CN110287624A - A method of for cultivating salinity effect model foundation in bay during typhoon influence - Google Patents
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Abstract
The present invention provides a kind of methods for cultivating salinity effect model foundation in bay during typhoon influence, the problem of not can solve salt angle value during Exact Forecast different type typhoon influence, this method for being used to cultivate salinity effect model foundation in bay during typhoon influence, first by obtaining salinity routine lunar calendar monthly changing characteristics and salinity Seasonal variation, establish conventional salinity effect model, then precipitation during acquisition typhoon influence, evaporation capacity and tidal level variable quantity are to seawater salinity variable quantity forecasting model, finally two kinds of models are combined, the forecasting model of bay salinity is forecast during choosing corresponding typhoon influence respectively to different type typhoon., can be in the case where including the routine variation such as precipitation, tide, evaporation using this method, the predicted value of salinity altercation when constructing two class typhoon influences, thus to take specific aim measure to provide technical support than more sensitive marine product salinity altercation.
Description
Technical field
The present invention relates to Meteorological Services technical field, more particularly to one kind are pre- for cultivating bay salinity during typhoon influence
The method for reporting model foundation.
Background technique
Sea-farming is important one of the industrial economy in coastal area, is the part of Sustainable Development of Marine Economy.Marine products
Yield, quality and the breeding water body salinity of product etc. are closely related, and the fine forecast of salinity etc. is Meteorological Services in sea-farming
Important content, especially the diastrous weathers such as typhoon influence when, it is bigger to influence on water body, may cause the hair of marine product
Disease, in addition it is dead.Associated specialist there has been some researchs before, and Guo Weidong etc. has tentatively probed into XIAMEN BAY table during Heavy Rain of Typhoon
The variation characteristic of layer seawater salinity, huge concentration precipitation makes runoff increase severely during finding typhoon, and salinity is caused sharply to decline；Zhao
Clever flood dragon etc. carries out analysis to salinity altercation feature during " sea anemone " typhoon and grinds using the ocean monitoring buoy data in Xiangshan Bay
Study carefully, it is found that this typhoon storm wind is surged and import Xiangshan Bay together plus periphery massif runoff, increases water in port, salinity is in platform
Wind logs in rear 5h and minimizes；Xu Dongfeng etc. is had found using Western Pacific warm pool Argo source investigation, when typhoon is by sea,
Sea surface salinity variation depends on rainfall, evaporation increases, mixing enhancing and spring layer knot final between gushing and rising 4 effects in mixed layer
Fruit, wherein TYPHOON PRECIPITATION may inhibit high wind bring mixing aggravation effect, salinity can be caused to decline when most of typhoons pass through.
These study the feature of salinity altercation during analyzing typhoon influence from different perspectives, also give the certain methods of research.
But influence of the different typhoons to salinity has notable difference, as during Fitow typhoon influence in 2013, salinity from
28 ‰ rapid drawdowns to 20 ‰ hereinafter, and during the multiple typhoon influences of 7~August in 2018, salinity is kept at 28 ‰ or so.Therefore needle
To different type typhoon, distinct methods need to be used, salinity altercation feature during typhoon influence is analyzed and simulated to be had very much
It is necessary.Present analysis method is broadly divided into physical method and statistical method.Physical method is mechanistic strong, but pre- used in possibility
It reports the factor more single, causes model error larger；Statistical method calculating is relatively easy, but the forecast precision of model built is by mould
Various influences such as formula resolution ratio, initial field condition.
Summary of the invention
The technical problem to be solved by the present invention is to be used for different typhoons at present the impact analysis method of salinity
Predictor it is more single, model error is larger；And calculate relatively easy, the forecast precision of model built is differentiated by mode
The problem of various influences such as rate, initial field condition, provide it is a kind of using frequency analysis, linear regression method is to no platform
Salinity altercation feature is simulated when wind effect, probes into the factor for influencing salinity altercation, on this basis for different types of
Typhoon is respectively adopted many kinds of parameters and establishes corresponding forecasting model by canonical correlation analysis, optimal subset regression method etc.,
Salinity altercation during forecast different type typhoon influence is used for typhoon influence for sea-farming Meteorological Services increase utility
The method of period cultivation bay salinity effect model foundation.
In order to achieve the above object, the technical scheme adopted by the invention is as follows it is a kind of for cultivating bay during typhoon influence
The method of salinity effect model foundation, comprising the following steps:
S1: since the moon phase variety period is 29.5 days, the period that lunation is approximatively defined in the present embodiment is 30 days.It obtains
Per day/highest/lowest salinity long-time average annual value daily in lunation when presetting no typhoon influence is taken, and to acquisition
Per day/highest/lowest salinity is simulated using harmonic wave method, obtains per day/day of lunation when no typhoon influence
The forecasting model of highest/day lowest salinity:
Wherein:
The per day salinity of lunation during Save is no typhoon influence；
The day highest salinity of lunation during Smax is no typhoon influence；
The day lowest salinity of lunation during Smin is no typhoon influence；
The weather monthly average salt angle value of lunation during a is no typhoon influence；
The weather moon highest salt angle value of lunation during b is no typhoon influence；
The weather moon lowest salinity value of lunation during c is no typhoon influence；
T is first day, the 30th day second day ... of lunation；
S2: defining precipitation (P) and the difference of evaporation capacity (E) in some period is effectiv precipitation.Obtain the default time and
The sum of preceding 2 months effectiv precipitations of lunation (P-E), it is effective according to first 2 months of default time and default lunation
The sum of precipitation (P-E) obtains the forecasting model of the monthly average of default time and default lunation/moon highest/moon lowest salinity:
Wherein:
For the monthly average salinity for presetting time and lunation；
For the moon highest salinity for presetting time and lunation；
For the moon lowest salinity for presetting time and lunation；
P is default the sum of the time and the preceding 2 months precipitation of lunation；
E is default the sum of the time and preceding 2 months evaporation capacity of lunation；
E is not consider antecedent precipitation and evaporation, and this area presets the monthly average salt angle value of time and lunation；
F is not consider antecedent precipitation and evaporation, and this area presets the moon highest salt angle value of time and lunation；
G is not consider antecedent precipitation and evaporation, and this area presets the moon lowest salinity value of time and lunation.
S3: the monthly average of default time and lunation salinity/moon highest salinity/moon lowest salinity is replaced to do not have typhoon shadow
The weather monthly average salinity of lunation when ringing/weather moon highest salinity/weather moon lowest salinity, i.e., by default time and lunation
Monthly average salinity/moon highest salinity/moon lowest salinity when substituting into no typhoon influence lunation it is per day/day highest/day
In the forecasting model of lowest salinity, when obtaining predicting no typhoon influence default time and lunation it is per day/day highest/day
The forecasting model of lowest salinity:
SyaveFor the forecasting model of the per day salinity of lunation during no typhoon influence；
SymaxDo not have lunation during typhoon influence day highest salinity forecasting model；
SyminDo not have lunation during typhoon influence day lowest salinity forecasting model；
T is first day, the 30th day second day ... of lunation；
It wherein presets the time and lunation is the default synodic month in each time in the default time, such as yin in 1999
August is gone through, wherein the date in lunar calendar August has 30 days, and wherein t takes 1,2,3 ... 30.
S4: take it is per day during preset data sample typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3, platform
Day adds up precipitation/daily evaporation amount/per day tidal level variable quantity X during wind effect1/X2/X3, by optimal subset method, obtain
It is per day during typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3, and during typhoon influence day add up precipitation/
Daily evaporation amount/per day tidal level variable quantity X1/X2/X3Between relationship model:
Y1=-0.2-0.01X1-0.115X2+2.855X3 (10)
Y2=-0.21-0.007X1+1.316X3 (11)
Y3=-0.81-0.014X1+0.069X2+3.814X3 (12)
By it is per day during typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3Increase respectively to no typhoon
During influence lunation it is per day/day highest/day lowest salinity forecasting model Syave/Symax/SyminIn prediction can be obtained
During typhoon influence lunation it is per day/day highest/day lowest salinity forecasting model:
Further, in step S1 further include:
Proxima luce (prox. luc) salinity A and salinity B during typhoon influence during acquisition typhoon influence；
Obtain the difference (A-B) of salinity B minimum during proxima luce (prox. luc) salinity A and typhoon influence during typhoon influence；
Judge the difference (A-B) of salinity minimum during proxima luce (prox. luc) salinity and typhoon influence during typhoon influence whether less than 0；
If (A-B) is less than 0, it is determined that the typhoon is first kind typhoon；If (A-B) is not less than 0, it is determined that the typhoon is the
Two class typhoons.
Further, in step S2 further include:
Respectively to the sum of preceding 2 months effectiv precipitations in default time and lunation (P-E) and default time and lunar calendar
Month monthly average/highest/lowest salinity value analyzed according to cross correlation analysis method, obtain default time and lunation
The related coefficient of the sum of salinity and preceding 2 months effectiv precipitations；
Phase relation to the sum of 2 months effectiv precipitations before default time and lunation salinity and default time and lunation
Number carries out significance test, obtains level of significance test value, judges whether the significance test by the level of α=0.01；
If so, carrying out default time and lunation by presetting the sum of 2 months effectiv precipitations before time and lunation
Salinity effect.
Further, step S4 is further comprised the steps of:
The difference of minimum per day tidal level during defining the typhoon influence first day and influencing is tidal level variable quantity, defines typhoon shadow
Minimum per day/highest/lowest salinity difference during ringing the first day and influencing is respectively that average/highest/lowest salinity changes
Amount.
Per day during first kind typhoon influence/highest/lowest salinity variable quantity is had with during first kind typhoon influence
Per day/highest/lowest salinity variable quantity and first kind typhoon during the related coefficient and first kind typhoon influence of effect precipitation
The related coefficient of effective tidal level variable quantity carries out significance test during influence, obtains level of significance test value；
During obtaining the second class typhoon influence during per day/highest/lowest salinity variable quantity and the second class typhoon influence
Per day/highest/lowest salinity variable quantity and the second class during the related coefficient of effectiv precipitation and the second class typhoon influence
The related coefficient of effective tidal level variable quantity during typhoon influence；
Per day/highest/lowest salinity variable quantity during second class typhoon influence is had with during the second class typhoon influence
Per day/highest/lowest salinity variable quantity and the second class typhoon during the related coefficient and the second class typhoon influence of effect precipitation
The related coefficient of effective tidal level variable quantity carries out significance test during influence, obtains level of significance test value；
According to the level of significance test value of the first kind typhoon of acquisition and the second class typhoon, first kind typhoon influence is confirmed
The impact factor of the impact factor of the influence salinity altercation of period and the influence salinity altercation during the second class typhoon influence.
Further, in step S4 further include:
It is per day during obtaining preset data sample first kind typhoon influence/day highest/lowest salinity variable quantity (same day day
The difference of salinity and proxima luce (prox. luc) salinity) Y1/Y2/Y3, adding up precipitation during the first kind typhoon influence day, (the typhoon influence first day arrives
The precipitation on the same day)/daily evaporation amount/per day tidal level variable quantity (difference of same day mean tide tlevel and proxima luce (prox. luc) mean tide tlevel)
X1/X2/X3, to Y and X, this two groups of data carry out canonical correlation analysis, obtain the related coefficient between them and show to it
Work property is examined, and level of significance test value is obtained, add up salinity altercation amount and day during confirming the first kind typhoon influence precipitation,
Correlation between daily evaporation amount and per day tidal level variable quantity.
It is per day during calculating preset data sample first kind typhoon influence/day highest/day lowest salinity variable quantity Y1/
Y2/Y3, day adds up subset all in precipitation/daily evaporation amount/per day tidal level variable quantity X1/X2/X3 during typhoon influence
It returns, and therefrom determines 1 optimal subset regression by CSC criterion.
The present invention is include at least the following beneficial effects:
(1) first kind typhoon and second can be divided into according to influence of the current typhoon of analysis to bay and coastal waters salinity is calculated
Class typhoon, so as to extra large during establishing different typhoon influences for influence of the inhomogeneous typhoon to bay and coastal waters salinity
Gulf cultivates salinity effect model；
(2) salinity altercation feature carries out mould when this method uses frequency analysis, linear regression method to no typhoon influence
It is quasi-, the impact factor of salinity altercation is obtained, and be directed to different type typhoon, passes through canonical correlation analysis, optimal subset regression side
Method, effectiv precipitation, tidal level variable quantity and evaporation capacity are to the shadow of bay salinity during typhoon influence during obtaining typhoon influence
It rings, and establishes corresponding salinity effect model, increase practical tool for sea-farming Meteorological Services.
Detailed description of the invention
Fig. 1 is this for cultivating the method flow block diagram of bay salinity effect model foundation during typhoon influence；
Specific embodiment
Following is a specific embodiment of the present invention in conjunction with the accompanying drawings, technical scheme of the present invention will be further described,
However, the present invention is not limited to these examples.
Embodiment
A kind of method for cultivating salinity effect model foundation in bay during typhoon influence is present embodiments provided, is such as schemed
Shown in 1, the wherein influence of typhoon is divided to two classes, and the first kind is that per day/highest/lowest salinity variable quantity is respectively less than 0 between typhoon period,
The difference (A-B) of salinity B minimum during proxima luce (prox. luc) salinity A and typhoon influence during typhoon influence is obtained less than 0, illustrates that typhoon is made
It is decreased obviously at salinity.Such typhoon is first kind typhoon, other are the second class typhoon.
Wherein this is first in terms of weather for the method for cultivation bay salinity effect model foundation during typhoon influence
The lunation of the extraction and analysis that feature is carried out to salinity altercation, the salinity that is averaged for many years when specifically including no typhoon influence becomes
Change the extraction and analysis of extraction and the analysis and default time and lunation salinity altercation feature of feature.
The extraction and analysis of the lunar calendar monthly changing characteristics for the salinity that is averaged for many years when without typhoon influence are to pass through harmonic wave
Per day/highest/lowest salinity long-time average annual value daily in lunation is simulated, is divided when method is to no typhoon influence
Analyse the period of salinity altercation；Wherein harmonic wave method is the superposition by the Time Series of element for different harmonic waves, judges element
Whether there is feature harmonic period:
K is harmonic wave serial number, and since the period of moon phase variety is 29.5d, it is 30d that we, which approximatively define basic cycle T, the
The k subharmonic period is T/k, k value range 1,2,3 ... 15.
a0For monthly average value, akAnd bkFor Fourier coefficient, ωk=2 π k/T are kth harmonic frequency.
Harmonic wave simulates the selection of optimal factor (m) based on the cumulative proportion in ANOVA (F of each order harmonicsm), to salinity sample
Harmonic wave simulation is carried out, by each wave subharmonic variance (Sk) descending sequence, the variance of m before ranking different wave subharmonic is tired out
Add, if gained cumulative proportion in ANOVA FmSurpass 85% and the variance contribution ratios of variance m+1 wave subharmonic of ranking is no more than
5%, then m wave is preferred harmonic.
Using harmonic wave method, to per day/lunation of the highest/lowest salinity in no typhoon influence average for many years
Salinity altercation feature is simulated, and obtains the forecasting model of current salinity i.e.:
Save、Smax、SminRespectively per day, highest, lowest salinity, t are the date.
Wherein 23.66,23.91 and the 23.36 of model (1) are when not having typhoon influence within t=30 days in the present embodiment
The weather monthly average salt angle value of lunation, without typhoon influence when lunation highest salt angle value and there is no typhoon shadow by a weather moon
The weather moon lowest salinity value of lunation when ringing；WhereinIt is humorous with 30 days 1 time for the period
Wave pattern, variance 10.59 pass through the significance test of the level of α=0.01；,For with 15
It is the 2 subharmonic models in period, variance 10.93, also by the significance test of the level of α=0.01.1 subharmonic and 2
Subharmonic constitutes 2 order harmonics, i.e., above-mentioned preferred harmonic.Similarly the variance in model (2) and model (3) is also by conspicuousness
It examines.
The extraction and analysis of default time and lunation salinity altercation feature, the same precipitation of the ocean surface salinity regularity of distribution
And the regularity of distribution of the difference (P-E) of evaporation capacity has preferable consistency, and there are one for salinity altercation relative evaporation and Precipitation Process
Fixed hysteresis quality.
Equally climatically there is also similar situations: due to local different year, the precipitation and evaporation capacity in different months
There is notable difference, causes the month seawater salinity after precipitation different.Definition precipitation and the difference (P-E) of evaporation capacity are
Effectiv precipitation, calculate separately different year average/highest/lowest salinity monthly average value and default time and lunation it
The effectiv precipitation in preceding month carries out cross correlation analysis to salinity and effectiv precipitation, can obtain salinity and effectively drop with first 2 months
The correlation of the sum of water is most strong, and related coefficient is 0.5 or more.
Therefore, using the sum of preceding 2 months effectiv precipitations of default time and lunation (P-E), the default time is obtained
And monthly average/highest/lowest salinity of lunationForecasting model are as follows:
Wherein model (4), (5), 26.3,26.6 and 25.9 in (6) do not consider antecedent precipitation and evaporation capacity respectively, obtain
The monthly average in the default time and lunation that take/moon highest/moon lowest salinity value；Model (4)~(6) are substituted into harmonic-model
(1)~(3), the moon salinity effect model and same day obtained using 2 months before default time and lunation effectiv precipitations
Lunar calendar day combines, the per day/highest/lowest salinity model in default time and lunation when predicting no typhoon influence i.e.:
T is lunar date, value 1,2 ... 30；
Per day/highest/lowest salinity model when the model of above-mentioned acquisition is no typhoon influence；
When typhoon diminishing amplitude is larger or Storm Surge Height of Typhoon amplitude is smaller and typhoon precipitation is larger, it is significant to can lead to salinity
Decline.
The difference of minimum per day tidal level during defining the typhoon influence first day and influencing is tidal level variable quantity, defines typhoon shadow
Minimum per day/highest/lowest salinity difference during ringing the first day and influencing is respectively that average/highest/lowest salinity changes
Amount.
Wherein in first kind Typhoon Process, average/highest/lowest salinity variable quantity (defines the typhoon influence first day and typhoon
The difference of minimum during influence is salinity altercation amount) it is negatively correlated with effectiv precipitation, related coefficient is respectively 0.8,0.63
With 0.83, (difference of the minimum per day tidal level during defining the typhoon influence first day and influencing is that tidal level changes with tidal level variable quantity
Amount, per day tidal level are the average gained of real time tide level for 24 hours) it is positively correlated, related coefficient is respectively 0.88,0.86 and 0.85,
Pass through the horizontal significance test in α=0.01；
Wherein in the second class Typhoon Process, the correlation of salinity and each element is not significant.
Therefore actually forecast typhoon influence during per day/highest/lowest salinity when, the second class typhoon is only needed
Model (7)~(9) are substituted into, first kind typhoon are also needed to calculate by precipitation, evaporation capacity and tidal level variable quantity every
The salinity altercation amount of day.
Further, first kind variable Y takes per day, highest, lowest salinity variable quantity (same day salinity and proxima luce (prox. luc) salinity
Difference), be denoted as Y1、Y2、Y3, the second class variable X takes a day accumulative rainfall amount (precipitation of the typhoon influence first day to the same day), day
Evaporation capacity and per day tidal level variable quantity (difference of same day mean tide tlevel and proxima luce (prox. luc) mean tide tlevel), are denoted as X1、X2、X3, every group
Data sample quantity n=28.Carrying out correlation analysis by canonical correlation method can obtain: salinity altercation amount is in accumulative rainfall amount
It is significant negatively correlated, it is significantly positively correlated with tidal level variable quantity, it is negatively correlated with evaporation capacity.
Therefore dependent variable Y1、Y2、Y3Per day, highest, the lowest salinity range of decrease are taken respectively, select 3 independents variable: day accumulation
Precipitation, evaporation capacity and per day tidal level variable quantity (X1、X2、X3) calculate all possible subset regression, and by CSC criterion from
1 optimal subset regression of middle determination.Obtain Y1、Y3Optimal subset is X1、X2、X3, Y2Optimal subset is X1And X3。
Y1=-0.2-0.01X1-0.115X2+2.855X3 (10)
Y2=-0.21-0.007X1+1.316X3 (11)
Y3=-0.81-0.014X1+0.069X2+3.814X3 (12)
Model (10)~(12) substitution (7)~(9) can be obtained to the forecasting model of salinity during first kind typhoon influence:
Wherein, t is lunar date, and value 1,2 ... 30, P is the preceding 2 months precipitation in default time and lunation
The sum of, E is default the sum of time and preceding 2 months evaporation capacity of lunation, X1、X2、X3Respectively day accumulative rainfall amount, evaporation
Amount and per day tidal level variable quantity.
Based on default many years bay culture zone Salinity Data and its neighbouring tide and meteorological data, using frequency analysis,
Salinity altercation feature is simulated when linear regression method is to no typhoon influence, probes into the factor for influencing salinity altercation, herein
On the basis of for different type typhoon by canonical correlation analysis, optimal subset regression method etc., built respectively using many kinds of parameters
Corresponding forecasting model is found, salinity altercation during forecast typhoon influence is attempted, increases utility for sea-farming Meteorological Services.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
In generation, however, it does not deviate from the spirit of the invention or beyond the scope of the appended claims.
Claims (5)
1. a kind of method for cultivating salinity effect model foundation in bay during typhoon influence, which is characterized in that including following
Step:
S1: it is average that per day/highest/lowest salinity default many years daily in lunation when presetting no typhoon influence are obtained
Value, and per day/default long-time average annual value of highest/lowest salinity of acquisition is simulated using harmonic wave method, do not had
When having typhoon influence lunation it is per day/day highest/day lowest salinity forecasting model:
The per day salinity of lunation when Save is no typhoon influence；
The day highest salinity of lunation when Smax is no typhoon influence；
The day lowest salinity of lunation when Smin is no typhoon influence；
The weather monthly average salt angle value of lunation when a is no typhoon influence；
The weather moon highest salt angle value of lunation when b is no typhoon influence；
The weather moon lowest salinity value of lunation when c is no typhoon influence；
T is first day, the 30th day second day ... of lunation；
S2: obtaining the sum of preceding 2 months effectiv precipitation of default time and lunation (P-E), according to the default time and
The sum of preceding 2 months effectiv precipitations of default lunation (P-E) obtains monthly average/moon of default time and default lunation most
The forecasting model of height/moon lowest salinity:
Wherein:
For the monthly average salinity for presetting time and lunation；
For the moon highest salinity for presetting time and lunation；
For the moon lowest salinity for presetting time and lunation；
P is default the sum of the time and the preceding 2 months precipitation of lunation；
E is default the sum of the time and preceding 2 months evaporation capacity of lunation；
E is not consider antecedent precipitation and evaporation, presets the monthly average salt angle value of time and lunation；
F is not consider antecedent precipitation and evaporation, presets the moon highest salt angle value of time and lunation；
G is not consider antecedent precipitation and evaporation, presets the moon lowest salinity value of time and lunation；
S3: when the monthly average of default time and lunation salinity/moon highest salinity/moon lowest salinity substitution is not had typhoon influence
Lunation it is per day/day highest/day lowest salinity forecasting model in, obtain predicting when no typhoon influence the default time and
Lunation it is per day/day highest/day lowest salinity forecasting model:
SyaveFor the forecasting model of the per day salinity of lunation during no typhoon influence；
SymaxFor during no typhoon influence lunation day highest salinity forecasting model；
SyminFor during no typhoon influence lunation day lowest salinity forecasting model；
T is first day, the 30th day second day ... of lunation；
S4: take it is per day during preset data sample typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3, typhoon shadow
Day adds up precipitation/daily evaporation amount/per day tidal level variable quantity X during sound1/X2/X3, typhoon is obtained by optimal subset method
It is per day during influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3And add up day to steam precipitation/day during typhoon influence
Hair amount/per day tidal level variable quantity X1/X2/X3Between relationship model:
Y1=-0.2-0.01X1-0.115X2+2.855X3 (10)
Y2=-0.21-0.007X1+1.316X3 (11)
Y3=-0.81-0.014X1+0.069.Xz+3.814X3 (12)
By it is per day during typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3Increase respectively to no typhoon influence
Period lunation it is per day/day highest/day lowest salinity forecasting model Syave/Symax/SyminIn obtain prediction have typhoon shadow
During sound lunation it is per day/day highest/day lowest salinity forecasting model:
2. a kind of method for cultivating salinity effect model foundation in bay during typhoon influence according to claim 1,
It is characterized in that, in step S1 further include:
Proxima luce (prox. luc) salinity A and salinity B during typhoon influence during acquisition typhoon influence；
Obtain the difference of salinity B minimum during proxima luce (prox. luc) salinity A and typhoon influence during typhoon influence: (A-B)
Judge the difference (A-B) of salinity minimum during proxima luce (prox. luc) salinity and typhoon influence during typhoon influence whether less than 0；
If (A-B) is less than 0, it is determined that the typhoon is first kind typhoon；If (A-B) is not less than 0, it is determined that the typhoon is the second class
Typhoon.
3. a kind of method for cultivating salinity effect model foundation in bay during typhoon influence according to claim 1,
It is characterized in that, in step S2 further include:
Respectively to the sum of preceding 2 months effectiv precipitations in default time and lunation (P-E) and default time and lunation
Monthly average/highest/lowest salinity is analyzed according to cross correlation analysis method, obtains the salinity of default time and lunation
With the related coefficient of the sum of preceding 2 months effectiv precipitations；
To the related coefficients of the sum of 2 months effectiv precipitations before default time and lunation salinity and default time and lunation into
Row significance test obtains level of significance test value, judges whether the significance test by the level of α=0.01；
If so, carrying out the salt of default time and lunation by presetting the sum of time and preceding 2 months effectiv precipitations of lunation
Degree forecast.
4. a kind of method for cultivating salinity effect model foundation in bay during typhoon influence according to claim 2,
It is characterized in that, step S4 is further comprised the steps of:
It obtains during first kind typhoon influence during per day/highest/lowest salinity variable quantity and first kind typhoon influence effectively
Per day/highest/lowest salinity variable quantity and first kind typhoon during the related coefficient and first kind typhoon influence of precipitation
The related coefficient of tidal level variable quantity during influence；
Per day during first kind typhoon influence/highest/lowest salinity variable quantity is effectively dropped with during first kind typhoon influence
Per day/highest/lowest salinity variable quantity and first kind typhoon influence during the related coefficient and first kind typhoon influence of water
The related coefficient of period effective tidal level variable quantity carries out significance test, obtains level of significance test value；
During obtaining the second class typhoon influence during per day/highest/lowest salinity variable quantity and the second class typhoon influence effectively
Per day/highest/lowest salinity variable quantity and the second class typhoon during the related coefficient of precipitation and the second class typhoon influence
The related coefficient of effective tidal level variable quantity during influence；
Per day/highest/lowest salinity variable quantity during second class typhoon influence is effectively dropped with during the second class typhoon influence
Per day/highest/lowest salinity variable quantity and the second class typhoon influence during the related coefficient of water and the second class typhoon influence
The related coefficient of period effective tidal level variable quantity carries out significance test, obtains level of significance test value；
According to the level of significance test value of the first kind typhoon of acquisition and the second class typhoon, during confirming first kind typhoon influence
Influence salinity altercation impact factor and during the second class typhoon influence influence salinity altercation impact factor.
5. a kind of method for cultivating salinity effect model foundation in bay during typhoon influence according to claim 1,
It is characterized in that, in step S4 further include:
It is per day during obtaining preset data sample first kind typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3,
Day adds up precipitation/daily evaporation amount/per day tidal level variable quantity X1/X2/X3 during first kind typhoon influence, to this two groups of Y and X
Data carry out canonical correlation analysis, obtain the related coefficient between them and carry out significance test to it, obtain conspicuousness inspection
Level value is tested, salinity altercation amount and day add up precipitation, daily evaporation amount and per day tidal level during confirming first kind typhoon influence
Correlation between variable quantity；
It is per day during calculating preset data sample first kind typhoon influence/day highest/day lowest salinity variable quantity Y1/Y2/Y3,
Add up subset regression all in precipitation/daily evaporation amount/per day tidal level variable quantity X1/X2/X3 during typhoon influence day, and
1 optimal subset regression is therefrom determined by CSC criterion.
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