CN108363676A - A kind of altimeter stormy waves and significant wave height separation method of surging - Google Patents
A kind of altimeter stormy waves and significant wave height separation method of surging Download PDFInfo
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Abstract
The present invention relates to a kind of altimeter stormy waves and significant wave height separation method of surging, and include the following steps：Build characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age；Solve the inverse function relationship of wind speed and wave age about two waveband backscattering coefficient, the two waveband backscattering coefficient calculation of wind speed and wave age observed using altimeter；Stormy waves significant wave height is calculated, and the total significant wave height wave height of wave of altimeter observation is combined to calculate significant wave height of surging.The present invention realizes the separation of stormy waves and significant wave height of surging in the wave significant wave height that altimeter is observed, and improves its ocean dynamical environment monitoring identification capability, obtains altimeter new types of data product, meet the different demands of scientific research and engineer application.
Description
Technical field
The present invention relates to the separation methods of a kind of stormy waves and significant wave height of surging, specifically, being a kind of altimeter stormy waves
With significant wave height separation method of surging, belong to marine remote sensing technology field.
Background technology
Wave is the most significant physical phenomenon of ocean surface.Wave often by stormy waves and surge and the superposition of wind wave and swell deposited in the form of deposit
Refer to the wave that local wind generates in, stormy waves, and it is the wave transmitted by other sea areas to surge.It stormy waves and surges and has significant spy
Levy difference：Stormy waves has strong nonlinearity feature, is the important research object of Marine atmospheric boundary layer process；And it surges with stronger broken
Bad power has important application in ocean engineering.Therefore, accurately the stormy waves in separation wave and surge ingredient, obtain stormy waves and
Surge it is long-term, observe data on a large scale, have important science and actual application value.
Wave on sea is a kind of random process, and wave height is not of uniform size, usually selects certain representative in practical applications
The feature wave height of meaning, significant wave height represent 1/3 big wave mean wave height, are most common wave characteristics parameters.Current existing sight
The observation of survey means, only sea ocean weather station observation and boat-carrying can obtain stormy waves and significant wave height data of surging.Sea ocean weather station observation
It is based primarily upon buoy observation, its advantage is that accuracy of observation and reliability are high, but observational networks are sparse, and observation area is extremely limited,
It is difficult to realize observe on a large scale.There is also the limited problems of observation scope for boat-carrying observation, and that there are observation times is short, observe cost
The problems such as high.The means of space-borne observation wave can be based on synthetic aperture radar and altimeter, and wherein synthetic aperture radar is one
As be only capable of observation under sea situation and surge wave height, can not observe stormy waves significant wave height.Wave significant wave height may be implemented in altimeter
The observation in Global coverage region, but prior art can not detach the stormy waves in its wave significant wave height and ingredient of surging.Development
A kind of stormy waves based on the observation of altimeter substar and surge significant wave height separation method, with provide a wide range of scale stormy waves and
Significant wave height of surging observes data, realizes the more accurately observation identification of wave state, will be scientific research of seas and engineering
Using offer strong support.
Invention content
Insufficient in view of the above technology, the object of the present invention is to provide a kind of altimeter stormy waves and the significant wave height side of separation that surges
Method.The separation of stormy waves and significant wave height of surging in the wave significant wave height that altimeter is observed may be implemented in this method, has filled up phase
The blank for closing technical field improves the identification capability of the wave of the sea state of altimeter observation.
For achieving the above object, the present invention is achieved using following technical proposals：It a kind of altimeter stormy waves and gushes
Unrestrained significant wave height separation method, includes the following steps：
Build characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age；
Solve the inverse function relationship of wind speed and wave age about two waveband backscattering coefficient, the double wave observed by altimeter
Section backscattering coefficient calculation of wind speed and wave age；
Stormy waves significant wave height is obtained according to wind speed and wave age, and the wave significant wave height of altimeter observation is combined to be surged
Significant wave height.
Build characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age, including following step
Suddenly：
Altimeter two waveband backscattering coefficient is established about wind speed and wave by mirror-reflection theory and wind wave spectrum model
The characteristic function relationship in age；
The undetermined coefficient in characteristic function relationship is determined by observing data, brings undetermined coefficient into characteristic function relationship
In, obtain the characteristic function relationship of two waveband backscattering coefficient.
It is described that altimeter two waveband backscattering coefficient is established about wind speed by mirror-reflection theory and wind wave spectrum model
Include the following steps with the characteristic function relationship of wave age：
Backscattering coefficient σ0It is expressed as Fresnel reflection coefficient and the steep ratio of equal square wave：
σ0=R/s2 (1)
Wherein R is Fresnel reflection coefficient, s2It is that the equal square wave of extra large table is steep, wherein equal square wave is the shape of stormy waves spectral integral suddenly
Formula：
WhereinIt is wind wave spectra,It is wave-number vector, k is wave number variable, kdIt is to block wave number, the microwave with altimeter
Tranmitting frequency is related, kpIt is spectral peak wave number, wind velocity U can be expressed as10With the relationship of wave age β：kp=g/ (U10β)2, wherein g is
Acceleration of gravity；Fresnel reflection coefficient in formula is：
Wherein it is kemIt is the transmitting microwave signal wave number of altimeter, atIt is undetermined coefficient；For the form of stormy waves spectral integral:
Wherein krIt is wave number lower limit, it is related with the Microwave emission frequency of altimeter；
Wind wave spectrum model：
Wherein Bl(k) it is expressed as:
Wherein αpIt is and the relevant parameter of wave age, αp=0.006 β-0.55,cpThe velocity of wave of main wave, can be expressed as wind speed and
The relationship of wave age：cp=β U10,GHIt is that peak rises the factor：
G=1.71≤β≤1.2
G=1.7+6log (β-1) 0.2 ＜ β ＜ 1
Bh(k) it is expressed as
αmIt is balance field parameter, the relationship α of wind speed can be expressed asm=0.014 (0.036U10/cm), cmIt is minimal wave speed,
Its value is cm=0.23, c are velocities of wave, can be expressed as the relationship of wave numberkmIt is the corresponding wave number of minimal wave speed,
Value is km=370.
Formula (5)-(7) are substituted into equal square wave steep (2) and Fresnel reflection coefficient (3)-(4) respectively, and are finally substituted into public
In formula (1), characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age is obtained：
σ0=F (U10,β) (8)
Wherein σ0Corresponding Ku wave bands (σ0Ku) or C-band (σ0C) backscattering coefficient, the characteristic parameter (k of different-wavebandem,
kd,kr,at) there is different values.
The inverse function relationship that wind speed and wave age are solved about two waveband backscattering coefficient, is observed by altimeter
Two waveband backscattering coefficient calculation of wind speed and wave age, include the following steps：
1) neural network method, the characteristic function relationship of Converse solved two waveband backscattering coefficient is utilized to obtain wind speed
Inverse function relationship with wave age about two waveband backscattering coefficient：It, will be double using wind speed and wave age as the output of neural network
Input of the wave band backscattering coefficient as neural network, training obtains neural network parameter, and substitutes into neural network；
2) it is based on inverse function relationship, according to the two waveband backscattering coefficient that altimeter is observed, obtains wind speed and wave age.
It is described that stormy waves significant wave height is obtained according to wind speed and wave age, and the wave significant wave height of altimeter observation is combined to obtain
Significant wave height of surging includes the following steps：
Based on Wind Wave Growth Relations, stormy waves significant wave height is calculated using wind speed and wave age；
Based on wave height-wave energy relationship, the stormy waves for obtaining the wave of altimeter observation and being calculated based on Wind Wave Growth Relations is had
The difference between wave height is imitated, and then obtains significant wave height of surging.
The invention has the advantages that and advantage：
1. the method for the present invention is observed applied to altimeter substar, realizes the extension of altimeter observation method, provide one kind
Novel sea environmental monitoring technology improves its ocean dynamical environment monitoring identification capability.
2. the method for the present invention realizes the separation of stormy waves and significant wave height of surging in the wave significant wave height that altimeter is observed,
Altimeter new types of data product is obtained, the different demands of scientific research of seas and ocean engineering application can be met.
Description of the drawings
Fig. 1 is the implementing procedure figure that the present invention is applied to the stormy waves of altimeter and significant wave height separation method of surging；
Fig. 2 is the flow chart of the Converse solved characteristic function relational expression of neural network method.
Specific implementation mode
Technical scheme of the present invention is described in further detail with reference to the accompanying drawings and detailed description.
A kind of altimeter stormy waves and significant wave height separation method of surging, including altimeter two waveband backscattering coefficient about
The building process of the characteristic function relationship of wind speed and wave age, the Converse solved process of characteristic function relationship, the meter of wind speed and wave age
The calculating separation process of calculation process, the calculating process of stormy waves significant wave height, and significant wave height of surging.The implementation of each process is all
It is based on ripe theory and technology method, the structure of wherein two waveband backscattering coefficient characteristic function is to be based on specular scattering
Theoretical and wind wave spectrum model, the Converse solved of characteristic function is to be based on neural network method, and the calculating of stormy waves significant wave height is base
In Wind Wave Growth Relations, it is to be based on wave height-wave energy relationship that the calculating for significant wave height of surging, which detaches,.The present invention is by considering altimeter
The feature difference of the two waveband scattered signal of substar realizes the stormy waves in wave and surges in conjunction with observation and theory analysis
The separation of significant wave height improves the identification capability of the wave of the sea state of altimeter substar observation.
A kind of altimeter stormy waves and significant wave height separation method of surging, include the following steps：
Build characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age；
Solve the inverse function relationship of wind speed and wave age about two waveband backscattering coefficient, the double wave observed using altimeter
Section backscattering coefficient calculation of wind speed and wave age；
It calculates stormy waves significant wave height and the wave significant wave height of altimeter observation is combined to calculate significant wave height of surging.
Characteristic function of the structure altimeter two waveband backscattering coefficient about wind speed and wave age, including following step
Suddenly：
Altimeter two waveband backscattering coefficient is established about wind speed and wave by mirror-reflection theory and wind wave spectrum model
The characteristic function relationship in age；
By observing data, determines the undetermined coefficient in characteristic model, establish the feature letter of two waveband backscattering coefficient
Number.
Inverse function relationship of the solution wind speed and wave age about two waveband backscattering coefficient, is observed using altimeter
Two waveband backscattering coefficient calculation of wind speed and wave age, include the following steps：
Using neural network method, the characteristic function relationship of Converse solved two waveband backscattering coefficient, obtain wind speed and
Inverse function relationship of the wave age about two waveband backscattering coefficient；
Pass through inverse function relationship, using the two waveband backscattering coefficient of altimeter observation, calculation of wind speed and wave age parameter.
Isolated surge of the total significant wave height of wave of the calculating stormy waves significant wave height and combination altimeter observation has
Wave height is imitated, is included the following steps：
Based on Wind Wave Growth Relations, stormy waves significant wave height is calculated using wind speed and wave age；
Based on wave height-wave energy relational expression, calculated in conjunction with the significant wave height of altimeter observation and based on Wind Wave Growth Relations
The difference of stormy waves significant wave height, obtains significant wave height of surging.
As shown in Figure 1, the present invention includes the following steps：
1. using specular scattering theory and wind wave spectrum model structure altimeter two waveband backscattering coefficient about wind speed and
The characteristic function relationship of wave age, and determine the undetermined coefficient in characteristic function using observation data；
2. solving characteristic function relationship using neural network method, wind speed and wave age are obtained about two waveband back scattering system
Several inverse function relationships；Use altimeter substar two waveband backscattering coefficient calculation of wind speed and wave age；
3. being based on Wind Wave Growth Relations, stormy waves significant wave height is calculated using wind speed and wave age；It is seen in conjunction with altimeter substar
The total significant wave height of wave of survey calculates significant wave height of surging by wave height-wave energy relationship.
The present embodiment is as follows：
The structure of characteristic function relationship is based on that specular scattering is theoretical and wind wave spectrum model, and mirror-reflection theory is by back scattering
Coefficient (σ0) Fresnel reflection coefficient and the steep ratio of equal square wave can be expressed as：
σ0=R/s2 (1)
Wherein R is Fresnel reflection coefficient, s2It is that the equal square wave of extra large table is steep, wherein equal square wave can be expressed as wind wave spectra product suddenly
The form divided：
WhereinIt is wind wave spectra,It is wave-number vector, k is wave number, kdIt is to block wave number, it is right according to microwave remote sensing theory
It can be taken as 100 and 40m respectively in the Ku wave bands and C-band of altimeter-1, kpIt is spectral peak wave number, wind speed (U can be expressed as10) and
The relationship of wave age (β)：kp=g/ (U10β)2, wherein g is acceleration of gravity (g=9.8)；Fresnel reflection coefficient in formula can be with
It is expressed as：
Wherein it is kemIt is the transmitting signal wave number of altimeter, Ku wave bands and C-band for altimeter are respectively 300 Hes
120m-1, atIt is undetermined coefficient.It is represented by the form of stormy waves spectral integral:
Wherein krIt is wave number lower limit, according to microwave remote sensing theory, the Ku wave bands and C-band of altimeter is taken as respectively
120 and 50m-1。
Wind wave spectrum model can be expressed as：
Wherein Bl(k) it is expressed as:
Wherein αpIt is and the relevant parameter of wave age, αp=0.006 β-0.55,cpIt is the velocity of wave of main wave, is expressed as wind speed and wave age
Relationship：cp=β U10,GHIt is that peak rises the factor：
G=1.71≤β≤1.2
G=1.7+6log (β-1) 0.2 ＜ β ＜ 1
Bh(k) it is expressed as
αmIt is balance field parameter, the relationship α of wind speed can be expressed asm=0.014 (0.036U10/cm), cmIt is minimal wave speed,
Its value is cm=0.23, c are velocities of wave, can be expressed as the relationship of wave numberkmIt is the corresponding wave number of minimal wave speed,
Value is km=370.
Wind wave spectrum model (5-7) is substituted into equal square wave steep (2) and Fresnel reflection coefficient (3-4) respectively, and is finally substituted into
In mirror-reflection theory relation (1), characteristic function of the altimeter two waveband backscattering coefficient about wind speed and wave age can be obtained
Relationship：
σ0=F (U10,β) (8)
Wherein σ0Corresponding Ku wave bands (σ0Ku) or C-band (σ0C) backscattering coefficient, the characteristic parameter (k of different-wavebandem,
kd,kr,at) there is different values.
In characteristic function relational expression (8), it is still necessary to determine undetermined coefficient atValue, altimeter and ground buoy can be used
Time-space relation synchrodata determines that time-space relation window is selected as 50km and 30 minute, i.e., the observational data of the two is in time and sky
Between on meet this standard is considered synchronous.Ground buoy provides the observation data of wind speed and wave age, and altimeter provides
Two waveband backscattering coefficient observes data.Altimeter data comes from TOPEX, Jason-1 and Jason-2, these three altimeters
All it is dual-band operation pattern (Ku wave bands：13.6Hz C-band：5.4Hz), the satellite number during 2000-2012 is selected here
According to.It is to choose offshore distance to be more than 100km that ground buoy data, which select the buoy public data at American National center, selection standard,
Buoy, to avoid the interference that altimeter is observed on land, meet condition has 44 buoy erect-positions.Altimeter data and buoy
Data carry out time-space relation, and 13789 groups of synchrodatas are obtained.By above-mentioned observation data, it is fitted by least square method
Determine the characteristic coefficient a of Ku wave bandstIt is 0.73, C-band characteristic coefficient atIt is 1.28.
Converse solved relational expression (8) can obtain wind speed and wave age and be closed about the inverse function of two waveband backscattering coefficient
System：
U10=F1(σ0Ku,σ0C)；β=F2(σ0Ku,σ0C)； (9)
It is carried out using Artificial Neural Network Converse solved.Neural network is using a three-decker comprising 2
A input node, 4 implicit nodes, 2 output nodes.Input layer to hidden layer transmit data form be：
Wherein xiAnd HjInput value and default value are respectively represented, n and l are the node number of input layer and hidden layer respectively.
wijIt is weight coefficient；ajIt is initial threshold；F is represented by:F (t)=1/ [1-exp (- t)] hidden layers transmit number to output layer
According to form be：
Wherein OkIt is the output valve of hidden layer, m is the number of nodes of output layer,It is weight coefficient, bpIt is initial threshold .g
It is represented by g=t.
Weight coefficient and initial threshold are periodically adjusted during training network, to reduce network algorithm error,
This is realized by error back propagation.
Fig. 2, which gives, utilizes the Converse solved flow of neural network method.
As shown in Fig. 2, specific implementation step is as follows：Wind speed setting is divided into 0.1m/s, wave between 1-30m/s ranges, wind speed
Age in the sections 0.4-1.2, is divided into 0.05, first, Ku is calculated separately with the feature mode functional relation (8) proposed above
The backscattering coefficient of wave band and C-band, then using the two waveband backscattering coefficient being calculated as input item, with setting
Wind speed and wave age are that output item obtains the inverse function of characteristic function to the weight coefficient and initial threshold of training neural network
Relational expression (9).
The two waveband backscattering coefficient that altimeter is observed is updated in functional relation (9), corresponding wind can be calculated
The numerical value of speed and wave age.
According to Wind Wave Growth Relations, stormy waves significant wave height (Hs,windsea) functional relation of wind speed and wave age can be expressed as：
Due to significant wave height (Hs) there are inner links with wave energy (E), i.e.,It can be observed by altimeter
Wave and the capacity volume variance of stormy waves that calculates of front, calculating surge significant wave height (Hs_swell)：
Pass through relational expression (12) and relational expression (13), you can realize the separation of altimeter stormy waves and significant wave height of surging.
In this embodiment, altimeter substar observes isolated stormy waves and surges significant wave height, and previously mentioned
Time-space registration the observation of synchronization ground buoy stormy waves and significant wave height of surging carry out contrast verification, stormy waves and significant wave of surging
High mean error is respectively -0.08 meter and 0.02 meter, and root-mean-square error is respectively 0.38 meter and 0.45 meter, has good one
Cause property, to confirm validity of the present invention for altimeter stormy waves and significant wave height separation method of surging.
Claims (5)
1. a kind of altimeter stormy waves and significant wave height separation method of surging, it is characterised in that include the following steps：
Build characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age；
Inverse function relationship about two waveband backscattering coefficient of wind speed and wave age is solved, after the two waveband observed by altimeter
To scattering coefficient calculation of wind speed and wave age；
Stormy waves significant wave height is obtained according to wind speed and wave age, and the wave significant wave height of altimeter observation is combined to obtain surging effectively
Wave height.
2. a kind of altimeter stormy waves according to claim 1 and significant wave height separation method of surging, it is characterised in that described
Characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age is built, is included the following steps：
Altimeter two waveband backscattering coefficient is established about wind speed and wave age by mirror-reflection theory and wind wave spectrum model
Characteristic function relationship；
The undetermined coefficient in characteristic function relationship is determined by observing data, and undetermined coefficient is brought into characteristic function relationship, is obtained
To the characteristic function relationship of two waveband backscattering coefficient.
3. a kind of altimeter stormy waves according to claim 2 and significant wave height separation method of surging, it is characterised in that described
Feature of the altimeter two waveband backscattering coefficient about wind speed and wave age is established by mirror-reflection theory and wind wave spectrum model
Functional relation includes the following steps：
Backscattering coefficient σ0It is expressed as Fresnel reflection coefficient and the steep ratio of equal square wave：
σ0=R/s2 (1)
Wherein R is Fresnel reflection coefficient, s2It is that the equal square wave of extra large table is steep, wherein equal square wave is the form of stormy waves spectral integral suddenly：
WhereinIt is wind wave spectra,It is wave-number vector, k is wave number, kdIt is to block wave number, kpIt is spectral peak wave number；Fei Nie in formula
You are at reflectance factor：
Wherein it is kemIt is the transmitting signal wave number of altimeter, atIt is undetermined coefficient；For the form of stormy waves spectral integral:
Wherein krIt is wave number lower limit；
Wind wave spectrum model：
Wherein Bl(k) and Bh(k) it is expressed as:
Wherein αpIt is and the relevant parameter of wave age, cpIt is the velocity of wave of main wave, kpIt is spectral peak wave number, GHIt is that peak rises the factor, U10It is wind
Speed, cmIt is minimal wave speed, kmIt is the corresponding wave number of minimal wave speed, c is velocity of wave, αmIt is balance field parameter；
Formula (5)-(7) are substituted into equal square wave steep (2) and Fresnel reflection coefficient (3)-(4) respectively, and finally substitute into formula (1)
In, obtain characteristic function relationship of the altimeter two waveband backscattering coefficient about wind speed and wave age：
σ0=F (U10,β) (8)
Wherein σ0For Ku wave band backscattering coefficients σ0KuOr the backscattering coefficient σ of C-band0C, β is wave age.
4. a kind of altimeter stormy waves according to claim 1 and significant wave height separation method of surging, it is characterised in that described
Inverse function relationship about two waveband backscattering coefficient of wind speed and wave age is solved, to dissipating after the two waveband observed by altimeter
Coefficient calculation of wind speed and wave age are penetrated, is included the following steps：
1) neural network method, the characteristic function relationship of Converse solved two waveband backscattering coefficient is utilized to obtain wind speed and wave
Inverse function relationship of the age about two waveband backscattering coefficient：Using wind speed and wave age as the output of neural network, by two waveband
Input of the backscattering coefficient as neural network, training obtains neural network parameter, and substitutes into neural network；
2) it is based on inverse function relationship, according to the two waveband backscattering coefficient that altimeter is observed, obtains wind speed and wave age.
5. a kind of altimeter stormy waves according to claim 1 and significant wave height separation method of surging, it is characterised in that described
Stormy waves significant wave height is obtained according to wind speed and wave age, and the wave significant wave height of altimeter observation is combined to obtain significant wave height of surging
Include the following steps：
Based on Wind Wave Growth Relations, stormy waves significant wave height is calculated using wind speed and wave age；
Based on wave height-wave energy relationship, the stormy waves significant wave for obtaining the wave of altimeter observation and being calculated based on Wind Wave Growth Relations
Difference between height, and then obtain significant wave height of surging.
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| CN112394353A (en) * | 2020-11-30 | 2021-02-23 | 中国舰船研究设计中心 | Sea wave number spectrum reconstruction method based on steep function appraisal |
| CN112464139A (en) * | 2020-11-27 | 2021-03-09 | 国家海洋环境预报中心 | Wind and wave element data quality control method based on single classifier |
| CN113049220A (en) * | 2021-03-17 | 2021-06-29 | 中国船舶科学研究中心 | Method for identifying wave and surge component in mixed waves |
| CN113221312A (en) * | 2021-02-05 | 2021-08-06 | 中国人民解放军国防科技大学 | Sea surface roughness parameterization method based on sea waves and sea foam |
| CN116992193A (en) * | 2023-09-28 | 2023-11-03 | 中国科学院海洋研究所 | Method, storage medium and equipment for calculating wind speed from sea wave information |
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| 李水清: "基于现场观测和海洋遥感的气体交换速率的研究", 《中国博士学位论文全文数据库 基础科学辑》 * |
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| CN112464139A (en) * | 2020-11-27 | 2021-03-09 | 国家海洋环境预报中心 | Wind and wave element data quality control method based on single classifier |
| CN112394353A (en) * | 2020-11-30 | 2021-02-23 | 中国舰船研究设计中心 | Sea wave number spectrum reconstruction method based on steep function appraisal |
| CN113221312A (en) * | 2021-02-05 | 2021-08-06 | 中国人民解放军国防科技大学 | Sea surface roughness parameterization method based on sea waves and sea foam |
| CN113049220A (en) * | 2021-03-17 | 2021-06-29 | 中国船舶科学研究中心 | Method for identifying wave and surge component in mixed waves |
| CN113049220B (en) * | 2021-03-17 | 2022-04-12 | 中国船舶科学研究中心 | Method for identifying wave and surge component in mixed waves |
| CN116992193A (en) * | 2023-09-28 | 2023-11-03 | 中国科学院海洋研究所 | Method, storage medium and equipment for calculating wind speed from sea wave information |
| CN116992193B (en) * | 2023-09-28 | 2023-12-19 | 中国科学院海洋研究所 | Method, storage medium and equipment for calculating wind speed from sea wave information |
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