CN104809508A - Novel statistical forecasting method for precipitation in raining seasons in middle and lower Yangtz River - Google Patents
Novel statistical forecasting method for precipitation in raining seasons in middle and lower Yangtz River Download PDFInfo
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Abstract
The invention provides a novel statistical forecasting method for precipitation in raining seasons in the middle and lower Yangtz River. The method specifically includes: 1), performing interannual and interdecadal time scale separation on the precipitation in the reasons in the middle and lower Yangtz River by adopting a harmonic analysis method, and separating interannual and interdecadal time scales into an interannual component (RA) of a period of 2 years </=T,8 years, an interdecadal component (RD1) of a period of 8 years</=T<30 years and an interdecadal component (RD2) of a period >/=30 years; 2), searching physical factors related to the RA, the RD1 and the RD2 in the global range as forecasting factors by adopting a related analysis method; 3), respectively establishing different statistical forecasting models according to the RA, the RD1 and the RD2 by adopting a linear regression method and adding the RA, the RD1 and the RD2 which are forecast to acquire forecast precipitation in the raining seasons in the middle and lower Yangtz River. With the method, the precipitation of different time scales in the raining seasons in the middle and lower Yangtz River can be respectively forecast can be forecast, the impact on forecasting results due to inconformity of the internanual and interdecadal forecasting signals is avoided, and a good forecasting effect is achieved for the precipitation in the raining seasons in the middle and lower Yangtz River.
Description
Technical field
The present invention relates to the statistical prediction methods of a kind of middle and lower reach of Yangtze River Summer Rainfall, middle and lower reach of Yangtze River Summer Rainfall can be carried out time scale separation by one specifically, and the Summer Rainfall of Different time scales is predicted respectively, and then obtain the method for middle and lower reach of Yangtze River flood season precipitation prediction value.
Background technology
The flood season of the middle and lower reach of Yangtze River mainly refers to annual 6-7 month, due to this period, rainy persistent time is long, intensity is large, therefore often there is flood in In Middle And Lower Reaches of Changjiang River, the foremost flood several times occurred as modern age occurs in 1954,1991,1998 and 1999 respectively, causes great loss to the economy of In Middle And Lower Reaches of Changjiang River and people's property safety.Therefore, middle and lower reach of Yangtze River flood season precipitation prediction is annual climate in china Flood Period Prediction key content.
Because Asian Monsoon Region is the region that in Global Monsoon district, interannual variability is the strongest, the large I of interannual variability of East Asian monsoon reaches the magnitude of Seasonality.Affect by this, middle and lower reach of Yangtze River Summer Rainfall has very strong interannual variability, wherein, quasi-biennial oscillation (TBO) and accurate 4 years oscillation characteristicses the most obvious.Except having Annual variations feature, Interdecadal Variations is also a very important time scale of middle and lower reach of Yangtze River Summer Rainfall change, after wherein the most obvious interdecadal variability occurs in the end of the seventies in last century.Because East Asia Summer Monsoon is by turning by force weak, cause China's In Middle And Lower Reaches of Changjiang River precipitation to increase, and Precipitation In North China reducing, presenting significant " drought in the north and flooding in the south " variation tendency, making In Middle And Lower Reaches of Changjiang River enter the rainy stage by the stage short of rain.
The physical agent causing middle and lower reach of Yangtze River Summer Rainfall change is many-sided, as East Asia Summer Monsoon, ENSO circulation, western Pacific Ocean seamount thermodynamic status, Snow Cover On The Qinghai-xizang Plateau, polar region sea ice, solar activity etc.In these factors, the factor affecting middle and lower reach of Yangtze River Summer Rainfall interannual relationship is different.The change of middle and lower reach of Yangtze River Summer Rainfall is the coefficient result of the interdecadal variability Summing Factor Annual variations factor.But owing to there is complicated interaction between these factor and air, and on the change of middle and lower reach of Yangtze River Summer Rainfall, there is different impacts, make the difficulty of Accurate Prediction middle and lower reach of Yangtze River Summer Rainfall very large.The traffic forecast skill of the people such as Zhao Zhenguo to 15 Drought And Floods in the middle and lower reach of Yangtze River is assessed, and finds to only have the time of 53% can be successful.And the interannual relationship prediction signal that one of middle and lower reach of Yangtze River flood season precipitation prediction level major reason on the low side is middle and lower reach of Yangtze River Summer Rainfall sometimes and inconsistent.Ordinary etc. to point out, the Summer Rainfall change of the Accurate Prediction middle and lower reach of Yangtze River, these two kinds of time scales of inter-decadal and inter-annual variation must be separated.
Therefore, design one had both considered a year border prediction signal, considered Interdecadal Variations prediction signal again, and the Statistical Prediction Model can predicted the middle and lower reach of Yangtze River Summer Rainfall of Different time scales, be a research contents very with practical value.
Summary of the invention
The invention provides a kind of time scale of middle and lower reach of Yangtze River Summer Rainfall can being carried out and be separated the new method predicted, the method had both considered the year border prediction signal of middle and lower reach of Yangtze River Summer Rainfall, consider again its Interdecadal Variations prediction signal, can predict respectively the middle and lower reach of Yangtze River Summer Rainfall of Different time scales, avoid the inconsistent impact on prediction effect of year border and Interdecadal Variations prediction signal, reach the object of the predictablity rate improving middle and lower reach of Yangtze River Summer Rainfall.
The technical solution used in the present invention is as follows:
Step 1: adopt the method for frequency analysis to carry out year border to middle and lower reach of Yangtze River Summer Rainfall (RO) and be separated with Interdecadal Variations time scale.Concrete grammar is that RO time series is carried out Fourier transform; the ripple of cycle 2 years≤T<8 is classified as a year border component (RA); using the component of cycle 8 years≤T<30 as Interdecadal Variations component (RD1), using cycle >=component of 30 years is as Interdecadal Variations component (RD2);
Step 2: the method adopting correlation analysis, finds the physical agent relevant to RA, RD1, RD2 in the world as predictor.Choose the standard of predictor: one be related coefficient will be the significance test of 0.05 by reliability, and two is to have clear and definite physical significance;
Step 3: the method adopting linear regression, sets up different Statistical Prediction Models respectively for RA, RD1 and RD2.Finally, RA, RD1 and RD2 of prediction are added, namely obtain the RO predicted;
When in step 1 time scale separation being carried out to RO, for avoiding the impact on border, Fourier transform is carried out to the RO of 1951-2012 and decomposites RA, RD1 and RD2, but only intercept 1966-2000 RA, RD1 and the RD2 in totally 35 years carry out predictor screening and modeling;
Screen in the process of predictor in step 2, because the correlativity of premeasuring and predictor changes with monthly variation, even within same season, have contrary change, therefore adopt monthly average data instead of season data carry out predictor screening;
In step 3 according to the predictor that step 2 is screened, utilize the method for multiple linear regression and the data of 1966-2000 to set up forecast model to RA, RD1 and RD2 respectively, RO is drawn by following formula:
, wherein
for the long-time average annual value of middle and lower reach of Yangtze River Summer Rainfall, get 1951-2012 annual mean here.
Accompanying drawing explanation
Fig. 1 is process flow diagram of the invention process.
Fig. 2 is (a) RO, (b) RA, (c) RD1 and (d) RD2 of 1966-2005 reality (zero) and simulation (●).
Embodiment
By reference to the accompanying drawings 1 and embodiment the specific embodiment of the present invention is described in further detail:
Step 1: adopt the method for frequency analysis to carry out year border to middle and lower reach of Yangtze River Summer Rainfall (RO) and be separated with Interdecadal Variations time scale.Concrete grammar is that RO time series is carried out Fourier transform, the ripple of cycle 2 years≤T<8 is classified as a year border component (RA), using the component of cycle 8 years≤T<30 as Interdecadal Variations component (RD1), using cycle >=component of 30 years is as Interdecadal Variations component (RD2).
In step 1, first the predictor of RA is screened.The correlativity of 1966-2006 RA and Global Sst is analyzed, finds mainly to be distributed in Eastern Pacific in Dec to the 1-2 month then the year before last by the related coefficient of significance test.Wherein, both correlativitys are the strongest in February.After March, the related coefficient of RA and middle Eastern Pacific and even Global Sst diminishes all rapidly, substantially cannot pass through significance test, and therefore, Ni o3 index is first predictor that prediction RA is selected.RA and Ni o3 index is 0.48 in the related coefficient of 1966-2005, can by the significance test of reliability 0.05.
Do correlation analysis by RA and global 500hPa geopotential unit (H500), find RA and the H500 correlativity in April best.Reason may be that March and May are the Seasonal conversion moons in winter to spring and spring to summer, and atmospheric circulation form is unstable, and April the representational spring circulation form that is most.RA and April Northeast Asia H500 negative correlation, with the H500 positive correlation of the European northwestward and northern North america, this illustrates that the atmospheric long wave of high latitude in RA and 4 month has substantial connection, when Eurasian vat develops, and its upstream and downstream has pressure ridge to develop, be conducive to strong cold air activity.There are some researches prove: the East Asia Summer Monsoon that strong East Asian winter monsoon can be corresponding weak, makes middle and lower reach of Yangtze River Summer Rainfall increase.Except 500hPa Circulation, we also find that 300hPa broadwise wind field (U300) is positioned at the position residing for East Asian Subtropical torrent with the strong correlation district of RA, and the exception of upper westerly jet is an index well reflecting dry monsoon power, spring, subtropical jet stream was partially strong, was conducive to dry monsoon intensity partially strong.Therefore, the prediction signal that U300 reflects and H500 are consistent, all reflect the impact of cold air on middle and lower reach of Yangtze River Summer Rainfall.
In addition, middle and lower reach of Yangtze River Summer Rainfall and the H500 positive correlation of overhead, Western Pacific in April, and this positive correlation can last till the 5-7 month always, this illustrates that spring, Tibetan high (west is too secondary high) intensity was directly proportional to middle and lower reach of Yangtze River Summer Rainfall.And have research verified: when wet monsoon is on the weak side, the too secondary high strength in west strengthens, and the cold sky that warm-humid air is enlivened in In Middle And Lower Reaches of Changjiang River and the north crosses, and is conducive to middle and lower reach of Yangtze River Summer Rainfall and increases.
Middle and lower reach of Yangtze River Summer Rainfall, except relevant with the circulation in the Northern Hemisphere, also has relation with some circulation systems in the Southern Hemisphere.As can be seen from the correlation analysis of middle and lower reach of Yangtze River Summer Rainfall and sea-level pressure (SLP), middle and lower reach of Yangtze River Summer Rainfall and SLP are significant positive correlation district near Mascarene Islands, this illustrates when Mascarene High in spring partially strong (on the weak side), middle and lower reach of Yangtze River Summer Rainfall (on the low side) on the high side, this point is proved to be in much research.
According to above analysis, we define Northeast Asia circulation index H500_ENA(150 ° ~ 90 ° W, 5 ° of S ~ 5 ° N), Northern Europe circulation index H500_ENU(120 ° ~ 160 ° E, 55 ° ~ 60 ° N), too WNPSH indices H_WP(20 ° ~ 40 °, west E, 65 ° ~ 73N), westerly jet index U300(130 ° ~ 145 ° E, 45 ° ~ 50 ° N) and Mascarene High index SLP_MH(40 ° ~ 50 ° E,-35 ° ~ 25 ° S) as predictor, the related coefficient of they and RA is 0.48 respectively,-0.50, 0.48, 0.54 and 0.47.
Except dynamic factor, heating power factor pair RA also has stronger impact.Do relevant by RA to the temperature field in global range, find that RA and torrid areas are proportionate to 200hPa temperature, its remarkable positive correlation is mainly distributed in the torrid zone.And tropical atmosphere temperature drift, illustrate that solar radiation is partially strong to the heating of low latitude air, Hadley circulation is partially strong.Have research to point out, spring, Hadley circulation had significant lagging influence for East Asian Summer Rainfall, when Hadley circulation partially strong (weak), and middle and lower reach of Yangtze River Summer Rainfall (lacking) on the high side.Based on above analysis, by the predictor one of of the medial temperature (0 ° ~ 360 ° ,-10 ° of S ~ 10 ° N) of torrid areas in April as RA.
Secondly, the predictor of RD1 is screened.When screening the predictor of RD1, we adopt the method same with RA, and each variable in RD1 and global range is done correlation analysis, find that the predictor of RD1 and the predictor of RA have very large difference.First, can find from the correlation analysis of RD1 and Global Sst, although RD1 also concentrates on 3 months of annual winter in deepwater prediction signal, region not under the line in Eastern Pacific, but in Northern Hemisphere and Southern Hemisphere high latitude marine site.RD1 and North Pacific SST negative correlation are weak positive correlation with Middle East Pacific SST data, and this illustrates that RD1 and PDO has certain relation in the cycle of 8-30.And the mutual relationship of RD1 and South Pacific Ocean SST is studied less at present, its physical mechanism is not clear, awaits further research.Therefore, definition SST in Northern Pacific index SST_NP(180 ° ~ 160 ° W, 45 ° ~ 50 ° N), PSW sea warm index SST_SWP(170 ° ~ 240 ° of W, 50 ° ~ 35 ° S) and the warm index SST_SEP(110 ° ~ 90 ° of W in southeast Pacific sea, 60 ° ~ 50 ° S) as the predictor of RD1, the related coefficient of they and RD1 is respectively 0.45 ,-0.60 and 0.44.
RD1 and global sea air pressure (SLP) are done correlation analysis find, distribution of correlation coefficient presents typical North Pacific oscillation (NPO) mode, the i.e. SLP positive correlation of RD1 and tropical Pacific, and with North Pacific SLP negative correlation, and this correlation distribution is continued until May from January, this illustrates that the interdecadal variability of RD1 and NPO has substantial connection.NPO affects middle and lower reach of Yangtze River Summer Rainfall mainly through Hadley circulation, has research to point out, NPO and Hadley circulation year border and and Interdecadal Variations yardstick on have significant positive correlation.When NPO just (is bearing) position phase time, Hadley circulation partially strong (weak), middle and lower reach of Yangtze River Summer Rainfall is easily on the high side.Therefore, define tropical Pacific SLP index SLP_TP(160 ° ~ 160 ° W, 10 ° of S ~ 5 ° N) as the predictor of RD1, the related coefficient of he and RD1 is 0.44.
Then, the predictor of RD2 is screened.RD2 and Global Sst are done correlation analysis find, distribution of correlation coefficient presents typical PDO mode, i.e. RD2 and North Pacific SST negative correlation, and with Middle East Pacific SST data positive correlation, visible, in the time scale of cycle >30, the correlativity of middle and lower reach of Yangtze River Summer Rainfall and PDO is the strongest, and RD2 and PDO index has significant positive correlation, related coefficient is 0.49, is the significance test of 0.05 by reliability.
Finally, (table 1) is summarized to the predictor of RA, RD1 and RD2, find in most cases, Summer Rainfall prediction signal in an atmosphere in the middle and lower reach of Yangtze River mainly concentrates on spring, particularly April signal the most obvious, and mainly concentrate on winter in deepwater prediction signal, particularly the most obvious in February.
The predictor of table 1 Different time scales precipitation.
Utilize the method for multiple linear regression, obtain the predictive equation of RA, RD1 and RD2 respectively:
（1）
（2）
（3）
（4）
Wherein
for the long-time average annual value of middle and lower reach of Yangtze River Summer Rainfall, get 1951-2012 annual mean here.Simulate with the middle and lower reach of Yangtze River Summer Rainfall of this forecast model to 1966-2005, as shown in Figure 2, find that this model can well simulate the interannual relationship of middle and lower reach of Yangtze River Summer Rainfall, wherein the multiple correlation coefficient of RA predictive equation is 0.77, the multiple correlation coefficient of RD1 predictive equation is the multiple correlation coefficient of 0.79, RD2 predictive equation is 0.49.Finally, RA, RD1 and RD2 are updated in equation (4), obtain the RO simulated, the related coefficient of it and actual RO reaches 0.72.
Utilize this forecast model within totally 7 years, to return 2006-2012 years, the results are shown in Table 2.For assessing the effect of Result, we adopt relative error to test.The formula of relative error is:
.As can be seen from Table 2, this forecast model except to 2008 and predicated error in 2011 comparatively large except, the relative error in other times is all less than 10%, and the Prediction of Precipitation error particularly to 2007,2010,2012 is very little.The 2006-2012 average relative error of 7 years is-10.1%, and prediction effect is satisfaction comparatively.
The relative error (unit: %) of prediction RA, RD1, RD2 of table 2 2006-2012 Changjiang River middle and lower reaches Summer Rainfall and gross precipitation, observation gross precipitation (unit: mm) and prediction gross precipitation.
We can also find from table 2 in addition, in some time, year border signal be consistent with Interdecadal Variations signal, as 2008, only RA component was the quantity of precipitation being not enough to reach observation, but Interdecadal Variations component is all on the high side, made the RO of final prediction close to live.And some time, year border signal and Interdecadal Variations signal be inconsistent, as 2012, although RA is on the low side, RD1 is on the high side, under the modulation of RD1, makes final RO closer to fact.Point out as everyone knows, Decadal Oscillation is the disturbance of superposition on Secular Variation Tendency, is again the important background of interannual variability, produces important modulating action to year border climate change.Therefore, year border is considered and Interdecadal Variations signal is very necessary to falling water mitigation.
Claims (4)
1. a statistical forecast new method for middle and lower reach of Yangtze River Summer Rainfall, is characterized in that it comprises step:
Step 1: adopt the method for frequency analysis to carry out year border to middle and lower reach of Yangtze River Summer Rainfall (RO) and be separated with Interdecadal Variations time scale; concrete grammar is that RO time series is carried out Fourier transform; the ripple of cycle 2 years≤T<8 is classified as a year border component (RA); using the component of cycle 8 years≤T<30 as Interdecadal Variations component (RD1), using cycle >=component of 30 years is as Interdecadal Variations component (RD2);
Step 2: the method adopting correlation analysis; find the physical agent relevant to RA, RD1, RD2 in the world as predictor; choose the standard of predictor: one be related coefficient will be the significance test of 0.05 by reliability, and two is to have clear and definite physical significance;
Step 3: the method adopting linear regression, sets up different Statistical Prediction Models respectively for RA, RD1 and RD2, finally, RA, RD1 and RD2 of prediction is added, namely obtains the RO predicted.
2. the statistical forecast new method of a kind of middle and lower reach of Yangtze River according to claim 1 Summer Rainfall, it is characterized in that: when in step 1 time scale separation being carried out to RO, for avoiding the impact on border, Fourier transform is carried out to the RO of 1951-2012 and decomposites RA, RD1 and RD2, but only intercept 1966-2000 RA, RD1 and the RD2 in totally 35 years carry out predictor screening and modeling.
3. the statistical forecast new method of the middle and lower reach of Yangtze River according to claim 1 Summer Rainfall, it is characterized in that: screen in the process of predictor in step 2, because the correlativity of premeasuring and predictor changes with monthly variation, even within same season, have contrary change, therefore adopt monthly average data instead of season data carry out predictor screening.
4. the statistical forecast new method of a kind of middle and lower reach of Yangtze River according to claim 1 Summer Rainfall, it is characterized in that: in step 3 according to the predictor that step 2 is screened, utilize the method for multiple linear regression and the data of 1966-2000 to set up forecast model to RA, RD1 and RD2 respectively, RO is drawn by following formula:
, wherein
for the long-time average annual value of middle and lower reach of Yangtze River Summer Rainfall, get 1951-2012 annual mean here.
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| CN108957590A (en) * | 2018-05-22 | 2018-12-07 | 南京信息工程大学 | A kind of extracting method based on the real-time index of EEOF quasi-biweekly oscillation |
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- 2015-05-08 CN CN201510231779.2A patent/CN104809508A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108957590A (en) * | 2018-05-22 | 2018-12-07 | 南京信息工程大学 | A kind of extracting method based on the real-time index of EEOF quasi-biweekly oscillation |
| CN108957590B (en) * | 2018-05-22 | 2020-10-09 | 南京信息工程大学 | Extraction method based on EEOF quasi-bi-periodic oscillation real-time index |
| CN110287624A (en) * | 2019-06-28 | 2019-09-27 | 宁波市气象台 | A method of for cultivating salinity effect model foundation in bay during typhoon influence |
| CN110287624B (en) * | 2019-06-28 | 2020-10-02 | 宁波市气象台 | Method for building salinity forecasting model of aquaculture bay during typhoon influence period |
| CN112561140A (en) * | 2020-12-04 | 2021-03-26 | 南京大学 | China four-season rainfall prediction method based on cooperative change of east Asia subtropical zone torrent and extreme torrent |
| CN114580711A (en) * | 2022-01-29 | 2022-06-03 | 国家气候中心 | North China rainy season starting date prediction method based on mode key circulation system |
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