CN105046358A - Storm scale ensemble forecast perturbation method - Google Patents

Abstract

The invention relates to a storm scale ensemble forecast perturbation method. Observation data analysis, assimilation and numerical simulation are used as major measures; an ensemble forecast method is combined with severe convection weather forecast; and by aiming at the essential differences of the global medium-range ensemble forecast and the storm scale severe convection ensemble forecast, the final goal of building a storm scale ensemble forecast system which is applicable to various kinds of storm systems and constructs the perturbation scheme in a self-adaptive way according to the real-time developed severe convection system features is achieved. The method has the beneficial effects that through a variational assimilation ensemble, the ensemble perturbation realizes the physical and power harmony; the ensemble dispersion degree of the boundary layer mode variable is improved by a random physical harmony method; through self-adaptive selection on perturbation variables sensitive to the real-time developed storm system, the variable with the most obvious influence and the highest sensitivity on the storm development is selected for perturbation; high pertinence is realized; and the ensemble dispersion degree is also improved.

Description

A kind of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method

Technical field

The present invention relates to weather forecasting techniques field, particularly relate to a kind of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method.

Background technology

A series of researchs in past show, storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM is feasible and effective, but the perturbation motion method of current each storm scale systems ensemble prediction system need perfect.As U.S. storm is analyzed and the storm scale systems ensemble prediction system of forecasting centre (CAPS), forecast score can be improved by raising number of members and resolution, but its set disturbance scheme is fixing, namely the initial value disturbance of each set member adopts fixing response excursion, and mates with specific physical schemes; The lateral boundary conditions of part set member is provided by the short-time forecast of NAM pattern, and lateral boundary conditions identical between member will limit the development of dispersion to a certain extent; On the other hand, this system does not consider the mismatch problem of disturbance yardstick between lateral boundaries disturbance and initial value disturbance.Above-mentioned typical problem embodies all to some extent in each storm scale systems ensemble prediction system, and initial value disturbance, physics (parameter) disturbance, combination problem between lateral boundaries disturbance and initial value disturbance all play a key effect for the success or not of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM.

Because initial error differentiation in time has difference significantly in baroclinic instability and convective instability, the initial disturbance of gathering perturbation motion method structure mid-term cannot increase fast in convection system, also namely the development of initial disturbance structure and storm system is incompatible, and then causes set member's dispersion lower than rational level; On the other hand, the initial value disturbance of storm scale systems and the incompatible growth that also will limit initial disturbance and gather dispersion of the yardstick of lateral boundaries disturbance.Many physical processes and multi-mode set contribute to improving dispersion problem, but it is different that the threshold condition of the Rainfall forecast in the Microphysical scheme of pattern and microphysical processes judges, all have precipitation intensity and scope forecast of settling in an area and affect significantly, for the dissimilar storm system occurred in real time, choosing different mode Microphysical scheme with adopting changeless set configuration associativity is blindly.

Summary of the invention

The object of the invention is the deficiency overcoming above prior art, provides a kind of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method, specifically has following technical scheme to realize:

Described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method, comprises the steps:

1) WRF-ARW Numerical Prediction Models is adopted to set up outer, an internal layer HORIZONTAL PLAID apart from the storm scale systems ensemble prediction system being respectively 12,2 kilometers; The analysis field of the control forecast of described system is generated by the observational data of ECMWF high resolving power whole world analysis field, and the boundary condition of the set member of described system is provided by the DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF worldwide collection forecast system 35 kilometers of resolution;

2) adaptively selected disturbance variable: for any one strong convective weather, when two or more pattern variables above all support that it occurs, automatically the pattern variable that disturbance is comparatively responsive in this strong convective weather is set as most suitable disturbance variable;

3) determine operation area and resolution, by multiple example statistics and integrating step 2) in most suitable disturbance variable, determine the physical process needing disturbance, carry out disturbance set;

4) calmodulin binding domain CaM DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM comparatively Small-scale fluctuation structure, mutually orthogonal and the perturbations that can increase fast at convective region at pattern ectonexine Area generation, adopt the hybrid technology of frequency analysis and analysis of spectrum to combine by the initial disturbance of outer mode region with from worldwide collection disturbance, and provide initial disturbance for outer mode region; Then carry out second time mixed process, the disturbance by outer mode region and internal layer mode region adjusts, and obtains the disturbance information of rational set member;

5) disturbance information of described rational set member is constructed three set components: the observation set of disturbance, the background condition set coming from the short-time forecast of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM and the worldwide collection forecast starting condition set assimilated with mode of observation, Three-dimensional Variational Data Assimilation is carried out to the set member of described three set components, guarantee that each set member is while the dispersion keeping self and other members, makes set member self closer to true value and is carrying out heat power coordination to mesoscale flow to the multiple dimensioned of synoptic scale.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step 3) in comprise the steps:

A) generate one and meet the two-dimentional Perturbation r distributed just very much, having standard deviation S TD is 0.5, and range of disturbance is defined as [-2STD, 2STD] simultaneously;

B) by time autocorrelation function with pattern synchronization integration, realize r over time.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step a) in, first the variance spectrum of a noise is defined, the space distribution of the disturbance obtained is composed by this variance, use and intend Fourier transform, the fluctuation of wavelength is synthesized to together, each member's independent operating, obtain corresponding with member variance spectrum, and then generate mutually independently and meet the Perturbation r distributed just very much based on this variance spectrum.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step 4) comprise the steps:

I) adding up once a nearest example at set intervals, adding up, to determine the breeding cycle of ETR by reading described example;

II) by sensitivity experiments and the wavelength coverage determining the disturbance that can increase fast in dissimilar storm according to the running environment of user;

III) after determining optimum breeding cycle and Optimal Disturbance wavelength period, the external grid of hybrid technology based on ETR technology and frequency analysis and analysis of spectrum carries out first time disturbance;

IV) by ETR technology, namely sized set transform technology, interior net region generates the second time disturbance mutually orthogonal with outer grid, and reuses described hybrid technology, the disturbance of adjustment internal layer grid.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step II) in, when determining wavelength coverage, the separation of wavelength uses Barnes filtering method, ask poor by the result of twice filtering to set member's disturbance, isolate the disturbance space structure that any wavelength period is corresponding.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, the coverage of described disturbance is obtained by reflectivity or vertical speed estimation, and the established standards on its disturbance border is that reflectivity and its graded are all less than an empirical value N.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step III) comprise following two steps:

A, according to optimum breeding cycle T minute, before the initial time of formal forecast, use and carry out sized set transform by the initial sets of Optimal Disturbance wavelength period perturbation structure, until arrive the initial time of formal forecast;

B, from this initial time, using the hybrid technology based on frequency analysis and analysis of spectrum, combining now gathering with the ECMWF of synoptic scale the set of mesoscale flow.

The further design of described storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method is, described step 5) comprise the steps:

A) by the method minimization cost function of iteration to obtain the estimated value x of statistically optimum Real Atmosphere state, described cost function such as formula shown in (3),

$J\left(x\right)=\frac{1}{2}{(x-x_b)}^T{B}^{-1}(x-x_b)+\frac{1}{2}{(y-H(x\left)\right)}^T{R}^{-1}(y-H(x))---\left(3\right)$

Suppose x _lsrepresent and background x _bwith observation y incoherent worldwide collection forecast starting condition, then new cost function will be expressed as:

J(x)＝J _b+J _o+(x-x _ls) ^TV ^-1(x-x _ls)(4)

Wherein J _band J _orespectively front with equation (3) two corresponding; V is x _lsagitation error covariance matrix.

B) in WRF3DVAR assimilation system, J is added _cmodule, J _cexpression formula such as formula shown in (5),

J _c＝(x-x _ls) ^TV ^-1(x-x _ls)(5)

Described J _cmodule comprises: x _lsi/O and cost function, use Eigenvalues Decomposition mode to calculate the inverse of V when calculating;

C) from the Global Scale DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF, extract multiple Vertical Profile comprising each meteorological element, and it is exported by the prebuff form that WRF3DVAR is used;

D) once J is comprised for each set member runs _cthe WRF3DVAR assimilation system of module, the set of assimilation observation set and large-scale model field, generates the final set member carrying out DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM.

Advantage of the present invention is as follows:

1, described method provides a kind of pooling information assimilation method, i.e. the set of variational Assimilation.The disturbance information of storm scale systems and large scale can organically combine by the set member that the method obtains, and meanwhile, cost function is dynamic effect in mode, makes to gather the harmony that disturbance has physics and power.

2, described method, be different from traditional random physical disturbance, the method carries out tendency disturbance to completely independently physical process, object is the conservativeness of tendency disturbance on energy of Assured Mode variable, make the method can improve the set dispersion of boundary layer model variable, this will significantly improve the forecast level of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM.

3, propose the disturbance variable of the storm system sensitivity selected adaptively development in real time, the way of widespread perturbations different from the past, selects the variable remarkable and the most responsive to storm influence on development to carry out disturbance, more targetedly, too increases set dispersion.

Accompanying drawing explanation

Fig. 1 is described storm scale systems ensemble prediction system framework and schematic flow sheet thereof.

Embodiment

Below in conjunction with accompanying drawing, the present invention program is described in detail.

As Fig. 1, the storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method that the present embodiment provides, comprises the steps:

1) WRF-ARW Numerical Prediction Models is adopted to set up outer, an internal layer HORIZONTAL PLAID apart from the storm scale systems ensemble prediction system being respectively 12,2 kilometers; The analysis field of the control forecast of system is generated by the observational data of ECMWF high resolving power whole world analysis field, and the boundary condition of the set member of system is provided by the DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF worldwide collection forecast system 35 kilometers of resolution.Wherein, WRF-ARW is WeatherResearchandForecastingModel-AdvancedResearchWRF weather research and forecast pattern---advanced studies version, and ECMWF is EuropeanCentreforMedium-RangeWeatherForecasts European Center for Medium Weather Forecasting.

2) for any one strong convective weather, when two or more pattern variables above all support that it occurs, automatically the pattern variable that disturbance is comparatively responsive in this strong convective weather is set as most suitable disturbance variable.

3) determine operation area and resolution, by multiple example statistics and integrating step 2) in most suitable disturbance variable, determine the physical process needing disturbance, carry out disturbance set.

4) calmodulin binding domain CaM DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM comparatively Small-scale fluctuation structure, mutually orthogonal and the perturbations that can increase fast at convective region at pattern ectonexine Area generation, adopt the hybrid technology of frequency analysis and analysis of spectrum to combine by the initial disturbance of outer mode region with from worldwide collection disturbance, and provide initial disturbance for outer mode region; Then carry out second time mixed process, the disturbance by outer mode region and internal layer mode region adjusts, and obtains the disturbance information of rational set member.

5) disturbance information of rational set member is constructed three set components: the observation set of disturbance, the background condition set coming from the short-time forecast of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM and the worldwide collection forecast starting condition set assimilated with mode of observation, Three-dimensional Variational Data Assimilation is carried out to the set member of three set components, guarantee that each set member is while the dispersion keeping self and other members, makes set member self closer to true value and is carrying out heat power coordination to mesoscale flow to the multiple dimensioned of synoptic scale.

Step 2) in, the core of adaptively selected disturbance variable is comprehensive various criterion, estimate the situation of following contingent convection current, and select pattern variable comparatively responsive in this situation or its diagnosis amount to carry out disturbance accordingly, rationally to have according to effectively constructing initial sets member.

Adaptively selected disturbance variable compared to the single criterion of traditional dependence or need manual select the advantage of the method for disturbance variable to be can the information of comprehensive different criterion, find the type being in the strong convective weather in different criterion scope of application coincidence district, and can according to this type, automatically select most suitable disturbance variable objectively, do not need manual intervention completely.

For vertical wind shear and convective available potential energy, equation (1), (2) are respectively the vertical wind shear of Density Weighted and the computing method of convective available potential energy.Suppose that SSEFS is by judging to think that vertical wind shear and convective available potential energy have reached the possibility triggering storm to the environment before storm generation, then based on historical statistics relation, SSEFS automatically can carry out the adjustment with response excursion of choosing of crucial disturbance variable according to both relative importance and numerical value thereof.Now, disturbance variable can be pattern variable u, v component or the temperature t of vertical wind shear and convective available potential energy or both correspondences, and the selection of this disturbance variable will depend on that pattern variable and stability index are to the statistical research result of the susceptibility that storm system develops.

With vertical wind shear (Shr) for transverse axis, convective available potential energy (CAPE) is the longitudinal axis, set up the distribution plan (scatter diagram) of the dissimilar strong convective weather of China with this Two Variables, and sort out, determine the array mode (ratio) of above Two Variables when dissimilar strong convection occurs.

$Shr=\left\{{\∫}_0^z\mathrm{\ρ}\left(z\right)\right|V\left(z\right)|dz/{\∫}_0^z\mathrm{\ρ}\left(z\right)dz-0.5\[|V\left(0\right)+V\left(0.5km\right)|\]\}/(Z-0)---\left(1\right)$

$CAPE={\∫}_{p_{EL}}^{p_{LFC}}{R}_d(T_{vp}-T_{ve})d\ln p---\left(2\right)$

When ambient wind is close to geostrophic wind, helicity (helicity characterizes the vertical wind shear of air) can be represented with thermal wind, set up the distribution plan (scatter diagram) of the dissimilar strong convective weather of China with temperature advection and CAPE, and sort out, determine the array mode (ratio) of above Two Variables when dissimilar strong convection occurs.With the helicity (TudurfandRamis1997) that temperature advection represents under geostrophic approximation

$H={\∫}_{p_0}^{p_h}\frac{R}{fp}\left(-V_g\·{\▿}_{p}T\right)dp---\left(3\right)$

When Sharpe index essence refers to that the conservative air parcel at 850hPa place is raised to 500hPa, the difference of environment temperature and air parcel temperature, when SI is less than zero, represents stratification stability, good negative correlation is had with CAPE value, relevant with buoyancy size more than level of free convection (LFC).Set up dissimilar convection current equally to cut with Sharpe index and vertically-supplying air or the scatter diagram of temperature advection, determine the relation between index and strong convection.

SI＝T ₅₀₀-T _L

Wherein T500 is the actual temperature of 500hPa, and TL is the temperature that air parcel prolongs that from level of free convection (LFC) moist adiabat is lifted to 500hPa.

The same, criterion also comprises strong convection classification with the sign Jeffersonindex (Jefferson, 1963,1966) of buoyancy and the change of vertical wind shear

$Jeff=1.6{\mathrm{\θ}}_{w_{850}}-T_{500}-0.5(T_{700}-T_{d_{700}})-8$

For any one strong convective weather, when two or more criterions above all support that it occurs, SSEFS by the pattern variable of disturbance comparatively sensitivity in this strong convective weather, the such as variable such as u, v or temperature.

Further design is, step 3) in comprise the steps:

A) generate one and meet the two-dimentional Perturbation r distributed just very much, having standard deviation S TD is 0.5, and range of disturbance is defined as [-2STD, 2STD] simultaneously.

B) by time autocorrelation function with pattern synchronization integration, realize r over time.

Step a) in, first the variance spectrum of a noise is defined, the space distribution of the disturbance obtained is composed by this variance, use and intend Fourier transform, the fluctuation of wavelength is synthesized to together, each member's independent operating, obtains corresponding with member variance spectrum, and then generates mutually independently and meet the Perturbation r distributed just very much based on this variance spectrum.

Step 4) in, comprise the steps:

I) adding up once a nearest example at set intervals, adding up, to determine the breeding cycle of ETR (sized set transform technology) by reading an example.Determine the breeding cycle of ETR, need the statistics of carrying out multiple example just can obtain.Because climate change can affect the environment that convection current occurs, therefore the result of passing statistics is not necessarily applicable to present case, needs to add up once a nearest example at set intervals.

II) by sensitivity experiments and the wavelength coverage determining the disturbance that can increase fast in dissimilar storm according to the running environment of user.This scope also needs to add up separately according to the running environment of user to draw.This is mainly because the design conditions of different users are different, grid resolution and the scope of use are all different, numerical model is to Same Wavelength, or the response of same strong convection system is also different, and therefore this scope can only be added up again and be drawn after the running environment of user is determined.

Step II) in, the separation of wavelength uses Barnes filtering method, by the result of disturbance twice filtering to set member ask difference and separable certain go out the disturbance space structure of certain wavelength period, each set member independently carries out this operation.The coverage of this disturbance is estimated to obtain by reflectivity or vertical speed, the established standards on the border of its disturbance is that reflectivity and its graded are all less than a certain empirical value, perhaps, this numerical value sets according to actual conditions, because the grid resolution of user may be different, Grad has obvious difference.

III) after determining optimum breeding cycle and Optimal Disturbance wavelength period, the external grid of hybrid technology based on ETR technology and frequency analysis and analysis of spectrum carries out first time disturbance.

Step III) comprise following two steps:

A), according to optimum breeding cycle T minute, before the initial time of formal forecast, use and carry out sized set transform by the initial sets of Optimal Disturbance wavelength period perturbation structure, until arrive the initial time of formal forecast.

B), from this initial time, using the hybrid technology based on frequency analysis and analysis of spectrum, combining now gathering with the ECMWF of synoptic scale the set of mesoscale flow.

IV) by ETR technology, interior net region generates the second time disturbance mutually orthogonal with outer grid, and reuses hybrid technology, the disturbance of adjustment internal layer grid.

Step 5) in, comprise the steps:

A) by the method minimization cost function of iteration to obtain the estimated value x of statistically optimum Real Atmosphere state, its cost function can be expressed as and be added the x of the inverse matrix institute weighting being observed error covariance (R) and the distance observing y by the x of inverse matrix institute weighting of background error covariance (B) and the distance of ambient field xb, cost function is such as formula shown in (3)

$J\left(x\right)=\frac{1}{2}{(x-x_b)}^T{B}^{-1}(x-x_b)+\frac{1}{2}{(y-H(x\left)\right)}^T{R}^{-1}(y-H(x))---\left(3\right)$

Suppose x _lsrepresent and background x _band observation _yincoherent worldwide collection forecast starting condition, then new cost function will be expressed as:

J(x)＝J _b+J _o+(x-x _ls) ^TV ^-1(x-x _ls)(4)

Wherein J _band J _orespectively front with equation (3) two corresponding; V is the agitation error covariance matrix of xls.Can see from equation (4), set assimilates the starting condition that obtains by the Small-scale fluctuation information of the Large Scale Disturbance information and storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM that comprise worldwide collection forecast, and this disturbance information is that itself is as dynamic effect in mode, and the result therefore gathering variational Assimilation has the consistance of physics and the harmony of power.

B) in WRF3DVAR assimilation system, J is added _cmodule, J _cexpression formula such as formula shown in (5),

J _c＝(x-x _ls) ^TV ^-1(x-x _ls)(5)

J _cmodule comprises: x _lsi/O and cost function, use Eigenvalues Decomposition mode to calculate the inverse of V when calculating, wherein, WRF3DVAR represents WRF-3DVariationalDataAssimilation weather research and forecast pattern---Three-dimensional Variational Data Assimilation.

C) from the Global Scale DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF, extract multiple Vertical Profile comprising each meteorological element, and it is exported by the prebuff form that WRF3DVAR is used;

D) once J is comprised for each set member runs _cthe WRF3DVAR assimilation system of module, the set of assimilation observation set and large-scale model field, generates the final set member carrying out DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM.

Claims (8)

1. a storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method, is characterized in that comprising the steps:

1) WRF-ARW Numerical Prediction Models is adopted to set up outer, an internal layer HORIZONTAL PLAID apart from the storm scale systems ensemble prediction system being respectively 12,2 kilometers; The analysis field of the control forecast of described system is generated by the observational data of ECMWF high resolving power whole world analysis field, and the boundary condition of the set member of described system is provided by the DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF worldwide collection forecast system 35 kilometers of resolution;

2) adaptively selected disturbance variable: for any one strong convective weather, when two or more pattern variables above all support that it occurs, automatically the pattern variable that disturbance is comparatively responsive in this strong convective weather is set as most suitable disturbance variable;

3) determine operation area and resolution, by multiple example statistics and integrating step 2) in most suitable disturbance variable, determine the physical process needing disturbance, carry out disturbance set;

4) calmodulin binding domain CaM DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM comparatively Small-scale fluctuation structure, the mutually orthogonal and perturbations that can increase fast at convective region at pattern ectonexine Area generation, adopts humorous region to provide initial disturbance; Then carry out second time mixed process, the disturbance by outer mode region and internal layer mode region adjusts, and obtains the disturbance information of rational set member;

5) disturbance information of described rational set member is constructed three set components: the observation set of disturbance, the background condition set coming from the short-time forecast of storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM and the worldwide collection forecast starting condition set assimilated with mode of observation, Three-dimensional Variational Data Assimilation is carried out to the set member of described three set components, guarantee that each set member is while the dispersion keeping self and other members, makes set member self closer to true value and is carrying out heat power coordination to mesoscale flow to the multiple dimensioned of synoptic scale.

2. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 1, is characterized in that described step 3) in comprise the steps:

A) generate one and meet the two-dimentional Perturbation r distributed just very much, having standard deviation S TD is 0.5, and range of disturbance is defined as [-2STD, 2STD] simultaneously;

B) by time autocorrelation function with pattern synchronization integration, realize r over time.

3. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 2, in it is characterized in that described step a), first the variance spectrum of a noise is defined, the space distribution of the disturbance obtained is composed by this variance, use and intend Fourier transform, the fluctuation of wavelength is synthesized to together, each member's independent operating, obtain corresponding with member variance spectrum, and then generate mutually independently and meet the Perturbation r distributed just very much based on this variance spectrum.

4. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 3, is characterized in that described step 4) comprise the steps:

I) adding up once a nearest example at set intervals, adding up, to determine the breeding cycle of ETR by reading described example;

II) by sensitivity experiments and the wavelength coverage determining the disturbance that can increase fast in dissimilar storm according to the running environment of user;

III) after determining optimum breeding cycle and Optimal Disturbance wavelength period, the external grid of hybrid technology based on ETR technology and frequency analysis and analysis of spectrum carries out first time disturbance;

IV) by ETR technology, sized set transform technology, interior net region generates the second time disturbance mutually orthogonal with outer grid, and reuses described hybrid technology, the disturbance of adjustment internal layer grid.

5. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 4, it is characterized in that described step II) in, when determining wavelength coverage, the separation of wavelength uses Barnes filtering method, ask poor by the result of twice filtering to set member's disturbance, isolate the disturbance space structure that any wavelength period is corresponding.

6. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 5, it is characterized in that the coverage of described disturbance is obtained by reflectivity or vertical speed estimation, the established standards on its disturbance border is that reflectivity and its graded are all less than an empirical value N.

7. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 4, is characterized in that described step III) comprise following two steps:

A, according to optimum breeding cycle T minute, before the initial time of formal forecast, use and carry out sized set transform by the initial sets of Optimal Disturbance wavelength period perturbation structure, until arrive the initial time of formal forecast;

B, from this initial time, using the hybrid technology based on frequency analysis and analysis of spectrum, combining now gathering with the ECMWF of synoptic scale the set of mesoscale flow.

8. storm scale systems DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM perturbation motion method according to claim 2, is characterized in that described step 5) comprise the steps:

A) by the method minimization cost function of iteration to obtain the estimated value x of statistically optimum Real Atmosphere state, described cost function such as formula shown in (3),

$J\left(x\right)=\frac{1}{2}{(x-x_b)}^T{B}^{-1}(x-x_b)+\frac{1}{2}{(y-H(x\left)\right)}^T{R}^{-1}(y-H(x\left)\right)---\left(3\right)$

Suppose x _lsrepresent and background x _bwith observation y incoherent worldwide collection forecast starting condition, then new cost function will be expressed as:

J(x)＝J _b+J _o+(x-x _ls) ^TV ^-1(x-x _ls)(4)

Wherein J _band J _orespectively front with equation (3) two corresponding; V is x _lsagitation error covariance matrix.

B) in WRF3DVAR assimilation system, J is added _cmodule, J _cexpression formula such as formula shown in (5),

J _c＝(x-x _ls) ^TV ^-1(x-x _ls)(5)

Described J _cmodule comprises: x _lsi/O and cost function, use Eigenvalues Decomposition mode to calculate the inverse of V when calculating;

C) from the Global Scale DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM of ECMWF, extract multiple Vertical Profile comprising each meteorological element, and it is exported by the prebuff form that WRF3DVAR is used;

D) once J is comprised for each set member runs _cthe WRF3DVAR assimilation system of module, the set of assimilation observation set and large-scale model field, generates the final set member carrying out DATA PROCESSING IN ENSEMBLE PREDICTION SYSTEM.