CN106202949B - A kind of ENSO periods icing responsiveness analysis method - Google Patents
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Abstract
The invention discloses a kind of ENSO periods icing responsiveness analysis method, this method is following step：(1), data acquisition；(2.1), ENSO exponent datas divide；(2.2), icing data divide；(3), mean value calculation；(4.1), maximum icing number of days anomaly value calculates；(4.2), maximum ice covering thickness anomaly value calculates；(5.1), maximum icing number of days and ENSO intensity dependences calculate；(5.2), maximum ice covering thickness and ENSO intensity dependence calculates；(6.1), ENSO period anomaly value response condition；(6.2), ENSO period correlations response condition.The beneficial effects of the invention are as follows：1st, ENSO period powerline ice-covering generality features and its response condition to ENSO events more can comprehensively be recognized；2nd, it is workable；3rd, the specific aim of powerline ice-covering preventing and controlling is improved.
Description
Technical field
The invention belongs to electrical engineering technical field, more particularly to a kind of ENSO periods icing responsiveness calculates and analysis
Method.
Background technology
With the propulsion of energy internet and the construction of interregional grid, many environmental factor shadows that power transmission line corridor is subject to
Sound is increasingly valued by people.Icing serious threat transmission line safety stable operation.The southern area ice damage of 2008
Cause transmission line of electricity and fall tower more than 1300 bases, property loss more than 12,000,000,000 yuan, stop transport, steady to society by the wide electric railway in capital
Fixed and people production causes serious threat with life.Liaoning " 11.7 " ice damage in 2015 causes 38 general-purpose families to have a power failure, and tripping operation exceedes
300 times, add up the kilowatt hour of power loss 640,000, expose northern area transmission line of electricity and exist not in terms of icing disaster is resisted
Foot.Therefore, the prediction of winter icing and icing signature analysis are carried out for rational allocation resource, necessity of reduction icing casualty loss
Property is self-evident.And ENSO events (including EI Nino event and Ramsey numbers) are by influenceing China's climate characteristic, one
Determine to control winter icing occurrence condition in degree.Although ENSO is influenceed to examine by current power network icing degree Forecasting Methodology
Including worry, but indifference statistics is carried out mainly for the data of a period of time, ignore the particularity in ENSO periods, therefore dividing
The obvious situation of less pertinence is still had during the general feature of analysis ENSO periods icing response.For summarize icing occur and
Increasing law, the research and analysis of progress ENSO period icing responsiveness are imperative, targetedly covered to carry out
Ice prediction and warning, power network Disaster Prevention Measures are formulated as early as possible, reduce the loss that power network disaster may be brought, safeguard that electricity net safety stable is transported
OK.
The content of the invention
Lack analysis for ENSO period powerline ice-covering generality features and its to the response condition of ENSO events
Present situation, the present invention provide a kind of ENSO periods icing responsiveness analysis method, this method thinking novelty, clear process, operation
Simply.
To achieve the above object, technical scheme is as follows：
A kind of ENSO periods icing responsiveness analysis method, comprises the following steps：
(1) the ENSO indexes of icing data and every month icing phase corresponding to regional the past period to be analyzed, are obtained
Data, icing data include regional maximum icing number of days to be analyzed every month icing phase and maximum ice covering thickness；
(2.1), the property according to ENSO events, during by ENSO exponent datas according to EI Nino period data, La Nina
Issue evidence, non-ENSO period datas are divided into three classes, are arranged per the data in a kind of still according to time sequencing；
(2.2), EI Nino period, La Nina's period, the non-ENSO periods that control ENSO indexes are characterized, it is analysed to
Regional icing data are respectively divided into EI Nino period data, La Nina's period data, the non-class of ENSO period datas three, each
Data in class arrange still according to time sequencing；
(3.1) the regional EI Nino period icing data to be analyzed, obtained in selecting step (2.2), according to formula
(1) average value of its EI Nino period maximum icing number of days, is calculatedWith the average value of maximum ice covering thicknessAgain
Regional La Nina's period icing data to be analyzed are chosen, according to formula (1), its La Nina period maximum icing number of days is calculated
Average valueWith the average value of maximum ice covering thicknessThe non-ENSO periods icing data in area to be analyzed are chosen, according to formula
(1) average value of its non-ENSO periods maximum icing number of days, is calculatedWith the average value of maximum ice covering thickness
In formula,For non-ENSO periods, EI Nino period or La Nina when interim a certain period maximum icing number of days or most
The average value of big ice covering thickness, xiFor the data of this period maximum icing number of days or maximum ice covering thickness, n is the period data
Total amount；
(3.2) icing data, are replaced with ENSO exponent datas, repeat step (3.1), different times ENSO indexes is obtained and puts down
Average；
(4.1), the regional EI Nino period maximum icing number of days average value to be analyzed that will be obtained in step (3.1)
With the non-ENSO periods maximum icing number of days average value in area to be analyzedSubtract each other, obtained result is as regional ell Buddhist nun to be analyzed
Promise period maximum icing number of days anomaly value
(4.2), the regional EI Nino period maximum ice covering thickness average value to be analyzed that will be obtained in step (3.1)With
The non-ENSO periods maximum ice covering thickness average value in area to be analyzedSubtract each other, obtained result is as regional ell Buddhist nun to be analyzed
Promise period maximum ice covering thickness anomaly value
(4.3), respectively with regional La Nina's period maximum icing number of days average value to be analyzedPut down with maximum ice covering thickness
AverageInstead ofWithRepeat step (4.1)~(4.2), obtain regional La Nina's period maximum icing number of days to be analyzed away from
Level values Aa2With maximum ice covering thickness anomaly value Ab2；
(5.1), the EI Nino period ENSO exponent datas obtained in selecting step (2.1)~(4.3) with to be analyzedly
Area's EI Nino period maximum icing number of days, according to formula (2), the maximum icing number of days in area to be analyzed and ell Buddhist nun is calculated
The correlation coefficient r of promise intensitya1：
In formula, r is that the maximum icing number of days in area to be analyzed or maximum ice covering thickness and strength of El Nino or La Nina are strong
The coefficient correlation of degree, xiFor EI Nino period or La Nina when interim a certain period maximum icing number of days or maximum icing it is thick
Degree,For the average value of this kind of icing data of this period, yiFor the data of this period ENSO indexes,For this period
The average value of ENSO indexes, n are this period data total amount；
(5.2), with regional EI Nino period maximum ice covering thickness data to be analyzed and maximum ice covering thickness average value point
Not instead of EI Nino period maximum icing number of days data and maximum icing number of days average value, formula (2) is substituted into, is calculated and treats
The correlation coefficient r of the maximum ice covering thickness in analysis area and strength of El Ninob1；
(5.3) when, replacing EI Nino respectively with regional La Nina's period maximum icing number of days to be analyzed and ice covering thickness
Phase maximum icing number of days and ice covering thickness, repeat step (5.1)~(5.2), the maximum icing number of days in area to be analyzed are obtained with drawing
The correlation coefficient r of Naina intensitya2With maximum ice covering thickness and the correlation coefficient r of La Nina's intensityb2；
(6.1), the EI Nino period anomaly value that step (4.1)~(4.2) are calculated is analyzed, if to be analyzed
Regional EI Nino period maximum icing number of days anomaly value Aa1Or maximum ice covering thickness anomaly value Ab1For just, then it is assumed that ell Buddhist nun
Promise easily causes the increase of maximum icing number of days or maximum ice covering thickness；Otherwise it is assumed that EI Nino easily causes maximum icing day
The reduction of several or maximum ice covering thickness；
Again by above-mentioned Aa1And Ab1Formula (3) is substituted into, EI Nino, which is calculated, influences coefficient：
In formula, E is that ENSO influences coefficient, and it obtains EI Nino influence coefficient, generation after substituting into EI Nino period data
La Nina's influence coefficient, A are obtained after entering La Nina's period dataaFor corresponding EI Nino period or La Nina's period maximum icing
Number of days anomaly value, AbFor this period maximum ice covering thickness anomaly value；
Influenceed based on EI Nino shown in the icing anomaly responsiveness judgment mode such as table (1) of coefficient：
Table (1) icing anomaly responsiveness table
(6.2) the regional icing to be analyzed and strength of El Nino coefficient correlation, obtained to step (5.1)~(5.2) enters
Row significance test, test of significance of coefficient of correlation table is looked into, if the maximum icing number of days in area to be analyzed and strength of El Nino
Correlation coefficient ra1Absolute value or the correlation coefficient r of maximum ice covering thickness and strength of El Ninob1Absolute value be more than table in it is right
Answer the significantly correlated threshold value r under the free degree0, then it is assumed that the coefficient correlation by significance test, treat point by EI Nino event
The influence for analysing regional icing duration or ice covering thickness is significant；Otherwise it is assumed that the coefficient correlation is examined not over conspicuousness
Test, EI Nino event treats the analysis regional icing duration or the influence of ice covering thickness there may be, but and inapparent；
(6.3), respectively with La Nina's period anomaly value and area to be analyzed maximum icing number of days/maximum ice covering thickness with drawing
Naina interaural correlation coefficient replaces the maximum icing number of days of EI Nino period anomaly value and area to be analyzed/maximum icing thick respectively
Degree and strength of El Nino coefficient correlation, repeat step (6.1)~(6.2), progress La Nina's period anomaly value and correlation
Response analysis, step (5.1)~(5.2) are replaced with step (5.3) in step (6.2).
The beneficial effects of the invention are as follows：
1st, ENSO period powerline ice-covering generality features and its sound to ENSO events more can comprehensively be recognized
Answer situation；
2nd, it is workable；
3rd, the specific aim of powerline ice-covering preventing and controlling is improved.According to analysis result, accordingly should can carry out in time
Anxious Disposal Measures, for the icing area obvious to ENSO event responses, carry out in the winter in ENSO periods and tackle in advance
Work, reduce grid loss.
Brief description of the drawings
Fig. 1 is the flow chart of analysis method of the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawings and example, the present invention will be further described.
The thinking of the embodiment of the present invention is：A kind of ENSO periods icing responsiveness analysis method, consider that each province transmits electricity
General feature and ENSO event intensity influence to powerline ice-covering of the line ice coating in ENSO periods, foundation are based on
The computational methods of ENSO period icing anomaly values and icing and ENSO intensity dependences, obtain ENSO period icing responders
Analytical conclusions.
As shown in figure 1, analysis method of the embodiment of the present invention comprises the steps.
(1), data acquisition.Icing data and ENSO exponent datas corresponding to the time are obtained, each province is obtained and goes over 20 years
Icing data, including the maximum icing number of days of each province's every month icing phase and maximum ice covering thickness.Obtain 20 years icing phases in the past
The ENSO exponent datas of every month；
(2.1), ENSO exponent datas divide.According to ENSO events property (ENSO events include EI Nino event and
Ramsey numbers), by ENSO exponent datas according to EI Nino period data, La Nina's period data, non-ENSO period datas
Three classes are divided into, are arranged per the data in a kind of still according to time sequencing；
(2.2), icing data divide.Control ENSO indexes characterized EI Nino period, La Nina's period, non-ENSO
In period, each province's icing data are respectively divided into EI Nino period data, La Nina's period data, non-ENSO period datas three
Class, arranged per the data in a kind of still according to time sequencing；
(3.1), mean value calculation.Certain obtained in selecting step (2.2) saves EI Nino period icing data, according to public affairs
Formula (1), the average value of its EI Nino period maximum icing number of days is calculatedWith the average value of maximum ice covering thickness
Province La Nina period icing data are chosen again, and according to formula (1), the flat of its La Nina period maximum icing number of days is calculated
AverageWith the average value of maximum ice covering thicknessThe non-ENSO periods icing data of the province are chosen, according to formula (1), are calculated
To the average value of its non-ENSO periods maximum icing number of daysWith the average value of maximum ice covering thickness
In formula,For maximum icing number of days of a certain period (non-ENSO periods, EI Nino period or La Nina's period) or most
The average value of big ice covering thickness, xiFor this period (non-ENSO periods, EI Nino period or La Nina's period) maximum icing
The data of number of days or maximum ice covering thickness, n are the period data total amount.
(3.2) icing data, are replaced with ENSO exponent datas, repeat step (3.1), different times ENSO indexes is obtained and puts down
Average；
(4.1), maximum icing number of days anomaly value calculates.Certain obtained in step (3) is saved into EI Nino period maximum to cover
Ice day number average valueWith the non-ENSO periods maximum icing number of days average value in corresponding provinceSubtract each otherObtain
As a result it is used as province's EI Nino period maximum icing number of days anomaly value Aa1；
(4.2), maximum ice covering thickness anomaly value calculates.Certain obtained in step (3) is saved into EI Nino period maximum to cover
Ice thickness average valueWith the non-ENSO periods maximum ice covering thickness average value in corresponding provinceSubtract each otherObtain
As a result it is used as province's EI Nino period maximum ice covering thickness anomaly value Ab1。
(4.3), respectively with selected province La Nina period maximum icing number of days average valueIt is averaged with maximum ice covering thickness
ValueInstead ofWithRepeat step (4.1)~(4.2), obtain province La Nina period maximum icing number of days anomaly value Aa2
With maximum ice covering thickness anomaly value Ab2；
(5.1), maximum icing number of days and ENSO intensity dependences calculate.The strategic point obtained in selecting step (2.1)~(4.3)
That Nino period ENSO exponent datas and certain province's EI Nino period maximum icing number of days, according to formula (2), are calculated the province
The correlation coefficient r of maximum icing number of days and strength of El Ninoa1：
In formula, r is that the maximum icing number of days in area to be analyzed or maximum ice covering thickness and strength of El Nino or La Nina are strong
The coefficient correlation of degree, xiFor certain icing data (maximum icing day in a certain period (EI Nino period or La Nina's period)
Several or maximum ice covering thickness),For the average value of this kind of icing data of this period, yiFor the data of this period ENSO indexes,For the average value of this period ENSO indexes, n is this period data total amount；
(5.2), maximum ice covering thickness and ENSO intensity dependence calculates.With certain province's EI Nino period maximum ice covering thickness
The average value of data and maximum ice covering thickness replaces EI Nino period maximum icing number of days data and maximum icing number of days respectively
Average value, formula (2) is substituted into, the correlation coefficient r of province's maximum ice covering thickness and strength of El Nino is calculatedb1。
(5.3) EI Nino period, is replaced with selected province La Nina period maximum icing number of days and ice covering thickness respectively
Maximum icing number of days and ice covering thickness, repeat step (5.1)~(5.2), obtain province's maximum icing number of days and La Nina's intensity
Correlation coefficient ra2With maximum ice covering thickness and the correlation coefficient r of La Nina's intensityb2；
(6.1), ENSO period anomaly value response condition.The EI Nino period that step (4.1)~(4.2) are calculated
Anomaly value is analyzed, if certain saves EI Nino period maximum icing number of days anomaly value Aa1Or maximum ice covering thickness anomaly value Ab1
For just, then it is assumed that EI Nino easily causes the increase of maximum icing number of days or maximum ice covering thickness.Otherwise it is assumed that EI Nino
Easily cause the reduction of maximum icing number of days or maximum ice covering thickness.
Again by above-mentioned Aa1And Ab1Formula (3) is substituted into, EI Nino, which is calculated, influences coefficient：
In formula, E is that ENSO influences coefficient (obtains EI Nino influence coefficient after substituting into EI Nino period data, substituted into
La Nina is obtained after La Nina's period data influences coefficient), AaFor corresponding period (EI Nino period or La Nina's period) most
Big icing number of days anomaly value, AbFor this period maximum ice covering thickness anomaly value.
Influenceed based on EI Nino shown in the icing anomaly responsiveness judgment mode such as table (1) of coefficient：
Table (1) icing anomaly responsiveness table
(6.2), ENSO period correlations response condition.Each province's icing that step (5.1)~(5.2) are obtained and ell Buddhist nun
Promise interaural correlation coefficient carries out significance test, looks into test of significance of coefficient of correlation table, if certain saves maximum icing number of days and ell
The correlation coefficient r of Nino intensitya1Absolute value or the correlation coefficient r of maximum ice covering thickness and strength of El Ninob1Absolute value
More than the significantly correlated threshold value r corresponded in table under the free degree0, then it is assumed that the coefficient correlation passes through significance test, EI Nino
Influence of the event to province's icing duration or ice covering thickness is significant.Otherwise it is assumed that the coefficient correlation is not over notable
Property examine, influence of the EI Nino event to province's icing duration or ice covering thickness there may be, but and inapparent；
(6.3) it is strong with La Nina with La Nina's period anomaly value and each province's maximum icing number of days (maximum ice covering thickness) respectively
Spend coefficient correlation and replace EI Nino period anomaly value and each province's maximum icing number of days (maximum ice covering thickness) and ell Buddhist nun respectively
Promise interaural correlation coefficient, repeat step (6.1)~(6.2), carry out the response analysis of La Nina's period anomaly value and correlation；This
When step (6.2) in step (5.1)~(5.2) need to be replaced with step (5.3).
Also repeatable step (3.1)~(6.2), complete the response analysis in all provinces.
The beneficial effect of the embodiment of the present invention is：
1st, ENSO period powerline ice-covering generality features and its sound to ENSO events more can comprehensively be recognized
Answer situation；
2nd, it is workable；
3rd, the specific aim of powerline ice-covering preventing and controlling is improved.According to analysis result, accordingly should can carry out in time
Anxious Disposal Measures, for the icing area obvious to ENSO event responses, carry out in the winter in ENSO periods and tackle in advance
Work, reduce grid loss.
The inventive method is illustrated by taking Liaoning Province as an example below.This method comprises the following steps：
(1), data acquisition.Obtain icing data and ENSO exponent datas corresponding to the time：Liaoning Province is obtained to go over 20 years
Icing data, including the maximum icing number of days of every month icing phase and maximum ice covering thickness；It is every to obtain 20 years icing phases in the past
A kind of individual month ONI (ocean NINO indexes, ENSO indexes) data；
(2.1), ENSO exponent datas divide.According to ENSO events property (ENSO events include EI Nino event and
Ramsey numbers), ONI data are divided into according to EI Nino period data, La Nina's period data, non-ENSO period datas
Three classes, arranged per the data in a kind of still according to time sequencing；
(2.2), icing data divide.Choose Liaoning Province icing data, control ONI characterized EI Nino period,
La Nina's period, non-ENSO periods, icing data are respectively divided into EI Nino period data, La Nina's period data, non-
The class of ENSO period datas three, arranged per the data in a kind of still according to time sequencing；
(3.1), mean value calculation.Based on the data obtained in step (2.2), non-ENSO periods icing data are chosen, are pressed
According to formula (1), the average value of its non-ENSO periods maximum icing number of days and maximum ice covering thickness is calculated.Choose EI Nino
Period icing data, according to formula (1), the flat of its EI Nino period maximum icing number of days and maximum ice covering thickness is calculated
Average.
(3.2) La Nina's period icing data, are chosen again, according to formula (1), its La Nina period maximum are calculated and covers
The average value of ice day number and maximum ice covering thickness.Icing data are replaced with ONI data, repeat step (3.1), obtain different times
ONI average values；
(4.1), maximum icing number of days anomaly value calculates.The EI Nino period maximum icing day that will be obtained in step (3)
Number average value subtracts each other with corresponding non-ENSO periods maximum icing number of days average value, obtains EI Nino period maximum icing number of days
Anomaly value 1.3 days；
(4.2), maximum ice covering thickness anomaly value calculates.The EI Nino period maximum icing obtained in step (3) is thick
Degree average value subtracts each other with corresponding non-ENSO periods maximum ice covering thickness average value, obtains EI Nino period maximum ice covering thickness
2.1 millimeters of anomaly value；
(4.3) EI Nino period maximum icing, is replaced with La Nina's period maximum icing number of days and ice covering thickness respectively
Number of days and ice covering thickness, repeat step (4.1)~(4.2) obtain La Nina's period maximum icing number of days anomaly value 1.5 days and most
Big 1.1 millimeters of ice covering thickness anomaly value；
(5.1), maximum icing number of days and ENSO intensity dependences calculate.The strategic point obtained in selecting step (2.1)~(4.3)
That Nino period ONI data and EI Nino period maximum icing number of days, according to formula (2), are calculated maximum icing number of days
Coefficient correlation with strength of El Nino is 0.26；
(5.2), maximum ice covering thickness and ENSO intensity dependence calculates.The strategic point obtained in selecting step (2.1)~(4.2)
That Nino period ONI data and EI Nino period maximum ice covering thickness, according to formula (2), are calculated maximum ice covering thickness
Coefficient correlation with strength of El Nino is 0.19；
(5.3) EI Nino period maximum icing, is replaced with La Nina's period maximum icing number of days and ice covering thickness respectively
Number of days and ice covering thickness, repeat step (5.1)~(5.2), obtain the coefficient correlation of maximum icing number of days and La Nina's intensity
0.21 and the coefficient correlation 0.28 of maximum ice covering thickness and La Nina's intensity；
(6.1), ENSO period anomaly value response condition.The EI Nino period that step (4.1)~(4.2) are calculated
Anomaly value is analyzed, because Liaoning Province's EI Nino period maximum icing number of days (maximum ice covering thickness) anomaly value is just, to recognize
The increase of maximum icing number of days (maximum ice covering thickness) is easily caused for EI Nino.Ell is calculated by formula (3)
It is 1.3 that Nino, which influences coefficient, it is believed that icing anomaly has slight response to EI Nino；
(6.2), ENSO period correlations response condition.Liaoning Province's icing and ell that step (5.1)~(5.2) are obtained
Nino interaural correlation coefficient carries out significance test, looks into test of significance of coefficient of correlation table, (maximum is covered due to maximum icing number of days
Ice thickness) it is less than with the coefficient correlation absolute value of strength of El Nino in table and corresponds under the free degree, under 95% significance
Significantly correlated threshold value 0.29, then it is assumed that influence of the EI Nino event to Liaoning Province's icing duration (icing intensity) does not show
Write；
(6.3) respectively with La Nina's period anomaly value and Liaoning Province's maximum icing number of days (maximum ice covering thickness) and La Nina
Interaural correlation coefficient replaces EI Nino period anomaly value and Liaoning Province's maximum icing number of days (maximum ice covering thickness) and strategic point respectively
That Nino interaural correlation coefficient, repeat step (6.1)~(6.2), carries out La Nina's period anomaly value and correlation response analysis,
Now step (5.1)~(5.2) need to be replaced with step (5.3) in step (6.2).It is again seen that La Nina easily causes Liaoning Province
Slight response, while La Nina's thing to La Nina be present in the increase of maximum icing number of days (maximum ice covering thickness), Liaoning Province's icing
Influence of the part to Liaoning Province's icing duration (icing intensity) be not notable.
Claims (1)
1. a kind of ENSO periods icing responsiveness analysis method, it is characterised in that comprise the following steps：
(1) the ENSO exponent datas of icing data and every month icing phase corresponding to regional the past period to be analyzed, are obtained,
Icing data include regional maximum icing number of days to be analyzed every month icing phase and maximum ice covering thickness；
(2.1), the property according to ENSO events, by ENSO exponent datas according to EI Nino period data, La Nina's epoch number
Three classes are divided into according to, non-ENSO period datas, are arranged per the data in a kind of still according to time sequencing；
(2.2), EI Nino period, La Nina's period, the non-ENSO periods that control ENSO indexes are characterized, it is analysed to area
Icing data are respectively divided into EI Nino period data, La Nina's period data, the non-class of ENSO period datas three, in a kind of
Data still according to time sequencing arrange；
(3.1) the regional EI Nino period icing data to be analyzed, obtained in selecting step (2.2), according to formula (1), meter
Calculation obtains the average value of its EI Nino period maximum icing number of daysWith the average value of maximum ice covering thicknessChoose and treat again
Regional La Nina's period icing data are analyzed, according to formula (1), being averaged for its La Nina period maximum icing number of days is calculated
ValueWith the average value of maximum ice covering thicknessThe non-ENSO periods icing data in area to be analyzed are chosen, according to formula (1), meter
Calculation obtains the average value of its non-ENSO periods maximum icing number of daysWith the average value of maximum ice covering thickness
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In formula,For non-ENSO periods, EI Nino period or La Nina when interim a certain period maximum icing number of days or maximum cover
The average value of ice thickness, xiFor the data of this period maximum icing number of days or maximum ice covering thickness, n is that the period data is total
Amount；
(3.2) icing data, are replaced with ENSO exponent datas, repeat step (3.1), obtain different times ENSO exponential averages
Value；
(4.1), the regional EI Nino period maximum icing number of days average value to be analyzed that will be obtained in step (3.1)With treating point
The non-ENSO periods maximum icing number of days average value in analysis areaSubtract each other, when obtained result is as regional EI Nino to be analyzed
Phase maximum icing number of days anomaly value
(4.2), the regional EI Nino period maximum ice covering thickness average value to be analyzed that will be obtained in step (3.1)With treating point
The non-ENSO periods maximum ice covering thickness average value in analysis areaSubtract each other, obtained result is as regional EI Nino period to be analyzed
Maximum ice covering thickness anomaly value
(4.3), respectively with regional La Nina's period maximum icing number of days average value to be analyzedWith maximum ice covering thickness average valueInstead ofWithRepeat step (4.1)~(4.2), obtain regional La Nina's period maximum icing number of days anomaly value to be analyzed
Aa2With maximum ice covering thickness anomaly value Ab2；
(5.1), the EI Nino period ENSO exponent datas obtained in selecting step (2.1)~(4.3) and area strategic point to be analyzed
That Nino period maximum icing number of days, according to formula (2), is calculated the maximum icing number of days in area to be analyzed and EI Nino is strong
The correlation coefficient r of degreea1：
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In formula, r is the maximum icing number of days in area to be analyzed or maximum ice covering thickness and strength of El Nino or La Nina's intensity
Coefficient correlation, xiFor EI Nino period or La Nina when interim a certain period maximum icing number of days or maximum ice covering thickness,
For the average value of this kind of icing data of this period, yiFor the data of this period ENSO indexes,For this period ENSO indexes
Average value, n is this period data total amount；
(5.2), distinguished with the average value of regional EI Nino period maximum ice covering thickness data to be analyzed and maximum ice covering thickness
Instead of EI Nino period maximum icing number of days data and maximum icing number of days average value, formula (2) is substituted into, is calculated and treats point
The correlation coefficient r of the maximum ice covering thickness in analysis area and strength of El Ninob1；
(5.3) EI Nino period, is replaced most with regional La Nina's period maximum icing number of days to be analyzed and ice covering thickness respectively
Big icing number of days and ice covering thickness, repeat step (5.1)~(5.2), obtain the maximum icing number of days in area to be analyzed and La Nina
The correlation coefficient r of intensitya2With maximum ice covering thickness and the correlation coefficient r of La Nina's intensityb2；
(6.1), the EI Nino period anomaly value that step (4.1)~(4.2) are calculated is analyzed, if area to be analyzed
EI Nino period maximum icing number of days anomaly value Aa1Or maximum ice covering thickness anomaly value Ab1For just, then it is assumed that EI Nino holds
Easily cause the increase of maximum icing number of days or maximum ice covering thickness；Otherwise it is assumed that EI Nino easily cause maximum icing number of days or
The reduction of maximum ice covering thickness；
Again by above-mentioned Aa1And Ab1Formula (3) is substituted into, EI Nino, which is calculated, influences coefficient：
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In formula, E is that ENSO influences coefficient, and it obtains EI Nino influence coefficient after substituting into EI Nino period data, substitutes into and draws
La Nina is obtained after Naina period data influences coefficient, AaFor corresponding EI Nino period or La Nina's period maximum icing number of days
Anomaly value, AbFor this period maximum ice covering thickness anomaly value；
Based on EI Nino influence coefficient icing anomaly responsiveness judgment mode be：
If section where influenceing coefficient E is E≤1.5, icing is slight to ENSO responsiveness；
If section where influenceing coefficient E is 1.5 ＜ E≤3.8, icing is weak to ENSO responsiveness；
If section where influenceing coefficient E is 3.8 ＜ E≤6.9, during icing is to ENSO responsiveness；
If section where influenceing coefficient E is 6.9 ＜ E≤10, icing is strong to ENSO responsiveness；
If section where influenceing coefficient E is 10 ＜ E, icing is extremely strong to ENSO responsiveness；
(6.2) the regional icing to be analyzed and strength of El Nino coefficient correlation, obtained to step (5.1)~(5.2) shows
Work property is examined, and test of significance of coefficient of correlation table is looked into, if the maximum icing number of days in area to be analyzed is related to strength of El Nino
Coefficient ra1Absolute value or the correlation coefficient r of maximum ice covering thickness and strength of El Ninob1Absolute value be more than in table it is corresponding from
By the significantly correlated threshold value r under degree0, then it is assumed that the coefficient correlation is treated analytically by significance test, EI Nino event
The influence of area's icing duration or ice covering thickness is significant；Otherwise it is assumed that the coefficient correlation is not over significance test,
EI Nino event treats the analysis regional icing duration or the influence of ice covering thickness there may be, but and inapparent；
(6.3), La Nina's period anomaly value that step (4.3) is calculated is analyzed, if during regional La Nina to be analyzed
Phase maximum icing number of days anomaly value Aa2Or maximum ice covering thickness anomaly value Ab2For just, then it is assumed that La Nina easily causes maximum and covered
The increase of ice day number or maximum ice covering thickness；Otherwise it is assumed that La Nina easily causes maximum icing number of days or maximum ice covering thickness
Reduce；
Again by above-mentioned Aa2And Ab2Formula (3) is substituted into, La Nina, which is calculated, influences coefficient E；
Based on La Nina influence coefficient icing anomaly responsiveness judgment mode be：
If section where influenceing coefficient E is E≤1.5, icing is slight to ENSO responsiveness；
If section where influenceing coefficient E is 1.5 ＜ E≤3.8, icing is weak to ENSO responsiveness；
If section where influenceing coefficient E is 3.8 ＜ E≤6.9, during icing is to ENSO responsiveness；
If section where influenceing coefficient E is 6.9 ＜ E≤10, icing is strong to ENSO responsiveness；
If section where influenceing coefficient E is 10 ＜ E, icing is extremely strong to ENSO responsiveness；
The regional icing to be analyzed obtained to step (5.3) carries out significance test with La Nina's interaural correlation coefficient, looks into correlation
Coefficient significance test table, if the maximum icing number of days in area to be analyzed and the correlation coefficient r of La Nina's intensitya2Absolute value or most
Big ice covering thickness and the correlation coefficient r of La Nina's intensityb2Absolute value be more than in table and correspond to significantly correlated threshold value under the free degree
r0, then it is assumed that the coefficient correlation is by significance test, and Ramsey numbers treat the analysis regional icing duration or icing is thick
The influence of degree is significant；Otherwise it is assumed that the coefficient correlation, not over significance test, Ramsey numbers treat analysis area
The influence of icing duration or ice covering thickness there may be, but and inapparent.
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