CN103870676A - Altimeter sea wave mean wave period inversion method suitable for Chinese offshore area - Google Patents

Abstract

The invention discloses an altimeter sea wave mean wave period inversion method suitable for a Chinese offshore area. The altimeter sea wave mean wave period inversion method is characterized in that the inversion accuracy of a built mean wave period inversion model is obviously superior to that of am existing model, and the built mean wave period inversion model has the universality on various altimeter data as altimeter data in a modeling data set are an integration result of multiple existing on-orbit altimeter data; in addition, the built mean wave period inversion model is dedicated to the Chinese offshore area and has an obvious area characteristic, better inversion accuracy in a area is obtained, the altimeter sea wave mean wave period inversion method disclosed by the invention can be also extended for being applied to other seas, and thus the scalability is obtained.

Description

A kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region

Technical field

Patent of the present invention relates to a kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region.

Background technology

Wave is a kind of important marine dynamic process, generation and the mechanism of Evolution of research wave, disclose its inner structure and external feature, become an important research field in physical oceangraphy, it is all significant for construction of national defence, shipping, shipbuilding, harbour and offshore oil platform etc.Wave height, period of wave are two important characteristic quantities describing wave, mainly obtain at present the characteristic quantity of wave by numerical wave prediction pattern and remote sensing.Altitude gauge is a kind of sensor of novel microwave remote sensing, can round-the-clock, the round-the-clock long-time observation on a large scale that realizes wave field, and be a kind of important means of carrying out at present wave observation.The measurement data set of altitude gauge can directly provide the information of significant wave height and the sea wind speed of wave, but mean wave cycle parameter cannot be directly provided, need to utilize significant wave height, wind speed and backscattering coefficient inverting to obtain by various inversion methods for the mean wave cycle.The observation that utilizes altitude gauge to realize wave field is a kind of result of field observation, closer to actual conditions, set up and can obtain the information of more complete wave field based on significant wave height, the method in wind speed inverting mean wave cycle, have great importance for the development of altitude gauge observation wave.

Prior art scheme: 1991, Challenor and Srokosz proposed can set up according to the relation between spectral moment and significant wave height and backscattering coefficient the theoretical model (CS91 model) of a mean wave cycle and significant wave height and backscattering coefficient first.2003, the people such as Gommenginger are the theoretical formula based on above just, had drawn two empirical models (G03 model) by buoy data fitting.1998, the people such as Hwang obtained the approximation relation of mean wave cycle and significant wave height and wind speed based on wave dynamics and wave measurement data, and then had obtained the inverse model (H98 model) in mean wave cycle.

2004, the people such as Quilfen were based on TOPEX/Poseidon satellite altimeter and buoy associating data set, and applied neural network algorithm and obtained the empirical model (Quilfen model) between mean wave cycle and significant wave height and backscattering coefficient.2008, the people such as Mackay set up respectively new argument model period of wave (Mackay model) for different satellites based on buoy and different satellite data.2012, the relation of the people such as Miao Hongli based between zero dimension wave height and pseudo-wave age, utilized ERA-40 and Jason-1 associating data set to set up the quartic polynomial empirical model of global mean wave cycle inverting, and efficiency of inverse process is better than aforementioned several model.

The method at present existing multiple altitude gauge inverting wave mean wave cycle, the maximum problem that these methods exist is: the observation data based on limited and specific satellite altimeter are effective, the applicability in region and the versatility of various satellite altimeter are poor, cannot be applied to the inverting in wave mean wave cycle of CHINESE OFFSHORE region.Therefore need to set up model and the method for the altitude gauge mean wave cycle inverting that is exclusively used in CHINESE OFFSHORE region.

The problem that patent of the present invention exists for current existing altitude gauge inverting wave mean wave cycle method, the altitude gauge data and the ERA-Interim that merge based on the many stars of AVSIO analyze data again, set up the altitude gauge mean wave cycle inversion method that is exclusively used in CHINESE OFFSHORE region.

Summary of the invention

The technical problem to be solved in the present invention is to provide that a kind of versatility is better, and inversion accuracy is high, has the altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region of good extensibility simultaneously.

For solving the problems of the technologies described above, the present invention adopts following technical scheme: comprise the following steps:

1) the altitude gauge data and the ERA-Interim data configuration modeling data collection that first utilize the many stars of AVISO to merge, adopt least square fitting to obtain multinomial coefficient, sets up the multinomial model of mean wave cycle inverting, and the form of its model is as follows:

$1.44\frac{{\mathrm{<figure-callout\; id="2"\; label="gT\; Z"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">gT</figure-callout>}}_Z}{{2\mathrm{\&pi;<figure-callout\; id="10"\; label="U"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">U</figure-callout>}}_{10}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{a}_i{\left(\frac{{\mathrm{<figure-callout\; id="10"\; label="gH\; S\; U"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">gH</figure-callout>}}_S}{{U_{}}^{}}\right)}^i+C$

2) secondly, modeling data collection is carried out to segmentation according to significant wave height, the mean wave cycle inverse model of setting up respectively each segmentation is polynomial expression segmentation inverse model;

3) then, use with above identical modeling data collection and calculate zero dimension wave height and pseudo-wave age, taking zero dimension wave height as input, pseudo-wave age is for exporting, and neural network training has obtained the BP neural network model of mean wave cycle inverting;

4) finally utilize altitude gauge data and the ERA-Interim data that the many stars of AVISO merge to form verification msg collection, three kinds of models setting up and the precision in a kind of existing H98 model inversion mean wave cycle have been carried out to contrast verification;

5) through the checking of indices, polynomial expression segmentation inverse model is the optimum altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region.

As preferably, in step 1, Hs is significant wave height, and Tz is upper across the mean wave cycle at zero point, and U10 is the wind speed at 10 meters of, sea.

As preferably, in step 1,2, find that by research polynomial expression exponent number is at 5 o'clock, the root-mean-square error of inversion result is less, and therefore, polynomial exponent number is defined as 5 rank.

The present invention is applicable to the beneficial effect of the altitude gauge wave mean wave cycle inversion method in CHINESE OFFSHORE region: 1. the inversion accuracy of the mean wave cycle inverse model of setting up is obviously better than existing model; 2. because the concentrated altitude gauge data of modeling data are results of the multiple existing data fusion of altitude gauge in-orbit, therefore, the mean wave cycle inverse model of foundation has versatility to various altitude gauge data; 3. the mean wave cycle inverse model of setting up is exclusively used in CHINESE OFFSHORE region, has obvious provincial characteristics, has good inversion accuracy in region, also can expand to be applied to other marine site to the method, therefore has extensibility.

Brief description of the drawings

Fig. 1 is the schematic diagram of H98 model inversion result in the present invention;

Fig. 2 is the schematic diagram of multinomial model inversion result in the present invention;

Fig. 3 is the schematic diagram of polynomial expression segmentation inverse model inversion result in the present invention;

Fig. 4 is the schematic diagram of BP neural network model inverse model inversion result in the present invention.

Embodiment

Verify the effect of the proposed by the invention altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region below by a specific embodiment.

In the present embodiment, shown in Fig. 4, a kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region, specifically comprises the following steps:

1) the altitude gauge data (1 ° × 1 °) and the ERA-Interim data configuration modeling data collection (1 ° × 1 °) that first utilize the many stars of AVISO to merge, adopt least square fitting to obtain multinomial coefficient, the multinomial model (QP_AVISO_model) of setting up the inverting of mean wave cycle, the form of its model is as follows:

$1.44\frac{{\mathrm{<figure-callout\; id="2"\; label="gT\; Z"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">gT</figure-callout>}}_Z}{{2\mathrm{\&pi;<figure-callout\; id="10"\; label="U"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">U</figure-callout>}}_{10}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{a}_i{\left(\frac{{\mathrm{<figure-callout\; id="10"\; label="gH\; S\; U"\; filenames="HDA0000461118460000011.png,HDA0000461118460000012.png"\; state="\{\{state\}\}">gH</figure-callout>}}_S}{{U_{}}^{}}\right)}^i+C$

2) secondly, modeling data collection is carried out to segmentation according to significant wave height, the mean wave cycle inverse model of setting up respectively each segmentation is polynomial expression segmentation inverse model (PQP_AVISO_model).

3) then, use with above identical modeling data collection and calculate zero dimension wave height and pseudo-wave age, taking zero dimension wave height as input, pseudo-wave age is for exporting, and neural network training has obtained the BP neural network model (MWP_NN_model) of mean wave cycle inverting.

4) finally utilize altitude gauge data and the ERA-Interim data that the many stars of AVISO merge to form verification msg collection, three kinds of models setting up and the precision in a kind of existing H98 model inversion mean wave cycle have been carried out to contrast verification.

5) through the checking of indices, polynomial expression segmentation inverse model is the optimum altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region.

In step 1, Hs is significant wave height, and Tz is upper across the mean wave cycle at zero point, and U10 is the wind speed at 10 meters of, sea.In step 1,2, find that by research polynomial expression exponent number is at 5 o'clock, the root-mean-square error (RMSE) of inversion result is less, and therefore, polynomial exponent number is defined as 5 rank.

According to shown in Fig. 1 to Fig. 4, the deviation (Bias) of H98 model inversion result and root-mean-square error (RMSE) maximum, be respectively-1.33s and 1.74s; The deviation of polynomial expression segmentation inverse model and root-mean-square error minimum, be respectively-0.27s and 0.86s; Deviation and the root-mean-square error of multinomial model and BP neural network model are suitable, be-0.42s of deviation, and root-mean-square error is respectively 1.07s and 1.05s.The related coefficient (Correlation) of four kinds of models is all in 0.7 left and right, and difference is little; Scattering index (SI) magnitude relationship and the error of four kinds of models are similar, and H98 model maximum is 0.21, and polynomial expression segmentation inverse model minimum, is 0.15, and all the other two kinds of models are suitable.The SI of three kinds of models that the present invention sets up is all lower than 0.20, and the SI of H98 model is greater than 0.20, illustrates that the model of forefathers' foundation is general to the applicability of China sea.As can be seen here, the inversion accuracy of the polynomial expression segmentation inverse model that the present invention sets up in four kinds of models is the highest, and deviation, root-mean-square error scattering index are minimum, and indices is all better than existing H98 model and other model.Therefore, the present invention has determined that polynomial expression segmentation inverse model is the optimum altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region.

The beneficial effect of a kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region of the present invention: the 1. inversion accuracy of the mean wave cycle inverse model of setting up is obviously better than existing model; 2. because the concentrated altitude gauge data of modeling data are results of the multiple existing data fusion of altitude gauge in-orbit, therefore, the mean wave cycle inverse model of foundation has versatility to various altitude gauge data; 3. the mean wave cycle inverse model of setting up is exclusively used in CHINESE OFFSHORE region, has obvious provincial characteristics, has good inversion accuracy in region, also can expand to be applied to other marine site to the method, therefore has extensibility.

Above-described embodiment, just an example of the present invention, is not for limiting enforcement of the present invention and interest field, all or technical schemes of being equal to identical with content described in the claims in the present invention, all should be included in protection domain of the present invention.

Claims (3)

1. an altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region, is characterized in that: comprise the following steps:

1) the altitude gauge data and the ERA-Interim data configuration modeling data collection that first utilize the many stars of AVISO to merge, adopt least square fitting to obtain multinomial coefficient, sets up the multinomial model of mean wave cycle inverting, and the form of model is as follows:

$1.44\frac{{\mathrm{gT}}_Z}{{2\mathrm{\&pi;U}}_{10}}=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{a}_i{\left(\frac{{\mathrm{gH}}_S}{{U_{10}}^2}\right)}^i+C$

2) secondly, modeling data collection is carried out to segmentation according to significant wave height, the mean wave cycle inverse model of setting up respectively each segmentation is polynomial expression segmentation inverse model;

3) then, use with above identical modeling data collection and calculate zero dimension wave height and pseudo-wave age, taking zero dimension wave height as input, pseudo-wave age is for exporting, and neural network training has obtained the BP neural network model of mean wave cycle inverting;

4) finally utilize altitude gauge data and the ERA-Interim data that the many stars of AVISO merge to form verification msg collection, three kinds of models setting up and the precision in a kind of existing H98 model inversion mean wave cycle have been carried out to contrast verification;

5) through the checking of indices, polynomial expression segmentation inverse model is the optimum altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region.

2. a kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region according to claim 1, is characterized in that: in step 1, Hs is significant wave height, and Tz is upper across the mean wave cycle at zero point, and U10 is the wind speed at 10 meters of, sea.

3. a kind of altitude gauge wave mean wave cycle inversion method that is applicable to CHINESE OFFSHORE region according to claim 1, it is characterized in that: in step 1,2, find that by research polynomial expression exponent number is at 5 o'clock, the root-mean-square error of inversion result is less, therefore, polynomial exponent number is defined as 5 rank.

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