Wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value.
The atmospheric precipitation amount determination module 13 specifically includes: an atmospheric precipitation amount determination unit.
Wherein the atmospheric precipitation amount determination unit is configured to determine the atmospheric precipitation amount in the entire troposphere using the formula PWV (i) =qx (i) ×pwv according to the extracted meteorological factor.
Wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
In the method and the system for establishing the three-dimensional water vapor grid model, the ZWD is inverted by using GNSS data, so as to calculate PWV, meanwhile, the PWV is calculated by using the data of the exploration station, and the two are subjected to data fusion by using least square difference estimation.
And acquiring an atmospheric profile by using the occultation data and the sounding data, and layering the atmospheric profile along the vertical direction according to different heights. Meteorological factors in the atmospheric profile are extracted, the same starting time and space interval are set, and unified time and space references are established. And (3) realizing the optimal weighting of three data by using an MINQUE variance component estimation method, and calculating PWV on the height of each layer to obtain a three-dimensional water vapor model.
The method is to determine time and space references of depth fusion based on GNSS/sounding/occultation inversion water vapor, and establish a grid water vapor model based on multi-source data. The invention breaks through the limitation of taking the traditional whole troposphere as a research object, and the built layered water vapor model can extract the refined precipitation relation, provides a theoretical basis for refined weather forecast and has a certain practical significance.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A method of creating a three-dimensional water vapor mesh model comprising:
acquiring GNSS observation data and sounding station layering data; the sounding station hierarchy data includes: liquid water density, vapor density in the atmosphere, overall troposphere height, vapor pressure and absolute temperature;
adopting GNSS data processing and analysis software to determine delay caused when satellite signals longitudinally pass through a troposphere to reach the ground according to the GNSS observation data;
determining the total delay of the troposphere of the station measurement receiver in the zenith direction according to the delay inversion;
separating according to the total delay to obtain zenith wet delay;
determining a first atmospheric precipitation amount according to the zenith wet delay;
determining the atmospheric precipitation amount of the air above the measuring station by adopting the layering data of the sounding station to obtain a second atmospheric precipitation amount;
constructing a GNSS/sounding water vapor model according to the first atmospheric precipitation amount and the second atmospheric precipitation amount; the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation;
determining occultation data and sounding data according to the GNSS/sounding water vapor model;
determining an atmospheric profile according to the occultation data and the sounding data;
acquiring preset same starting time and preset space interval;
determining unified time and space references according to the preset same starting time and the preset space interval;
extracting meteorological factors in the atmospheric profile according to the unified time and space references;
determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors;
and constructing a three-dimensional water vapor grid model according to the atmospheric precipitation.
2. The method for building a three-dimensional water vapor grid model according to claim 1, wherein the separating according to the total delay to obtain zenith wet delay specifically comprises:
acquiring latitude of a measuring station, ground height and air pressure of a position where the measuring station is located;
determining zenith dry delay from the latitude, the geodetic altitude and the barometric pressure; the zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure;
determining zenith wet delay from the zenith dry delay and the total delay; the zenith wet delay is:
ZWD＝ZTD-ZHD；
where ZWD is zenith wet delay and ZTD is total delay.
3. The method for modeling a three-dimensional water vapor grid as defined in claim 1 wherein said determining a first atmospheric precipitation based on said zenith wet delay comprises:
using the formula PWV 1 Pi.zwd, determining a first atmospheric precipitation from the zenith wet delayQuantity PWV 1 ；
Wherein ZWD is zenith wet delay, and pi is dimensionless scale factor.
4. The method for building a three-dimensional water vapor grid model according to claim 1, wherein determining the atmospheric precipitation amount of the air above the measuring station by using the layer data of the measuring station to obtain the second atmospheric precipitation amount comprises:
using the formulaDetermining the second atmospheric precipitation PWV from the probe station stratification data 2 ；
Wherein ρ is water Is the liquid water density ρ w R is the density of water vapor in the atmosphere v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapor pressure, T is the absolute temperature.
5. The method for building a three-dimensional water vapor grid model according to claim 1, wherein the extracting weather factors in the atmosphere profile according to the unified time and space references specifically comprises:
layering the atmospheric profile according to a preset height;
the average temperature, air pressure and water vapor pressure of each layer are taken as dependent variables, and a formula is adopted
Determining weather layering factors of each layer;
determining the meteorological factors according to the meteorological layering factors;
wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value.
6. The method for building a three-dimensional water vapor grid model according to claim 1, wherein the determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors comprises:
determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors by adopting a formula PWV (i) =qx (i) ×pwv;
wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
7. A system for modeling a three-dimensional water vapor grid, comprising:
the first acquisition module is used for acquiring GNSS observation data and sounding station layering data; the sounding station hierarchy data includes: liquid water density, vapor density in the atmosphere, overall troposphere height, vapor pressure and absolute temperature;
the delay amount determining module is used for determining the delay amount caused when the satellite signal longitudinally passes through the troposphere to reach the ground according to the GNSS observation data by adopting GNSS data processing and analyzing software;
the total delay determining module is used for determining the total delay of the troposphere of the station measurement receiver in the zenith direction according to the delay inversion;
the zenith wet delay determining module is used for separating to obtain zenith wet delay according to the total delay;
the first atmospheric precipitation determining module is used for determining the first atmospheric precipitation according to the zenith wet delay;
the second atmospheric precipitation determining module is used for determining the atmospheric precipitation above the measuring station by adopting the sounding station layering data to obtain the second atmospheric precipitation;
the GNSS/sounding water vapor model construction module is used for constructing a GNSS/sounding water vapor model according to the first atmospheric precipitation and the second atmospheric precipitation; the GNSS/sounding water vapor model is an atmospheric precipitation combination obtained by integrating and encrypting the first atmospheric precipitation and the second atmospheric precipitation;
the occultation data determining module is used for determining occultation data and sounding data according to the GNSS/sounding water vapor model;
the atmosphere profile determining module is used for determining an atmosphere profile according to the occultation data and the sounding data;
the second acquisition module is used for acquiring preset same starting time and preset space interval;
the time and space reference determining module is used for determining unified time and space references according to the preset same starting time and the preset space interval;
the meteorological factor extraction module is used for extracting meteorological factors in the atmospheric profile according to the unified time and space references;
the atmospheric precipitation determining module is used for determining the atmospheric precipitation in the whole troposphere according to the extracted meteorological factors;
and the three-dimensional water vapor grid model construction module is used for constructing a three-dimensional water vapor grid model according to the atmospheric precipitation.
8. The system for modeling a three-dimensional water vapor grid as defined in claim 7 wherein said zenith wet delay determination module comprises:
the acquisition unit is used for acquiring the latitude of the measuring station, the ground height of the position and the air pressure;
a zenith dry delay determining unit configured to determine a zenith dry delay according to the latitude, the ground altitude, and the air pressure; the zenith dry delay is:
wherein ZHD is zenith dry delay,is latitude, h s Is the height of the earth, P s Is air pressure;
a zenith wet delay determination unit configured to determine a zenith wet delay from the zenith dry delay and the total delay; the zenith wet delay is:
ZWD＝ZTD-ZHD；
where ZWD is zenith wet delay and ZTD is total delay.
9. The system for modeling a three-dimensional water vapor grid as defined in claim 7 wherein said first atmospheric precipitation determination module comprises:
a first atmospheric precipitation amount determination unit for applying the formula PWV 1 Pi·zwd, determining a first atmospheric precipitation PWV from the zenith wet delay 1 ；
Wherein ZWD is zenith wet delay, and pi is a dimensionless scale factor;
the second atmospheric precipitation amount determining module specifically includes:
a second atmospheric precipitation amount determination unit for applying the formulaDetermining the second atmospheric precipitation PWV from the probe station stratification data 2 ；
Wherein ρ is water Is the liquid water density ρ w R is the density of water vapor in the atmosphere v Is the specific gas constant of water vapor, H is the height of the whole troposphere, P w Is the water vapor pressure, T is the absolute temperature.
10. The system for building a three-dimensional water vapor grid model according to claim 7, wherein the meteorological factor extraction module specifically comprises:
the layering unit is used for layering the atmospheric profile according to a preset height;
a weather layering factor determining unit for using average temperature, air pressure and water vapor pressure of each layer as dependent variables and adopting formulaDetermining weather layering factors of each layer;
the weather factor determining unit is used for determining the weather factor according to the weather layering factor;
wherein QX (i) is a weather layering factor, n is the total layer number of the atmosphere profile, i is the ith layer of the atmosphere profile, phi 1 、Φ 2 And phi is 3 All are weight factors, t is a temperature average value, p is a barometric pressure average value, and q is a water vapor pressure average value;
the atmospheric precipitation amount determination module specifically includes:
an atmospheric precipitation amount determination unit configured to determine an atmospheric precipitation amount in the entire troposphere using a formula PWV (i) =qx (i) ×pwv, based on the extracted meteorological factors;
wherein i is the ith layer of stratified water vapor, PWV (i) is the atmosphere precipitation amount of the ith layer, PWV is the atmosphere precipitation amount combination, and QX (i) is the weather stratification factor.
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| CN114415266B (en) * | 2021-12-31 | 2022-09-20 | 中国气象局气象探测中心 | Water vapor data processing method and device, electronic equipment and computer readable medium |
| CN114357770B (en) * | 2022-01-04 | 2022-10-11 | 中南大学 | Troposphere chromatography method |
| CN115099159B (en) * | 2022-07-20 | 2023-03-07 | 武汉大学 | MODIS water vapor inversion method based on neural network and considering earth surface difference |
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